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79 changed files with 2770 additions and 2001 deletions
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@ -8,7 +8,7 @@
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}
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},
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"source": [
|
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"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/00_intro/00_content.ipynb)."
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"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/00_intro/00_content.ipynb)."
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]
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},
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{
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@ -135,7 +135,7 @@
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"source": [
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"To \"read\" this book in the most meaningful way, a working installation of **Python 3.8** with [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) is needed.\n",
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"\n",
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"For a tutorial on how to install Python on your computer, follow the instructions in the [README.md](https://github.com/webartifex/intro-to-python/blob/develop/README.md#installation) file in the project's [GitHub repository <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python). If you cannot install Python on your own machine, you may open the book interactively in the cloud with [Binder <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab)."
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||||
"For a tutorial on how to install Python on your computer, follow the instructions in the [README.md](https://github.com/webartifex/intro-to-python/blob/main/README.md#installation) file in the project's [GitHub repository <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python). If you cannot install Python on your own machine, you may open the book interactively in the cloud with [Binder <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab)."
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]
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},
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{
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@ -161,7 +161,7 @@
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"\n",
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"\"Jupyter\" is an [acronym <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Acronym) derived from the names of the three major programming languages **[Julia](https://julialang.org/)**, **[Python <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://www.python.org)**, and **[R](https://www.r-project.org/)**, all of which play significant roles in the world of data science. The Jupyter Project's idea is to serve as an integrating platform such that different programming languages and software packages can be used together within the same project.\n",
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"\n",
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"Jupyter notebooks have become a de-facto standard for communicating and exchanging results in the data science community - both in academia and business - and provide an alternative to command-line interface (CLI or \"terminal\") based ways of running Python code. As an example for the latter case, we could start the default [Python interpreter <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/tutorial/interpreter.html) that comes with every installation by typing the `python` command into a CLI (or `poetry run python` if the project is managed with the [poetry](https://python-poetry.org/docs/) CLI tool as explained in the [README.md](https://github.com/webartifex/intro-to-python/blob/develop/README.md#alternative-installation-for-instructors) file). Then, as the screenshot below shows, we could execute Python code like `1 + 2` or `print(\"Hello World\")` line by line simply by typing it following the `>>>` **prompt** and pressing the **Enter** key. For an introductory course, however, this would be rather tedious and probably scare off many beginners."
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"Jupyter notebooks have become a de-facto standard for communicating and exchanging results in the data science community - both in academia and business - and provide an alternative to command-line interface (CLI or \"terminal\") based ways of running Python code. As an example for the latter case, we could start the default [Python interpreter <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/tutorial/interpreter.html) that comes with every installation by typing the `python` command into a CLI (or `poetry run python` if the project is managed with the [poetry](https://python-poetry.org/docs/) CLI tool as explained in the [README.md](https://github.com/webartifex/intro-to-python/blob/main/README.md#alternative-installation-for-instructors) file). Then, as the screenshot below shows, we could execute Python code like `1 + 2` or `print(\"Hello World\")` line by line simply by typing it following the `>>>` **prompt** and pressing the **Enter** key. For an introductory course, however, this would be rather tedious and probably scare off many beginners."
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]
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},
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{
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@ -291,7 +291,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Python 3.8.6\n"
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"Python 3.12.2\n"
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]
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}
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],
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@ -750,11 +750,11 @@
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"**Part A: Expressing Logic**\n",
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"\n",
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"- What is a programming language? What kind of words exist?\n",
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" - *Chapter 1*: [Elements of a Program <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb)\n",
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" - *Chapter 2*: [Functions & Modularization <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb)\n",
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||||
" - *Chapter 1*: [Elements of a Program <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb)\n",
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||||
" - *Chapter 2*: [Functions & Modularization <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/00_content.ipynb)\n",
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"- What is the flow of execution? How can we form sentences from words?\n",
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" - *Chapter 3*: [Conditionals & Exceptions <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/03_conditionals/00_content.ipynb)\n",
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" - *Chapter 4*: [Recursion & Looping <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/00_content.ipynb)"
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||||
" - *Chapter 3*: [Conditionals & Exceptions <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/03_conditionals/00_content.ipynb)\n",
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||||
" - *Chapter 4*: [Recursion & Looping <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/00_content.ipynb)"
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]
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},
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{
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@ -768,14 +768,14 @@
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"**Part B: Managing Data and Memory**\n",
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"\n",
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"- How is data stored in memory?\n",
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" - *Chapter 5*: [Numbers & Bits <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/00_content.ipynb)\n",
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||||
" - *Chapter 6*: [Text & Bytes <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/00_content.ipynb)\n",
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||||
" - *Chapter 7*: [Sequential Data <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/00_content.ipynb)\n",
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||||
" - *Chapter 8*: [Map, Filter, & Reduce <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/00_content.ipynb)\n",
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||||
" - *Chapter 9*: [Mappings & Sets <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/00_content.ipynb)\n",
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||||
" - *Chapter 5*: [Numbers & Bits <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/00_content.ipynb)\n",
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||||
" - *Chapter 6*: [Text & Bytes <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/00_content.ipynb)\n",
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||||
" - *Chapter 7*: [Sequential Data <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/00_content.ipynb)\n",
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||||
" - *Chapter 8*: [Map, Filter, & Reduce <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/00_content.ipynb)\n",
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||||
" - *Chapter 9*: [Mappings & Sets <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/00_content.ipynb)\n",
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" - *Chapter 10*: Arrays & Dataframes\n",
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"- How can we create custom data types?\n",
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" - *Chapter 11*: [Classes & Instances <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/00_content.ipynb)"
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||||
" - *Chapter 11*: [Classes & Instances <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/00_content.ipynb)"
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]
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},
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{
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@ -841,7 +841,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.6"
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"version": "3.12.2"
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},
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"livereveal": {
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"auto_select": "code",
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@ -4,7 +4,7 @@
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"cell_type": "markdown",
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||||
"metadata": {},
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||||
"source": [
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||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/00_intro/02_exercises.ipynb)."
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||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/00_intro/02_exercises.ipynb)."
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||||
]
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},
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{
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@ -18,7 +18,7 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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||||
"The exercises below assume that you have read [Chapter 0 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/00_intro/00_content.ipynb)."
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||||
"The exercises below assume that you have read [Chapter 0 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/00_intro/00_content.ipynb)."
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||||
]
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||||
},
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||||
{
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@ -94,7 +94,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.6"
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"version": "3.12.2"
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},
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"toc": {
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"base_numbering": 1,
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@ -11,7 +11,7 @@
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"cell_type": "markdown",
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"metadata": {},
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||||
"source": [
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||||
"The questions below assume that you have read [Chapter 0 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/00_intro/00_content.ipynb).\n",
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||||
"The questions below assume that you have read [Chapter 0 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/00_intro/00_content.ipynb).\n",
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"\n",
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"Be concise in your answers! Most questions can be answered in *one* sentence."
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||||
]
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@ -194,7 +194,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.6"
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"version": "3.12.2"
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},
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"toc": {
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"base_numbering": 1,
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@ -8,7 +8,7 @@
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}
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},
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"source": [
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||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/01_elements/00_content.ipynb)."
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"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/01_elements/00_content.ipynb)."
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]
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},
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{
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@ -1165,7 +1165,7 @@
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"source": [
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"These addresses are *not* meaningful for anything other than checking if two variables reference the *same* object.\n",
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"\n",
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"Obviously, `a` and `b` have the same *value* as revealed by the **equality operator** `==`: We say `a` and `b` \"evaluate equal.\" The resulting `True` - and the `False` further below - is yet another data type, a so-called **boolean**. We look into them in [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/03_conditionals/00_content.ipynb#Boolean-Expressions)."
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"Obviously, `a` and `b` have the same *value* as revealed by the **equality operator** `==`: We say `a` and `b` \"evaluate equal.\" The resulting `True` - and the `False` further below - is yet another data type, a so-called **boolean**. We look into them in [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/03_conditionals/00_content.ipynb#Boolean-Expressions)."
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]
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},
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{
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"source": [
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"Different types imply different behaviors for the objects. The `b` object, for example, may be \"asked\" if it is a whole number with the [.is_integer() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#float.is_integer) \"functionality\" that comes with *every* `float` object.\n",
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"\n",
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"Formally, we call such type-specific functionalities **methods** (i.e., as opposed to functions) and we look at them in detail in [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/00_content.ipynb). For now, it suffices to know that we access them with the **dot operator** `.` on the object. Of course, `b` is a whole number, which the boolean object `True` tells us."
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"Formally, we call such type-specific functionalities **methods** (i.e., as opposed to functions) and we look at them in detail in [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/00_content.ipynb). For now, it suffices to know that we access them with the **dot operator** `.` on the object. Of course, `b` is a whole number, which the boolean object `True` tells us."
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]
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},
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{
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"outputs": [
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{
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"ename": "SyntaxError",
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"evalue": "invalid syntax (<ipython-input-47-cafa82e54b9c>, line 1)",
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"evalue": "invalid syntax (73631267.py, line 1)",
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"output_type": "error",
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"traceback": [
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"\u001b[0;36m File \u001b[0;32m\"<ipython-input-47-cafa82e54b9c>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m 3.99 $ + 10.40 $\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
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"\u001b[0;36m Cell \u001b[0;32mIn[47], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m 3.99 $ + 10.40 $\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
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]
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}
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],
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"outputs": [
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{
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"ename": "SyntaxError",
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"evalue": "invalid syntax (<ipython-input-48-499e4d0d0cbb>, line 1)",
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"evalue": "expected ':' (2545637715.py, line 1)",
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"output_type": "error",
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"traceback": [
|
||||
"\u001b[0;36m File \u001b[0;32m\"<ipython-input-48-499e4d0d0cbb>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m for number in numbers\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
|
||||
"\u001b[0;36m Cell \u001b[0;32mIn[48], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m for number in numbers\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m expected ':'\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -1721,10 +1721,10 @@
|
|||
"outputs": [
|
||||
{
|
||||
"ename": "IndentationError",
|
||||
"evalue": "expected an indented block (<ipython-input-49-19398c5f89de>, line 2)",
|
||||
"evalue": "expected an indented block after 'for' statement on line 1 (1544118965.py, line 2)",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;36m File \u001b[0;32m\"<ipython-input-49-19398c5f89de>\"\u001b[0;36m, line \u001b[0;32m2\u001b[0m\n\u001b[0;31m print(number)\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mIndentationError\u001b[0m\u001b[0;31m:\u001b[0m expected an indented block\n"
|
||||
"\u001b[0;36m Cell \u001b[0;32mIn[49], line 2\u001b[0;36m\u001b[0m\n\u001b[0;31m print(number)\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mIndentationError\u001b[0m\u001b[0;31m:\u001b[0m expected an indented block after 'for' statement on line 1\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -1775,7 +1775,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mZeroDivisionError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-50-bc757c3fda29>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;36m1\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[50], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;241;43m1\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\n",
|
||||
"\u001b[0;31mZeroDivisionError\u001b[0m: division by zero"
|
||||
]
|
||||
}
|
||||
|
|
@ -1934,7 +1934,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"For example, while the above code to calculate the average of the even numbers in `[7, 11, 8, 5, 3, 12, 2, 6, 9, 10, 1, 4]` is correct, a Pythonista would rewrite it in a more \"Pythonic\" way and use the built-in [sum() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#sum) and [len() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#len) functions (cf., [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb#Built-in-Functions)) as well as a so-called **list comprehension** (cf., [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/00_content.ipynb#List-Comprehensions)). Pythonic code runs faster in many cases and is less error-prone."
|
||||
"For example, while the above code to calculate the average of the even numbers in `[7, 11, 8, 5, 3, 12, 2, 6, 9, 10, 1, 4]` is correct, a Pythonista would rewrite it in a more \"Pythonic\" way and use the built-in [sum() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#sum) and [len() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#len) functions (cf., [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/00_content.ipynb#Built-in-Functions)) as well as a so-called **list comprehension** (cf., [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/00_content.ipynb#List-Comprehensions)). Pythonic code runs faster in many cases and is less error-prone."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -2136,7 +2136,7 @@
|
|||
"\n",
|
||||
"At the same time, for a beginner's course, it is often easier to code linearly.\n",
|
||||
"\n",
|
||||
"In real data science projects, one would probably employ a mixed approach and put reusable code into so-called Python modules (i.e., *.py* files; cf., [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb#Local-Modules-and-Packages)) and then use Jupyter notebooks to build up a linear report or storyline for an analysis."
|
||||
"In real data science projects, one would probably employ a mixed approach and put reusable code into so-called Python modules (i.e., *.py* files; cf., [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/00_content.ipynb#Local-Modules-and-Packages)) and then use Jupyter notebooks to build up a linear report or storyline for an analysis."
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -2156,7 +2156,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/01_elements/01_exercises.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/01_elements/01_exercises.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -18,7 +18,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The exercises below assume that you have read the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb) of Chapter 1.\n",
|
||||
"The exercises below assume that you have read the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb) of Chapter 1.\n",
|
||||
"\n",
|
||||
"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
|
||||
]
|
||||
|
|
@ -151,7 +151,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/01_elements/02_exercises.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/01_elements/02_exercises.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -18,7 +18,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The exercises below assume that you have read the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb) of Chapter 1.\n",
|
||||
"The exercises below assume that you have read the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb) of Chapter 1.\n",
|
||||
"\n",
|
||||
"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
|
||||
]
|
||||
|
|
@ -36,7 +36,7 @@
|
|||
"source": [
|
||||
"`for`-loops are extremely versatile in Python. That is different from many other programming languages.\n",
|
||||
"\n",
|
||||
"As shown in the first example in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#Example:-Averaging-all-even-Numbers-in-a-List), we can create a `list` like `numbers` and loop over the numbers in it on a one-by-one basis."
|
||||
"As shown in the first example in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#Example:-Averaging-all-even-Numbers-in-a-List), we can create a `list` like `numbers` and loop over the numbers in it on a one-by-one basis."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -197,7 +197,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/01_elements/03_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/01_elements/03_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -350,7 +350,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-13-1748287bc46a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mvariable\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[13], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mvariable\u001b[49m\n",
|
||||
"\u001b[0;31mNameError\u001b[0m: name 'variable' is not defined"
|
||||
]
|
||||
}
|
||||
|
|
@ -367,7 +367,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Some variables magically exist when a Python process is started or are added by Jupyter. We may safely ignore the former until [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/00_content.ipynb) and the latter for good."
|
||||
"Some variables magically exist when a Python process is started or are added by Jupyter. We may safely ignore the former until [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/00_content.ipynb) and the latter for good."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -419,6 +419,7 @@
|
|||
"text/plain": [
|
||||
"['In',\n",
|
||||
" 'Out',\n",
|
||||
" 'Path',\n",
|
||||
" '_',\n",
|
||||
" '_10',\n",
|
||||
" '_11',\n",
|
||||
|
|
@ -435,6 +436,7 @@
|
|||
" '__loader__',\n",
|
||||
" '__name__',\n",
|
||||
" '__package__',\n",
|
||||
" '__session__',\n",
|
||||
" '__spec__',\n",
|
||||
" '_dh',\n",
|
||||
" '_i',\n",
|
||||
|
|
@ -457,11 +459,17 @@
|
|||
" '_ii',\n",
|
||||
" '_iii',\n",
|
||||
" '_oh',\n",
|
||||
" 'atexit',\n",
|
||||
" 'exit',\n",
|
||||
" 'get_ipython',\n",
|
||||
" 'history',\n",
|
||||
" 'history_path',\n",
|
||||
" 'open',\n",
|
||||
" 'os',\n",
|
||||
" 'quit',\n",
|
||||
" 'register_readline_completion',\n",
|
||||
" 'sys']"
|
||||
" 'readline',\n",
|
||||
" 'state_home',\n",
|
||||
" 'write_history']"
|
||||
]
|
||||
},
|
||||
"execution_count": 15,
|
||||
|
|
@ -636,10 +644,10 @@
|
|||
"outputs": [
|
||||
{
|
||||
"ename": "SyntaxError",
|
||||
"evalue": "cannot assign to operator (<ipython-input-23-ec51dae29567>, line 1)",
|
||||
"evalue": "cannot assign to expression here. Maybe you meant '==' instead of '='? (202417111.py, line 1)",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;36m File \u001b[0;32m\"<ipython-input-23-ec51dae29567>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m address@work = \"WHU, Burgplatz 2, Vallendar\"\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m cannot assign to operator\n"
|
||||
"\u001b[0;36m Cell \u001b[0;32mIn[23], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m address@work = \"WHU, Burgplatz 2, Vallendar\"\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m cannot assign to expression here. Maybe you meant '==' instead of '='?\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -679,7 +687,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Variables with leading and trailing double underscores, referred to as **dunder** in Python jargon, are used for built-in functionalities and to implement object-oriented features as we see in [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/00_content.ipynb). We must *not* use this style for variables!"
|
||||
"Variables with leading and trailing double underscores, referred to as **dunder** in Python jargon, are used for built-in functionalities and to implement object-oriented features as we see in [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/00_content.ipynb). We must *not* use this style for variables!"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -960,7 +968,7 @@
|
|||
"source": [
|
||||
"Let's change the first element of `x`.\n",
|
||||
"\n",
|
||||
"[Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/00_content.ipynb#The-list-Type) discusses lists in more depth. For now, let's view a `list` object as some sort of **container** that holds an arbitrary number of references to other objects and treat the brackets `[]` attached to it as yet another operator, namely the **indexing operator**. So, `x[0]` instructs Python to first follow the reference from the global list of all names to the `x` object. Then, it follows the first reference it finds there to the `1` object we put in the list. The indexing operator must be an operator as we merely *read* the first element and do not change anything in memory permanently.\n",
|
||||
"[Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/00_content.ipynb#The-list-Type) discusses lists in more depth. For now, let's view a `list` object as some sort of **container** that holds an arbitrary number of references to other objects and treat the brackets `[]` attached to it as yet another operator, namely the **indexing operator**. So, `x[0]` instructs Python to first follow the reference from the global list of all names to the `x` object. Then, it follows the first reference it finds there to the `1` object we put in the list. The indexing operator must be an operator as we merely *read* the first element and do not change anything in memory permanently.\n",
|
||||
"\n",
|
||||
"Python **begins counting at 0**. This is not the case for many other languages, for example, [MATLAB <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/MATLAB), [R <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/R_%28programming_language%29), or [Stata <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Stata). To understand why this makes sense, see this short [note](https://www.cs.utexas.edu/users/EWD/transcriptions/EWD08xx/EWD831.html) by one of the all-time greats in computer science, the late [Edsger Dijkstra <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Edsger_W._Dijkstra)."
|
||||
]
|
||||
|
|
@ -1136,7 +1144,7 @@
|
|||
"\n",
|
||||
"In simple words, anything that may be used on the *right-hand* side of an assignment statement without creating a `SyntaxError` is an expression.\n",
|
||||
"\n",
|
||||
"What we have said about *individual* operators before, namely that they have *no* permanent side effects in memory, actually belongs here, to begin with: The absence of any *permanent* side effects is the characteristic property of expressions, and all the code cells in the \"*(Arithmetic) Operators*\" section in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#%28Arithmetic%29-Operators) of this chapter are examples of expressions.\n",
|
||||
"What we have said about *individual* operators before, namely that they have *no* permanent side effects in memory, actually belongs here, to begin with: The absence of any *permanent* side effects is the characteristic property of expressions, and all the code cells in the \"*(Arithmetic) Operators*\" section in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#%28Arithmetic%29-Operators) of this chapter are examples of expressions.\n",
|
||||
"\n",
|
||||
"The simplest possible expressions contain only one variable or literal. The output below a code cell is Jupyter's way of returning the reference to the object to us!\n",
|
||||
"\n",
|
||||
|
|
@ -1406,7 +1414,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"... calling the built-in [print() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#print) function does *neither* change the memory *nor* evaluate to an object (disregarding the `None` object explained in [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb#Function-Definitions)). We could view changing the computer's screen as a side effect but this is outside of Python's memory!\n",
|
||||
"... calling the built-in [print() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#print) function does *neither* change the memory *nor* evaluate to an object (disregarding the `None` object explained in [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/00_content.ipynb#Function-Definitions)). We could view changing the computer's screen as a side effect but this is outside of Python's memory!\n",
|
||||
"\n",
|
||||
"Also, the cell below has *no* output! It only looks like it does as Jupyter redirects whatever [print() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#print) writes to the \"screen\" to below a cell. We see a difference to the expressions above in that there are no brackets `[...]` next to the output showing the execution count number."
|
||||
]
|
||||
|
|
@ -1685,7 +1693,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/01_elements/04_exercises.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/01_elements/04_exercises.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -18,7 +18,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The exercises below assume that you have read the [second part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/03_content.ipynb) Chapter 1.\n",
|
||||
"The exercises below assume that you have read the [second part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/03_content.ipynb) Chapter 1.\n",
|
||||
"\n",
|
||||
"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
|
||||
]
|
||||
|
|
@ -191,7 +191,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
@ -45,7 +45,7 @@
|
|||
" - distinct and well-contained areas/parts of the memory that hold the actual data\n",
|
||||
" - the concept by which Python manages the memory for us\n",
|
||||
" - can be classified into objects of the same **type** (i.e., same abstract \"structure\" but different concrete data)\n",
|
||||
" - built-in objects (incl. **literals**) vs. user-defined objects (cf., [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/00_content.ipynb))\n",
|
||||
" - built-in objects (incl. **literals**) vs. user-defined objects (cf., [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/00_content.ipynb))\n",
|
||||
" - e.g., `1`, `1.0`, and `\"one\"` are three different objects of distinct types that are also literals (i.e., by the way we type them into the command line Python knows what the value and type are)\n",
|
||||
"\n",
|
||||
"\n",
|
||||
|
|
@ -80,14 +80,14 @@
|
|||
" - ignored by Python\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"- functions (cf., [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb))\n",
|
||||
"- functions (cf., [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/00_content.ipynb))\n",
|
||||
" - named sequences of instructions\n",
|
||||
" - the smaller parts in a larger program\n",
|
||||
" - make a program more modular and thus easier to understand\n",
|
||||
" - include [built-in functions <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html) like [print() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#print), [sum() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#sum), or [len() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#len)\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"- flow control (cf., [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/03_conditionals/00_content.ipynb) and [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/00_content.ipynb))\n",
|
||||
"- flow control (cf., [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/03_conditionals/00_content.ipynb) and [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/00_content.ipynb))\n",
|
||||
" - expression of **business logic** or an **algorithm**\n",
|
||||
" - conditional execution of parts of a program (e.g., `if` statements)\n",
|
||||
" - repetitive execution of parts of a program (e.g., `for`-loops)"
|
||||
|
|
@ -110,7 +110,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -11,7 +11,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb) and the [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/03_content.ipynb) part of Chapter 1.\n",
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb) and the [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/03_content.ipynb) part of Chapter 1.\n",
|
||||
"\n",
|
||||
"Be concise in your answers! Most questions can be answered in *one* sentence."
|
||||
]
|
||||
|
|
@ -194,7 +194,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/01_elements/07_resources.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/01_elements/07_resources.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -83,7 +83,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/02_functions/00_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/02_functions/00_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -30,7 +30,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"In [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#Example:-Averaging-all-even-Numbers-in-a-List), we simply typed the code to calculate the average of the even numbers in a list of whole numbers into several code cells. Then, we executed them one after another. We had no way of *reusing* the code except for either executing cells multiple times. And, whenever we find ourselves doing repetitive manual work, we can be sure that there must be a way of automating what we are doing.\n",
|
||||
"In [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#Example:-Averaging-all-even-Numbers-in-a-List), we simply typed the code to calculate the average of the even numbers in a list of whole numbers into several code cells. Then, we executed them one after another. We had no way of *reusing* the code except for either executing cells multiple times. And, whenever we find ourselves doing repetitive manual work, we can be sure that there must be a way of automating what we are doing.\n",
|
||||
"\n",
|
||||
"This chapter shows how Python offers language constructs that let us **define** functions ourselves that we may then **call** just like the built-in ones. Also, we look at how we can extend our Python installation with functionalities written by other people."
|
||||
]
|
||||
|
|
@ -307,7 +307,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"To execute a function, we **call** it with the **call operator** `()` as shown many times in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb) and above.\n",
|
||||
"To execute a function, we **call** it with the **call operator** `()` as shown many times in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb) and above.\n",
|
||||
"\n",
|
||||
"If we are unsure whether a variable references a function or not, we can verify that with the built-in [callable() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#callable) function.\n",
|
||||
"\n",
|
||||
|
|
@ -538,7 +538,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Notice the subtle difference compared to the behavior of the `//` operator in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb##%28Arithmetic#%29-Operators) that \"rounds\" towards minus infinity: [int() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#int) always \"rounds\" towards `0`."
|
||||
"Notice the subtle difference compared to the behavior of the `//` operator in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb##%28Arithmetic#%29-Operators) that \"rounds\" towards minus infinity: [int() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#int) always \"rounds\" towards `0`."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -592,7 +592,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-18-af421b358f21>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"seven\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[18], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;43mint\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mseven\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mValueError\u001b[0m: invalid literal for int() with base 10: 'seven'"
|
||||
]
|
||||
}
|
||||
|
|
@ -869,7 +869,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"We may create so-called *user-defined* **functions** with the `def` statement (cf., [reference <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/reference/compound_stmts.html#function-definitions)). To extend an already familiar example, we reuse the introductory example from [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#Best-Practices) in its final Pythonic version and transform it into the function `average_evens()` below. We replace the variable name `numbers` with `integers` for didactical purposes in the first couple of examples.\n",
|
||||
"We may create so-called *user-defined* **functions** with the `def` statement (cf., [reference <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/reference/compound_stmts.html#function-definitions)). To extend an already familiar example, we reuse the introductory example from [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#Best-Practices) in its final Pythonic version and transform it into the function `average_evens()` below. We replace the variable name `numbers` with `integers` for didactical purposes in the first couple of examples.\n",
|
||||
"\n",
|
||||
"A function's **name** must be chosen according to the same naming rules as ordinary variables since Python manages function names like variables. In this book, we further adopt the convention of ending function names with parentheses `()` in text cells for faster comprehension when reading (i.e., `average_evens()` vs. `average_evens`). These are *not* part of the name but must always be written out in the `def` statement for syntactic reasons.\n",
|
||||
"\n",
|
||||
|
|
@ -881,7 +881,7 @@
|
|||
"\n",
|
||||
"A function may specify an *explicit* **return value** (i.e., \"result\" or \"output\") with the `return` statement (cf., [reference <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/reference/simple_stmts.html#the-return-statement)): Functions that have one are considered **fruitful**; otherwise, they are **void**. Functions of the latter kind are still useful because of their **side effects**. For example, the built-in [print() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#print) function changes what we see on the screen. Strictly speaking, [print() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#print) and other void functions also have an *implicit* return value, namely the `None` object.\n",
|
||||
"\n",
|
||||
"A function should define a **docstring** that describes what it does in a short subject line, what parameters it expects (i.e., their types), and what it returns, if anything. A docstring is a syntactically valid multi-line string (i.e., type `str`) defined within **triple-double quotes** `\"\"\"`. Strings are covered in depth in [Chapter 6 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/00_content.ipynb#The-str-Type). Widely adopted standards for docstrings are [PEP 257 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://www.python.org/dev/peps/pep-0257/) and section 3.8 of [Google's Python Style Guide <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/google/styleguide/blob/gh-pages/pyguide.md)."
|
||||
"A function should define a **docstring** that describes what it does in a short subject line, what parameters it expects (i.e., their types), and what it returns, if anything. A docstring is a syntactically valid multi-line string (i.e., type `str`) defined within **triple-double quotes** `\"\"\"`. Strings are covered in depth in [Chapter 6 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/00_content.ipynb#The-str-Type). Widely adopted standards for docstrings are [PEP 257 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://www.python.org/dev/peps/pep-0257/) and section 3.8 of [Google's Python Style Guide <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/google/styleguide/blob/gh-pages/pyguide.md)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1012,7 +1012,7 @@
|
|||
"source": [
|
||||
"Its value may seem awkward at first: It consists of a location showing where the function is defined (i.e., `__main__` here, which is Python's way of saying \"in this notebook\") and the signature wrapped inside angle brackets `<` and `>`.\n",
|
||||
" \n",
|
||||
"The angle brackets are a convention to indicate that the value may *not* be used as a *literal* (i.e., typed back into another code cell). [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/00_content.ipynb) introduces the concept of a **text representation** of an object, which is related to the *semantic* meaning of an object's value as discussed in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#Value-/-\"Meaning\"), and the angle brackets convention is one such way to represent an object as text. When executed, the angle brackets cause a `SyntaxError` because Python expects the `<` operator to come with an operand on both sides (cf., [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/03_conditionals/00_content.ipynb#Relational-Operators))."
|
||||
"The angle brackets are a convention to indicate that the value may *not* be used as a *literal* (i.e., typed back into another code cell). [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/00_content.ipynb) introduces the concept of a **text representation** of an object, which is related to the *semantic* meaning of an object's value as discussed in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#Value-/-\"Meaning\"), and the angle brackets convention is one such way to represent an object as text. When executed, the angle brackets cause a `SyntaxError` because Python expects the `<` operator to come with an operand on both sides (cf., [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/03_conditionals/00_content.ipynb#Relational-Operators))."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1026,10 +1026,10 @@
|
|||
"outputs": [
|
||||
{
|
||||
"ename": "SyntaxError",
|
||||
"evalue": "invalid syntax (<ipython-input-31-7f49dff38622>, line 1)",
|
||||
"evalue": "invalid syntax (2246690741.py, line 1)",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;36m File \u001b[0;32m\"<ipython-input-31-7f49dff38622>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m <function __main__.average_evens(numbers)>\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
|
||||
"\u001b[0;36m Cell \u001b[0;32mIn[31], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m <function __main__.average_evens(numbers)>\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -1102,10 +1102,10 @@
|
|||
"\n",
|
||||
"average_evens(integers)\n",
|
||||
" Calculate the average of all even numbers in a list.\n",
|
||||
" \n",
|
||||
"\n",
|
||||
" Args:\n",
|
||||
" integers (list of int's): whole numbers to be averaged\n",
|
||||
" \n",
|
||||
"\n",
|
||||
" Returns:\n",
|
||||
" average (float)\n",
|
||||
"\n"
|
||||
|
|
@ -1148,8 +1148,8 @@
|
|||
"\n",
|
||||
"Returns:\n",
|
||||
" average (float)\n",
|
||||
"\u001b[0;31mFile:\u001b[0m ~/repos/intro-to-python/02_functions/<ipython-input-27-bcb78a3113d7>\n",
|
||||
"\u001b[0;31mType:\u001b[0m function\n"
|
||||
"\u001b[0;31mFile:\u001b[0m /tmp/ipykernel_152540/3598721284.py\n",
|
||||
"\u001b[0;31mType:\u001b[0m function"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
|
|
@ -1197,8 +1197,8 @@
|
|||
"\u001b[0;34m\u001b[0m \u001b[0mevens\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mn\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mn\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mintegers\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0;36m2\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\n",
|
||||
"\u001b[0;34m\u001b[0m \u001b[0maverage\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mevens\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mevens\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n",
|
||||
"\u001b[0;34m\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0maverage\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;31mFile:\u001b[0m ~/repos/intro-to-python/02_functions/<ipython-input-27-bcb78a3113d7>\n",
|
||||
"\u001b[0;31mType:\u001b[0m function\n"
|
||||
"\u001b[0;31mFile:\u001b[0m /tmp/ipykernel_152540/3598721284.py\n",
|
||||
"\u001b[0;31mType:\u001b[0m function"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
|
|
@ -1237,7 +1237,7 @@
|
|||
"\n",
|
||||
"sum(iterable, /, start=0)\n",
|
||||
" Return the sum of a 'start' value (default: 0) plus an iterable of numbers\n",
|
||||
" \n",
|
||||
"\n",
|
||||
" When the iterable is empty, return the start value.\n",
|
||||
" This function is intended specifically for use with numeric values and may\n",
|
||||
" reject non-numeric types.\n",
|
||||
|
|
@ -1416,7 +1416,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-41-756dfa02d4a8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mintegers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[41], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mintegers\u001b[49m\n",
|
||||
"\u001b[0;31mNameError\u001b[0m: name 'integers' is not defined"
|
||||
]
|
||||
}
|
||||
|
|
@ -1441,7 +1441,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-42-df246468d241>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mevens\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[42], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mevens\u001b[49m\n",
|
||||
"\u001b[0;31mNameError\u001b[0m: name 'evens' is not defined"
|
||||
]
|
||||
}
|
||||
|
|
@ -1466,7 +1466,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-43-c3fe9b4213f6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0maverage\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[43], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43maverage\u001b[49m\n",
|
||||
"\u001b[0;31mNameError\u001b[0m: name 'average' is not defined"
|
||||
]
|
||||
}
|
||||
|
|
@ -1483,7 +1483,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"[PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0A%0Adef%20average_evens%28integers%29%3A%0A%20%20%20%20evens%20%3D%20%5Bn%20for%20n%20in%20integers%20if%20n%20%25%202%20%3D%3D%200%5D%0A%20%20%20%20average%20%3D%20sum%28evens%29%20/%20len%28evens%29%0A%20%20%20%20return%20average%0A%0Aresult%20%3D%20average_evens%28numbers%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) visualizes what happens in memory: To be precise, in the exact moment when the function call is initiated and `numbers` passed in as the `integers` argument, there are *two* references to the *same* `list` object (cf., steps 4-5 in the visualization). We also see how Python creates a *new* **frame** that holds the function's local scope (i.e., \"internal names\") in addition to the **global** frame. Frames are nothing but [namespaces <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Namespace) to *isolate* the names of different **scopes** from each other. The list comprehension `[n for n in integers if n % 2 == 0]` constitutes yet another frame that is in scope as the `list` object assigned to `evens` is *being* created (cf., steps 6-20). When the function returns, only the global frame is left (cf., last step)."
|
||||
"[PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0A%0Adef%20average_evens%28integers%29%3A%0A%20%20%20%20evens%20%3D%20%5Bn%20for%20n%20in%20integers%20if%20n%20%25%202%20%3D%3D%200%5D%0A%20%20%20%20average%20%3D%20sum%28evens%29%20/%20len%28evens%29%0A%20%20%20%20return%20average%0A%0Aresult%20%3D%20average_evens%28numbers%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) visualizes what happens in memory: To be precise, in the exact moment when the function call is initiated and `numbers` passed in as the `integers` argument, there are *two* references to the *same* `list` object (cf., steps 4-5 in the visualization). We also see how Python creates a *new* **frame** that holds the function's local scope (i.e., \"internal names\") in addition to the **global** frame. Frames are nothing but [namespaces <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Namespace) to *isolate* the names of different **scopes** from each other. The list comprehension `[n for n in integers if n % 2 == 0]` constitutes yet another frame that is in scope as the `list` object assigned to `evens` is *being* created (cf., steps 6-20). When the function returns, only the global frame is left (cf., last step)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1645,9 +1645,9 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"[PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0A%0Adef%20average_wrong%28integers%29%3A%0A%20%20%20%20evens%20%3D%20%5Bn%20for%20n%20in%20numbers%20if%20n%20%25%202%20%3D%3D%200%5D%0A%20%20%20%20average%20%3D%20sum%28evens%29%20/%20len%28evens%29%0A%20%20%20%20return%20average%0A%0Aresult%20%3D%20average_wrong%28%5B123,%20456,%20789%5D%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) is again helpful at visualizing the error interactively: Creating the `list` object `evens` eventually references takes *16* computational steps, namely two for managing the list comprehension, one for setting up an empty `list` object, *twelve* for filling it with elements derived from `numbers` in the global scope (i.e., that is the error), and one to make `evens` reference it (cf., steps 6-21).\n",
|
||||
"[PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0A%0Adef%20average_wrong%28integers%29%3A%0A%20%20%20%20evens%20%3D%20%5Bn%20for%20n%20in%20numbers%20if%20n%20%25%202%20%3D%3D%200%5D%0A%20%20%20%20average%20%3D%20sum%28evens%29%20/%20len%28evens%29%0A%20%20%20%20return%20average%0A%0Aresult%20%3D%20average_wrong%28%5B123,%20456,%20789%5D%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) is again helpful at visualizing the error interactively: Creating the `list` object `evens` eventually references takes *16* computational steps, namely two for managing the list comprehension, one for setting up an empty `list` object, *twelve* for filling it with elements derived from `numbers` in the global scope (i.e., that is the error), and one to make `evens` reference it (cf., steps 6-21).\n",
|
||||
"\n",
|
||||
"The frames logic shown by PythonTutor is the mechanism with which Python not only manages the names inside *one* function call but also for *many* potentially *simultaneous* calls, as revealed in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/00_content.ipynb#Trivial-Example:-Countdown). It is the reason why we may reuse the same names for the parameters and variables inside both `average_evens()` and `average_wrong()` without Python mixing them up. So, as we already read in the [Zen of Python <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://www.python.org/dev/peps/pep-0020/), \"namespaces are one honking great idea\" (cf., `import this`), and a frame is just a special kind of namespace."
|
||||
"The frames logic shown by PythonTutor is the mechanism with which Python not only manages the names inside *one* function call but also for *many* potentially *simultaneous* calls, as revealed in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/00_content.ipynb#Trivial-Example:-Countdown). It is the reason why we may reuse the same names for the parameters and variables inside both `average_evens()` and `average_wrong()` without Python mixing them up. So, as we already read in the [Zen of Python <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://www.python.org/dev/peps/pep-0020/), \"namespaces are one honking great idea\" (cf., `import this`), and a frame is just a special kind of namespace."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1786,7 +1786,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-51-f47586a118b9>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32massert\u001b[0m \u001b[0maverage_evens\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m40.0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m41.1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m42.2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m43.3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m44.4\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m87.0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[51], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m average_evens([\u001b[38;5;241m40.0\u001b[39m, \u001b[38;5;241m41.1\u001b[39m, \u001b[38;5;241m42.2\u001b[39m, \u001b[38;5;241m43.3\u001b[39m, \u001b[38;5;241m44.4\u001b[39m]) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m87.0\u001b[39m\n",
|
||||
"\u001b[0;31mAssertionError\u001b[0m: "
|
||||
]
|
||||
}
|
||||
|
|
@ -1910,7 +1910,7 @@
|
|||
"source": [
|
||||
"The reason why everything works is that *every* time we (re-)assign an object to a variable *inside* a function's body with the `=` statement, this is done in the *local* scope by default. There are ways to change variables existing in an outer scope from within a function, but this is a rather advanced topic.\n",
|
||||
"\n",
|
||||
"[PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0A%0Adef%20average_evens%28integers%29%3A%0A%20%20%20%20numbers%20%3D%20%5Bround%28n%29%20for%20n%20in%20integers%5D%0A%20%20%20%20evens%20%3D%20%5Bn%20for%20n%20in%20numbers%20if%20n%20%25%202%20%3D%3D%200%5D%0A%20%20%20%20average%20%3D%20sum%28evens%29%20/%20len%28evens%29%0A%20%20%20%20return%20average%0A%0Aresult%20%3D%20average_evens%28%5B40.0,%2041.1,%2042.2,%2043.3,%2044.4%5D%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows how *two* `numbers` variables exist in *different* scopes referencing *different* objects (cf., steps 14-25) when we execute `average_evens([40.0, 41.1, 42.2, 43.3, 44.4])`.\n",
|
||||
"[PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0A%0Adef%20average_evens%28integers%29%3A%0A%20%20%20%20numbers%20%3D%20%5Bround%28n%29%20for%20n%20in%20integers%5D%0A%20%20%20%20evens%20%3D%20%5Bn%20for%20n%20in%20numbers%20if%20n%20%25%202%20%3D%3D%200%5D%0A%20%20%20%20average%20%3D%20sum%28evens%29%20/%20len%28evens%29%0A%20%20%20%20return%20average%0A%0Aresult%20%3D%20average_evens%28%5B40.0,%2041.1,%2042.2,%2043.3,%2044.4%5D%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows how *two* `numbers` variables exist in *different* scopes referencing *different* objects (cf., steps 14-25) when we execute `average_evens([40.0, 41.1, 42.2, 43.3, 44.4])`.\n",
|
||||
"\n",
|
||||
"Variables whose names collide with the ones of variables in enclosing scopes - and the global scope is just the most enclosing scope - are said to **shadow** them.\n",
|
||||
"\n",
|
||||
|
|
@ -1999,7 +1999,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"[PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0A%0Adef%20average_evens%28numbers%29%3A%0A%20%20%20%20evens%20%3D%20%5Bn%20for%20n%20in%20numbers%20if%20n%20%25%202%20%3D%3D%200%5D%0A%20%20%20%20average%20%3D%20sum%28evens%29%20/%20len%28evens%29%0A%20%20%20%20return%20average%0A%0Aresult%20%3D%20average_evens%28numbers%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) reveals that in this example there are *two* `numbers` variables in *different* scope referencing the *same* `list` object in memory (cf., steps 4-23)."
|
||||
"[PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0A%0Adef%20average_evens%28numbers%29%3A%0A%20%20%20%20evens%20%3D%20%5Bn%20for%20n%20in%20numbers%20if%20n%20%25%202%20%3D%3D%200%5D%0A%20%20%20%20average%20%3D%20sum%28evens%29%20/%20len%28evens%29%0A%20%20%20%20return%20average%0A%0Aresult%20%3D%20average_evens%28numbers%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) reveals that in this example there are *two* `numbers` variables in *different* scope referencing the *same* `list` object in memory (cf., steps 4-23)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -2021,7 +2021,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"So far, we have specified only one parameter in each of our user-defined functions. In [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#%28Arithmetic%29-Operators), however, we saw the built-in [divmod() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#divmod) function take two arguments. And, the order in which they are passed in matters! Whenever we call a function and list its arguments in a comma separated manner, we say that we pass in the arguments *by position* or refer to them as **positional arguments**."
|
||||
"So far, we have specified only one parameter in each of our user-defined functions. In [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#%28Arithmetic%29-Operators), however, we saw the built-in [divmod() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#divmod) function take two arguments. And, the order in which they are passed in matters! Whenever we call a function and list its arguments in a comma separated manner, we say that we pass in the arguments *by position* or refer to them as **positional arguments**."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -2274,10 +2274,10 @@
|
|||
"outputs": [
|
||||
{
|
||||
"ename": "SyntaxError",
|
||||
"evalue": "positional argument follows keyword argument (<ipython-input-65-b00eb6f72e84>, line 1)",
|
||||
"evalue": "positional argument follows keyword argument (159253642.py, line 1)",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;36m File \u001b[0;32m\"<ipython-input-65-b00eb6f72e84>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m scaled_average_evens(numbers=numbers, 2)\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m positional argument follows keyword argument\n"
|
||||
"\u001b[0;36m Cell \u001b[0;32mIn[65], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m scaled_average_evens(numbers=numbers, 2)\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m positional argument follows keyword argument\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -2312,7 +2312,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-66-d910518345ec>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mscaled_average_evens\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnumbers\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[66], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mscaled_average_evens\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnumbers\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: scaled_average_evens() missing 1 required positional argument: 'scalar'"
|
||||
]
|
||||
}
|
||||
|
|
@ -2337,7 +2337,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-67-2e7ca1d2a555>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mscaled_average_evens\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnumbers\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[67], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mscaled_average_evens\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnumbers\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m3\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: scaled_average_evens() takes 2 positional arguments but 3 were given"
|
||||
]
|
||||
}
|
||||
|
|
@ -2782,7 +2782,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-81-12eb635366db>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0maverage_evens\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnumbers\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[81], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43maverage_evens\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnumbers\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: average_evens() takes 1 positional argument but 2 were given"
|
||||
]
|
||||
}
|
||||
|
|
@ -3012,7 +3012,7 @@
|
|||
"source": [
|
||||
"The main point of having functions without a reference to them is to use them in a situation where we know ahead of time that we use the function only *once*.\n",
|
||||
"\n",
|
||||
"Popular applications of lambda expressions occur in combination with the **map-filter-reduce** paradigm (cf., [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/00_content.ipynb#Lambda-Expressions))."
|
||||
"Popular applications of lambda expressions occur in combination with the **map-filter-reduce** paradigm (cf., [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/00_content.ipynb#Lambda-Expressions))."
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -3032,7 +3032,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/02_functions/01_exercises.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/02_functions/01_exercises.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -18,7 +18,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The exercises below assume that you have read the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb) of Chapter 2.\n",
|
||||
"The exercises below assume that you have read the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/00_content.ipynb) of Chapter 2.\n",
|
||||
"\n",
|
||||
"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
|
||||
]
|
||||
|
|
@ -38,7 +38,7 @@
|
|||
"\n",
|
||||
"Hints:\n",
|
||||
"- use an appropriate approximation for $\\pi$\n",
|
||||
"- you may use the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html) to do so if you have already looked at the [second part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/02_content.ipynb) of Chapter 2."
|
||||
"- you may use the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html) to do so if you have already looked at the [second part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/02_content.ipynb) of Chapter 2."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -220,7 +220,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/02_functions/02_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/02_functions/02_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -127,7 +127,7 @@
|
|||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"<module 'math' from '/home/webartifex/.pyenv/versions/3.8.6/lib/python3.8/lib-dynload/math.cpython-38-x86_64-linux-gnu.so'>"
|
||||
"<module 'math' from '/usr/lib64/python3.12/lib-dynload/math.cpython-312-x86_64-linux-gnu.so'>"
|
||||
]
|
||||
},
|
||||
"execution_count": 2,
|
||||
|
|
@ -227,6 +227,7 @@
|
|||
" 'atan',\n",
|
||||
" 'atan2',\n",
|
||||
" 'atanh',\n",
|
||||
" 'cbrt',\n",
|
||||
" 'ceil',\n",
|
||||
" 'comb',\n",
|
||||
" 'copysign',\n",
|
||||
|
|
@ -238,6 +239,7 @@
|
|||
" 'erf',\n",
|
||||
" 'erfc',\n",
|
||||
" 'exp',\n",
|
||||
" 'exp2',\n",
|
||||
" 'expm1',\n",
|
||||
" 'fabs',\n",
|
||||
" 'factorial',\n",
|
||||
|
|
@ -254,6 +256,7 @@
|
|||
" 'isinf',\n",
|
||||
" 'isnan',\n",
|
||||
" 'isqrt',\n",
|
||||
" 'lcm',\n",
|
||||
" 'ldexp',\n",
|
||||
" 'lgamma',\n",
|
||||
" 'log',\n",
|
||||
|
|
@ -262,6 +265,7 @@
|
|||
" 'log2',\n",
|
||||
" 'modf',\n",
|
||||
" 'nan',\n",
|
||||
" 'nextafter',\n",
|
||||
" 'perm',\n",
|
||||
" 'pi',\n",
|
||||
" 'pow',\n",
|
||||
|
|
@ -271,10 +275,12 @@
|
|||
" 'sin',\n",
|
||||
" 'sinh',\n",
|
||||
" 'sqrt',\n",
|
||||
" 'sumprod',\n",
|
||||
" 'tan',\n",
|
||||
" 'tanh',\n",
|
||||
" 'tau',\n",
|
||||
" 'trunc']"
|
||||
" 'trunc',\n",
|
||||
" 'ulp']"
|
||||
]
|
||||
},
|
||||
"execution_count": 5,
|
||||
|
|
@ -428,7 +434,7 @@
|
|||
"source": [
|
||||
"Observe how the arguments passed to functions do not need to be just variables or simple literals. Instead, we may pass in any *expression* that evaluates to a *new* object of the type the function expects.\n",
|
||||
"\n",
|
||||
"So just as a reminder from the expression vs. statement discussion in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/03_content.ipynb#Expressions): An expression is *any* syntactically correct combination of variables and literals with operators. And the call operator `()` is yet another operator. So both of the next two code cells are just expressions! They have no permanent side effects in memory. We may execute them as often as we want *without* changing the state of the program (i.e., this Jupyter notebook).\n",
|
||||
"So just as a reminder from the expression vs. statement discussion in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/03_content.ipynb#Expressions): An expression is *any* syntactically correct combination of variables and literals with operators. And the call operator `()` is yet another operator. So both of the next two code cells are just expressions! They have no permanent side effects in memory. We may execute them as often as we want *without* changing the state of the program (i.e., this Jupyter notebook).\n",
|
||||
"\n",
|
||||
"So, regarding the very next cell in particular: Although the `2 ** 2` creates a *new* object `4` in memory that is then immediately passed into the [math.sqrt() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/math.html#math.sqrt) function, once that function call returns, \"all is lost\" and the newly created `4` object is forgotten again, as well as the return value of [math.sqrt() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/math.html#math.sqrt)."
|
||||
]
|
||||
|
|
@ -589,7 +595,7 @@
|
|||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"<module 'random' from '/home/webartifex/.pyenv/versions/3.8.6/lib/python3.8/random.py'>"
|
||||
"<module 'random' from '/usr/lib64/python3.12/random.py'>"
|
||||
]
|
||||
},
|
||||
"execution_count": 16,
|
||||
|
|
@ -609,7 +615,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Besides the usual dunder-style attributes, the built-in [dir() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#dir) function lists some attributes in an upper case naming convention and many others starting with a *single* underscore `_`. To understand the former, we must wait until [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/00_content.ipynb), while the latter is explained further below."
|
||||
"Besides the usual dunder-style attributes, the built-in [dir() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#dir) function lists some attributes in an upper case naming convention and many others starting with a *single* underscore `_`. To understand the former, we must wait until [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/00_content.ipynb), while the latter is explained further below."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -632,8 +638,8 @@
|
|||
" 'SG_MAGICCONST',\n",
|
||||
" 'SystemRandom',\n",
|
||||
" 'TWOPI',\n",
|
||||
" '_ONE',\n",
|
||||
" '_Sequence',\n",
|
||||
" '_Set',\n",
|
||||
" '__all__',\n",
|
||||
" '__builtins__',\n",
|
||||
" '__cached__',\n",
|
||||
|
|
@ -650,8 +656,14 @@
|
|||
" '_cos',\n",
|
||||
" '_e',\n",
|
||||
" '_exp',\n",
|
||||
" '_fabs',\n",
|
||||
" '_floor',\n",
|
||||
" '_index',\n",
|
||||
" '_inst',\n",
|
||||
" '_isfinite',\n",
|
||||
" '_lgamma',\n",
|
||||
" '_log',\n",
|
||||
" '_log2',\n",
|
||||
" '_os',\n",
|
||||
" '_pi',\n",
|
||||
" '_random',\n",
|
||||
|
|
@ -664,6 +676,7 @@
|
|||
" '_urandom',\n",
|
||||
" '_warn',\n",
|
||||
" 'betavariate',\n",
|
||||
" 'binomialvariate',\n",
|
||||
" 'choice',\n",
|
||||
" 'choices',\n",
|
||||
" 'expovariate',\n",
|
||||
|
|
@ -674,6 +687,7 @@
|
|||
" 'lognormvariate',\n",
|
||||
" 'normalvariate',\n",
|
||||
" 'paretovariate',\n",
|
||||
" 'randbytes',\n",
|
||||
" 'randint',\n",
|
||||
" 'random',\n",
|
||||
" 'randrange',\n",
|
||||
|
|
@ -1013,7 +1027,7 @@
|
|||
"source": [
|
||||
"[numpy](http://www.numpy.org/) is the de-facto standard in the Python world for handling **array-like** data. That is a fancy word for data that can be put into a matrix or vector format.\n",
|
||||
"\n",
|
||||
"As [numpy](http://www.numpy.org/) is *not* in the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html), it must be *manually* installed, for example, with the [pip](https://pip.pypa.io/en/stable/) tool. As mentioned in [Chapter 0 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/00_intro/00_content.ipynb#Markdown-Cells-vs.-Code-Cells), to execute terminal commands from within a Jupyter notebook, we start a code cell with an exclamation mark.\n",
|
||||
"As [numpy](http://www.numpy.org/) is *not* in the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html), it must be *manually* installed, for example, with the [pip](https://pip.pypa.io/en/stable/) tool. As mentioned in [Chapter 0 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/00_intro/00_content.ipynb#Markdown-Cells-vs.-Code-Cells), to execute terminal commands from within a Jupyter notebook, we start a code cell with an exclamation mark.\n",
|
||||
"\n",
|
||||
"If you are running this notebook with an installation of the [Anaconda Distribution](https://www.anaconda.com/distribution/), then [numpy](http://www.numpy.org/) is probably already installed. Running the cell below confirms that."
|
||||
]
|
||||
|
|
@ -1031,7 +1045,7 @@
|
|||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Requirement already satisfied: numpy in /home/webartifex/repos/intro-to-python/.venv/lib/python3.8/site-packages (1.19.2)\n"
|
||||
"Requirement already satisfied: numpy in /home/alexander/Repositories/intro-to-python/.venv/lib64/python3.12/site-packages (1.26.4)\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -1086,7 +1100,7 @@
|
|||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"<module 'numpy' from '/home/webartifex/repos/intro-to-python/.venv/lib/python3.8/site-packages/numpy/__init__.py'>"
|
||||
"<module 'numpy' from '/home/alexander/Repositories/intro-to-python/.venv/lib64/python3.12/site-packages/numpy/__init__.py'>"
|
||||
]
|
||||
},
|
||||
"execution_count": 31,
|
||||
|
|
@ -1318,7 +1332,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"For sure, we can create local modules and packages. In the Chapter 2 directory, there is a [*sample_module.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/02_functions/sample_module.py) file that contains, among others, a function equivalent to the final version of `average_evens()`. To be realistic, this sample module is structured in a modular manner with several functions building on each other. It is best to skim over it *now* before reading on.\n",
|
||||
"For sure, we can create local modules and packages. In the Chapter 2 directory, there is a [*sample_module.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/02_functions/sample_module.py) file that contains, among others, a function equivalent to the final version of `average_evens()`. To be realistic, this sample module is structured in a modular manner with several functions building on each other. It is best to skim over it *now* before reading on.\n",
|
||||
"\n",
|
||||
"To make code we put into a *.py* file available in our program, we import it as a module just as we did above with modules in the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html) or third-party packages.\n",
|
||||
"\n",
|
||||
|
|
@ -1338,7 +1352,7 @@
|
|||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"/home/webartifex/repos/intro-to-python/02_functions\n"
|
||||
"/home/alexander/Repositories/intro-to-python/02_functions\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -1384,7 +1398,7 @@
|
|||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"<module 'sample_module' from '/home/webartifex/repos/intro-to-python/02_functions/sample_module.py'>"
|
||||
"<module 'sample_module' from '/home/alexander/Repositories/intro-to-python/02_functions/sample_module.py'>"
|
||||
]
|
||||
},
|
||||
"execution_count": 41,
|
||||
|
|
@ -1404,7 +1418,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Disregarding the dunder-style attributes, `mod` defines the attributes `_round_all`, `_scaled_average`, `average`, `average_evens`, and `average_odds`, which are exactly the ones we would expect from reading the [*sample_module.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/02_functions/sample_module.py) file.\n",
|
||||
"Disregarding the dunder-style attributes, `mod` defines the attributes `_round_all`, `_scaled_average`, `average`, `average_evens`, and `average_odds`, which are exactly the ones we would expect from reading the [*sample_module.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/02_functions/sample_module.py) file.\n",
|
||||
"\n",
|
||||
"A convention when working with imported code is to *disregard* any attributes starting with a single underscore `_`. These are considered **private** and constitute **implementation details** the author of the imported code might change in a future version of his software. We *must not* rely on them in any way.\n",
|
||||
"\n",
|
||||
|
|
@ -1455,7 +1469,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"We use the imported `mod.average_evens()` just like `average_evens()` defined in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb) of this chapter. The advantage we get from **modularization** with *.py* files is that we can now easily reuse functions across different Jupyter notebooks without redefining them again and again. Also, we can \"source out\" code that distracts from the storyline told in a notebook."
|
||||
"We use the imported `mod.average_evens()` just like `average_evens()` defined in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/00_content.ipynb) of this chapter. The advantage we get from **modularization** with *.py* files is that we can now easily reuse functions across different Jupyter notebooks without redefining them again and again. Also, we can \"source out\" code that distracts from the storyline told in a notebook."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1499,12 +1513,12 @@
|
|||
"\n",
|
||||
"average_evens(numbers, *, scalar=1)\n",
|
||||
" Calculate the average of all even numbers in a list.\n",
|
||||
" \n",
|
||||
"\n",
|
||||
" Args:\n",
|
||||
" numbers (list of int's/float's): numbers to be averaged;\n",
|
||||
" if non-whole numbers are provided, they are rounded\n",
|
||||
" scalar (float, optional): multiplies the average; defaults to 1\n",
|
||||
" \n",
|
||||
"\n",
|
||||
" Returns:\n",
|
||||
" scaled_average (float)\n",
|
||||
"\n"
|
||||
|
|
@ -1571,7 +1585,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Packages are a generalization of modules, and we look at one in detail in [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/04_content.ipynb#Packages-vs.-Modules).\n",
|
||||
"Packages are a generalization of modules, and we look at one in detail in [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/04_content.ipynb#Packages-vs.-Modules).\n",
|
||||
"\n",
|
||||
"As a further reading on modules and packages, we refer to the [official tutorial <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/tutorial/modules.html)."
|
||||
]
|
||||
|
|
@ -1593,7 +1607,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -58,7 +58,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -11,7 +11,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb) and the [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/02_content.ipynb) part of Chapter 2.\n",
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/00_content.ipynb) and the [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/02_content.ipynb) part of Chapter 2.\n",
|
||||
"\n",
|
||||
"Be concise in your answers! Most questions can be answered in *one* sentence."
|
||||
]
|
||||
|
|
@ -208,7 +208,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/03_conditionals/00_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/03_conditionals/00_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -30,7 +30,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"We analyzed every aspect of the `average_evens()` function in [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb) except for the `if`-related parts. While it does what we expect it to, there is a whole lot more to learn by taking it apart. In particular, the `if` may occur within both a **statement** or an **expression**, analogous as to how a noun in a natural language can be the subject of *or* an object in a sentence. What is common to both usages is that it leads to code being executed for *parts* of the input only. It is a way of controlling the **flow of execution** in a program.\n",
|
||||
"We analyzed every aspect of the `average_evens()` function in [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/00_content.ipynb) except for the `if`-related parts. While it does what we expect it to, there is a whole lot more to learn by taking it apart. In particular, the `if` may occur within both a **statement** or an **expression**, analogous as to how a noun in a natural language can be the subject of *or* an object in a sentence. What is common to both usages is that it leads to code being executed for *parts* of the input only. It is a way of controlling the **flow of execution** in a program.\n",
|
||||
"\n",
|
||||
"After deconstructing `if` in the first part of this chapter, we take a close look at a similar concept, namely handling **exceptions**."
|
||||
]
|
||||
|
|
@ -150,7 +150,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"There are, however, cases where the `==` operator seems to not work intuitively. [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/00_content.ipynb#Imprecision) provides more insights into this \"bug.\""
|
||||
"There are, however, cases where the `==` operator seems to not work intuitively. [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/00_content.ipynb#Imprecision) provides more insights into this \"bug.\""
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -351,7 +351,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Let's not confuse the boolean `False` with `None`, another built-in object! We saw the latter before in [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb#Function-Definitions) as the *implicit* return value of a function without a `return` statement.\n",
|
||||
"Let's not confuse the boolean `False` with `None`, another built-in object! We saw the latter before in [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/00_content.ipynb#Function-Definitions) as the *implicit* return value of a function without a `return` statement.\n",
|
||||
"\n",
|
||||
"We might think of `None` indicating a \"maybe\" or even an \"unknown\" answer; however, for Python, there are no \"maybe\" or \"unknown\" objects, as we see further below!\n",
|
||||
"\n",
|
||||
|
|
@ -438,7 +438,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"`True`, `False`, and `None` have the property that they each exist in memory only *once*. Objects designed this way are so-called **singletons**. This **[design pattern <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Design_Patterns)** was originally developed to keep a program's memory usage at a minimum. It may only be employed in situations where we know that an object does *not* mutate its value (i.e., to reuse the bag analogy from [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#Objects-vs.-Types-vs.-Values), no flipping of $0$s and $1$s in the bag is allowed). In languages \"closer\" to the memory like C, we would have to code this singleton logic ourselves, but Python has this built in for *some* types.\n",
|
||||
"`True`, `False`, and `None` have the property that they each exist in memory only *once*. Objects designed this way are so-called **singletons**. This **[design pattern <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Design_Patterns)** was originally developed to keep a program's memory usage at a minimum. It may only be employed in situations where we know that an object does *not* mutate its value (i.e., to reuse the bag analogy from [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#Objects-vs.-Types-vs.-Values), no flipping of $0$s and $1$s in the bag is allowed). In languages \"closer\" to the memory like C, we would have to code this singleton logic ourselves, but Python has this built in for *some* types.\n",
|
||||
"\n",
|
||||
"We verify this with either the `is` operator or by comparing memory addresses."
|
||||
]
|
||||
|
|
@ -2606,7 +2606,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mZeroDivisionError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-78-7996bd5496ba>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0muser_input\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrandom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mchoice\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m4\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m5\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;36m1\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0muser_input\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[78], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m user_input \u001b[38;5;241m=\u001b[39m random\u001b[38;5;241m.\u001b[39mchoice([\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m3\u001b[39m, \u001b[38;5;241m4\u001b[39m, \u001b[38;5;241m5\u001b[39m])\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;241;43m1\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[43muser_input\u001b[49m\n",
|
||||
"\u001b[0;31mZeroDivisionError\u001b[0m: division by zero"
|
||||
]
|
||||
}
|
||||
|
|
@ -2799,7 +2799,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/03_conditionals/01_exercises.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/03_conditionals/01_exercises.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -18,7 +18,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The exercises below assume that you have read [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/03_conditionals/00_content.ipynb).\n",
|
||||
"The exercises below assume that you have read [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/03_conditionals/00_content.ipynb).\n",
|
||||
"\n",
|
||||
"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
|
||||
]
|
||||
|
|
@ -184,7 +184,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/03_conditionals/02_exercises.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/03_conditionals/02_exercises.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -18,7 +18,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The exercises below assume that you have read [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/03_conditionals/00_content.ipynb).\n",
|
||||
"The exercises below assume that you have read [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/03_conditionals/00_content.ipynb).\n",
|
||||
"\n",
|
||||
"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
|
||||
]
|
||||
|
|
@ -61,7 +61,7 @@
|
|||
"source": [
|
||||
"**Q2**: Loop over the `numbers` list and *replace* numbers for which one of the two (or both) conditions apply with text strings `\"Fizz\"`, `\"Buzz\"`, or `\"FizzBuzz\"` using the indexing operator `[]` and the assignment statement `=`.\n",
|
||||
"\n",
|
||||
"In [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/03_content.ipynb#Who-am-I?-And-how-many?), we saw that Python starts indexing with `0` as the first element. Keep that in mind.\n",
|
||||
"In [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/03_content.ipynb#Who-am-I?-And-how-many?), we saw that Python starts indexing with `0` as the first element. Keep that in mind.\n",
|
||||
"\n",
|
||||
"So in each iteration of the `for`-loop, you have to determine an `index` variable as well as check the actual `number` for its divisors.\n",
|
||||
"\n",
|
||||
|
|
@ -119,7 +119,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
@ -44,7 +44,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -11,7 +11,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The questions below assume that you have read [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/03_conditionals/00_content.ipynb).\n",
|
||||
"The questions below assume that you have read [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/03_conditionals/00_content.ipynb).\n",
|
||||
"\n",
|
||||
"Be concise in your answers! Most questions can be answered in *one* sentence."
|
||||
]
|
||||
|
|
@ -180,7 +180,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/04_iteration/00_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/04_iteration/00_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -163,7 +163,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"As trivial as this seems, a lot of complexity is hidden in this implementation. In particular, the order in which objects are created and de-referenced in memory might not be apparent right away as [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=def%20countdown%28n%29%3A%0A%20%20%20%20if%20n%20%3D%3D%200%3A%0A%20%20%20%20%20%20%20%20print%28%22Happy%20new%20Year!%22%29%0A%20%20%20%20else%3A%0A%20%20%20%20%20%20%20%20print%28n%29%0A%20%20%20%20%20%20%20%20countdown%28n%20-%201%29%0A%0Acountdown%283%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows: Each time `countdown()` is called, Python creates a *new* frame in the part of the memory where it manages all the names. This way, Python *isolates* all the different `n` variables from each other. As new frames are created until we reach the base case, after which the frames are destroyed in the *reversed* order, this is called a **[stack <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Stack_(abstract_data_type))** of frames in computer science terminology. In simple words, a stack is a last-in-first-out (LIFO) task queue. Each frame has a single parent frame, namely the one whose recursive function call created it."
|
||||
"As trivial as this seems, a lot of complexity is hidden in this implementation. In particular, the order in which objects are created and de-referenced in memory might not be apparent right away as [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=def%20countdown%28n%29%3A%0A%20%20%20%20if%20n%20%3D%3D%200%3A%0A%20%20%20%20%20%20%20%20print%28%22Happy%20new%20Year!%22%29%0A%20%20%20%20else%3A%0A%20%20%20%20%20%20%20%20print%28n%29%0A%20%20%20%20%20%20%20%20countdown%28n%20-%201%29%0A%0Acountdown%283%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows: Each time `countdown()` is called, Python creates a *new* frame in the part of the memory where it manages all the names. This way, Python *isolates* all the different `n` variables from each other. As new frames are created until we reach the base case, after which the frames are destroyed in the *reversed* order, this is called a **[stack <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Stack_(abstract_data_type))** of frames in computer science terminology. In simple words, a stack is a last-in-first-out (LIFO) task queue. Each frame has a single parent frame, namely the one whose recursive function call created it."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -273,7 +273,7 @@
|
|||
"source": [
|
||||
"When we read such code, it is often easier not to follow every function call (i.e., `factorial(n - 1)` here) in one's mind but assume we receive a return value as specified in the documentation. Some call this approach a **[leap of faith](http://greenteapress.com/thinkpython2/html/thinkpython2007.html#sec75)**. We practice this already whenever we call built-in functions (e.g., [print() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#print) or [len() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#len)) where we would have to read C code in many cases.\n",
|
||||
"\n",
|
||||
"To visualize *all* the computational steps of the exemplary `factorial(3)`, we use [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=def%20factorial%28n%29%3A%0A%20%20%20%20if%20n%20%3D%3D%200%3A%0A%20%20%20%20%20%20%20%20return%201%0A%20%20%20%20else%3A%0A%20%20%20%20%20%20%20%20recurse%20%3D%20factorial%28n%20-%201%29%0A%20%20%20%20%20%20%20%20result%20%3D%20n%20*%20recurse%0A%20%20%20%20%20%20%20%20return%20result%0A%0Asolution%20%3D%20factorial%283%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false): The recursion again creates a stack of frames in memory. In contrast to the previous trivial example, each frame leaves a return value in memory after it is destroyed. This return value is then assigned to the `recurse` variable within the parent frame and used to compute `result`."
|
||||
"To visualize *all* the computational steps of the exemplary `factorial(3)`, we use [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=def%20factorial%28n%29%3A%0A%20%20%20%20if%20n%20%3D%3D%200%3A%0A%20%20%20%20%20%20%20%20return%201%0A%20%20%20%20else%3A%0A%20%20%20%20%20%20%20%20recurse%20%3D%20factorial%28n%20-%201%29%0A%20%20%20%20%20%20%20%20result%20%3D%20n%20*%20recurse%0A%20%20%20%20%20%20%20%20return%20result%0A%0Asolution%20%3D%20factorial%283%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false): The recursion again creates a stack of frames in memory. In contrast to the previous trivial example, each frame leaves a return value in memory after it is destroyed. This return value is then assigned to the `recurse` variable within the parent frame and used to compute `result`."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -334,7 +334,7 @@
|
|||
"source": [
|
||||
"A Pythonista would formulate `factorial()` in a more concise way using the so-called **early exit** pattern: No `else`-clause is needed as reaching a `return` statement ends a function call *immediately*. Furthermore, we do not need the temporary variables `recurse` and `result`.\n",
|
||||
"\n",
|
||||
"As [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=def%20factorial%28n%29%3A%0A%20%20%20%20if%20n%20%3D%3D%200%3A%0A%20%20%20%20%20%20%20%20return%201%0A%20%20%20%20return%20n%20*%20factorial%28n%20-%201%29%0A%0Asolution%20%3D%20factorial%283%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows, this implementation is more efficient as it only requires 18 computational steps instead of 24 to calculate `factorial(3)`, an improvement of 25 percent! "
|
||||
"As [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=def%20factorial%28n%29%3A%0A%20%20%20%20if%20n%20%3D%3D%200%3A%0A%20%20%20%20%20%20%20%20return%201%0A%20%20%20%20return%20n%20*%20factorial%28n%20-%201%29%0A%0Asolution%20%3D%20factorial%283%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows, this implementation is more efficient as it only requires 18 computational steps instead of 24 to calculate `factorial(3)`, an improvement of 25 percent! "
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -448,9 +448,9 @@
|
|||
"text": [
|
||||
"Help on built-in function factorial in module math:\n",
|
||||
"\n",
|
||||
"factorial(x, /)\n",
|
||||
" Find x!.\n",
|
||||
" \n",
|
||||
"factorial(n, /)\n",
|
||||
" Find n!.\n",
|
||||
"\n",
|
||||
" Raise a ValueError if x is negative or non-integral.\n",
|
||||
"\n"
|
||||
]
|
||||
|
|
@ -675,8 +675,8 @@
|
|||
"text": [
|
||||
"Help on built-in function gcd in module math:\n",
|
||||
"\n",
|
||||
"gcd(x, y, /)\n",
|
||||
" greatest common divisor of x and y\n",
|
||||
"gcd(*integers)\n",
|
||||
" Greatest Common Divisor.\n",
|
||||
"\n"
|
||||
]
|
||||
}
|
||||
|
|
@ -870,11 +870,11 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"This implementation is *highly* **inefficient** as small Fibonacci numbers already take a very long time to compute. The reason for this is **exponential growth** in the number of function calls. As [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=def%20fibonacci%28i%29%3A%0A%20%20%20%20if%20i%20%3D%3D%200%3A%0A%20%20%20%20%20%20%20%20return%200%0A%20%20%20%20elif%20i%20%3D%3D%201%3A%0A%20%20%20%20%20%20%20%20return%201%0A%20%20%20%20return%20fibonacci%28i%20-%201%29%20%2B%20fibonacci%28i%20-%202%29%0A%0Arv%20%3D%20fibonacci%285%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows, `fibonacci()` is called again and again with the same `i` arguments.\n",
|
||||
"This implementation is *highly* **inefficient** as small Fibonacci numbers already take a very long time to compute. The reason for this is **exponential growth** in the number of function calls. As [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=def%20fibonacci%28i%29%3A%0A%20%20%20%20if%20i%20%3D%3D%200%3A%0A%20%20%20%20%20%20%20%20return%200%0A%20%20%20%20elif%20i%20%3D%3D%201%3A%0A%20%20%20%20%20%20%20%20return%201%0A%20%20%20%20return%20fibonacci%28i%20-%201%29%20%2B%20fibonacci%28i%20-%202%29%0A%0Arv%20%3D%20fibonacci%285%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows, `fibonacci()` is called again and again with the same `i` arguments.\n",
|
||||
"\n",
|
||||
"To understand this in detail, we have to study algorithms and data structures (e.g., with [this book](https://www.amazon.de/Introduction-Algorithms-Press-Thomas-Cormen/dp/0262033844/ref=sr_1_1?__mk_de_DE=%C3%85M%C3%85%C5%BD%C3%95%C3%91&crid=1JNE8U0VZGU0O&qid=1569837169&s=gateway&sprefix=algorithms+an%2Caps%2C180&sr=8-1)), a discipline within computer science, and dive into the analysis of **[time complexity of algorithms <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Time_complexity)**.\n",
|
||||
"\n",
|
||||
"Luckily, in the Fibonacci case, the inefficiency can be resolved with a **caching** (i.e., \"reuse\") strategy from the field of **[dynamic programming <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Dynamic_programming)**, namely **[memoization <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Memoization)**. We do so in [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/02_content.ipynb#Memoization), after introducing the `dict` data type.\n",
|
||||
"Luckily, in the Fibonacci case, the inefficiency can be resolved with a **caching** (i.e., \"reuse\") strategy from the field of **[dynamic programming <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Dynamic_programming)**, namely **[memoization <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Memoization)**. We do so in [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/02_content.ipynb#Memoization), after introducing the `dict` data type.\n",
|
||||
"\n",
|
||||
"Let's measure the average run times for `fibonacci()` and varying `i` arguments with the `%%timeit` [cell magic](https://ipython.readthedocs.io/en/stable/interactive/magics.html#magic-timeit) that comes with Jupyter."
|
||||
]
|
||||
|
|
@ -1022,10 +1022,11 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mRecursionError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-28-62f686a9f8a1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mrun_forever\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-27-80575699c62c>\u001b[0m in \u001b[0;36mrun_forever\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mrun_forever\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;34m\"\"\"Also a pointless function should have a docstring.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mrun_forever\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"... last 1 frames repeated, from the frame below ...\n",
|
||||
"\u001b[0;32m<ipython-input-27-80575699c62c>\u001b[0m in \u001b[0;36mrun_forever\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mrun_forever\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;34m\"\"\"Also a pointless function should have a docstring.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mrun_forever\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[28], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mrun_forever\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[27], line 3\u001b[0m, in \u001b[0;36mrun_forever\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrun_forever\u001b[39m():\n\u001b[1;32m 2\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Also a pointless function should have a docstring.\"\"\"\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m \u001b[43mrun_forever\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[27], line 3\u001b[0m, in \u001b[0;36mrun_forever\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrun_forever\u001b[39m():\n\u001b[1;32m 2\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Also a pointless function should have a docstring.\"\"\"\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m \u001b[43mrun_forever\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
" \u001b[0;31m[... skipping similar frames: run_forever at line 3 (2974 times)]\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[27], line 3\u001b[0m, in \u001b[0;36mrun_forever\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrun_forever\u001b[39m():\n\u001b[1;32m 2\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Also a pointless function should have a docstring.\"\"\"\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m \u001b[43mrun_forever\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mRecursionError\u001b[0m: maximum recursion depth exceeded"
|
||||
]
|
||||
}
|
||||
|
|
@ -4014,21 +4015,42 @@
|
|||
"-2949.9\n",
|
||||
"-2950.9\n",
|
||||
"-2951.9\n",
|
||||
"-2952.9\n"
|
||||
"-2952.9\n",
|
||||
"-2953.9\n",
|
||||
"-2954.9\n",
|
||||
"-2955.9\n",
|
||||
"-2956.9\n",
|
||||
"-2957.9\n",
|
||||
"-2958.9\n",
|
||||
"-2959.9\n",
|
||||
"-2960.9\n",
|
||||
"-2961.9\n",
|
||||
"-2962.9\n",
|
||||
"-2963.9\n",
|
||||
"-2964.9\n",
|
||||
"-2965.9\n",
|
||||
"-2966.9\n",
|
||||
"-2967.9\n",
|
||||
"-2968.9\n",
|
||||
"-2969.9\n",
|
||||
"-2970.9\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"ename": "RecursionError",
|
||||
"evalue": "maximum recursion depth exceeded while calling a Python object",
|
||||
"evalue": "maximum recursion depth exceeded",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mRecursionError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-29-43e3ad331761>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mcountdown\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m3.1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-1-10499518927d>\u001b[0m in \u001b[0;36mcountdown\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m \u001b[0mcountdown\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"... last 1 frames repeated, from the frame below ...\n",
|
||||
"\u001b[0;32m<ipython-input-1-10499518927d>\u001b[0m in \u001b[0;36mcountdown\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m \u001b[0mcountdown\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;31mRecursionError\u001b[0m: maximum recursion depth exceeded while calling a Python object"
|
||||
"Cell \u001b[0;32mIn[29], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mcountdown\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m3.1\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[1], line 11\u001b[0m, in \u001b[0;36mcountdown\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 10\u001b[0m \u001b[38;5;28mprint\u001b[39m(n)\n\u001b[0;32m---> 11\u001b[0m \u001b[43mcountdown\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[1], line 11\u001b[0m, in \u001b[0;36mcountdown\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 10\u001b[0m \u001b[38;5;28mprint\u001b[39m(n)\n\u001b[0;32m---> 11\u001b[0m \u001b[43mcountdown\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
" \u001b[0;31m[... skipping similar frames: countdown at line 11 (2972 times)]\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[1], line 11\u001b[0m, in \u001b[0;36mcountdown\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 10\u001b[0m \u001b[38;5;28mprint\u001b[39m(n)\n\u001b[0;32m---> 11\u001b[0m \u001b[43mcountdown\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[1], line 10\u001b[0m, in \u001b[0;36mcountdown\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mHappy New Year!\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 9\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m---> 10\u001b[0m \u001b[38;5;28;43mprint\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mn\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 11\u001b[0m countdown(n \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m1\u001b[39m)\n",
|
||||
"File \u001b[0;32m~/Repositories/intro-to-python/.venv/lib/python3.12/site-packages/ipykernel/iostream.py:664\u001b[0m, in \u001b[0;36mOutStream.write\u001b[0;34m(self, string)\u001b[0m\n\u001b[1;32m 655\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrite\u001b[39m(\u001b[38;5;28mself\u001b[39m, string: \u001b[38;5;28mstr\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Optional[\u001b[38;5;28mint\u001b[39m]: \u001b[38;5;66;03m# type:ignore[override]\u001b[39;00m\n\u001b[1;32m 656\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Write to current stream after encoding if necessary\u001b[39;00m\n\u001b[1;32m 657\u001b[0m \n\u001b[1;32m 658\u001b[0m \u001b[38;5;124;03m Returns\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 662\u001b[0m \n\u001b[1;32m 663\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 664\u001b[0m parent \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparent_header\u001b[49m\n\u001b[1;32m 666\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(string, \u001b[38;5;28mstr\u001b[39m):\n\u001b[1;32m 667\u001b[0m msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mwrite() argument must be str, not \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtype\u001b[39m(string)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;66;03m# type:ignore[unreachable]\u001b[39;00m\n",
|
||||
"\u001b[0;31mRecursionError\u001b[0m: maximum recursion depth exceeded"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -4058,16 +4080,17 @@
|
|||
"outputs": [
|
||||
{
|
||||
"ename": "RecursionError",
|
||||
"evalue": "maximum recursion depth exceeded in comparison",
|
||||
"evalue": "maximum recursion depth exceeded",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mRecursionError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-30-188b816be8b6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfactorial\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m3.1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-6-88d8d933f651>\u001b[0m in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mfactorial\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"... last 1 frames repeated, from the frame below ...\n",
|
||||
"\u001b[0;32m<ipython-input-6-88d8d933f651>\u001b[0m in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mfactorial\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;31mRecursionError\u001b[0m: maximum recursion depth exceeded in comparison"
|
||||
"Cell \u001b[0;32mIn[30], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mfactorial\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m3.1\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[6], line 12\u001b[0m, in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m n \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 11\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m1\u001b[39m\n\u001b[0;32m---> 12\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m n \u001b[38;5;241m*\u001b[39m \u001b[43mfactorial\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[6], line 12\u001b[0m, in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m n \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 11\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m1\u001b[39m\n\u001b[0;32m---> 12\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m n \u001b[38;5;241m*\u001b[39m \u001b[43mfactorial\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
" \u001b[0;31m[... skipping similar frames: factorial at line 12 (2974 times)]\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[6], line 12\u001b[0m, in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m n \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 11\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m1\u001b[39m\n\u001b[0;32m---> 12\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m n \u001b[38;5;241m*\u001b[39m \u001b[43mfactorial\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mRecursionError\u001b[0m: maximum recursion depth exceeded"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -4382,8 +4405,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-38-188b816be8b6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfactorial\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m3.1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-35-54b57bc2107d>\u001b[0m in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 13\u001b[0m \"\"\"\n\u001b[1;32m 14\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 15\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Factorial is only defined for integers\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 16\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 17\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Factorial is not defined for negative integers\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[38], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mfactorial\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m3.1\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[35], line 15\u001b[0m, in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Calculate the factorial of a number.\u001b[39;00m\n\u001b[1;32m 3\u001b[0m \n\u001b[1;32m 4\u001b[0m \u001b[38;5;124;03mArgs:\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[38;5;124;03m ValueError: if n is negative\u001b[39;00m\n\u001b[1;32m 13\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 14\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(n, \u001b[38;5;28mint\u001b[39m):\n\u001b[0;32m---> 15\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFactorial is only defined for integers\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 16\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m n \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 17\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFactorial is not defined for negative integers\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: Factorial is only defined for integers"
|
||||
]
|
||||
}
|
||||
|
|
@ -4408,8 +4431,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-39-b06b2cada645>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfactorial\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m42\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-35-54b57bc2107d>\u001b[0m in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Factorial is only defined for integers\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 17\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Factorial is not defined for negative integers\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 18\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 19\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[39], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mfactorial\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[38;5;241;43m42\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[35], line 17\u001b[0m, in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFactorial is only defined for integers\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 16\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m n \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m---> 17\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFactorial is not defined for negative integers\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 18\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m n \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m1\u001b[39m\n",
|
||||
"\u001b[0;31mValueError\u001b[0m: Factorial is not defined for negative integers"
|
||||
]
|
||||
}
|
||||
|
|
@ -4445,8 +4468,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-40-32f1a9e8cf49>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfactorial\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m3.0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-35-54b57bc2107d>\u001b[0m in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 13\u001b[0m \"\"\"\n\u001b[1;32m 14\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 15\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Factorial is only defined for integers\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 16\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 17\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Factorial is not defined for negative integers\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[40], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mfactorial\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m3.0\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[35], line 15\u001b[0m, in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Calculate the factorial of a number.\u001b[39;00m\n\u001b[1;32m 3\u001b[0m \n\u001b[1;32m 4\u001b[0m \u001b[38;5;124;03mArgs:\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[38;5;124;03m ValueError: if n is negative\u001b[39;00m\n\u001b[1;32m 13\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 14\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(n, \u001b[38;5;28mint\u001b[39m):\n\u001b[0;32m---> 15\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFactorial is only defined for integers\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 16\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m n \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 17\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFactorial is not defined for negative integers\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: Factorial is only defined for integers"
|
||||
]
|
||||
}
|
||||
|
|
@ -4688,8 +4711,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-47-188b816be8b6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfactorial\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m3.1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-45-07dc981a3422>\u001b[0m in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 13\u001b[0m \"\"\"\n\u001b[1;32m 14\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 15\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"n is not integer-like; it has non-zero decimals\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 16\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 17\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[47], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mfactorial\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m3.1\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[45], line 15\u001b[0m, in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Calculate the factorial of a number.\u001b[39;00m\n\u001b[1;32m 3\u001b[0m \n\u001b[1;32m 4\u001b[0m \u001b[38;5;124;03mArgs:\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[38;5;124;03m ValueError: if n is negative\u001b[39;00m\n\u001b[1;32m 13\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 14\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m n \u001b[38;5;241m!=\u001b[39m \u001b[38;5;28mint\u001b[39m(n):\n\u001b[0;32m---> 15\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mn is not integer-like; it has non-zero decimals\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 16\u001b[0m n \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mint\u001b[39m(n)\n\u001b[1;32m 18\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m n \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m0\u001b[39m:\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: n is not integer-like; it has non-zero decimals"
|
||||
]
|
||||
}
|
||||
|
|
@ -4725,8 +4748,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-48-9a12eb120fc3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfactorial\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"text\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-45-07dc981a3422>\u001b[0m in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mnegative\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 13\u001b[0m \"\"\"\n\u001b[0;32m---> 14\u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 15\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"n is not integer-like; it has non-zero decimals\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[48], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mfactorial\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtext\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[45], line 14\u001b[0m, in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mfactorial\u001b[39m(n):\n\u001b[1;32m 2\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Calculate the factorial of a number.\u001b[39;00m\n\u001b[1;32m 3\u001b[0m \n\u001b[1;32m 4\u001b[0m \u001b[38;5;124;03m Args:\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[38;5;124;03m ValueError: if n is negative\u001b[39;00m\n\u001b[1;32m 13\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m---> 14\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m n \u001b[38;5;241m!=\u001b[39m \u001b[38;5;28;43mint\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mn\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 15\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mn is not integer-like; it has non-zero decimals\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 16\u001b[0m n \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mint\u001b[39m(n)\n",
|
||||
"\u001b[0;31mValueError\u001b[0m: invalid literal for int() with base 10: 'text'"
|
||||
]
|
||||
}
|
||||
|
|
@ -4801,8 +4824,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-50-9a12eb120fc3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfactorial\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"text\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-49-9ed22b5a2981>\u001b[0m in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[0mcasted_n\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 17\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"n cannot be casted as an integer\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 18\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 19\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mcasted_n\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[50], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mfactorial\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtext\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[49], line 17\u001b[0m, in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 15\u001b[0m casted_n \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mint\u001b[39m(n)\n\u001b[1;32m 16\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m:\n\u001b[0;32m---> 17\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mn cannot be casted as an integer\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 18\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m n \u001b[38;5;241m!=\u001b[39m casted_n:\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: n cannot be casted as an integer"
|
||||
]
|
||||
}
|
||||
|
|
@ -4827,8 +4850,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-51-188b816be8b6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfactorial\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m3.1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-49-9ed22b5a2981>\u001b[0m in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 18\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 19\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mcasted_n\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 20\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"n is not integer-like; it has non-zero decimals\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 21\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcasted_n\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 22\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[51], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mfactorial\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m3.1\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[49], line 20\u001b[0m, in \u001b[0;36mfactorial\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 18\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m n \u001b[38;5;241m!=\u001b[39m casted_n:\n\u001b[0;32m---> 20\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mn is not integer-like; it has non-zero decimals\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 21\u001b[0m n \u001b[38;5;241m=\u001b[39m casted_n\n\u001b[1;32m 23\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m n \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m0\u001b[39m:\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: n is not integer-like; it has non-zero decimals"
|
||||
]
|
||||
}
|
||||
|
|
@ -4887,7 +4910,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/04_iteration/01_exercises.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/04_iteration/01_exercises.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -18,7 +18,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The exercises below assume that you have read the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/00_content.ipynb) of Chapter 4.\n",
|
||||
"The exercises below assume that you have read the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/00_content.ipynb) of Chapter 4.\n",
|
||||
"\n",
|
||||
"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
|
||||
]
|
||||
|
|
@ -589,7 +589,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/04_iteration/02_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/04_iteration/02_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -30,7 +30,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"After learning about the concept of **recursion** in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/00_content.ipynb) of this chapter, we look at other ways of running code repeatedly, namely **looping** with the `for` and `while` statements. We start with the latter as it is more generic. Throughout this second part of the chapter, we revisit the same examples from the first part to show how recursion and looping are really two sides of the same coin."
|
||||
"After learning about the concept of **recursion** in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/00_content.ipynb) of this chapter, we look at other ways of running code repeatedly, namely **looping** with the `for` and `while` statements. We start with the latter as it is more generic. Throughout this second part of the chapter, we revisit the same examples from the first part to show how recursion and looping are really two sides of the same coin."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -137,7 +137,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"As [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=def%20countdown%28n%29%3A%0A%20%20%20%20while%20n%20!%3D%200%3A%0A%20%20%20%20%20%20%20%20print%28n%29%0A%20%20%20%20%20%20%20%20n%20-%3D%201%0A%0A%20%20%20%20print%28%22Happy%20new%20Year!%22%29%0A%0Acountdown%283%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows, there is a subtle but essential difference in the way a `while` statement is treated in memory: In short, `while` statements can *not* run into a `RecursionError` as only *one* frame is needed to manage the names. After all, there is only *one* function call to be made. For typical day-to-day applications, this difference is, however, not so important *unless* a problem instance becomes so big that a large (i.e., $> 3.000$) number of recursive calls must be made."
|
||||
"As [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=def%20countdown%28n%29%3A%0A%20%20%20%20while%20n%20!%3D%200%3A%0A%20%20%20%20%20%20%20%20print%28n%29%0A%20%20%20%20%20%20%20%20n%20-%3D%201%0A%0A%20%20%20%20print%28%22Happy%20new%20Year!%22%29%0A%0Acountdown%283%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows, there is a subtle but essential difference in the way a `while` statement is treated in memory: In short, `while` statements can *not* run into a `RecursionError` as only *one* frame is needed to manage the names. After all, there is only *one* function call to be made. For typical day-to-day applications, this difference is, however, not so important *unless* a problem instance becomes so big that a large (i.e., $> 3.000$) number of recursive calls must be made."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -582,7 +582,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"For sequences of integers, the [range() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-range) built-in makes the `for` statement even more convenient: It creates a `list`-like object of type `range` that generates integers \"on the fly,\" and we look closely at the underlying effects in memory in [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/00_content.ipynb#Mapping)."
|
||||
"For sequences of integers, the [range() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-range) built-in makes the `for` statement even more convenient: It creates a `list`-like object of type `range` that generates integers \"on the fly,\" and we look closely at the underlying effects in memory in [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/00_content.ipynb#Mapping)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -713,11 +713,11 @@
|
|||
"\n",
|
||||
"Now, just as we classify objects by data type, we also classify these data types (e.g., `int`, `float`, `str`, or `list`) into **abstract concepts**.\n",
|
||||
"\n",
|
||||
"We did this already in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/03_content.ipynb#Who-am-I?-And-how-many?) when we described a `list` object as \"some sort of container that holds [...] references to other objects\". So, abstractly speaking, **containers** are any objects that are \"composed\" of other objects and also \"manage\" how these objects are organized. `list` objects, for example, have the property that they model an order associated with their elements. There exist, however, other container types, many of which do *not* come with an order. So, containers primarily \"contain\" other objects and have *nothing* to do with looping.\n",
|
||||
"We did this already in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/03_content.ipynb#Who-am-I?-And-how-many?) when we described a `list` object as \"some sort of container that holds [...] references to other objects\". So, abstractly speaking, **containers** are any objects that are \"composed\" of other objects and also \"manage\" how these objects are organized. `list` objects, for example, have the property that they model an order associated with their elements. There exist, however, other container types, many of which do *not* come with an order. So, containers primarily \"contain\" other objects and have *nothing* to do with looping.\n",
|
||||
"\n",
|
||||
"On the contrary, the abstract concept of **iterables** is all about looping: Any object that we can loop over is, by definition, an iterable. So, `range` objects, for example, are iterables, even though they hold no references to other objects. Moreover, looping does *not* have to occur in a *predictable* order, although this is the case for both `list` and `range` objects.\n",
|
||||
"\n",
|
||||
"Typically, containers are iterables, and iterables are containers. Yet, only because these two concepts coincide often, we must not think of them as the same. In [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/00_content.ipynb#Collections-vs.-Sequences), we formalize these two concepts and introduce many more. Finally, [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/00_content.ipynb) gives an explanation how abstract concepts are implemented and play together.\n",
|
||||
"Typically, containers are iterables, and iterables are containers. Yet, only because these two concepts coincide often, we must not think of them as the same. In [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/00_content.ipynb#Collections-vs.-Sequences), we formalize these two concepts and introduce many more. Finally, [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/00_content.ipynb) gives an explanation how abstract concepts are implemented and play together.\n",
|
||||
"\n",
|
||||
"Let's continue with `first_names` below as an example an illustrate what iterable containers are."
|
||||
]
|
||||
|
|
@ -1268,7 +1268,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/04_iteration/03_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/04_iteration/03_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -30,7 +30,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"While what we learned about the `for` and `while` statements in the [second part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/02_content.ipynb) of this chapter suffices to translate any iterative algorithm into code, both come with some syntactic sugar to make life easier for the developer. This last part of the chapter shows how we can further customize the looping logic and introduces as \"trick\" for situations where we cannot come up with a stopping criterion in a `while`-loop."
|
||||
"While what we learned about the `for` and `while` statements in the [second part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/02_content.ipynb) of this chapter suffices to translate any iterative algorithm into code, both come with some syntactic sugar to make life easier for the developer. This last part of the chapter shows how we can further customize the looping logic and introduces as \"trick\" for situations where we cannot come up with a stopping criterion in a `while`-loop."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -352,7 +352,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Often, we process some iterable with numeric data, for example, a list of `numbers` as in this book's introductory example in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#Example:-Averaging-all-even-Numbers-in-a-List) or, more realistically, data from a CSV file with many rows and columns.\n",
|
||||
"Often, we process some iterable with numeric data, for example, a list of `numbers` as in this book's introductory example in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#Example:-Averaging-all-even-Numbers-in-a-List) or, more realistically, data from a CSV file with many rows and columns.\n",
|
||||
"\n",
|
||||
"Processing numeric data usually comes down to operations that may be grouped into one of the following three categories:\n",
|
||||
"\n",
|
||||
|
|
@ -360,7 +360,7 @@
|
|||
"- **filtering**: throw away individual numbers (e.g., statistical outliers in a sample)\n",
|
||||
"- **reducing**: collect individual numbers into summary statistics\n",
|
||||
"\n",
|
||||
"We study this **map-filter-reduce** paradigm extensively in [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/00_content.ipynb) after introducing more advanced data types that are needed to work with \"big\" data.\n",
|
||||
"We study this **map-filter-reduce** paradigm extensively in [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/00_content.ipynb) after introducing more advanced data types that are needed to work with \"big\" data.\n",
|
||||
"\n",
|
||||
"Here, we focus on *filtering out* some numbers in a `for`-loop."
|
||||
]
|
||||
|
|
@ -535,7 +535,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"With already three levels of indentation, less horizontal space is available for the actual code block. Of course, one could flatten the two `if` statements with the logical `and` operator, as shown in [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/03_conditionals/00_content.ipynb#The-if-Statement). Then, however, we trade off horizontal space against a more \"complex\" `if` logic, and this is *not* a real improvement."
|
||||
"With already three levels of indentation, less horizontal space is available for the actual code block. Of course, one could flatten the two `if` statements with the logical `and` operator, as shown in [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/03_conditionals/00_content.ipynb#The-if-Statement). Then, however, we trade off horizontal space against a more \"complex\" `if` logic, and this is *not* a real improvement."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -959,7 +959,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/04_iteration/04_exercises.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/04_iteration/04_exercises.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -18,7 +18,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The exercises below assume that you have read the [third part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/03_content.ipynb) of Chapter 4.\n",
|
||||
"The exercises below assume that you have read the [third part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/03_content.ipynb) of Chapter 4.\n",
|
||||
"\n",
|
||||
"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
|
||||
]
|
||||
|
|
@ -34,7 +34,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"In this exercise, you will model the throwing of dice within the context of a guessing game similar to the one shown in the \"*Example: Guessing a Coin Toss*\" section in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/03_content.ipynb#Example:-Guessing-a-Coin-Toss).\n",
|
||||
"In this exercise, you will model the throwing of dice within the context of a guessing game similar to the one shown in the \"*Example: Guessing a Coin Toss*\" section in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/03_content.ipynb#Example:-Guessing-a-Coin-Toss).\n",
|
||||
"\n",
|
||||
"As the game involves randomness, we import the [random <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/random.html) module from the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html). To follow best practices, we set the random seed as well."
|
||||
]
|
||||
|
|
@ -382,7 +382,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
@ -47,7 +47,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -11,7 +11,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/00_content.ipynb), [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/02_content.ipynb), and the [third <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/03_content.ipynb) part of Chapter 4.\n",
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/00_content.ipynb), [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/02_content.ipynb), and the [third <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/03_content.ipynb) part of Chapter 4.\n",
|
||||
"\n",
|
||||
"Be concise in your answers! Most questions can be answered in *one* sentence."
|
||||
]
|
||||
|
|
@ -247,7 +247,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/05_numbers/00_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/05_numbers/00_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -32,17 +32,17 @@
|
|||
"source": [
|
||||
"After learning about the basic building blocks of expressing and structuring the business logic in programs, we focus our attention on the **data types** Python offers us, both built-in and available via the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html) or third-party packages.\n",
|
||||
"\n",
|
||||
"We start with the \"simple\" ones: Numeric types in this chapter and textual data in [Chapter 6 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/00_content.ipynb). An important fact that holds for all objects of these types is that they are **immutable**. To reuse the bag analogy from [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#Objects-vs.-Types-vs.-Values), this means that the $0$s and $1$s making up an object's *value* cannot be changed once the bag is created in memory, implying that any operation with or method on the object creates a *new* object in a *different* memory location.\n",
|
||||
"We start with the \"simple\" ones: Numeric types in this chapter and textual data in [Chapter 6 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/00_content.ipynb). An important fact that holds for all objects of these types is that they are **immutable**. To reuse the bag analogy from [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#Objects-vs.-Types-vs.-Values), this means that the $0$s and $1$s making up an object's *value* cannot be changed once the bag is created in memory, implying that any operation with or method on the object creates a *new* object in a *different* memory location.\n",
|
||||
"\n",
|
||||
"[Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/00_content.ipynb), [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/00_content.ipynb), [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/00_content.ipynb), [Chapter 10 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/10_arrarys/00_content.ipynb) then cover the more \"complex\" data types, including, for example, the `list` type. Finally, [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/00_content.ipynb) completes the picture by introducing language constructs to create custom types.\n",
|
||||
"[Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/00_content.ipynb), [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/00_content.ipynb), [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/00_content.ipynb), [Chapter 10 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/10_arrarys/00_content.ipynb) then cover the more \"complex\" data types, including, for example, the `list` type. Finally, [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/00_content.ipynb) completes the picture by introducing language constructs to create custom types.\n",
|
||||
"\n",
|
||||
"We have already seen many hints indicating that numbers are not as trivial to work with as it seems at first sight:\n",
|
||||
"\n",
|
||||
"- [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#%28Data%29-Type-%2F-%22Behavior%22) reveals that numbers may come in *different* data types (i.e., `int` vs. `float` so far),\n",
|
||||
"- [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/03_conditionals/00_content.ipynb#Boolean-Expressions) raises questions regarding the **limited precision** of `float` numbers (e.g., `42 == 42.000000000000001` evaluates to `True`), and\n",
|
||||
"- [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/00_content.ipynb#Infinite-Recursion) shows that sometimes a `float` \"walks\" and \"quacks\" like an `int`, whereas the reverse is true in other cases.\n",
|
||||
"- [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#%28Data%29-Type-%2F-%22Behavior%22) reveals that numbers may come in *different* data types (i.e., `int` vs. `float` so far),\n",
|
||||
"- [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/03_conditionals/00_content.ipynb#Boolean-Expressions) raises questions regarding the **limited precision** of `float` numbers (e.g., `42 == 42.000000000000001` evaluates to `True`), and\n",
|
||||
"- [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/00_content.ipynb#Infinite-Recursion) shows that sometimes a `float` \"walks\" and \"quacks\" like an `int`, whereas the reverse is true in other cases.\n",
|
||||
"\n",
|
||||
"This chapter introduces all the [built-in numeric types <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#numeric-types-int-float-complex): `int`, `float`, and `complex`. To mitigate the limited precision of floating-point numbers, we also add an [Appendix <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/03_appendix.ipynb) where we look at two replacements for the `float` type in the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html), namely the `Decimal` type in the [decimals <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/decimal.html#decimal.Decimal) and the `Fraction` type in the [fractions <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/fractions.html#fractions.Fraction) module."
|
||||
"This chapter introduces all the [built-in numeric types <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#numeric-types-int-float-complex): `int`, `float`, and `complex`. To mitigate the limited precision of floating-point numbers, we also add an [Appendix <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/03_appendix.ipynb) where we look at two replacements for the `float` type in the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html), namely the `Decimal` type in the [decimals <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/decimal.html#decimal.Decimal) and the `Fraction` type in the [fractions <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/fractions.html#fractions.Fraction) module."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -64,7 +64,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"The simplest numeric type is the `int` type: It behaves like an [integer in ordinary math <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Integer) (i.e., the set $\\mathbb{Z}$) and supports operators in the way we saw in the section on arithmetic operators in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#%28Arithmetic%29-Operators).\n",
|
||||
"The simplest numeric type is the `int` type: It behaves like an [integer in ordinary math <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Integer) (i.e., the set $\\mathbb{Z}$) and supports operators in the way we saw in the section on arithmetic operators in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#%28Arithmetic%29-Operators).\n",
|
||||
"\n",
|
||||
"One way to create `int` objects is by simply writing its value as a literal with the digits `0` to `9`."
|
||||
]
|
||||
|
|
@ -257,10 +257,10 @@
|
|||
"outputs": [
|
||||
{
|
||||
"ename": "SyntaxError",
|
||||
"evalue": "leading zeros in decimal integer literals are not permitted; use an 0o prefix for octal integers (<ipython-input-7-9a7f0f99e867>, line 1)",
|
||||
"evalue": "leading zeros in decimal integer literals are not permitted; use an 0o prefix for octal integers (1481240458.py, line 1)",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;36m File \u001b[0;32m\"<ipython-input-7-9a7f0f99e867>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m 042\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m leading zeros in decimal integer literals are not permitted; use an 0o prefix for octal integers\n"
|
||||
"\u001b[0;36m Cell \u001b[0;32mIn[7], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m 042\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m leading zeros in decimal integer literals are not permitted; use an 0o prefix for octal integers\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -335,7 +335,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Whereas the integer division operator `//` \"rounds\" towards negative infinity (cf., the \"*(Arithmetic) Operators*\" section in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#%28Arithmetic%29-Operators)), the [int() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#int) built-in rounds towards `0`."
|
||||
"Whereas the integer division operator `//` \"rounds\" towards negative infinity (cf., the \"*(Arithmetic) Operators*\" section in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#%28Arithmetic%29-Operators)), the [int() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#int) built-in rounds towards `0`."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -413,7 +413,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-12-faae6b054331>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"42.0\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[12], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;43mint\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m42.0\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mValueError\u001b[0m: invalid literal for int() with base 10: '42.0'"
|
||||
]
|
||||
}
|
||||
|
|
@ -1104,7 +1104,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"The [Further Resources <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/06_resources.ipynb) section at the end of this chapter provides video tutorials on addition and multiplication in binary. Subtraction and division are a bit more involved but essentially also easy to understand."
|
||||
"The [Further Resources <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/06_resources.ipynb) section at the end of this chapter provides video tutorials on addition and multiplication in binary. Subtraction and division are a bit more involved but essentially also easy to understand."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1575,7 +1575,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"While there are conventions that model negative integers with $0$s and $1$s in memory (cf., [Two's Complement <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Two%27s_complement)), Python manages that for us, and we do not look into the theory here for brevity. We have learned all that a practitioner needs to know about how integers are modeled in a computer. The [Further Resources <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/06_resources.ipynb) section at the end of this chapter provides a video tutorial on how the [Two's Complement <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Two%27s_complement) idea works.\n",
|
||||
"While there are conventions that model negative integers with $0$s and $1$s in memory (cf., [Two's Complement <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Two%27s_complement)), Python manages that for us, and we do not look into the theory here for brevity. We have learned all that a practitioner needs to know about how integers are modeled in a computer. The [Further Resources <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/06_resources.ipynb) section at the end of this chapter provides a video tutorial on how the [Two's Complement <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Two%27s_complement) idea works.\n",
|
||||
"\n",
|
||||
"The binary and hexadecimal representations of negative integers are identical to their positive counterparts except that they start with a minus sign `-`. However, as the video tutorial at the end of the chapter reveals, that is *not* how the bits are organized in memory."
|
||||
]
|
||||
|
|
@ -2422,7 +2422,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/05_numbers/01_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/05_numbers/01_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -326,7 +326,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-10-c7953b8b7956>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfloat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"42. 87\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[10], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;43mfloat\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m42. 87\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mValueError\u001b[0m: could not convert string to float: '42. 87'"
|
||||
]
|
||||
}
|
||||
|
|
@ -497,10 +497,10 @@
|
|||
"outputs": [
|
||||
{
|
||||
"ename": "SyntaxError",
|
||||
"evalue": "invalid syntax (<ipython-input-15-1b5daaac0077>, line 1)",
|
||||
"evalue": "invalid syntax (1434619204.py, line 1)",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;36m File \u001b[0;32m\"<ipython-input-15-1b5daaac0077>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m 1.23 e0\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
|
||||
"\u001b[0;36m Cell \u001b[0;32mIn[15], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m 1.23 e0\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -519,10 +519,10 @@
|
|||
"outputs": [
|
||||
{
|
||||
"ename": "SyntaxError",
|
||||
"evalue": "invalid syntax (<ipython-input-16-a236c4a30231>, line 1)",
|
||||
"evalue": "invalid decimal literal (3971374856.py, line 1)",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;36m File \u001b[0;32m\"<ipython-input-16-a236c4a30231>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m 1.23e 0\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
|
||||
"\u001b[0;36m Cell \u001b[0;32mIn[16], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m 1.23e 0\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid decimal literal\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -541,10 +541,10 @@
|
|||
"outputs": [
|
||||
{
|
||||
"ename": "SyntaxError",
|
||||
"evalue": "invalid syntax (<ipython-input-17-05b9072d76be>, line 1)",
|
||||
"evalue": "invalid syntax (2795275998.py, line 1)",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;36m File \u001b[0;32m\"<ipython-input-17-05b9072d76be>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m 1.23e0.0\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
|
||||
"\u001b[0;36m Cell \u001b[0;32mIn[17], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m 1.23e0.0\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -579,7 +579,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-18-abc4de6ccb5e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0me0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[18], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43me0\u001b[49m\n",
|
||||
"\u001b[0;31mNameError\u001b[0m: name 'e0' is not defined"
|
||||
]
|
||||
}
|
||||
|
|
@ -1496,7 +1496,7 @@
|
|||
"source": [
|
||||
"The built-in [format() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#format) function allows us to show the **significant digits** of a `float` number as they exist in memory to arbitrary precision. To exemplify it, let's view a couple of `float` objects with `50` digits. This analysis reveals that almost no `float` number is precise! After 14 or 15 digits \"weird\" things happen. As we see further below, the \"random\" digits ending the `float` numbers do *not* \"physically\" exist in memory! Rather, they are \"calculated\" by the [format() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#format) function that is forced to show `50` digits.\n",
|
||||
"\n",
|
||||
"The [format() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#format) function is different from the [format() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#str.format) method on `str` objects introduced in the next chapter (cf., [Chapter 6 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/00_content.ipynb#format%28%29-Method)): Yet, both work with the so-called [format specification mini-language <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/string.html#format-specification-mini-language): `\".50f\"` is the instruction to show `50` digits of a `float` number."
|
||||
"The [format() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#format) function is different from the [format() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#str.format) method on `str` objects introduced in the next chapter (cf., [Chapter 6 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/00_content.ipynb#format%28%29-Method)): Yet, both work with the so-called [format specification mini-language <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/string.html#format-specification-mini-language): `\".50f\"` is the instruction to show `50` digits of a `float` number."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -2030,7 +2030,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"As seen in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#%28Data%29-Type-%2F-%22Behavior%22), the [.is_integer() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#float.is_integer) method tells us if a `float` can be casted as an `int` object without any loss in precision."
|
||||
"As seen in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#%28Data%29-Type-%2F-%22Behavior%22), the [.is_integer() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#float.is_integer) method tells us if a `float` can be casted as an `int` object without any loss in precision."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -2148,7 +2148,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/05_numbers/02_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/05_numbers/02_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -697,7 +697,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Analogous to the discussion of *containers* and *iterables* in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/02_content.ipynb#Containers-vs.-Iterables), we contrast the *concrete* numeric data types in this chapter with the *abstract* ideas behind [numbers in mathematics <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Number).\n",
|
||||
"Analogous to the discussion of *containers* and *iterables* in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/02_content.ipynb#Containers-vs.-Iterables), we contrast the *concrete* numeric data types in this chapter with the *abstract* ideas behind [numbers in mathematics <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Number).\n",
|
||||
"\n",
|
||||
"The figure below summarizes five *major* sets of [numbers in mathematics <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Number) as we know them from high school:\n",
|
||||
"\n",
|
||||
|
|
@ -819,7 +819,7 @@
|
|||
"\n",
|
||||
"For, example, as all numeric data types are `Complex` numbers in the abstract sense, they all work with the built-in [abs() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#abs) function (cf., [documentation <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/numbers.html#numbers.Complex)). While it is intuitively clear what the [absolute value <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Absolute_value) (i.e., \"distance\" from $0$) of an integer, a fraction, or any real number is, [abs() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#abs) calculates the equivalent of that for complex numbers. That concept is called the [magnitude <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Magnitude_%28mathematics%29) of a number, and is really a *generalization* of the absolute value.\n",
|
||||
"\n",
|
||||
"Relating back to the concept of **duck typing** mentioned in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/00_content.ipynb#Duck-Typing), `int`, `float`, and `complex` objects \"walk\" and \"quack\" alike in context of the [abs() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#abs) function."
|
||||
"Relating back to the concept of **duck typing** mentioned in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/00_content.ipynb#Duck-Typing), `int`, `float`, and `complex` objects \"walk\" and \"quack\" alike in context of the [abs() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#abs) function."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -991,7 +991,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-29-e40cd01fb15a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mround\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;36m2j\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[29], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;43mround\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43mj\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: type complex doesn't define __round__ method"
|
||||
]
|
||||
}
|
||||
|
|
@ -1174,7 +1174,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"However, if we model `1 / 10` as a `Fraction` object (cf., [Appendix <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/03_appendix.ipynb#The-Fraction-Type)), it is recognized as a `Rational` number."
|
||||
"However, if we model `1 / 10` as a `Fraction` object (cf., [Appendix <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/03_appendix.ipynb#The-Fraction-Type)), it is recognized as a `Rational` number."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1388,8 +1388,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-41-188b816be8b6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfactorial\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m3.1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-37-be6602f598f7>\u001b[0m in \u001b[0;36mfactorial\u001b[0;34m(n, strict)\u001b[0m\n\u001b[1;32m 17\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnumbers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mReal\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 18\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mstrict\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 19\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"n is not integer-like; it has non-zero decimals\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 20\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 21\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[41], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mfactorial\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m3.1\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[37], line 19\u001b[0m, in \u001b[0;36mfactorial\u001b[0;34m(n, strict)\u001b[0m\n\u001b[1;32m 17\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(n, numbers\u001b[38;5;241m.\u001b[39mReal):\n\u001b[1;32m 18\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m n \u001b[38;5;241m!=\u001b[39m \u001b[38;5;28mint\u001b[39m(n) \u001b[38;5;129;01mand\u001b[39;00m strict:\n\u001b[0;32m---> 19\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mn is not integer-like; it has non-zero decimals\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 20\u001b[0m n \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mint\u001b[39m(n)\n\u001b[1;32m 21\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: n is not integer-like; it has non-zero decimals"
|
||||
]
|
||||
}
|
||||
|
|
@ -1460,8 +1460,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-43-7296a74f5dcf>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfactorial\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;36m2j\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-37-be6602f598f7>\u001b[0m in \u001b[0;36mfactorial\u001b[0;34m(n, strict)\u001b[0m\n\u001b[1;32m 20\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 21\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 22\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Factorial is only defined for integers\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 23\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 24\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[43], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mfactorial\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43mj\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[37], line 22\u001b[0m, in \u001b[0;36mfactorial\u001b[0;34m(n, strict)\u001b[0m\n\u001b[1;32m 20\u001b[0m n \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mint\u001b[39m(n)\n\u001b[1;32m 21\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m---> 22\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFactorial is only defined for integers\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 24\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m n \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 25\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFactorial is not defined for negative integers\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: Factorial is only defined for integers"
|
||||
]
|
||||
}
|
||||
|
|
@ -1487,7 +1487,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/05_numbers/03_appendix.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/05_numbers/03_appendix.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -510,7 +510,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-16-a3cea145e6d1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;36m1.0\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mDecimal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m42\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[16], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;241;43m1.0\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mDecimal\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m42\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for *: 'float' and 'decimal.Decimal'"
|
||||
]
|
||||
}
|
||||
|
|
@ -681,7 +681,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mInvalidOperation\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-21-5b555b105c8f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtwo\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mquantize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mDecimal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"1e-28\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[21], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mtwo\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mquantize\u001b[49m\u001b[43m(\u001b[49m\u001b[43mDecimal\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m1e-28\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mInvalidOperation\u001b[0m: [<class 'decimal.InvalidOperation'>]"
|
||||
]
|
||||
}
|
||||
|
|
@ -964,7 +964,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mInvalidOperation\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-30-87950ebbd6ef>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mDecimal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"inf\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mDecimal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"-inf\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[30], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mDecimal\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43minf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mDecimal\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m-inf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mInvalidOperation\u001b[0m: [<class 'decimal.InvalidOperation'>]"
|
||||
]
|
||||
}
|
||||
|
|
@ -989,7 +989,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mInvalidOperation\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-31-996083f200c6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mDecimal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"inf\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mDecimal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"inf\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[31], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mDecimal\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43minf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mDecimal\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43minf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mInvalidOperation\u001b[0m: [<class 'decimal.InvalidOperation'>]"
|
||||
]
|
||||
}
|
||||
|
|
@ -1476,7 +1476,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -53,7 +53,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -11,7 +11,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/00_content.ipynb), [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/01_content.ipynb), and the [third <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/02_content.ipynb) part of Chapter 5. Some questions regard the [Appendix <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/03_appendix.ipynb); that is indicated with a **\\***.\n",
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/00_content.ipynb), [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/01_content.ipynb), and the [third <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/02_content.ipynb) part of Chapter 5. Some questions regard the [Appendix <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/03_appendix.ipynb); that is indicated with a **\\***.\n",
|
||||
"\n",
|
||||
"Be concise in your answers! Most questions can be answered in *one* sentence."
|
||||
]
|
||||
|
|
@ -306,7 +306,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/05_numbers/06_resources.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/05_numbers/06_resources.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -56,6 +56,7 @@
|
|||
" src=\"https://www.youtube.com/embed/RgklPQ8rbkg\"\n",
|
||||
" frameborder=\"0\"\n",
|
||||
" allowfullscreen\n",
|
||||
" \n",
|
||||
" ></iframe>\n",
|
||||
" "
|
||||
],
|
||||
|
|
@ -93,6 +94,7 @@
|
|||
" src=\"https://www.youtube.com/embed/xHWKYFhhtJQ\"\n",
|
||||
" frameborder=\"0\"\n",
|
||||
" allowfullscreen\n",
|
||||
" \n",
|
||||
" ></iframe>\n",
|
||||
" "
|
||||
],
|
||||
|
|
@ -140,6 +142,7 @@
|
|||
" src=\"https://www.youtube.com/embed/4qH4unVtJkE\"\n",
|
||||
" frameborder=\"0\"\n",
|
||||
" allowfullscreen\n",
|
||||
" \n",
|
||||
" ></iframe>\n",
|
||||
" "
|
||||
],
|
||||
|
|
@ -194,6 +197,7 @@
|
|||
" src=\"https://www.youtube.com/embed/PZRI1IfStY0\"\n",
|
||||
" frameborder=\"0\"\n",
|
||||
" allowfullscreen\n",
|
||||
" \n",
|
||||
" ></iframe>\n",
|
||||
" "
|
||||
],
|
||||
|
|
@ -248,6 +252,7 @@
|
|||
" src=\"https://www.youtube.com/embed/Jkv-55ndVYY\"\n",
|
||||
" frameborder=\"0\"\n",
|
||||
" allowfullscreen\n",
|
||||
" \n",
|
||||
" ></iframe>\n",
|
||||
" "
|
||||
],
|
||||
|
|
@ -281,7 +286,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/06_text/00_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/06_text/00_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -30,7 +30,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"In this chapter, we continue the study of the built-in data types. The next layer on top of numbers consists of **textual data** that are modeled primarily with the `str` type in Python. `str` objects are more complex than the numeric objects in [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/00_content.ipynb) as they *consist* of an *arbitrary* and possibly large number of *individual* characters that may be chosen from *any* alphabet in the history of humankind. Luckily, Python abstracts away most of this complexity from us. However, after looking at the `str` type in great detail, we briefly introduce the `bytes` type at the end of this chapter to understand how characters are modeled in memory."
|
||||
"In this chapter, we continue the study of the built-in data types. The next layer on top of numbers consists of **textual data** that are modeled primarily with the `str` type in Python. `str` objects are more complex than the numeric objects in [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/00_content.ipynb) as they *consist* of an *arbitrary* and possibly large number of *individual* characters that may be chosen from *any* alphabet in the history of humankind. Luckily, Python abstracts away most of this complexity from us. However, after looking at the `str` type in great detail, we briefly introduce the `bytes` type at the end of this chapter to understand how characters are modeled in memory."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -137,7 +137,7 @@
|
|||
"source": [
|
||||
"As seen before, a `str` object evaluates to itself in a literal notation with enclosing **single quotes** `'`.\n",
|
||||
"\n",
|
||||
"In [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#Value-/-(Semantic)-\"Meaning\"), we specify the double quotes `\"` convention this book follows. Yet, single quotes `'` and double quotes `\"` are *perfect* substitutes. We could use the reverse convention, as well. As [this discussion <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_so.png\">](https://stackoverflow.com/questions/56011/single-quotes-vs-double-quotes-in-python) shows, many programmers have *strong* opinions about such conventions. Consequently, the discussion was \"closed as not constructive\" by the moderators."
|
||||
"In [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#Value-/-(Semantic)-\"Meaning\"), we specify the double quotes `\"` convention this book follows. Yet, single quotes `'` and double quotes `\"` are *perfect* substitutes. We could use the reverse convention, as well. As [this discussion <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_so.png\">](https://stackoverflow.com/questions/56011/single-quotes-vs-double-quotes-in-python) shows, many programmers have *strong* opinions about such conventions. Consequently, the discussion was \"closed as not constructive\" by the moderators."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -290,7 +290,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"As an alternative to the literal notation, we may use the built-in [str() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#str) constructor to cast non-`str` objects as `str` ones. As [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/00_content.ipynb) reveals, basically any object in Python has a **text representation**. Because of that we may also pass `list` objects, the boolean `True` and `False`, or `None` to [str() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#str)."
|
||||
"As an alternative to the literal notation, we may use the built-in [str() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#str) constructor to cast non-`str` objects as `str` ones. As [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/00_content.ipynb) reveals, basically any object in Python has a **text representation**. Because of that we may also pass `list` objects, the boolean `True` and `False`, or `None` to [str() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#str)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -456,7 +456,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"As shown in the \"*Guessing a Coin Toss*\" example in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/03_content.ipynb#Example:-Guessing-a-Coin-Toss), the built-in [input() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#input) function displays a prompt to the user and returns whatever is entered as a `str` object. [input() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#input) is in particular valuable when writing command-line tools."
|
||||
"As shown in the \"*Guessing a Coin Toss*\" example in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/03_content.ipynb#Example:-Guessing-a-Coin-Toss), the built-in [input() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#input) function displays a prompt to the user and returns whatever is entered as a `str` object. [input() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#input) is in particular valuable when writing command-line tools."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -571,7 +571,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"[open() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#open) returns a **[proxy <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Proxy_pattern)** object of type `TextIOWrapper` that allows us to interact with the file on disk. `mode='r'` shows that we opened the file in read-only mode and `encoding='UTF-8'` is explained in detail in the [The `bytes` Type <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/01_content.ipynb#The-bytes-Type) section at the end of this chapter."
|
||||
"[open() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#open) returns a **[proxy <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Proxy_pattern)** object of type `TextIOWrapper` that allows us to interact with the file on disk. `mode='r'` shows that we opened the file in read-only mode and `encoding='UTF-8'` is explained in detail in the [The `bytes` Type <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/01_content.ipynb#The-bytes-Type) section at the end of this chapter."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1010,7 +1010,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Using syntax familiar from [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/03_conditionals/00_content.ipynb#The-try-Statement) to explain what the `with open(...) as file:` does above, we provide an alternative formulation with a `try` statement below: The `finally`-branch is *always* executed, even if an exception is raised inside the `for`-loop. Therefore, `file` is sure to be closed too. However, this formulation is somewhat less expressive."
|
||||
"Using syntax familiar from [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/03_conditionals/00_content.ipynb#The-try-Statement) to explain what the `with open(...) as file:` does above, we provide an alternative formulation with a `try` statement below: The `finally`-branch is *always* executed, even if an exception is raised inside the `for`-loop. Therefore, `file` is sure to be closed too. However, this formulation is somewhat less expressive."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1373,7 +1373,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"A **sequence** is yet another *abstract* concept (cf., the \"*Containers vs. Iterables*\" section in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/02_content.ipynb#Containers-vs.-Iterables)).\n",
|
||||
"A **sequence** is yet another *abstract* concept (cf., the \"*Containers vs. Iterables*\" section in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/02_content.ipynb#Containers-vs.-Iterables)).\n",
|
||||
"\n",
|
||||
"It unifies *four* [orthogonal <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Orthogonality) (i.e., \"independent\") concepts into one bigger idea: Any data type, such as `str`, is considered a sequence if it\n",
|
||||
"\n",
|
||||
|
|
@ -1382,11 +1382,11 @@
|
|||
"3. can be **iterated** over\n",
|
||||
"4. in a *predictable* **order**.\n",
|
||||
"\n",
|
||||
"[Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/00_content.ipynb#Collections-vs.-Sequences) formalizes these concepts in great detail. Here, we keep our focus on the `str` type that historically received its name as it models a **[string of characters <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/String_%28computer_science%29)**. *String* is simply another term for *sequence* in the computer science literature.\n",
|
||||
"[Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/00_content.ipynb#Collections-vs.-Sequences) formalizes these concepts in great detail. Here, we keep our focus on the `str` type that historically received its name as it models a **[string of characters <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/String_%28computer_science%29)**. *String* is simply another term for *sequence* in the computer science literature.\n",
|
||||
"\n",
|
||||
"Another example of a sequence is the `list` type. Because of that, `str` objects may be treated like `list` objects in many situations.\n",
|
||||
"\n",
|
||||
"Below, the built-in [len() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#len) function tells us how many characters make up `text`. [len() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#len) would not work with an \"infinite\" object. As anything modeled in a program must fit into a computer's finite memory, there cannot exist truly infinite objects; however, [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/00_content.ipynb#Iterators-vs.-Iterables) introduces specialized iterable data types that can be used to model an *infinite* series of \"things\" and that, consequently, have no concept of \"length.\""
|
||||
"Below, the built-in [len() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#len) function tells us how many characters make up `text`. [len() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#len) would not work with an \"infinite\" object. As anything modeled in a program must fit into a computer's finite memory, there cannot exist truly infinite objects; however, [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/00_content.ipynb#Iterators-vs.-Iterables) introduces specialized iterable data types that can be used to model an *infinite* series of \"things\" and that, consequently, have no concept of \"length.\""
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1605,7 +1605,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"As `str` objects are *ordered* and *finite*, we may **index** into them to obtain individual characters with the **indexing operator** `[]`. This is analogous to how we obtained individual elements of a `list` object in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/03_content.ipynb#Who-am-I?-And-how-many?)."
|
||||
"As `str` objects are *ordered* and *finite*, we may **index** into them to obtain individual characters with the **indexing operator** `[]`. This is analogous to how we obtained individual elements of a `list` object in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/03_content.ipynb#Who-am-I?-And-how-many?)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1678,13 +1678,13 @@
|
|||
"outputs": [
|
||||
{
|
||||
"ename": "TypeError",
|
||||
"evalue": "string indices must be integers",
|
||||
"evalue": "string indices must be integers, not 'float'",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-54-31fb90bbe515>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtext\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1.0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m: string indices must be integers"
|
||||
"Cell \u001b[0;32mIn[54], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mtext\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m1.0\u001b[39;49m\u001b[43m]\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: string indices must be integers, not 'float'"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -1754,7 +1754,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-56-ffa3e1bc2f86>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtext\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m27\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;31m# == text[len(text)]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[56], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mtext\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m27\u001b[39;49m\u001b[43m]\u001b[49m \u001b[38;5;66;03m# == text[len(text)]\u001b[39;00m\n",
|
||||
"\u001b[0;31mIndexError\u001b[0m: string index out of range"
|
||||
]
|
||||
}
|
||||
|
|
@ -2292,9 +2292,9 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Whereas elements of a `list` object *may* be *re-assigned*, as shortly hinted at in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/03_content.ipynb#Who-am-I?-And-how-many?), this is *not* allowed for the individual characters of `str` objects. Once created, they can *not* be changed. Formally, we say that `str` objects are **immutable**. In that regard, they are like the numeric types in [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/00_content.ipynb).\n",
|
||||
"Whereas elements of a `list` object *may* be *re-assigned*, as shortly hinted at in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/03_content.ipynb#Who-am-I?-And-how-many?), this is *not* allowed for the individual characters of `str` objects. Once created, they can *not* be changed. Formally, we say that `str` objects are **immutable**. In that regard, they are like the numeric types in [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/00_content.ipynb).\n",
|
||||
"\n",
|
||||
"On the contrary, objects that may be changed after creation, are called **mutable**. We already saw in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/03_content.ipynb#Who-am-I?-And-how-many?) how mutable objects are more difficult to reason about for a beginner, in particular, if more than one variable references it. Yet, mutability does have its place in a programmer's toolbox, and we revisit this idea in the next chapters.\n",
|
||||
"On the contrary, objects that may be changed after creation, are called **mutable**. We already saw in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/03_content.ipynb#Who-am-I?-And-how-many?) how mutable objects are more difficult to reason about for a beginner, in particular, if more than one variable references it. Yet, mutability does have its place in a programmer's toolbox, and we revisit this idea in the next chapters.\n",
|
||||
"\n",
|
||||
"The `TypeError` indicates that `str` objects are *immutable*: Assignment to an index or a slice are *not* supported."
|
||||
]
|
||||
|
|
@ -2315,7 +2315,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-72-d8a1e6b0b786>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtext\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"X\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[72], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mtext\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mX\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: 'str' object does not support item assignment"
|
||||
]
|
||||
}
|
||||
|
|
@ -2340,7 +2340,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-73-def135e84998>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtext\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"random\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[73], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mtext\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m]\u001b[49m \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrandom\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: 'str' object does not support item assignment"
|
||||
]
|
||||
}
|
||||
|
|
@ -3377,7 +3377,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"As mentioned in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#Operator-Overloading), the `+` and `*` operators are *overloaded* and used for **string concatenation**. They always create *new* `str` objects. That has nothing to do with the `str` type's immutability, but is the default behavior of operators."
|
||||
"As mentioned in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#Operator-Overloading), the `+` and `*` operators are *overloaded* and used for **string concatenation**. They always create *new* `str` objects. That has nothing to do with the `str` type's immutability, but is the default behavior of operators."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -3447,7 +3447,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"The *relational* operators also work with `str` objects, another example of operator overloading. Comparison is done one character at a time in a pairwise fashion until the first pair differs or one operand ends. However, `str` objects are sorted in a \"weird\" way. For example, all upper case characters come before all lower case characters. The reason for that is given in the \"*Characters are Numbers with a Convention*\" sub-section in the [second part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/02_content.ipynb#Characters-are-Numbers-with-a-Convention) of this chapter."
|
||||
"The *relational* operators also work with `str` objects, another example of operator overloading. Comparison is done one character at a time in a pairwise fashion until the first pair differs or one operand ends. However, `str` objects are sorted in a \"weird\" way. For example, all upper case characters come before all lower case characters. The reason for that is given in the \"*Characters are Numbers with a Convention*\" sub-section in the [second part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/02_content.ipynb#Characters-are-Numbers-with-a-Convention) of this chapter."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -3857,7 +3857,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"The `%` operator that we saw in the context of modulo division in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#%28Arithmetic%29-Operators) is overloaded with string interpolation when its first operand is a `str` object. The second operand consists of all expressions to be filled in. Format specifiers work with a `%` instead of curly braces and according to a different set of rules referred to as **[printf-style string formatting <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#printf-style-string-formatting)**. So, `{:.2f}` becomes `%.2f`.\n",
|
||||
"The `%` operator that we saw in the context of modulo division in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#%28Arithmetic%29-Operators) is overloaded with string interpolation when its first operand is a `str` object. The second operand consists of all expressions to be filled in. Format specifiers work with a `%` instead of curly braces and according to a different set of rules referred to as **[printf-style string formatting <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#printf-style-string-formatting)**. So, `{:.2f}` becomes `%.2f`.\n",
|
||||
"\n",
|
||||
"This way of string interpolation is the oldest and originates from the [C language <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/C_%28programming_language%29). It is still widely spread, but we should use one of the other two ways instead. We show it here mainly for completeness sake."
|
||||
]
|
||||
|
|
@ -3894,7 +3894,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"To insert more than one expression, we must list them in order and between parenthesis `(` and `)`. As [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/00_content.ipynb#The-tuple-Type) reveals, this literal syntax creates an object of type `tuple`. Also, to format an expression as text, we use the format specifier `%s`."
|
||||
"To insert more than one expression, we must list them in order and between parenthesis `(` and `)`. As [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/00_content.ipynb#The-tuple-Type) reveals, this literal syntax creates an object of type `tuple`. Also, to format an expression as text, we use the format specifier `%s`."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -3938,7 +3938,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/06_text/01_exercises.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/06_text/01_exercises.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -18,7 +18,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The exercises below assume that you have read the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/00_content.ipynb) of Chapter 6.\n",
|
||||
"The exercises below assume that you have read the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/00_content.ipynb) of Chapter 6.\n",
|
||||
"\n",
|
||||
"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
|
||||
]
|
||||
|
|
@ -38,7 +38,7 @@
|
|||
"\n",
|
||||
"In this exercise, you implement various functions that check if the given arguments are palindromes or not. We start with an iterative implementation and end with a recursive one.\n",
|
||||
"\n",
|
||||
"Conceptually, the first function, `unpythonic_palindrome()`, is similar to the \"*Is the square of a number in `[7, 11, 8, 5, 3, 12, 2, 6, 9, 10, 1, 4]` greater than `100`?*\" example in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/03_content.ipynb#Example:-Is-the-square-of-a-number-in-[7,-11,-8,-5,-3,-12,-2,-6,-9,-10,-1,-4]-greater-than-100?): It assumes that the `text` argument is a palindrome (i.e., it initializes `is_palindrom` to `True`) and then checks in a `for`-loop if a pair of corresponding characters, `forward` and `backward`, contradicts that.\n",
|
||||
"Conceptually, the first function, `unpythonic_palindrome()`, is similar to the \"*Is the square of a number in `[7, 11, 8, 5, 3, 12, 2, 6, 9, 10, 1, 4]` greater than `100`?*\" example in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/03_content.ipynb#Example:-Is-the-square-of-a-number-in-[7,-11,-8,-5,-3,-12,-2,-6,-9,-10,-1,-4]-greater-than-100?): It assumes that the `text` argument is a palindrome (i.e., it initializes `is_palindrom` to `True`) and then checks in a `for`-loop if a pair of corresponding characters, `forward` and `backward`, contradicts that.\n",
|
||||
"\n",
|
||||
"**Q1**: How many iterations are needed in the `for`-loop? Take into account that `text` may contain an even or odd number of characters! Inside `unpythonic_palindrome()` below, write an expression whose result is assigned to `chars_to_check`!"
|
||||
]
|
||||
|
|
@ -974,7 +974,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/06_text/01_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/06_text/01_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -315,6 +315,16 @@
|
|||
"C:\\Programs\n",
|
||||
"ew_application\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"<>:1: SyntaxWarning: invalid escape sequence '\\P'\n",
|
||||
"<>:1: SyntaxWarning: invalid escape sequence '\\P'\n",
|
||||
"/tmp/ipykernel_159416/1102122489.py:1: SyntaxWarning: invalid escape sequence '\\P'\n",
|
||||
" print(\"C:\\Programs\\new_application\")\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
|
|
@ -343,10 +353,10 @@
|
|||
"outputs": [
|
||||
{
|
||||
"ename": "SyntaxError",
|
||||
"evalue": "(unicode error) 'unicodeescape' codec can't decode bytes in position 2-3: truncated \\UXXXXXXXX escape (<ipython-input-10-61308f43d404>, line 1)",
|
||||
"evalue": "(unicode error) 'unicodeescape' codec can't decode bytes in position 2-3: truncated \\UXXXXXXXX escape (2296736867.py, line 1)",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;36m File \u001b[0;32m\"<ipython-input-10-61308f43d404>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m print(\"C:\\Users\\Administrator\\Desktop\\Project\")\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m (unicode error) 'unicodeescape' codec can't decode bytes in position 2-3: truncated \\UXXXXXXXX escape\n"
|
||||
"\u001b[0;36m Cell \u001b[0;32mIn[10], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m print(\"C:\\Users\\Administrator\\Desktop\\Project\")\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m (unicode error) 'unicodeescape' codec can't decode bytes in position 2-3: truncated \\UXXXXXXXX escape\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -481,7 +491,7 @@
|
|||
"source": [
|
||||
"So far, we used the term **character** without any further consideration. In this section, we briefly look into what characters are and how they are modeled in software.\n",
|
||||
"\n",
|
||||
"[Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/00_content.ipynb) gives us an idea on how individual **bits** are used to express all types of numbers, from \"simple\" `int` objects to \"complex\" `float` ones. To model characters, another **layer of abstraction** is put on top of whole numbers. So, just as bits are used to express integers, they themselves are used to express characters."
|
||||
"[Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/00_content.ipynb) gives us an idea on how individual **bits** are used to express all types of numbers, from \"simple\" `int` objects to \"complex\" `float` ones. To model characters, another **layer of abstraction** is put on top of whole numbers. So, just as bits are used to express integers, they themselves are used to express characters."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -627,7 +637,7 @@
|
|||
"\n",
|
||||
"For example, the digit `5` is mapped to the number `53` in ASCII. The binary representation of `53` is `0b_11_0101` and the least significant four bits, `0101`, mean $5$. Similarly, the letter `\"E\"` is the fifth letter in the alphabet. It is encoded with the number `69` in ASCII, which is `0b_100_0101` in binary. And, the least significant bits, `0_0101`, mean $5$. Analogously, `\"e\"` is encoded with `101` in ASCII, which is `0b_110_0101` in binary. And, the least significant bits, `0_0101`, mean $5$ again. This encoding was chosen mainly because programmers \"in the old days\" needed to implement these encodings \"by hand.\" Python abstracts that logic away from its users.\n",
|
||||
"\n",
|
||||
"This encoding scheme is also the cause for the \"weird\" sorting in the \"*String Comparison*\" section in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/01_content.ipynb#String-Comparison) of this chapter, where `\"apple\"` comes *after* `\"Banana\"`. As `\"a\"` is encoded with `97` and `\"B\"` with `66`, `\"Banana\"` must of course be \"smaller\" than `\"apple\"` when comparison is done in a pairwise fashion of the individual characters."
|
||||
"This encoding scheme is also the cause for the \"weird\" sorting in the \"*String Comparison*\" section in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/01_content.ipynb#String-Comparison) of this chapter, where `\"apple\"` comes *after* `\"Banana\"`. As `\"a\"` is encoded with `97` and `\"B\"` with `66`, `\"Banana\"` must of course be \"smaller\" than `\"apple\"` when comparison is done in a pairwise fashion of the individual characters."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1174,10 +1184,10 @@
|
|||
"outputs": [
|
||||
{
|
||||
"ename": "SyntaxError",
|
||||
"evalue": "EOL while scanning string literal (<ipython-input-34-4cef690f1f4a>, line 1)",
|
||||
"evalue": "unterminated string literal (detected at line 1) (2682216481.py, line 1)",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;36m File \u001b[0;32m\"<ipython-input-34-4cef690f1f4a>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m \"\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m EOL while scanning string literal\n"
|
||||
"\u001b[0;36m Cell \u001b[0;32mIn[34], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m \"\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m unterminated string literal (detected at line 1)\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -1835,7 +1845,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mUnicodeDecodeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-55-1630cf8a20cc>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplace\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mencode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"iso-8859-1\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdecode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[55], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mplace\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mencode\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43miso-8859-1\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdecode\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mUnicodeDecodeError\u001b[0m: 'utf-8' codec can't decode byte 0xe9 in position 3: invalid continuation byte"
|
||||
]
|
||||
}
|
||||
|
|
@ -1871,7 +1881,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mUnicodeEncodeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-56-8dd3b1bfcf5d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;34m\"Dobrý den, přátelé!\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mencode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"iso-8859-1\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[56], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mDobrý den, přátelé!\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mencode\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43miso-8859-1\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mUnicodeEncodeError\u001b[0m: 'latin-1' codec can't encode character '\\u0159' in position 12: ordinal not in range(256)"
|
||||
]
|
||||
}
|
||||
|
|
@ -1918,8 +1928,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mUnicodeDecodeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-57-83a7d1245cc7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"umlauts.txt\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfile\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreadlines\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m~/.pyenv/versions/3.8.6/lib/python3.8/codecs.py\u001b[0m in \u001b[0;36mdecode\u001b[0;34m(self, input, final)\u001b[0m\n\u001b[1;32m 320\u001b[0m \u001b[0;31m# decode input (taking the buffer into account)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 321\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuffer\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 322\u001b[0;31m \u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconsumed\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_buffer_decode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfinal\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 323\u001b[0m \u001b[0;31m# keep undecoded input until the next call\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 324\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuffer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mconsumed\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[57], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mopen\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mumlauts.txt\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m file:\n\u001b[0;32m----> 2\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(\u001b[43mfile\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreadlines\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m))\n",
|
||||
"File \u001b[0;32m<frozen codecs>:322\u001b[0m, in \u001b[0;36mdecode\u001b[0;34m(self, input, final)\u001b[0m\n",
|
||||
"\u001b[0;31mUnicodeDecodeError\u001b[0m: 'utf-8' codec can't decode byte 0xe4 in position 9: invalid continuation byte"
|
||||
]
|
||||
}
|
||||
|
|
@ -1981,7 +1991,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"A best practice is to *always* specify the `encoding`, especially on computers running on Windows (cf., the talk by Łukasz Langa in the [Further Resources <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/05_resources.ipynb#Unicode)) section at the end of this chapter.\n",
|
||||
"A best practice is to *always* specify the `encoding`, especially on computers running on Windows (cf., the talk by Łukasz Langa in the [Further Resources <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/05_resources.ipynb#Unicode)) section at the end of this chapter.\n",
|
||||
"\n",
|
||||
"Below is the first example involving [open() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#open) one last time: It shows how *all* the contents of a text file should be read into one `str` object."
|
||||
]
|
||||
|
|
@ -2068,7 +2078,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -43,7 +43,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -11,7 +11,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/00_content.ipynb) and [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/01_content.ipynb) part of Chapter 6.\n",
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/00_content.ipynb) and [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/01_content.ipynb) part of Chapter 6.\n",
|
||||
"\n",
|
||||
"Be concise in your answers! Most questions can be answered in *one* sentence."
|
||||
]
|
||||
|
|
@ -178,7 +178,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/06_text/05_resources.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/06_text/05_resources.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -62,6 +62,7 @@
|
|||
" src=\"https://www.youtube.com/embed/MijmeoH9LT4\"\n",
|
||||
" frameborder=\"0\"\n",
|
||||
" allowfullscreen\n",
|
||||
" \n",
|
||||
" ></iframe>\n",
|
||||
" "
|
||||
],
|
||||
|
|
@ -87,7 +88,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"In his [PyCon Australia 2018](https://2018.pycon-au.org/) talk titled \"*Unicode and Python: The absolute minimum you need to know*\" [Raphaël Merx](https://www.linkedin.com/in/raphaelmerx/) explains some caveats and best practices regarding Unicode."
|
||||
"In his [PyCon Australia 2018](https://2018.pycon-au.org/) talk titled \"*Unicode and Python: The absolute minimum you need to know*\" [Raphaël Merx](https://www.linkedin.com/raphaelmerx/) explains some caveats and best practices regarding Unicode."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -110,6 +111,7 @@
|
|||
" src=\"https://www.youtube.com/embed/oXVmZGN6plY\"\n",
|
||||
" frameborder=\"0\"\n",
|
||||
" allowfullscreen\n",
|
||||
" \n",
|
||||
" ></iframe>\n",
|
||||
" "
|
||||
],
|
||||
|
|
@ -134,7 +136,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"In a similar talk at [PyCon 2017](https://us.pycon.org/2017/) titled \"*Unicode what is the big deal*\" [Łukasz Langa](https://www.linkedin.com/in/llanga/) provides further lessons learned regarding Unicode."
|
||||
"In a similar talk at [PyCon 2017](https://us.pycon.org/2017/) titled \"*Unicode what is the big deal*\" [Łukasz Langa](https://www.linkedin.com/llanga/) provides further lessons learned regarding Unicode."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -157,6 +159,7 @@
|
|||
" src=\"https://www.youtube.com/embed/7m5JA3XaZ4k\"\n",
|
||||
" frameborder=\"0\"\n",
|
||||
" allowfullscreen\n",
|
||||
" \n",
|
||||
" ></iframe>\n",
|
||||
" "
|
||||
],
|
||||
|
|
@ -204,6 +207,7 @@
|
|||
" src=\"https://www.youtube.com/embed/sgHbC6udIqc\"\n",
|
||||
" frameborder=\"0\"\n",
|
||||
" allowfullscreen\n",
|
||||
" \n",
|
||||
" ></iframe>\n",
|
||||
" "
|
||||
],
|
||||
|
|
@ -235,7 +239,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Lastly, in his entertaining talk at [PyCon.DE 2019](https://de.pycon.org/) titled \"*Your Name is Invalid!*\" [Miroslav Šedivý](https://www.linkedin.com/in/%C5%A1ediv%C3%BD/) shows how hard it actually is to write software that can process any name a human can possibly have. Miroslav also gave a lightning talk where he shows how he uses only one keyboard for the 12 (!!!) languages he speaks."
|
||||
"Lastly, in his entertaining talk at [PyCon.DE 2019](https://de.pycon.org/) titled \"*Your Name is Invalid!*\" [Miroslav Šedivý](https://www.linkedin.com/%C5%A1ediv%C3%BD/) shows how hard it actually is to write software that can process any name a human can possibly have. Miroslav also gave a lightning talk where he shows how he uses only one keyboard for the 12 (!!!) languages he speaks."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -258,6 +262,7 @@
|
|||
" src=\"https://www.youtube.com/embed/pBuS7EUPnQA\"\n",
|
||||
" frameborder=\"0\"\n",
|
||||
" allowfullscreen\n",
|
||||
" \n",
|
||||
" ></iframe>\n",
|
||||
" "
|
||||
],
|
||||
|
|
@ -294,6 +299,7 @@
|
|||
" src=\"https://www.youtube.com/embed/-4QjII981sM\"\n",
|
||||
" frameborder=\"0\"\n",
|
||||
" allowfullscreen\n",
|
||||
" \n",
|
||||
" ></iframe>\n",
|
||||
" "
|
||||
],
|
||||
|
|
@ -327,7 +333,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/07_sequences/00_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/07_sequences/00_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -30,11 +30,11 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"We studied numbers (cf., [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/00_content.ipynb)) and textual data (cf., [Chapter 6 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/00_content.ipynb)) first mainly because objects of the presented data types are \"simple.\" That is so for two reasons: First, they are *immutable*, and, as we saw in the \"*Who am I? And how many?*\" section in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/03_content.ipynb#Who-am-I?-And-how-many?), mutable objects can quickly become hard to reason about. Second, they are \"flat\" in the sense that they are *not* composed of other objects.\n",
|
||||
"We studied numbers (cf., [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/00_content.ipynb)) and textual data (cf., [Chapter 6 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/00_content.ipynb)) first mainly because objects of the presented data types are \"simple.\" That is so for two reasons: First, they are *immutable*, and, as we saw in the \"*Who am I? And how many?*\" section in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/03_content.ipynb#Who-am-I?-And-how-many?), mutable objects can quickly become hard to reason about. Second, they are \"flat\" in the sense that they are *not* composed of other objects.\n",
|
||||
"\n",
|
||||
"The `str` type is a bit of a corner case in this regard. While one could argue that a longer `str` object, for example, `\"text\"`, is composed of individual characters, this is *not* the case in memory as the literal `\"text\"` only creates *one* object (i.e., one \"bag\" of $0$s and $1$s modeling all characters).\n",
|
||||
"\n",
|
||||
"This chapter, [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/00_content.ipynb), [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/00_content.ipynb), and [Chapter 10 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/10_arrays/00_content.ipynb) introduce various \"complex\" data types. While some are mutable and others are not, they all share that they are primarily used to \"manage,\" or structure, the memory in a program (i.e., they provide references to other objects). Unsurprisingly, computer scientists refer to the ideas behind these data types as **[data structures <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Data_structure)**.\n",
|
||||
"This chapter, [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/00_content.ipynb), [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/00_content.ipynb), and [Chapter 10 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/10_arrays/00_content.ipynb) introduce various \"complex\" data types. While some are mutable and others are not, they all share that they are primarily used to \"manage,\" or structure, the memory in a program (i.e., they provide references to other objects). Unsurprisingly, computer scientists refer to the ideas behind these data types as **[data structures <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Data_structure)**.\n",
|
||||
"\n",
|
||||
"In this chapter, we focus on data types that model all kinds of sequential data. Examples of such data are [spreadsheets <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Spreadsheet) or [matrices <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Matrix_%28mathematics%29) and [vectors <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Vector_%28mathematics_and_physics%29). These formats share the property that they are composed of smaller units that come in a sequence of, for example, rows/columns/cells or elements/entries."
|
||||
]
|
||||
|
|
@ -58,9 +58,9 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"[Chapter 6 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/00_content.ipynb#A-\"String\"-of-Characters) already describes the **sequence** properties of `str` objects. In this section, we take a step back and study these properties one by one.\n",
|
||||
"[Chapter 6 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/00_content.ipynb#A-\"String\"-of-Characters) already describes the **sequence** properties of `str` objects. In this section, we take a step back and study these properties one by one.\n",
|
||||
"\n",
|
||||
"The [collections.abc <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.abc.html) module in the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html) defines a variety of **abstract base classes** (ABCs). We saw ABCs already in [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/02_content.ipynb#The-Numerical-Tower), where we use the ones from the [numbers <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/numbers.html) module in the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html) to classify Python's numeric data types according to mathematical ideas. Now, we take the ABCs from the [collections.abc <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.abc.html) module to classify the data types in this chapter according to their behavior in various contexts.\n",
|
||||
"The [collections.abc <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.abc.html) module in the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html) defines a variety of **abstract base classes** (ABCs). We saw ABCs already in [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/02_content.ipynb#The-Numerical-Tower), where we use the ones from the [numbers <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/numbers.html) module in the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html) to classify Python's numeric data types according to mathematical ideas. Now, we take the ABCs from the [collections.abc <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.abc.html) module to classify the data types in this chapter according to their behavior in various contexts.\n",
|
||||
"\n",
|
||||
"As an illustration, consider `numbers` and `text` below, two objects of *different* types."
|
||||
]
|
||||
|
|
@ -142,7 +142,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"In [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/02_content.ipynb#Containers-vs.-Iterables), we referred to such types as *iterables*. That is *not* a proper [English](https://dictionary.cambridge.org/spellcheck/english-german/?q=iterable) word, even if it may sound like one at first sight. Yet, it is an official term in the Python world formalized with the `Iterable` ABC in the [collections.abc <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.abc.html) module.\n",
|
||||
"In [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/02_content.ipynb#Containers-vs.-Iterables), we referred to such types as *iterables*. That is *not* a proper [English](https://dictionary.cambridge.org/spellcheck/english-german/?q=iterable) word, even if it may sound like one at first sight. Yet, it is an official term in the Python world formalized with the `Iterable` ABC in the [collections.abc <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.abc.html) module.\n",
|
||||
"\n",
|
||||
"For the data science practitioner, it is worthwhile to know such terms as, for example, the documentation on the [built-ins <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html) uses them extensively: In simple words, any built-in that takes an argument called \"*iterable*\" may be called with *any* object that supports being looped over. Already familiar [built-ins <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html) include [enumerate() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#enumerate), [sum() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#sum), or [zip() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#zip). So, they do *not* require the argument to be of a certain data type (e.g., `list`); instead, any *iterable* type works."
|
||||
]
|
||||
|
|
@ -192,7 +192,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"As seen in [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/02_content.ipynb#Goose-Typing), we can use ABCs with the built-in [isinstance() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#isinstance) function to check if an object supports a behavior.\n",
|
||||
"As seen in [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/02_content.ipynb#Goose-Typing), we can use ABCs with the built-in [isinstance() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#isinstance) function to check if an object supports a behavior.\n",
|
||||
"\n",
|
||||
"So, let's \"ask\" Python if it can loop over `numbers` or `text`."
|
||||
]
|
||||
|
|
@ -307,7 +307,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-9-8249bf25b5b7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mdigit\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;36m999\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdigit\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[9], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mdigit\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;241;43m999\u001b[39;49m\u001b[43m:\u001b[49m\n\u001b[1;32m 2\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mprint\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mdigit\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: 'int' object is not iterable"
|
||||
]
|
||||
}
|
||||
|
|
@ -325,7 +325,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Most of the data types in this chapter and [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/00_content.ipynb) and [Chapter 10 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/10_arrays/00_content.ipynb) exhibit three [orthogonal <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Orthogonality) (i.e., \"independent\") behaviors, formalized by ABCs in the [collections.abc <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.abc.html) module as:\n",
|
||||
"Most of the data types in this chapter and [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/00_content.ipynb) and [Chapter 10 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/10_arrays/00_content.ipynb) exhibit three [orthogonal <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Orthogonality) (i.e., \"independent\") behaviors, formalized by ABCs in the [collections.abc <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.abc.html) module as:\n",
|
||||
"- `Iterable`: An object may be looped over.\n",
|
||||
"- `Container`: An object \"contains\" references to other objects; a \"whole\" is composed of many \"parts.\"\n",
|
||||
"- `Sized`: The number of references to other objects, the \"parts,\" is *finite*.\n",
|
||||
|
|
@ -491,7 +491,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-15-b3e0b3c32aec>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;36m9\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;36m999\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[15], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;241;43m9\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;241;43m999\u001b[39;49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: argument of type 'int' is not iterable"
|
||||
]
|
||||
}
|
||||
|
|
@ -658,7 +658,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-21-ae09c1aa5305>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m999\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[21], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m999\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: object of type 'int' has no len()"
|
||||
]
|
||||
}
|
||||
|
|
@ -902,11 +902,11 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"The data types introduced in this chapter are sequences. Nevertheless, we also look at some data types that are neither collections nor sequences but are still useful to model sequential data in practice in [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/00_content.ipynb).\n",
|
||||
"The data types introduced in this chapter are sequences. Nevertheless, we also look at some data types that are neither collections nor sequences but are still useful to model sequential data in practice in [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/00_content.ipynb).\n",
|
||||
"\n",
|
||||
"In Python-related documentations, the terms collection and sequence are heavily used, and the data science practitioner should always think of them in terms of the three or four behaviors they exhibit.\n",
|
||||
"\n",
|
||||
"Data types that are collections but not sequences are covered in [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/00_content.ipynb)."
|
||||
"Data types that are collections but not sequences are covered in [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/00_content.ipynb)."
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -926,7 +926,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/07_sequences/01_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/07_sequences/01_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -113,7 +113,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"[PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=empty%20%3D%20%5B%5D%0Asimple%20%3D%20%5B40,%2050%5D%0Anested%20%3D%20%5Bempty,%2010,%2020.0,%20%22Thirty%22,%20simple%5D&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows how `nested` holds references to the `empty` and `simple` objects. Technically, it holds three more references to the `10`, `20.0`, and `\"Thirty\"` objects as well. However, to simplify the visualization, these three objects are shown right inside the `nested` object. That may be done because they are immutable and \"flat\" data types. In general, the $0$s and $1$s inside a `list` object in memory always constitute references to other objects only."
|
||||
"[PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=empty%20%3D%20%5B%5D%0Asimple%20%3D%20%5B40,%2050%5D%0Anested%20%3D%20%5Bempty,%2010,%2020.0,%20%22Thirty%22,%20simple%5D&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows how `nested` holds references to the `empty` and `simple` objects. Technically, it holds three more references to the `10`, `20.0`, and `\"Thirty\"` objects as well. However, to simplify the visualization, these three objects are shown right inside the `nested` object. That may be done because they are immutable and \"flat\" data types. In general, the $0$s and $1$s inside a `list` object in memory always constitute references to other objects only."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -209,7 +209,7 @@
|
|||
"source": [
|
||||
"Alternatively, we use the built-in [list() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-list) constructor to create a `list` object out of any (finite) *iterable* we pass to it as the argument.\n",
|
||||
"\n",
|
||||
"For example, we can wrap the [range() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-range) built-in with [list() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-list): As described in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/02_content.ipynb#Containers-vs.-Iterables), `range` objects, like `range(1, 13)` below, are iterable and generate `int` objects \"on the fly\" (i.e., one by one). The [list() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-list) around it acts like a `for`-loop and **materializes** twelve `int` objects in memory that then become the elements of the newly created `list` object. [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=r%20%3D%20range%281,%2013%29%0Al%20%3D%20list%28range%281,%2013%29%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows this difference visually."
|
||||
"For example, we can wrap the [range() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-range) built-in with [list() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-list): As described in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/02_content.ipynb#Containers-vs.-Iterables), `range` objects, like `range(1, 13)` below, are iterable and generate `int` objects \"on the fly\" (i.e., one by one). The [list() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-list) around it acts like a `for`-loop and **materializes** twelve `int` objects in memory that then become the elements of the newly created `list` object. [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=r%20%3D%20range%281,%2013%29%0Al%20%3D%20list%28range%281,%2013%29%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows this difference visually."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -263,7 +263,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mMemoryError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-8-dbb397cbb3b9>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m999_999_999_999\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[8], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mrange\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m999_999_999_999\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mMemoryError\u001b[0m: "
|
||||
]
|
||||
}
|
||||
|
|
@ -614,7 +614,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-17-cb216f4a067e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnested\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[17], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mnested\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m]\u001b[49m\n",
|
||||
"\u001b[0;31mIndexError\u001b[0m: list index out of range"
|
||||
]
|
||||
}
|
||||
|
|
@ -1039,7 +1039,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"However, as [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=nested%20%3D%20%5B%5B%5D,%2010,%2020.0,%20%22Thirty%22,%20%5B40,%2050%5D%5D%0Anested_copy%20%3D%20nested%5B%3A%5D&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) reveals, only the *references* to the elements are copied, and not the objects in `nested` themselves! Because of that, `nested_copy` is a so-called **[shallow copy <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Object_copying#Shallow_copy)** of `nested`.\n",
|
||||
"However, as [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=nested%20%3D%20%5B%5B%5D,%2010,%2020.0,%20%22Thirty%22,%20%5B40,%2050%5D%5D%0Anested_copy%20%3D%20nested%5B%3A%5D&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) reveals, only the *references* to the elements are copied, and not the objects in `nested` themselves! Because of that, `nested_copy` is a so-called **[shallow copy <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Object_copying#Shallow_copy)** of `nested`.\n",
|
||||
"\n",
|
||||
"We could also see this with the [id() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#id) function: The respective first elements in both `nested` and `nested_copy` are the *same* object, namely `empty`. So, we have three ways of accessing the *same* address in memory. Also, we say that `nested` and `nested_copy` partially share the *same* state."
|
||||
]
|
||||
|
|
@ -1191,7 +1191,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Now, the first elements of `nested` and `nested_deep_copy` are *different* objects, and [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=import%20copy%0Anested%20%3D%20%5B%5B%5D,%2010,%2020.0,%20%22Thirty%22,%20%5B40,%2050%5D%5D%0Anested_deep_copy%20%3D%20copy.deepcopy%28nested%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows that there are *six* `list` objects in memory."
|
||||
"Now, the first elements of `nested` and `nested_deep_copy` are *different* objects, and [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=import%20copy%0Anested%20%3D%20%5B%5B%5D,%2010,%2020.0,%20%22Thirty%22,%20%5B40,%2050%5D%5D%0Anested_deep_copy%20%3D%20copy.deepcopy%28nested%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows that there are *six* `list` objects in memory."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1569,7 +1569,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"That is precisely the confusion we talked about above when we said that `nested_copy` is a *shallow* copy of `nested`. [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=nested%20%3D%20%5B%5B%5D,%2010,%2020.0,%20%22Thirty%22,%20%5B40,%2050%5D%5D%0Anested_copy%20%3D%20nested%5B%3A%5D%0Anested%5B%3A4%5D%20%3D%20%5B100,%20100,%20100%5D%0Anested_copy%5B-1%5D%5B%3A%5D%20%3D%20%5B1,%202,%203%5D&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows how both reference the *same* nested `list` object that is changed *in place* from `[40, 50]` into `[1, 2, 3]`.\n",
|
||||
"That is precisely the confusion we talked about above when we said that `nested_copy` is a *shallow* copy of `nested`. [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=nested%20%3D%20%5B%5B%5D,%2010,%2020.0,%20%22Thirty%22,%20%5B40,%2050%5D%5D%0Anested_copy%20%3D%20nested%5B%3A%5D%0Anested%5B%3A4%5D%20%3D%20%5B100,%20100,%20100%5D%0Anested_copy%5B-1%5D%5B%3A%5D%20%3D%20%5B1,%202,%203%5D&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows how both reference the *same* nested `list` object that is changed *in place* from `[40, 50]` into `[1, 2, 3]`.\n",
|
||||
"\n",
|
||||
"Lastly, we use the `del` statement to remove an element."
|
||||
]
|
||||
|
|
@ -1691,7 +1691,7 @@
|
|||
"source": [
|
||||
"The `list` type is an essential data structure in any real-world Python application, and many typical `list`-related algorithms from computer science theory are already built into it at the C level (cf., the [documentation <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#mutable-sequence-types) or the [tutorial <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/tutorial/datastructures.html#more-on-lists) for a full overview; unfortunately, not all methods have direct links). So, understanding and applying the built-in methods of the `list` type not only speeds up the development process but also makes programs significantly faster.\n",
|
||||
"\n",
|
||||
"In contrast to the `str` type's methods in [Chapter 6 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/00_content.ipynb#String-Methods) (e.g., [.upper() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#str.upper) or [.lower() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#str.lower)), the `list` type's methods that mutate an object do so *in place*. That means they *never* create *new* `list` objects and return `None` to indicate that. So, we must *never* assign the return value of `list` methods to the variable holding the list!\n",
|
||||
"In contrast to the `str` type's methods in [Chapter 6 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/00_content.ipynb#String-Methods) (e.g., [.upper() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#str.upper) or [.lower() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#str.lower)), the `list` type's methods that mutate an object do so *in place*. That means they *never* create *new* `list` objects and return `None` to indicate that. So, we must *never* assign the return value of `list` methods to the variable holding the list!\n",
|
||||
"\n",
|
||||
"Let's look at the following `names` example."
|
||||
]
|
||||
|
|
@ -2029,7 +2029,7 @@
|
|||
"source": [
|
||||
"The [.sort() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#list.sort) method and the [sorted() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#sorted) function sort the elements in `names` in alphabetical order, forward or backward. However, that does *not* hold in general.\n",
|
||||
"\n",
|
||||
"We mention above that `list` objects may contain objects of *any* type and even of *mixed* types. Because of that, the sorting is **[delegated <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Delegation_(object-oriented_programming))** to the elements in a `list` object. In a way, Python \"asks\" the elements in a `list` object to sort themselves. As `names` contains only `str` objects, they are sorted according the the comparison rules explained in [Chapter 6 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/00_content.ipynb#String-Comparison).\n",
|
||||
"We mention above that `list` objects may contain objects of *any* type and even of *mixed* types. Because of that, the sorting is **[delegated <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Delegation_(object-oriented_programming))** to the elements in a `list` object. In a way, Python \"asks\" the elements in a `list` object to sort themselves. As `names` contains only `str` objects, they are sorted according the the comparison rules explained in [Chapter 6 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/00_content.ipynb#String-Comparison).\n",
|
||||
"\n",
|
||||
"To customize the sorting, we pass a keyword-only `key` argument to [.sort() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#list.sort) or [sorted() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#sorted), which must be a `function` object accepting *one* positional argument. Then, the elements in the `list` object are passed to that one by one, and the return values are used as the **sort keys**. The `key` argument is also a popular use case for `lambda` expressions.\n",
|
||||
"\n",
|
||||
|
|
@ -2355,7 +2355,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-80-6bb75d50cf06>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnames\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Peter\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[80], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mnames\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mremove\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mPeter\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mValueError\u001b[0m: list.remove(x): x not in list"
|
||||
]
|
||||
}
|
||||
|
|
@ -2439,7 +2439,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-83-8c741a6680be>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnames\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Karl\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[83], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mnames\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mindex\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mKarl\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mValueError\u001b[0m: 'Karl' is not in list"
|
||||
]
|
||||
}
|
||||
|
|
@ -2967,7 +2967,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/07_sequences/02_exercises.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/07_sequences/02_exercises.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -18,7 +18,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The exercises below assume that you have read the [second part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/01_content.ipynb) of Chapter 7.\n",
|
||||
"The exercises below assume that you have read the [second part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/01_content.ipynb) of Chapter 7.\n",
|
||||
"\n",
|
||||
"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
|
||||
]
|
||||
|
|
@ -236,7 +236,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/07_sequences/03_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/07_sequences/03_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -96,7 +96,7 @@
|
|||
"source": [
|
||||
"While this function is being executed, two variables, namely `letters` in the global scope and `arg` inside the function's local scope, reference the *same* `list` object in memory. Furthermore, the passed in `arg` is also the return value.\n",
|
||||
"\n",
|
||||
"So, after the function call, `letters_with_xyz` and `letters` are **aliases** as well, referencing the *same* object. We can also visualize that with [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=letters%20%3D%20%5B%22a%22,%20%22b%22,%20%22c%22%5D%0A%0Adef%20add_xyz%28arg%29%3A%0A%20%20%20%20arg.extend%28%5B%22x%22,%20%22y%22,%20%22z%22%5D%29%0A%20%20%20%20return%20arg%0A%0Aletters_with_xyz%20%3D%20add_xyz%28letters%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false)."
|
||||
"So, after the function call, `letters_with_xyz` and `letters` are **aliases** as well, referencing the *same* object. We can also visualize that with [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=letters%20%3D%20%5B%22a%22,%20%22b%22,%20%22c%22%5D%0A%0Adef%20add_xyz%28arg%29%3A%0A%20%20%20%20arg.extend%28%5B%22x%22,%20%22y%22,%20%22z%22%5D%29%0A%20%20%20%20return%20arg%0A%0Aletters_with_xyz%20%3D%20add_xyz%28letters%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -170,9 +170,9 @@
|
|||
"source": [
|
||||
"A better practice is to first create a copy of `arg` within the function that is then modified and returned. If we are sure that `arg` contains immutable elements only, we get away with a shallow copy. The downside of this approach is the higher amount of memory necessary.\n",
|
||||
"\n",
|
||||
"The revised `add_xyz()` function below is more natural to reason about as it does *not* modify the passed in `arg` internally. [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=letters%20%3D%20%5B%22a%22,%20%22b%22,%20%22c%22%5D%0A%0Adef%20add_xyz%28arg%29%3A%0A%20%20%20%20new_arg%20%3D%20arg%5B%3A%5D%0A%20%20%20%20new_arg.extend%28%5B%22x%22,%20%22y%22,%20%22z%22%5D%29%0A%20%20%20%20return%20new_arg%0A%0Aletters_with_xyz%20%3D%20add_xyz%28letters%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows that as well. This approach is following the **[functional programming <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Functional_programming)** paradigm that is going through a \"renaissance\" currently. Two essential characteristics of functional programming are that a function *never* changes its inputs and *always* returns the same output given the same inputs.\n",
|
||||
"The revised `add_xyz()` function below is more natural to reason about as it does *not* modify the passed in `arg` internally. [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=letters%20%3D%20%5B%22a%22,%20%22b%22,%20%22c%22%5D%0A%0Adef%20add_xyz%28arg%29%3A%0A%20%20%20%20new_arg%20%3D%20arg%5B%3A%5D%0A%20%20%20%20new_arg.extend%28%5B%22x%22,%20%22y%22,%20%22z%22%5D%29%0A%20%20%20%20return%20new_arg%0A%0Aletters_with_xyz%20%3D%20add_xyz%28letters%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows that as well. This approach is following the **[functional programming <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Functional_programming)** paradigm that is going through a \"renaissance\" currently. Two essential characteristics of functional programming are that a function *never* changes its inputs and *always* returns the same output given the same inputs.\n",
|
||||
"\n",
|
||||
"For a beginner, it is probably better to stick to this idea and not change any arguments as the original `add_xyz()` above. However, functions that modify and return the argument passed in are an important aspect of object-oriented programming, as explained in [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/00_content.ipynb)."
|
||||
"For a beginner, it is probably better to stick to this idea and not change any arguments as the original `add_xyz()` above. However, functions that modify and return the argument passed in are an important aspect of object-oriented programming, as explained in [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/00_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -275,7 +275,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"If we want to modify the argument passed in, it is best to return `None` and not `arg`, as does the final version of `add_xyz()` below. Then, the user of our function cannot accidentally create two aliases to the same object. That is also why the list methods above all return `None`. [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=letters%20%3D%20%5B%22a%22,%20%22b%22,%20%22c%22%5D%0A%0Adef%20add_xyz%28arg%29%3A%0A%20%20%20%20arg.extend%28%5B%22x%22,%20%22y%22,%20%22z%22%5D%29%0A%20%20%20%20return%0A%0Aadd_xyz%28letters%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows how there is only *one* reference to `letters` after the function call."
|
||||
"If we want to modify the argument passed in, it is best to return `None` and not `arg`, as does the final version of `add_xyz()` below. Then, the user of our function cannot accidentally create two aliases to the same object. That is also why the list methods above all return `None`. [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=letters%20%3D%20%5B%22a%22,%20%22b%22,%20%22c%22%5D%0A%0Adef%20add_xyz%28arg%29%3A%0A%20%20%20%20arg.extend%28%5B%22x%22,%20%22y%22,%20%22z%22%5D%29%0A%20%20%20%20return%0A%0Aadd_xyz%28letters%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows how there is only *one* reference to `letters` after the function call."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1129,7 +1129,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-43-80fddf1304f0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnumbers\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m99\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[43], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mnumbers\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m]\u001b[49m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m99\u001b[39m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: 'tuple' object does not support item assignment"
|
||||
]
|
||||
}
|
||||
|
|
@ -1170,7 +1170,7 @@
|
|||
}
|
||||
],
|
||||
"source": [
|
||||
"numbers + (99,) "
|
||||
"numbers + (99,)"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1469,7 +1469,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"In the \"*List Operations*\" section in the [second part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/01_content.ipynb#List-Operations) of this chapter, the `*` symbol **unpacks** the elements of a `list` object into another one. This idea of *iterable unpacking* is built into Python at various places, even *without* the `*` symbol.\n",
|
||||
"In the \"*List Operations*\" section in the [second part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/01_content.ipynb#List-Operations) of this chapter, the `*` symbol **unpacks** the elements of a `list` object into another one. This idea of *iterable unpacking* is built into Python at various places, even *without* the `*` symbol.\n",
|
||||
"\n",
|
||||
"For example, we may write variables on the left-hand side of a `=` statement in a literal `tuple` style. Then, any *finite* iterable on the right-hand side is unpacked. So, `numbers` is unpacked into *twelve* variables below."
|
||||
]
|
||||
|
|
@ -1586,7 +1586,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-60-c5e79943681f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mn1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn4\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn5\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn6\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn7\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn8\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn9\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn10\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn11\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnumbers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[60], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m n1, n2, n3, n4, n5, n6, n7, n8, n9, n10, n11 \u001b[38;5;241m=\u001b[39m numbers\n",
|
||||
"\u001b[0;31mValueError\u001b[0m: too many values to unpack (expected 11)"
|
||||
]
|
||||
}
|
||||
|
|
@ -1611,7 +1611,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-61-214f2de70baf>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mn1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn4\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn5\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn6\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn7\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn8\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn9\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn10\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn11\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn12\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn13\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnumbers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[61], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m n1, n2, n3, n4, n5, n6, n7, n8, n9, n10, n11, n12, n13 \u001b[38;5;241m=\u001b[39m numbers\n",
|
||||
"\u001b[0;31mValueError\u001b[0m: not enough values to unpack (expected 13, got 12)"
|
||||
]
|
||||
}
|
||||
|
|
@ -2041,7 +2041,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Unpacking allows us to rewrite the iterative `fibonacci()` function from [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/02_content.ipynb#\"Hard-at-first-Glance\"-Example:-Fibonacci-Numbers-%28revisited%29) in a concise way."
|
||||
"Unpacking allows us to rewrite the iterative `fibonacci()` function from [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/02_content.ipynb#\"Hard-at-first-Glance\"-Example:-Fibonacci-Numbers-%28revisited%29) in a concise way."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -2240,8 +2240,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-83-640e0c632b8d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mproduct\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-80-02b0db9fbeab>\u001b[0m in \u001b[0;36mproduct\u001b[0;34m(*args)\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mproduct\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;34m\"\"\"Multiply all arguments.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0marg\u001b[0m \u001b[0;32min\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[83], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mproduct\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[80], line 3\u001b[0m, in \u001b[0;36mproduct\u001b[0;34m(*args)\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mproduct\u001b[39m(\u001b[38;5;241m*\u001b[39margs):\n\u001b[1;32m 2\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Multiply all arguments.\"\"\"\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43margs\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m arg \u001b[38;5;129;01min\u001b[39;00m args[\u001b[38;5;241m1\u001b[39m:]:\n\u001b[1;32m 6\u001b[0m result \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m=\u001b[39m arg\n",
|
||||
"\u001b[0;31mIndexError\u001b[0m: tuple index out of range"
|
||||
]
|
||||
}
|
||||
|
|
@ -2376,7 +2376,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"In the \"*Packing & Unpacking with Functions*\" [exercise <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/04_exercises.ipynb), we look at `product()` in more detail.\n",
|
||||
"In the \"*Packing & Unpacking with Functions*\" [exercise <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/04_exercises.ipynb), we look at `product()` in more detail.\n",
|
||||
"\n",
|
||||
"While we needed to unpack `one_hundred` above to avoid the semantic error, unpacking an argument in a function call may also be a convenience in general. For example, to print the elements of `one_hundred` in one line, we need to use a `for` statement, until now. With unpacking, we get away *without* a loop."
|
||||
]
|
||||
|
|
@ -2462,7 +2462,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/07_sequences/04_exercises.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/07_sequences/04_exercises.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -18,7 +18,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The exercises below assume that you have read the [third part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/03_content.ipynb) of Chapter 7.\n",
|
||||
"The exercises below assume that you have read the [third part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/03_content.ipynb) of Chapter 7.\n",
|
||||
"\n",
|
||||
"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
|
||||
]
|
||||
|
|
@ -34,7 +34,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"In the \"*Function Definitions & Calls*\" section in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/03_content.ipynb#Function-Definitions-&-Calls), we define the following function `product()`. In this exercise, you will improve it by making it more \"user-friendly.\""
|
||||
"In the \"*Function Definitions & Calls*\" section in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/03_content.ipynb#Function-Definitions-&-Calls), we define the following function `product()`. In this exercise, you will improve it by making it more \"user-friendly.\""
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -128,7 +128,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"In [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/00_content.ipynb#Function-Definitions-&-Calls), we also pass a `list` object, like `one_hundred`, to `product()`, and *no* exception is raised."
|
||||
"In [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/00_content.ipynb#Function-Definitions-&-Calls), we also pass a `list` object, like `one_hundred`, to `product()`, and *no* exception is raised."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -153,7 +153,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Q3**: What is wrong with that? What *kind* of error (cf., [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#Formal-vs.-Natural-Languages)) is that conceptually? Describe precisely what happens to the passed in `one_hundred` in every line within `product()`!"
|
||||
"**Q3**: What is wrong with that? What *kind* of error (cf., [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#Formal-vs.-Natural-Languages)) is that conceptually? Describe precisely what happens to the passed in `one_hundred` in every line within `product()`!"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -331,7 +331,7 @@
|
|||
"source": [
|
||||
"**Q7**: Rewrite `product()` so that it takes a *keyword-only* argument `start`, defaulting to the above *default* or *start* value, and use `start` internally instead of `result`!\n",
|
||||
"\n",
|
||||
"Hint: Remember that a *keyword-only* argument is any parameter specified in a function's header line after the first and only `*` (cf., [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb#Keyword-only-Arguments))."
|
||||
"Hint: Remember that a *keyword-only* argument is any parameter specified in a function's header line after the first and only `*` (cf., [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/00_content.ipynb#Keyword-only-Arguments))."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -544,7 +544,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Side Note**: Above, we make `product()` work with a single *collection* type argument instead of a *sequence* type to keep it more generic: For example, we can pass in a `set` object, like `{2, 5, 10}` below, and `product()` continues to work correctly. The `set` type is introducted in [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/00_content.ipynb#The-set-Type), and one essential difference to the `list` type is that objects of type `set` have *no* order regarding their elements. So, even though `[2, 5, 10]` and `{2, 5, 10}` look almost the same, the order implied in the literal notation gets lost in memory!"
|
||||
"**Side Note**: Above, we make `product()` work with a single *collection* type argument instead of a *sequence* type to keep it more generic: For example, we can pass in a `set` object, like `{2, 5, 10}` below, and `product()` continues to work correctly. The `set` type is introducted in [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/00_content.ipynb#The-set-Type), and one essential difference to the `list` type is that objects of type `set` have *no* order regarding their elements. So, even though `[2, 5, 10]` and `{2, 5, 10}` look almost the same, the order implied in the literal notation gets lost in memory!"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -642,7 +642,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/07_sequences/05_appendix.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/07_sequences/05_appendix.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -30,7 +30,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"In the [third part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/03_content.ipynb#Tuples-are-like-\"Immutable-Lists\") of the chapter, we proposed the idea that `tuple` objects are like \"immutable lists.\" Often, however, we use `tuple` objects to represent a **record** of related **fields**. Then, each element has a *semantic* meaning (i.e., a descriptive name).\n",
|
||||
"In the [third part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/03_content.ipynb#Tuples-are-like-\"Immutable-Lists\") of the chapter, we proposed the idea that `tuple` objects are like \"immutable lists.\" Often, however, we use `tuple` objects to represent a **record** of related **fields**. Then, each element has a *semantic* meaning (i.e., a descriptive name).\n",
|
||||
"\n",
|
||||
"As an example, think of a spreadsheet with information on students in a course. Each row represents a record and holds all the data associated with an individual student. The columns (e.g., matriculation number, first name, last name) are the fields that may come as *different* data types (e.g., `int` for the matriculation number, `str` for the names).\n",
|
||||
"\n",
|
||||
|
|
@ -82,7 +82,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"A better way is to create a *custom* data type. While that is covered in depth in [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/00_content.ipynb), the [collections <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.html) module in the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html) provides a [namedtuple() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.html#collections.namedtuple) **factory function** that creates \"simple\" custom data types on top of the standard `tuple` type."
|
||||
"A better way is to create a *custom* data type. While that is covered in depth in [Chapter 11 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/00_content.ipynb), the [collections <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.html) module in the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html) provides a [namedtuple() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.html#collections.namedtuple) **factory function** that creates \"simple\" custom data types on top of the standard `tuple` type."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -420,7 +420,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-13-b30d0b930bac>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mcurrent_position\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mz\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[13], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mcurrent_position\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mz\u001b[49m\n",
|
||||
"\u001b[0;31mAttributeError\u001b[0m: 'Point' object has no attribute 'z'"
|
||||
]
|
||||
}
|
||||
|
|
@ -577,7 +577,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -53,7 +53,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -11,7 +11,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/00_content.ipynb), [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/01_content.ipynb), and the [third <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/03_content.ipynb) part of Chapter 7. Some questions regard the [Appendix <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/05_appendix.ipynb); that is indicated with a **\\***.\n",
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/00_content.ipynb), [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/01_content.ipynb), and the [third <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/03_content.ipynb) part of Chapter 7. Some questions regard the [Appendix <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/05_appendix.ipynb); that is indicated with a **\\***.\n",
|
||||
"\n",
|
||||
"Be concise in your answers! Most questions can be answered in *one* sentence."
|
||||
]
|
||||
|
|
@ -34,7 +34,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Q1**: We have seen **containers** and **iterables** before in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/02_content.ipynb#Containers-vs.-Iterables). How do they relate to **sequences**? "
|
||||
"**Q1**: We have seen **containers** and **iterables** before in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/02_content.ipynb#Containers-vs.-Iterables). How do they relate to **sequences**? "
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -231,7 +231,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/08_mfr/00_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/08_mfr/00_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -32,9 +32,9 @@
|
|||
"source": [
|
||||
"In this chapter, we continue the study of sequential data by looking at memory efficient ways to process the elements in a sequence. That is an important topic for the data science practitioner who must be able to work with data that does *not* fit into a single computer's memory.\n",
|
||||
"\n",
|
||||
"As shown in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/02_content.ipynb#Containers-vs.-Iterables), both the `list` objects `[0, 1, 2, 3, 4]` and `[1, 3, 5, 7, 9]` on the one side and the `range` objects `range(5)` and `range(1, 10, 2)` on the other side allow us to loop over the same numbers. However, the latter two only create *one* `int` object in every iteration while the former two create *all* `int` objects before the loop even starts. In this aspect, we consider `range` objects to be \"rules\" in memory that know how to calculate the numbers *without* calculating them.\n",
|
||||
"As shown in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/02_content.ipynb#Containers-vs.-Iterables), both the `list` objects `[0, 1, 2, 3, 4]` and `[1, 3, 5, 7, 9]` on the one side and the `range` objects `range(5)` and `range(1, 10, 2)` on the other side allow us to loop over the same numbers. However, the latter two only create *one* `int` object in every iteration while the former two create *all* `int` objects before the loop even starts. In this aspect, we consider `range` objects to be \"rules\" in memory that know how to calculate the numbers *without* calculating them.\n",
|
||||
"\n",
|
||||
"In [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/01_content.ipynb#The-list-Type), we see how the built-in [list() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-list) constructor **materializes** the `range(1, 13)` object into the `list` object `[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]`. In other words, we make `range(1, 13)` calculate *all* numbers at once and store them in a `list` object for further processing.\n",
|
||||
"In [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/01_content.ipynb#The-list-Type), we see how the built-in [list() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-list) constructor **materializes** the `range(1, 13)` object into the `list` object `[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]`. In other words, we make `range(1, 13)` calculate *all* numbers at once and store them in a `list` object for further processing.\n",
|
||||
"\n",
|
||||
"In many cases, however, it is not necessary to do that, and, in this chapter, we look at other types of \"rules\" in memory and how we can compose different \"rules\" together to implement bigger computations.\n",
|
||||
"\n",
|
||||
|
|
@ -779,7 +779,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Using the [map() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#map) and [filter() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#filter) built-ins, we can quickly switch the order: Filter first and then transform the remaining elements. This variant equals the \"*A simple Filter*\" example in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/03_content.ipynb#Example:-A-simple-Filter). On the contrary, code with `for`-loops and `if` statements is more tedious to adapt. Additionally, `map` and `filter` objects loop \"at the C level\" and are a lot faster because of that. Because of that, experienced Pythonistas tend to *not* use explicit `for`-loops so often."
|
||||
"Using the [map() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#map) and [filter() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#filter) built-ins, we can quickly switch the order: Filter first and then transform the remaining elements. This variant equals the \"*A simple Filter*\" example in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/03_content.ipynb#Example:-A-simple-Filter). On the contrary, code with `for`-loops and `if` statements is more tedious to adapt. Additionally, `map` and `filter` objects loop \"at the C level\" and are a lot faster because of that. Because of that, experienced Pythonistas tend to *not* use explicit `for`-loops so often."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1129,7 +1129,7 @@
|
|||
"\n",
|
||||
"Often, such functions are used *only once* in a program. However, the primary purpose of functions is to *reuse* them. In such cases, it makes more sense to define them \"anonymously\" right at the position where the first argument goes.\n",
|
||||
"\n",
|
||||
"As mentioned in [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb#Anonymous-Functions), we use `lambda` expressions to create `function` objects *without* a name referencing them.\n",
|
||||
"As mentioned in [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/00_content.ipynb#Anonymous-Functions), we use `lambda` expressions to create `function` objects *without* a name referencing them.\n",
|
||||
"\n",
|
||||
"So, the above `sum_alt()` function could be rewritten as a `lambda` expression like so ..."
|
||||
]
|
||||
|
|
@ -1321,7 +1321,7 @@
|
|||
},
|
||||
"source": [
|
||||
"PythonTutor visualizes the differences in the number of computational steps and memory usage:\n",
|
||||
"- [Version 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=def%20is_even%28element%29%3A%0A%20%20%20%20if%20element%20%25%202%20%3D%3D%200%3A%0A%20%20%20%20%20%20%20%20return%20True%0A%20%20%20%20return%20False%0A%0Adef%20transform%28element%29%3A%0A%20%20%20%20return%20%28element%20**%202%29%20%2B%201%0A%0Anumbers%20%3D%20list%28range%281,%2013%29%29%0A%0Aevens%20%3D%20%5B%5D%0Afor%20number%20in%20numbers%3A%0A%20%20%20%20if%20is_even%28number%29%3A%0A%20%20%20%20%20%20%20%20evens.append%28number%29%0A%0Atransformed%20%3D%20%5B%5D%0Afor%20number%20in%20evens%3A%0A%20%20%20%20transformed.append%28transform%28number%29%29%0A%0Aresult%20%3D%20sum%28transformed%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false): With `for`-loops, `if` statements, and named functions -> **116** steps and **3** `list` objects\n",
|
||||
"- [Version 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=def%20is_even%28element%29%3A%0A%20%20%20%20if%20element%20%25%202%20%3D%3D%200%3A%0A%20%20%20%20%20%20%20%20return%20True%0A%20%20%20%20return%20False%0A%0Adef%20transform%28element%29%3A%0A%20%20%20%20return%20%28element%20**%202%29%20%2B%201%0A%0Anumbers%20%3D%20list%28range%281,%2013%29%29%0A%0Aevens%20%3D%20%5B%5D%0Afor%20number%20in%20numbers%3A%0A%20%20%20%20if%20is_even%28number%29%3A%0A%20%20%20%20%20%20%20%20evens.append%28number%29%0A%0Atransformed%20%3D%20%5B%5D%0Afor%20number%20in%20evens%3A%0A%20%20%20%20transformed.append%28transform%28number%29%29%0A%0Aresult%20%3D%20sum%28transformed%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false): With `for`-loops, `if` statements, and named functions -> **116** steps and **3** `list` objects\n",
|
||||
"- [Version 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20range%281,%2013%29%0Aevens%20%3D%20filter%28lambda%20x%3A%20x%20%25%202%20%3D%3D%200,%20numbers%29%0Atransformed%20%3D%20map%28lambda%20x%3A%20%28x%20**%202%29%20%2B%201,%20evens%29%0Aresult%20%3D%20sum%28transformed%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false): With named `map` and `filter` objects -> **58** steps and **no** `list` object\n",
|
||||
"- [Version 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=result%20%3D%20sum%28map%28lambda%20x%3A%20%28x%20**%202%29%20%2B%201,%20filter%28lambda%20x%3A%20x%20%25%202%20%3D%3D%200,%20range%281,%2013%29%29%29%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false): Everything in *one* expression -> **55** steps and **no** `list` object\n",
|
||||
"\n",
|
||||
|
|
@ -1349,7 +1349,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/08_mfr/01_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/08_mfr/01_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -30,7 +30,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"After introducing the Map-Filter-Reduce paradigm in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/00_content.ipynb) of this chapter, we first see how `list` comprehensions can replace the [map() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#map) and [filter() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#filter) built-ins in many cases. Then, we learn how `generator` expressions are like `list` comprehensions *without* using the memory. We end this part with a short discussion of the built-in [all() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#all) and [any() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#any) functions."
|
||||
"After introducing the Map-Filter-Reduce paradigm in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/00_content.ipynb) of this chapter, we first see how `list` comprehensions can replace the [map() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#map) and [filter() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#filter) built-ins in many cases. Then, we learn how `generator` expressions are like `list` comprehensions *without* using the memory. We end this part with a short discussion of the built-in [all() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#all) and [any() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#any) functions."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -52,7 +52,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Consider again the original \"*A simple Filter*\" example from [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/03_content.ipynb#Example:-A-simple-Filter), re-written such that both the mapping and the filtering are done in *one* `for`-loop instead of the *two* above."
|
||||
"Consider again the original \"*A simple Filter*\" example from [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/03_content.ipynb#Example:-A-simple-Filter), re-written such that both the mapping and the filtering are done in *one* `for`-loop instead of the *two* above."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -156,7 +156,7 @@
|
|||
"source": [
|
||||
"A list comprehension may always be used in a place where otherwise a `list` object would work.\n",
|
||||
"\n",
|
||||
"For example, let's rewrite the \"*A simple Filter*\" example from [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/03_content.ipynb#Example:-A-simple-Filter) in just one line. As a caveat, the code below *materializes* all elements in memory *before* summing them up, and may, therefore, cause a `MemoryError` when executed with a bigger `numbers` list. We see with [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20range%281,%2013%29%0Aresult%20%3D%20sum%28%5B%28n%20**%202%29%20%2B%201%20for%20n%20in%20numbers%20if%20n%20%25%202%20%3D%3D%200%5D%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) how a `list` object exists in memory at step 17 and then \"gets lost\" right after. As the next section shows, this downside may be mitigated."
|
||||
"For example, let's rewrite the \"*A simple Filter*\" example from [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/03_content.ipynb#Example:-A-simple-Filter) in just one line. As a caveat, the code below *materializes* all elements in memory *before* summing them up, and may, therefore, cause a `MemoryError` when executed with a bigger `numbers` list. We see with [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20range%281,%2013%29%0Aresult%20%3D%20sum%28%5B%28n%20**%202%29%20%2B%201%20for%20n%20in%20numbers%20if%20n%20%25%202%20%3D%3D%200%5D%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) how a `list` object exists in memory at step 17 and then \"gets lost\" right after. As the next section shows, this downside may be mitigated."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -639,7 +639,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"To find the overall product, we *unpack* the list comprehension into the `product()` function from the \"*Function Definitions & Calls*\" sub-section in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/03_content.ipynb#Function-Definitions-&-Calls)."
|
||||
"To find the overall product, we *unpack* the list comprehension into the `product()` function from the \"*Function Definitions & Calls*\" sub-section in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/03_content.ipynb#Function-Definitions-&-Calls)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -766,7 +766,7 @@
|
|||
"source": [
|
||||
"Because of the high memory consumption, Pythonistas avoid materialized `list` objects, and, thus, also `list` comprehensions, whenever possible. Instead, they prefer to work with **[`generator` expressions <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/reference/expressions.html#generator-expressions)**. Syntactically, they work like list comprehensions except that parentheses, `(` and `)`, replace brackets, `[` and `]`.\n",
|
||||
"\n",
|
||||
"Let's go back to the original \"*A simple Filter*\" example from [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/03_content.ipynb#Example:-A-simple-Filter) one more time, apply the transformation $y := x^2 + 1$ to all even `numbers`, and sum them up."
|
||||
"Let's go back to the original \"*A simple Filter*\" example from [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/03_content.ipynb#Example:-A-simple-Filter) one more time, apply the transformation $y := x^2 + 1$ to all even `numbers`, and sum them up."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -932,7 +932,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"A common use case is to reduce the elements into a single object instead, for example, by adding them up with [sum() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#sum) as in the original \"*A simple Filter*\" example. [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20range%281,%2013%29%0Asum_with_list%20%3D%20sum%28%5B%28n%20**%202%29%20%2B%201%20for%20n%20in%20numbers%20if%20n%20%25%202%20%3D%3D%200%5D%29%0Asum_with_gen%20%3D%20sum%28%28n%20**%202%29%20%2B%201%20for%20n%20in%20numbers%20if%20n%20%25%202%20%3D%3D%200%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows how the code cell below does *not* create a temporary `list` object in memory whereas a `list` comprehension would do so (cf., step 17)."
|
||||
"A common use case is to reduce the elements into a single object instead, for example, by adding them up with [sum() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#sum) as in the original \"*A simple Filter*\" example. [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20range%281,%2013%29%0Asum_with_list%20%3D%20sum%28%5B%28n%20**%202%29%20%2B%201%20for%20n%20in%20numbers%20if%20n%20%25%202%20%3D%3D%200%5D%29%0Asum_with_gen%20%3D%20sum%28%28n%20**%202%29%20%2B%201%20for%20n%20in%20numbers%20if%20n%20%25%202%20%3D%3D%200%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows how the code cell below does *not* create a temporary `list` object in memory whereas a `list` comprehension would do so (cf., step 17)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1050,7 +1050,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"`generator` objects work just like the `map` and `filter` objects in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/00_content.ipynb) of this chapter. So, with the [next() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#next) function, we can generate elements one by one."
|
||||
"`generator` objects work just like the `map` and `filter` objects in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/00_content.ipynb) of this chapter. So, with the [next() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#next) function, we can generate elements one by one."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1224,7 +1224,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mStopIteration\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-36-6e72e47198db>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnext\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgen\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[36], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;43mnext\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mgen\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mStopIteration\u001b[0m: "
|
||||
]
|
||||
}
|
||||
|
|
@ -1249,7 +1249,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mStopIteration\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-37-6e72e47198db>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnext\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgen\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[37], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;43mnext\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mgen\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mStopIteration\u001b[0m: "
|
||||
]
|
||||
}
|
||||
|
|
@ -1417,7 +1417,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Because `nested_numbers` has an internal structure (i.e., the inner `list` objects are series of consecutive `int` objects), we can even provide an effectively **memoryless** implementation by expressing it as a `generator` expression derived from `range` objects. [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=nested_numbers%20%3D%20%28%28range%28x,%20y%20%2B%201%29%29%20for%20x,%20y%20in%20zip%28range%281,%204%29,%20range%287,%2010%29%29%29%0Aresult%20%3D%20sum%28number%20for%20inner_numbers%20in%20nested_numbers%20for%20number%20in%20inner_numbers%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) confirms that no `list` objects materialize at any point in time."
|
||||
"Because `nested_numbers` has an internal structure (i.e., the inner `list` objects are series of consecutive `int` objects), we can even provide an effectively **memoryless** implementation by expressing it as a `generator` expression derived from `range` objects. [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=nested_numbers%20%3D%20%28%28range%28x,%20y%20%2B%201%29%29%20for%20x,%20y%20in%20zip%28range%281,%204%29,%20range%287,%2010%29%29%29%0Aresult%20%3D%20sum%28number%20for%20inner_numbers%20in%20nested_numbers%20for%20number%20in%20inner_numbers%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) confirms that no `list` objects materialize at any point in time."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1489,7 +1489,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"We must be careful when assigning a `generator` object to a variable: If we use `nested_numbers` again, for example, in the alternative formulation below, [sum() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#sum) returns `0` because `nested_numbers` is exhausted after executing the previous code cell. [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=nested_numbers%20%3D%20%28%28range%28x,%20y%20%2B%201%29%29%20for%20x,%20y%20in%20zip%28range%281,%204%29,%20range%287,%2010%29%29%29%0Aresult%20%3D%20sum%28number%20for%20inner_numbers%20in%20nested_numbers%20for%20number%20in%20inner_numbers%29%0Ano_result%20%3D%20sum%28sum%28inner_numbers%29%20for%20inner_numbers%20in%20nested_numbers%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) also shows that."
|
||||
"We must be careful when assigning a `generator` object to a variable: If we use `nested_numbers` again, for example, in the alternative formulation below, [sum() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#sum) returns `0` because `nested_numbers` is exhausted after executing the previous code cell. [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=nested_numbers%20%3D%20%28%28range%28x,%20y%20%2B%201%29%29%20for%20x,%20y%20in%20zip%28range%281,%204%29,%20range%287,%2010%29%29%29%0Aresult%20%3D%20sum%28number%20for%20inner_numbers%20in%20nested_numbers%20for%20number%20in%20inner_numbers%29%0Ano_result%20%3D%20sum%28sum%28inner_numbers%29%20for%20inner_numbers%20in%20nested_numbers%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) also shows that."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1564,7 +1564,7 @@
|
|||
"source": [
|
||||
"Now, the first of the two alternative solutions may be more appealing to many readers. In general, many practitioners seem to dislike `lambda` expressions.\n",
|
||||
"\n",
|
||||
"In the first solution, we *unpack* the elements produced by `(1 + (x / y) for x in first for y in second)` into the `product()` function from the \"*Function Definitions & Calls*\" sub-section in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/03_content.ipynb#Function-Definitions-&-Calls). However, inside `product()`, the elements are *packed* into `args`, a *materialized* `tuple` object! So, all the memory efficiency gained by using a generator expression is lost! [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=def%20product%28*args%29%3A%0A%20%20%20%20result%20%3D%20args%5B0%5D%0A%20%20%20%20for%20arg%20in%20args%5B1%3A%5D%3A%0A%20%20%20%20%20%20%20%20result%20*%3D%20arg%0A%20%20%20%20return%20result%0A%0Afirst%20%3D%20range%2810,%2031,%2010%29%0Asecond%20%3D%20range%2840,%2061,%2010%29%0A%0Aresult%20%3D%20product%28*%281%20%2B%20%28x%20/%20y%29%20for%20x%20in%20first%20for%20y%20in%20second%29%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows how a `tuple` object exists in steps 38-58."
|
||||
"In the first solution, we *unpack* the elements produced by `(1 + (x / y) for x in first for y in second)` into the `product()` function from the \"*Function Definitions & Calls*\" sub-section in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/03_content.ipynb#Function-Definitions-&-Calls). However, inside `product()`, the elements are *packed* into `args`, a *materialized* `tuple` object! So, all the memory efficiency gained by using a generator expression is lost! [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=def%20product%28*args%29%3A%0A%20%20%20%20result%20%3D%20args%5B0%5D%0A%20%20%20%20for%20arg%20in%20args%5B1%3A%5D%3A%0A%20%20%20%20%20%20%20%20result%20*%3D%20arg%0A%20%20%20%20return%20result%0A%0Afirst%20%3D%20range%2810,%2031,%2010%29%0Asecond%20%3D%20range%2840,%2061,%2010%29%0A%0Aresult%20%3D%20product%28*%281%20%2B%20%28x%20/%20y%29%20for%20x%20in%20first%20for%20y%20in%20second%29%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) shows how a `tuple` object exists in steps 38-58."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1599,7 +1599,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"On the contrary, the second solution with the [reduce() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functools.html#functools.reduce) function from the [functools <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functools.html) module and the `lambda` expression works *without* the elements materialized at the same time, and [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=from%20functools%20import%20reduce%0A%0Afirst%20%3D%20range%2810,%2031,%2010%29%0Asecond%20%3D%20range%2840,%2061,%2010%29%0A%0Aresult%20%3D%20reduce%28%0A%20%20%20%20lambda%20x,%20y%3A%20x%20*%20y,%0A%20%20%20%20%281%20%2B%20%28x%20/%20y%29%20for%20x%20in%20first%20for%20y%20in%20second%29%0A%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) confirms that. So, only the second alternative is truly memory-efficient!"
|
||||
"On the contrary, the second solution with the [reduce() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functools.html#functools.reduce) function from the [functools <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functools.html) module and the `lambda` expression works *without* the elements materialized at the same time, and [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=from%20functools%20import%20reduce%0A%0Afirst%20%3D%20range%2810,%2031,%2010%29%0Asecond%20%3D%20range%2840,%2061,%2010%29%0A%0Aresult%20%3D%20reduce%28%0A%20%20%20%20lambda%20x,%20y%3A%20x%20*%20y,%0A%20%20%20%20%281%20%2B%20%28x%20/%20y%29%20for%20x%20in%20first%20for%20y%20in%20second%29%0A%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) confirms that. So, only the second alternative is truly memory-efficient!"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1656,13 +1656,13 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"With the new concepts in this chapter, let's rewrite the book's introductory \"*Averaging all even Numbers in a List*\" example from [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#Example:-Averaging-all-even-Numbers-in-a-List) such that it efficiently handles a large sequence of numbers. We continue from its latest implementation, the `average_evens()` function in the \"*Keyword-only Arguments*\" section in [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb#Keyword-only-Arguments).\n",
|
||||
"With the new concepts in this chapter, let's rewrite the book's introductory \"*Averaging all even Numbers in a List*\" example from [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#Example:-Averaging-all-even-Numbers-in-a-List) such that it efficiently handles a large sequence of numbers. We continue from its latest implementation, the `average_evens()` function in the \"*Keyword-only Arguments*\" section in [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/00_content.ipynb#Keyword-only-Arguments).\n",
|
||||
"\n",
|
||||
"We assume that `average_evens()` is called with a *finite* and *iterable* object that generates a **stream** of numeric objects that can be cast as `int` objects. After all, the idea of even and odd numbers makes sense only in the context of whole numbers.\n",
|
||||
"\n",
|
||||
"The `generator` expression `(round(n) for n in numbers)` implements the type casting, and, when it is evaluated during a function call, *nothing* happens except that a `generator` object is assigned to `integers`. Then, with the [reduce() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functools.html#functools.reduce) function from the [functools <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functools.html) module, we *simultaneously* add up *and* count the even numbers with the `generator` object to which the inner `generator` expression `((n, 1) for n in integers if n % 2 == 0)` evaluates to. That `generator` object takes the `integers` generator as its source and produces `tuple` objects consisting of the next *even* number in line and `1`. Two such `tuple` objects are then iteratively passed to the `function` object to which the `lambda` expression evaluates to. `x` represents the total and the count of the even numbers processed so far, while `y`'s first element, `y[0]`, is the next *even* number to be added to the running total. The result of calling [reduce() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functools.html#functools.reduce) is again a `tuple` object, namely the final `total` and `count`. Lastly, we calculate the simple average and scale it.\n",
|
||||
"\n",
|
||||
"In summary, this implementation of `average_evens()` does *not* keep materialized `list` objects internally like its predecessors in [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb) but processes the elements of the `numbers` argument on a one-by-one basis."
|
||||
"In summary, this implementation of `average_evens()` does *not* keep materialized `list` objects internally like its predecessors in [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/00_content.ipynb) but processes the elements of the `numbers` argument on a one-by-one basis."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1871,14 +1871,14 @@
|
|||
"outputs": [
|
||||
{
|
||||
"ename": "TypeError",
|
||||
"evalue": "reduce() of empty sequence with no initial value",
|
||||
"evalue": "reduce() of empty iterable with no initial value",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-56-73a295f34553>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0maverage_evens\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mrandom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrandint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m49\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;36m1\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0m_\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10_000_000\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-49-29706a0855ba>\u001b[0m in \u001b[0;36maverage_evens\u001b[0;34m(numbers, scalar)\u001b[0m\n\u001b[1;32m 11\u001b[0m \"\"\"\n\u001b[1;32m 12\u001b[0m \u001b[0mintegers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mround\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mn\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mnumbers\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 13\u001b[0;31m total, count = reduce(\n\u001b[0m\u001b[1;32m 14\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mn\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mintegers\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0;36m2\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: reduce() of empty sequence with no initial value"
|
||||
"Cell \u001b[0;32mIn[56], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43maverage_evens\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mrandom\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrandint\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m49\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m_\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mrange\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m10_000_000\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[49], line 13\u001b[0m, in \u001b[0;36maverage_evens\u001b[0;34m(numbers, scalar)\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Calculate the average of all even numbers.\u001b[39;00m\n\u001b[1;32m 3\u001b[0m \n\u001b[1;32m 4\u001b[0m \u001b[38;5;124;03mArgs:\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[38;5;124;03m float: (scaled) average\u001b[39;00m\n\u001b[1;32m 11\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 12\u001b[0m integers \u001b[38;5;241m=\u001b[39m (\u001b[38;5;28mround\u001b[39m(n) \u001b[38;5;28;01mfor\u001b[39;00m n \u001b[38;5;129;01min\u001b[39;00m numbers)\n\u001b[0;32m---> 13\u001b[0m total, count \u001b[38;5;241m=\u001b[39m \u001b[43mreduce\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 14\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mlambda\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mx\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 15\u001b[0m \u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mn\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mintegers\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mn\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m%\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m==\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 16\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 17\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m scalar \u001b[38;5;241m*\u001b[39m total \u001b[38;5;241m/\u001b[39m count\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: reduce() of empty iterable with no initial value"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -2040,7 +2040,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"[all() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#all) can be viewed as syntactic sugar replacing a `for`-loop: Internally, [all() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#all) implements the *short-circuiting* strategy explained in [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/03_conditionals/00_content.ipynb#Short-Circuiting), and we mimic that by testing for the *opposite* condition in the `if` statement and stopping the `for`-loop early with the `break` statement. In the worst case, if `threshold` were, for example, `150`, we would loop over *all* elements in the `iterable` argument, which must be *finite* for the code to work. So, [all() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#all) is a *linear search* in disguise."
|
||||
"[all() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#all) can be viewed as syntactic sugar replacing a `for`-loop: Internally, [all() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#all) implements the *short-circuiting* strategy explained in [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/03_conditionals/00_content.ipynb#Short-Circuiting), and we mimic that by testing for the *opposite* condition in the `if` statement and stopping the `for`-loop early with the `break` statement. In the worst case, if `threshold` were, for example, `150`, we would loop over *all* elements in the `iterable` argument, which must be *finite* for the code to work. So, [all() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#all) is a *linear search* in disguise."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -2352,7 +2352,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/08_mfr/02_exercises.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/08_mfr/02_exercises.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -18,7 +18,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The exercises below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/00_content.ipynb) and [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/01_content.ipynb) part of Chapter 8.\n",
|
||||
"The exercises below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/00_content.ipynb) and [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/01_content.ipynb) part of Chapter 8.\n",
|
||||
"\n",
|
||||
"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
|
||||
]
|
||||
|
|
@ -335,7 +335,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"We provide a `stream` module with a `data` object that models an *infinite* **stream** of data (cf., the [*stream.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/08_mfr/stream.py) file in the repository)."
|
||||
"We provide a `stream` module with a `data` object that models an *infinite* **stream** of data (cf., the [*stream.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/08_mfr/stream.py) file in the repository)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -574,7 +574,7 @@
|
|||
"source": [
|
||||
"**Q10.2**: Just as in `standardized()`, write a `generator` expression that produces z-scores one by one! However, instead of just generating a z-score, the resulting `generator` object should produce `tuple` objects consisting of a \"raw\" number from `data` and its z-score.\n",
|
||||
"\n",
|
||||
"Hint: Look at the revisited \"*Averaging Even Numbers*\" example in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/01_content.ipynb#Example:-Averaging-all-even-Numbers-in-a-List-%28revisited%29) for some inspiration, which also contains a `generator` expression producing `tuple` objects."
|
||||
"Hint: Look at the revisited \"*Averaging Even Numbers*\" example in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/01_content.ipynb#Example:-Averaging-all-even-Numbers-in-a-List-%28revisited%29) for some inspiration, which also contains a `generator` expression producing `tuple` objects."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -739,7 +739,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/08_mfr/03_exercises.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/08_mfr/03_exercises.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -18,7 +18,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The exercises below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/00_content.ipynb) and [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/01_content.ipynb) part of Chapter 8.\n",
|
||||
"The exercises below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/00_content.ipynb) and [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/01_content.ipynb) part of Chapter 8.\n",
|
||||
"\n",
|
||||
"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
|
||||
]
|
||||
|
|
@ -34,7 +34,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Q1**: Copy your solution to **Q10** from the \"*Packing & Unpacking with Functions*\" exercise in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/04_exercises.ipynb) into the code cell below!"
|
||||
"**Q1**: Copy your solution to **Q10** from the \"*Packing & Unpacking with Functions*\" exercise in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/04_exercises.ipynb) into the code cell below!"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -152,7 +152,7 @@
|
|||
"\n",
|
||||
"**Q4**: Click through the following code cells and observe what they do!\n",
|
||||
"\n",
|
||||
"The [*stream.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/08_mfr/stream.py) module in the book's repository provides a `make_finite_stream()` function. It is a *factory* function creating objects of type `generator` that we use to model *streaming* data."
|
||||
"The [*stream.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/08_mfr/stream.py) module in the book's repository provides a `make_finite_stream()` function. It is a *factory* function creating objects of type `generator` that we use to model *streaming* data."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -434,7 +434,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/08_mfr/04_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/08_mfr/04_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -30,7 +30,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Similarly to how we classify different *concrete* data types like `list` or `str` by how they behave *abstractly* in a given context in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/00_content.ipynb#Collections-vs.-Sequences), we also do so for the data types we have introduced in this chapter."
|
||||
"Similarly to how we classify different *concrete* data types like `list` or `str` by how they behave *abstractly* in a given context in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/00_content.ipynb#Collections-vs.-Sequences), we also do so for the data types we have introduced in this chapter."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -174,7 +174,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Furthermore, we sharpen our definition of an *iterable* from [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/00_content.ipynb#Collections-vs.-Sequences): Just as we define an *iterator* to be any object that supports the [next() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#next) function, we define an *iterable* to be any object that supports the built-in [iter() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#iter) function.\n",
|
||||
"Furthermore, we sharpen our definition of an *iterable* from [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/00_content.ipynb#Collections-vs.-Sequences): Just as we define an *iterator* to be any object that supports the [next() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#next) function, we define an *iterable* to be any object that supports the built-in [iter() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#iter) function.\n",
|
||||
"\n",
|
||||
"The confused reader may now be wondering how the two concepts relate to each other.\n",
|
||||
"\n",
|
||||
|
|
@ -706,7 +706,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mStopIteration\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-25-0680f5ec8ce3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnext\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0miterator1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[25], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;43mnext\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43miterator1\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mStopIteration\u001b[0m: "
|
||||
]
|
||||
}
|
||||
|
|
@ -780,7 +780,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"In [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/02_content.ipynb#The-for-Statement), we argue that the `for` statement is syntactic sugar, replacing the `while` statement in many common scenarios. In particular, a `for`-loop saves us two tasks: Managing an index variable *and* obtaining the individual elements by indexing. In this sub-section, we look at a more realistic picture, using the new terminology as well.\n",
|
||||
"In [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/02_content.ipynb#The-for-Statement), we argue that the `for` statement is syntactic sugar, replacing the `while` statement in many common scenarios. In particular, a `for`-loop saves us two tasks: Managing an index variable *and* obtaining the individual elements by indexing. In this sub-section, we look at a more realistic picture, using the new terminology as well.\n",
|
||||
"\n",
|
||||
"Let's print out the elements of a `list` object as the *iterable* being looped over."
|
||||
]
|
||||
|
|
@ -924,9 +924,9 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Now that we know the concept of an *iterator*, let's compare some of the built-ins introduced in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/00_content.ipynb) in detail and make sure we understand what is going on in memory. This section also serves as a summary of all the concepts in this chapter.\n",
|
||||
"Now that we know the concept of an *iterator*, let's compare some of the built-ins introduced in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/00_content.ipynb) in detail and make sure we understand what is going on in memory. This section also serves as a summary of all the concepts in this chapter.\n",
|
||||
"\n",
|
||||
"We use two simple examples, `numbers` and `memoryless`: `numbers` creates *thirteen* objects in memory and `memoryless` only *one* (cf., [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0Amemoryless%20%3D%20range%281,%2013%29&cumulative=false&curInstr=2&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false))."
|
||||
"We use two simple examples, `numbers` and `memoryless`: `numbers` creates *thirteen* objects in memory and `memoryless` only *one* (cf., [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0Amemoryless%20%3D%20range%281,%2013%29&cumulative=false&curstr=2&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false))."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -965,7 +965,7 @@
|
|||
"source": [
|
||||
"The [sorted() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#sorted) function takes a *finite* `iterable` argument and *materializes* its elements into a *new* `list` object that is returned.\n",
|
||||
"\n",
|
||||
"The argument may already be materialized, as is the case with `numbers`, but may also be an *iterable* without any objects in it, such as `memoryless`. In both cases, we end up with materialized `list` objects with the elements sorted in *forward* order (cf., [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0Amemoryless%20%3D%20range%281,%2013%29%0Aresult1%20%3D%20sorted%28numbers%29%0Aresult2%20%3D%20sorted%28memoryless%29&cumulative=false&curInstr=4&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false))."
|
||||
"The argument may already be materialized, as is the case with `numbers`, but may also be an *iterable* without any objects in it, such as `memoryless`. In both cases, we end up with materialized `list` objects with the elements sorted in *forward* order (cf., [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0Amemoryless%20%3D%20range%281,%2013%29%0Aresult1%20%3D%20sorted%28numbers%29%0Aresult2%20%3D%20sorted%28memoryless%29&cumulative=false&curstr=4&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false))."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1024,7 +1024,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"By adding a keyword-only argument `reverse=True`, the materialized `list` objects are sorted in *reverse* order (cf., [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0Amemoryless%20%3D%20range%281,%2013%29%0Aresult1%20%3D%20sorted%28numbers,%20reverse%3DTrue%29%0Aresult2%20%3D%20sorted%28memoryless,%20reverse%3DTrue%29&cumulative=false&curInstr=4&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false))."
|
||||
"By adding a keyword-only argument `reverse=True`, the materialized `list` objects are sorted in *reverse* order (cf., [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0Amemoryless%20%3D%20range%281,%2013%29%0Aresult1%20%3D%20sorted%28numbers,%20reverse%3DTrue%29%0Aresult2%20%3D%20sorted%28memoryless,%20reverse%3DTrue%29&cumulative=false&curstr=4&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false))."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1142,7 +1142,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"The [reversed() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#reversed) built-in takes a `sequence` argument and returns an *iterator*. The argument must be *finite* and *reversible* (i.e., *iterable* in *reverse* order) as otherwise [reversed() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#reversed) could neither determine the last element that becomes the first nor loop in a *predictable* backward fashion. [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0Amemoryless%20%3D%20range%281,%2013%29%0Aiterator1%20%3D%20reversed%28numbers%29%0Aiterator2%20%3D%20reversed%28memoryless%29&cumulative=false&curInstr=4&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) confirms that [reversed() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#reversed) does *not* materialize any elements but only returns an *iterator*.\n",
|
||||
"The [reversed() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#reversed) built-in takes a `sequence` argument and returns an *iterator*. The argument must be *finite* and *reversible* (i.e., *iterable* in *reverse* order) as otherwise [reversed() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#reversed) could neither determine the last element that becomes the first nor loop in a *predictable* backward fashion. [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0Amemoryless%20%3D%20range%281,%2013%29%0Aiterator1%20%3D%20reversed%28numbers%29%0Aiterator2%20%3D%20reversed%28memoryless%29&cumulative=false&curstr=4&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) confirms that [reversed() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#reversed) does *not* materialize any elements but only returns an *iterator*.\n",
|
||||
"\n",
|
||||
"**Side Note**: Even though `range` objects, like `memoryless` here, do *not* \"contain\" references to other objects, they count as *sequence* types, and as such, they are also *container* types. The `in` operator works with `range` objects because we can always cast the object to be checked as an `int` and check if that lies within the `range` object's `start` and `stop` values, taking a potential `step` value into account (cf., this [blog post](https://treyhunner.com/2018/02/python-range-is-not-an-iterator/) for more details on the [range() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-range) built-in)."
|
||||
]
|
||||
|
|
@ -1203,7 +1203,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"To materialize the elements, we can pass the returned *iterators* to, for example, the [list() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-list) or [tuple() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-tuple) constructors. That creates *new* `list` and `tuple` objects (cf., [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0Amemoryless%20%3D%20range%281,%2013%29%0Aresult1%20%3D%20list%28reversed%28numbers%29%29%0Aresult2%20%3D%20tuple%28reversed%28memoryless%29%29&cumulative=false&curInstr=4&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false)).\n",
|
||||
"To materialize the elements, we can pass the returned *iterators* to, for example, the [list() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-list) or [tuple() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-tuple) constructors. That creates *new* `list` and `tuple` objects (cf., [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B7,%2011,%208,%205,%203,%2012,%202,%206,%209,%2010,%201,%204%5D%0Amemoryless%20%3D%20range%281,%2013%29%0Aresult1%20%3D%20list%28reversed%28numbers%29%29%0Aresult2%20%3D%20tuple%28reversed%28memoryless%29%29&cumulative=false&curstr=4&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false)).\n",
|
||||
"\n",
|
||||
"To reiterate some more new terminology from this chapter, we describe [reversed() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#reversed) as *lazy* whereas [list() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-list) and [tuple() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-tuple) are *eager*. The former has no significant side effect in memory, while the latter may require a lot of memory."
|
||||
]
|
||||
|
|
@ -1640,7 +1640,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -43,7 +43,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -11,7 +11,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/00_content.ipynb), [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/01_content.ipynb), and [third <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/04_content.ipynb) part in Chapter 8.\n",
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/00_content.ipynb), [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/01_content.ipynb), and [third <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/04_content.ipynb) part in Chapter 8.\n",
|
||||
"\n",
|
||||
"Be concise in your answers! Most questions can be answered in *one* sentence."
|
||||
]
|
||||
|
|
@ -193,7 +193,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/09_mappings/00_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/09_mappings/00_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -30,7 +30,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"While [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/00_content.ipynb) focuses on one special kind of *collection* types, namely *sequences*, this chapter introduces two more kinds: **Mappings** and **sets**. Both are presented in this chapter as they share the *same* underlying implementation.\n",
|
||||
"While [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/00_content.ipynb) focuses on one special kind of *collection* types, namely *sequences*, this chapter introduces two more kinds: **Mappings** and **sets**. Both are presented in this chapter as they share the *same* underlying implementation.\n",
|
||||
"\n",
|
||||
"The `dict` type (cf, [documentation <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/stdtypes.html#dict)) introduced in the next section is an essential part in a data scientist's toolbox for two reasons: First, Python employs `dict` objects basically everywhere internally. Second, after the many concepts involving *sequential* data, *mappings* provide a different perspective on data and enhance our general problem solving skills."
|
||||
]
|
||||
|
|
@ -56,7 +56,7 @@
|
|||
"source": [
|
||||
"A *mapping* is a one-to-one correspondence from a set of **keys** to a set of **values**. In other words, a *mapping* is a *collection* of **key-value pairs**, also called **items** for short.\n",
|
||||
"\n",
|
||||
"In the context of mappings, the term *value* has a meaning different from the *value* every object has: In the \"bag\" analogy from [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#Value-/-%28Semantic%29-\"Meaning\"), we describe an object's value to be the semantic meaning of the $0$s and $1$s it contains. Here, the terms *key* and *value* mean the *role* an object takes within a mapping. Both, *keys* and *values*, are *objects* on their own with distinct *values*.\n",
|
||||
"In the context of mappings, the term *value* has a meaning different from the *value* every object has: In the \"bag\" analogy from [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#Value-/-%28Semantic%29-\"Meaning\"), we describe an object's value to be the semantic meaning of the $0$s and $1$s it contains. Here, the terms *key* and *value* mean the *role* an object takes within a mapping. Both, *keys* and *values*, are *objects* on their own with distinct *values*.\n",
|
||||
"\n",
|
||||
"Let's continue with an example. To create a `dict` object, we commonly use the literal notation, `{..: .., ..: .., ...}`, and list all the items. `to_words` below maps the `int` objects `0`, `1`, and `2` to their English word equivalents, `\"zero\"`, `\"one\"`, and `\"two\"`, and `from_words` does the opposite. A stylistic side note: Pythonistas often expand `dict` or `list` definitions by writing each item or element on a line on their own. Also, the commas `,` after the respective *last* items, `2: \"two\"` and `\"two\": 2`, are *not* a mistake although they *may* be left out. Besides easier reading, such a style has technical advantages that we do not go into detail about here (cf., [source <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://www.python.org/dev/peps/pep-0008/#when-to-use-trailing-commas))."
|
||||
]
|
||||
|
|
@ -550,7 +550,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"In [Chapter 0 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/00_intro/00_content.ipynb#Isn't-C-a-lot-faster?), we argue that a major advantage of using Python is that it takes care of the memory managment for us. In line with that, we have never talked about the C level implementation thus far in the book. However, the `dict` type, among others, exhibits some behaviors that may seem \"weird\" for a beginner. To build some intuition, we describe the underlying implementation details on a conceptual level.\n",
|
||||
"In [Chapter 0 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/00_intro/00_content.ipynb#Isn't-C-a-lot-faster?), we argue that a major advantage of using Python is that it takes care of the memory managment for us. In line with that, we have never talked about the C level implementation thus far in the book. However, the `dict` type, among others, exhibits some behaviors that may seem \"weird\" for a beginner. To build some intuition, we describe the underlying implementation details on a conceptual level.\n",
|
||||
"\n",
|
||||
"The first unintuitive behavior is that we may *not* use a *mutable* object as a key. That results in a `TypeError`."
|
||||
]
|
||||
|
|
@ -571,7 +571,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-17-20a24130a135>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m {\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m\"zero\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"one\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m }\n",
|
||||
"Cell \u001b[0;32mIn[17], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m {\n\u001b[1;32m 2\u001b[0m [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mzero\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mone\u001b[39m\u001b[38;5;124m\"\u001b[39m]: [\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m1\u001b[39m],\n\u001b[1;32m 3\u001b[0m }\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: unhashable type: 'list'"
|
||||
]
|
||||
}
|
||||
|
|
@ -837,7 +837,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-24-1afa4b4779b0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mhash\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"zero\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"one\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[24], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;43mhash\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mzero\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mone\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: unhashable type: 'list'"
|
||||
]
|
||||
}
|
||||
|
|
@ -1176,7 +1176,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"In [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/00_content.ipynb#Collections-vs.-Sequences), we see how a *sequence* is a special kind of a *collection*, and that collections can be described as\n",
|
||||
"In [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/00_content.ipynb#Collections-vs.-Sequences), we see how a *sequence* is a special kind of a *collection*, and that collections can be described as\n",
|
||||
"- *iterable*\n",
|
||||
"- *containers*\n",
|
||||
"- with a *finite* number of elements.\n",
|
||||
|
|
@ -1245,7 +1245,7 @@
|
|||
"Also, `dict` objects may be looped over, for example, with the `for` statement. So, in the terminology of the [collections.abc <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.abc.html) module, they are `Iterable` objects.\n",
|
||||
"\n",
|
||||
"Regarding the *iteration order* things are not that easy, and programmers seem to often be confused about this (e.g., this [discussion](https://stackoverflow.com/questions/58413076/why-are-python-dictionaries-not-reversible-for-python3-7)). The confusion usually comes from one of two reasons:\n",
|
||||
"1. The internal implementation of the `dict` type has been changed over the last couple of minor release versions, and the communication thereof in the official release notes was done only in a later version. In a nutshell, before Python 3.6, the core developers did not care about the iteration order at all as the goal was to optimize `dict` objects for computational speed, primarily regarding key look-up (cf., the \"Indexing -> Key Look-up\" section below). That meant that looping over the *same* `dict` object several times during its lifetime could have resulted in *different* iteration orders. In Python 3.6, it was discovered that it is possible to make `dict` objects remember the order in that items have been inserted *without* giving up any computational speed or memory (cf., [Raymond Hettinger](https://github.com/rhettinger)'s talk in the [Further Resources <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/08_resources.ipynb#History-of-the-dict-Type) section at the end of the chapter. However, that change was kept an *implementation detail* and *not* made official in the release notes. That was then done in Python 3.7's release notes (cf., [Python 3.7 release notes <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://www.python.org/downloads/release/python-370/)).\n",
|
||||
"1. The internal implementation of the `dict` type has been changed over the last couple of minor release versions, and the communication thereof in the official release notes was done only in a later version. In a nutshell, before Python 3.6, the core developers did not care about the iteration order at all as the goal was to optimize `dict` objects for computational speed, primarily regarding key look-up (cf., the \"Indexing -> Key Look-up\" section below). That meant that looping over the *same* `dict` object several times during its lifetime could have resulted in *different* iteration orders. In Python 3.6, it was discovered that it is possible to make `dict` objects remember the order in that items have been inserted *without* giving up any computational speed or memory (cf., [Raymond Hettinger](https://github.com/rhettinger)'s talk in the [Further Resources <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/08_resources.ipynb#History-of-the-dict-Type) section at the end of the chapter. However, that change was kept an *implementation detail* and *not* made official in the release notes. That was then done in Python 3.7's release notes (cf., [Python 3.7 release notes <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://www.python.org/downloads/release/python-370/)).\n",
|
||||
"2. To make order an official part of a data type, it must adhere to the `Reversible` ABC in the [collections.abc <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.abc.html) module and support the [reversed() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#reversed) built-in. Even though the items' order inside a `dict` is remembered for Python 3.6 and 3.7, `dict` objects are *not* `Reversible`. That was then changed in Python 3.8, but again *not* officially communicated (cf., [Python 3.8 release notes](https://www.python.org/downloads/release/python-380/)).\n",
|
||||
"\n",
|
||||
"In summary, we can say that depending on the exact Python version a `dict` object *may* remember the **insertion order** of its items.\n",
|
||||
|
|
@ -1272,7 +1272,7 @@
|
|||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Python 3.8.6\n"
|
||||
"Python 3.12.2\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -1952,7 +1952,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-61-8602ef11ff73>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfrom_words\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"drei\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[61], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mfrom_words\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mdrei\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\n",
|
||||
"\u001b[0;31mKeyError\u001b[0m: 'drei'"
|
||||
]
|
||||
}
|
||||
|
|
@ -2840,7 +2840,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-91-30b825de37f0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mto_words\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[91], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mto_words\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n",
|
||||
"\u001b[0;31mKeyError\u001b[0m: 0"
|
||||
]
|
||||
}
|
||||
|
|
@ -3099,7 +3099,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-101-b91e52fa79fd>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfrom_words\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"zero\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[101], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mfrom_words\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpop\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mzero\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mKeyError\u001b[0m: 'zero'"
|
||||
]
|
||||
}
|
||||
|
|
@ -3541,7 +3541,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Analogous to `list` comprehensions in [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/01_content.ipynb#list-Comprehensions), `dict` comprehensions are a concise literal notation to derive new `dict` objects out of existing ones.\n",
|
||||
"Analogous to `list` comprehensions in [Chapter 8 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/01_content.ipynb#list-Comprehensions), `dict` comprehensions are a concise literal notation to derive new `dict` objects out of existing ones.\n",
|
||||
"\n",
|
||||
"For example, let's derive `from_words` out of `to_words` below by swapping the keys and values."
|
||||
]
|
||||
|
|
@ -3741,7 +3741,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/09_mappings/01_exercises.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/09_mappings/01_exercises.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -18,7 +18,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The exercises below assume that you have read the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/00_content.ipynb) of Chapter 9.\n",
|
||||
"The exercises below assume that you have read the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/00_content.ipynb) of Chapter 9.\n",
|
||||
"\n",
|
||||
"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
|
||||
]
|
||||
|
|
@ -407,7 +407,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/09_mappings/02_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/09_mappings/02_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -30,7 +30,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"After introducing the `dict` type in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/00_content.ipynb) of this chapter, we first look at an extension of the packing and unpacking syntax that involves `dict` objects. Then, we see how mappings can help us write computationally more efficient implementations to recursive solutions of problems as introduced in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/00_content.ipynb#Recursion). In a way, this second part of the chapter \"finishes\" Chapter 4."
|
||||
"After introducing the `dict` type in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/00_content.ipynb) of this chapter, we first look at an extension of the packing and unpacking syntax that involves `dict` objects. Then, we see how mappings can help us write computationally more efficient implementations to recursive solutions of problems as introduced in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/00_content.ipynb#Recursion). In a way, this second part of the chapter \"finishes\" Chapter 4."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -52,7 +52,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Just as a single `*` symbol is used for packing and unpacking iterables in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/03_content.ipynb#Packing-&-Unpacking), a double `**` symbol implements packing and unpacking for mappings.\n",
|
||||
"Just as a single `*` symbol is used for packing and unpacking iterables in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/03_content.ipynb#Packing-&-Unpacking), a double `**` symbol implements packing and unpacking for mappings.\n",
|
||||
"\n",
|
||||
"Let's say we have `to_words` and `more_words` as below and want to merge the items together into a *new* `dict` object."
|
||||
]
|
||||
|
|
@ -394,7 +394,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-13-21a06a55e707>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mprint_args2\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[13], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mprint_args2\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: print_args2() missing 1 required positional argument: 'positional'"
|
||||
]
|
||||
}
|
||||
|
|
@ -419,7 +419,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-14-06c908f24fbb>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mprint_args2\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"p\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mprint_args2\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mp\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: print_args2() missing 1 required keyword-only argument: 'keyword'"
|
||||
]
|
||||
}
|
||||
|
|
@ -608,7 +608,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"The *recursive* implementation of the [Fibonacci numbers <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Fibonacci_number) in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/00_content.ipynb#\"Easy-at-first-Glance\"-Example:-Fibonacci-Numbers) takes long to compute for large Fibonacci numbers. For easier comparison, we show the old `fibonacci()` version here again."
|
||||
"The *recursive* implementation of the [Fibonacci numbers <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Fibonacci_number) in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/00_content.ipynb#\"Easy-at-first-Glance\"-Example:-Fibonacci-Numbers) takes long to compute for large Fibonacci numbers. For easier comparison, we show the old `fibonacci()` version here again."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -831,7 +831,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"When we follow the flow of execution closely, we realize that the intermediate results represented by the left-most path in the graph above are calculated first. `fibonacci(1)`, the left-most leaf node $F(1)$, is the first base case reached, followed immediately by `fibonacci(0)`. From that moment onwards, the flow of execution moves back up the left-most path while adding together the two corresponding child nodes. Effectively, this mirrors the *iterative* implementation in that the order of all computational steps are *identical* (cf., the \"*Hard at first Glance*\" example in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/02_content.ipynb#\"Hard-at-first-Glance\"-Example:-Fibonacci-Numbers--(revisited))).\n",
|
||||
"When we follow the flow of execution closely, we realize that the intermediate results represented by the left-most path in the graph above are calculated first. `fibonacci(1)`, the left-most leaf node $F(1)$, is the first base case reached, followed immediately by `fibonacci(0)`. From that moment onwards, the flow of execution moves back up the left-most path while adding together the two corresponding child nodes. Effectively, this mirrors the *iterative* implementation in that the order of all computational steps are *identical* (cf., the \"*Hard at first Glance*\" example in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/02_content.ipynb#\"Hard-at-first-Glance\"-Example:-Fibonacci-Numbers--(revisited))).\n",
|
||||
"\n",
|
||||
"We added a keyword-only argument `debug` that allows the caller to print out a message every time a `i` was *not* in the `memo`."
|
||||
]
|
||||
|
|
@ -1045,17 +1045,16 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mRecursionError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-32-db4be504bbfd>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_cell_magic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'timeit'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'-n 1'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'fibonacci(9999)\\n'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m~/repos/intro-to-python/.venv/lib/python3.8/site-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mrun_cell_magic\u001b[0;34m(self, magic_name, line, cell)\u001b[0m\n\u001b[1;32m 2379\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuiltin_trap\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2380\u001b[0m \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mmagic_arg_s\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcell\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2381\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2382\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2383\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;32m<decorator-gen-53>\u001b[0m in \u001b[0;36mtimeit\u001b[0;34m(self, line, cell, local_ns)\u001b[0m\n",
|
||||
"\u001b[0;32m~/repos/intro-to-python/.venv/lib/python3.8/site-packages/IPython/core/magic.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(f, *a, **k)\u001b[0m\n\u001b[1;32m 185\u001b[0m \u001b[0;31m# but it's overkill for just that one bit of state.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 186\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mmagic_deco\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 187\u001b[0;31m \u001b[0mcall\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 188\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 189\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mcallable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;32m~/repos/intro-to-python/.venv/lib/python3.8/site-packages/IPython/core/magics/execution.py\u001b[0m in \u001b[0;36mtimeit\u001b[0;34m(self, line, cell, local_ns)\u001b[0m\n\u001b[1;32m 1171\u001b[0m \u001b[0;32mbreak\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1172\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1173\u001b[0;31m \u001b[0mall_runs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtimer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrepeat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrepeat\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnumber\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1174\u001b[0m \u001b[0mbest\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall_runs\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mnumber\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1175\u001b[0m \u001b[0mworst\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall_runs\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mnumber\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;32m~/.pyenv/versions/3.8.6/lib/python3.8/timeit.py\u001b[0m in \u001b[0;36mrepeat\u001b[0;34m(self, repeat, number)\u001b[0m\n\u001b[1;32m 203\u001b[0m \u001b[0mr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 204\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrepeat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 205\u001b[0;31m \u001b[0mt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtimeit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnumber\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 206\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 207\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;32m~/repos/intro-to-python/.venv/lib/python3.8/site-packages/IPython/core/magics/execution.py\u001b[0m in \u001b[0;36mtimeit\u001b[0;34m(self, number)\u001b[0m\n\u001b[1;32m 167\u001b[0m \u001b[0mgc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdisable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 168\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 169\u001b[0;31m \u001b[0mtiming\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minner\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mit\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtimer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 170\u001b[0m \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 171\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mgcold\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;32m<magic-timeit>\u001b[0m in \u001b[0;36minner\u001b[0;34m(_it, _timer)\u001b[0m\n",
|
||||
"\u001b[0;32m<ipython-input-26-dd55d928f4d4>\u001b[0m in \u001b[0;36mfibonacci\u001b[0;34m(i, debug)\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"fibonacci({i}) is calculated\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 17\u001b[0;31m \u001b[0mrecurse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfibonacci\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdebug\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mfibonacci\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdebug\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 18\u001b[0m \u001b[0mmemo\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrecurse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 19\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mrecurse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"... last 1 frames repeated, from the frame below ...\n",
|
||||
"\u001b[0;32m<ipython-input-26-dd55d928f4d4>\u001b[0m in \u001b[0;36mfibonacci\u001b[0;34m(i, debug)\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"fibonacci({i}) is calculated\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 17\u001b[0;31m \u001b[0mrecurse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfibonacci\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdebug\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mfibonacci\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdebug\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 18\u001b[0m \u001b[0mmemo\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrecurse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 19\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mrecurse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[32], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mget_ipython\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_cell_magic\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mtimeit\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m-n 1\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mfibonacci(9999)\u001b[39;49m\u001b[38;5;130;43;01m\\n\u001b[39;49;00m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"File \u001b[0;32m~/Repositories/intro-to-python/.venv/lib/python3.12/site-packages/IPython/core/interactiveshell.py:2541\u001b[0m, in \u001b[0;36mInteractiveShell.run_cell_magic\u001b[0;34m(self, magic_name, line, cell)\u001b[0m\n\u001b[1;32m 2539\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbuiltin_trap:\n\u001b[1;32m 2540\u001b[0m args \u001b[38;5;241m=\u001b[39m (magic_arg_s, cell)\n\u001b[0;32m-> 2541\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2543\u001b[0m \u001b[38;5;66;03m# The code below prevents the output from being displayed\u001b[39;00m\n\u001b[1;32m 2544\u001b[0m \u001b[38;5;66;03m# when using magics with decorator @output_can_be_silenced\u001b[39;00m\n\u001b[1;32m 2545\u001b[0m \u001b[38;5;66;03m# when the last Python token in the expression is a ';'.\u001b[39;00m\n\u001b[1;32m 2546\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mgetattr\u001b[39m(fn, magic\u001b[38;5;241m.\u001b[39mMAGIC_OUTPUT_CAN_BE_SILENCED, \u001b[38;5;28;01mFalse\u001b[39;00m):\n",
|
||||
"File \u001b[0;32m~/Repositories/intro-to-python/.venv/lib/python3.12/site-packages/IPython/core/magics/execution.py:1189\u001b[0m, in \u001b[0;36mExecutionMagics.timeit\u001b[0;34m(self, line, cell, local_ns)\u001b[0m\n\u001b[1;32m 1186\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m time_number \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0.2\u001b[39m:\n\u001b[1;32m 1187\u001b[0m \u001b[38;5;28;01mbreak\u001b[39;00m\n\u001b[0;32m-> 1189\u001b[0m all_runs \u001b[38;5;241m=\u001b[39m \u001b[43mtimer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrepeat\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrepeat\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnumber\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1190\u001b[0m best \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mmin\u001b[39m(all_runs) \u001b[38;5;241m/\u001b[39m number\n\u001b[1;32m 1191\u001b[0m worst \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mmax\u001b[39m(all_runs) \u001b[38;5;241m/\u001b[39m number\n",
|
||||
"File \u001b[0;32m/usr/lib64/python3.12/timeit.py:208\u001b[0m, in \u001b[0;36mTimer.repeat\u001b[0;34m(self, repeat, number)\u001b[0m\n\u001b[1;32m 206\u001b[0m r \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 207\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(repeat):\n\u001b[0;32m--> 208\u001b[0m t \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtimeit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnumber\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 209\u001b[0m r\u001b[38;5;241m.\u001b[39mappend(t)\n\u001b[1;32m 210\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m r\n",
|
||||
"File \u001b[0;32m~/Repositories/intro-to-python/.venv/lib/python3.12/site-packages/IPython/core/magics/execution.py:173\u001b[0m, in \u001b[0;36mTimer.timeit\u001b[0;34m(self, number)\u001b[0m\n\u001b[1;32m 171\u001b[0m gc\u001b[38;5;241m.\u001b[39mdisable()\n\u001b[1;32m 172\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 173\u001b[0m timing \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minner\u001b[49m\u001b[43m(\u001b[49m\u001b[43mit\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtimer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 174\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m 175\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m gcold:\n",
|
||||
"File \u001b[0;32m<magic-timeit>:1\u001b[0m, in \u001b[0;36minner\u001b[0;34m(_it, _timer)\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[26], line 17\u001b[0m, in \u001b[0;36mfibonacci\u001b[0;34m(i, debug)\u001b[0m\n\u001b[1;32m 14\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m debug: \u001b[38;5;66;03m# added for didactical purposes\u001b[39;00m\n\u001b[1;32m 15\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfibonacci(\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mi\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m) is calculated\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m---> 17\u001b[0m recurse \u001b[38;5;241m=\u001b[39m \u001b[43mfibonacci\u001b[49m\u001b[43m(\u001b[49m\u001b[43mi\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdebug\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdebug\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;241m+\u001b[39m fibonacci(i \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m2\u001b[39m, debug\u001b[38;5;241m=\u001b[39mdebug)\n\u001b[1;32m 18\u001b[0m memo[i] \u001b[38;5;241m=\u001b[39m recurse\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m recurse\n",
|
||||
"Cell \u001b[0;32mIn[26], line 17\u001b[0m, in \u001b[0;36mfibonacci\u001b[0;34m(i, debug)\u001b[0m\n\u001b[1;32m 14\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m debug: \u001b[38;5;66;03m# added for didactical purposes\u001b[39;00m\n\u001b[1;32m 15\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfibonacci(\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mi\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m) is calculated\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m---> 17\u001b[0m recurse \u001b[38;5;241m=\u001b[39m \u001b[43mfibonacci\u001b[49m\u001b[43m(\u001b[49m\u001b[43mi\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdebug\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdebug\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;241m+\u001b[39m fibonacci(i \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m2\u001b[39m, debug\u001b[38;5;241m=\u001b[39mdebug)\n\u001b[1;32m 18\u001b[0m memo[i] \u001b[38;5;241m=\u001b[39m recurse\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m recurse\n",
|
||||
" \u001b[0;31m[... skipping similar frames: fibonacci at line 17 (2969 times)]\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[26], line 17\u001b[0m, in \u001b[0;36mfibonacci\u001b[0;34m(i, debug)\u001b[0m\n\u001b[1;32m 14\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m debug: \u001b[38;5;66;03m# added for didactical purposes\u001b[39;00m\n\u001b[1;32m 15\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfibonacci(\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mi\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m) is calculated\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m---> 17\u001b[0m recurse \u001b[38;5;241m=\u001b[39m \u001b[43mfibonacci\u001b[49m\u001b[43m(\u001b[49m\u001b[43mi\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdebug\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdebug\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;241m+\u001b[39m fibonacci(i \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m2\u001b[39m, debug\u001b[38;5;241m=\u001b[39mdebug)\n\u001b[1;32m 18\u001b[0m memo[i] \u001b[38;5;241m=\u001b[39m recurse\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m recurse\n",
|
||||
"\u001b[0;31mRecursionError\u001b[0m: maximum recursion depth exceeded"
|
||||
]
|
||||
}
|
||||
|
|
@ -1205,7 +1204,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/09_mappings/03_exercises.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/09_mappings/03_exercises.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -18,7 +18,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The exercises below assume that you have read the [second part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/02_content.ipynb) of Chapter 9.\n",
|
||||
"The exercises below assume that you have read the [second part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/02_content.ipynb) of Chapter 9.\n",
|
||||
"\n",
|
||||
"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
|
||||
]
|
||||
|
|
@ -38,7 +38,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"It is considered *bad practice* to make a function and thereby its correctness dependent on a program's *global state*: For example, in the \"*Easy at second Glance: Fibonacci Numbers*\" section in [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/02_content.ipynb#\"Easy-at-second-Glance\"-Example:-Fibonacci-Numbers--%28revisited%29), we use a global `memo` to store the Fibonacci numbers that have already been calculated.\n",
|
||||
"It is considered *bad practice* to make a function and thereby its correctness dependent on a program's *global state*: For example, in the \"*Easy at second Glance: Fibonacci Numbers*\" section in [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/02_content.ipynb#\"Easy-at-second-Glance\"-Example:-Fibonacci-Numbers--%28revisited%29), we use a global `memo` to store the Fibonacci numbers that have already been calculated.\n",
|
||||
"\n",
|
||||
"That `memo` dictionary could be \"manipulated.\" More often than not, such things happen by accident: Imagine we wrote two independent recursive functions that both rely on memoization to solve different problems, and, unintentionally, we made both work with the *same* global `memo`. As a result, we would observe \"random\" bugs depending on the order in which we executed these functions. Such bugs are hard to track down in practice.\n",
|
||||
"\n",
|
||||
|
|
@ -185,7 +185,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The runtime of `fibonacci()` is now stable: There is no message that \"an intermediate result is being cached\" as in [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/02_content.ipynb#\"Easy-at-second-Glance\"-Example:-Fibonacci-Numbers--%28revisited%29).\n",
|
||||
"The runtime of `fibonacci()` is now stable: There is no message that \"an intermediate result is being cached\" as in [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/02_content.ipynb#\"Easy-at-second-Glance\"-Example:-Fibonacci-Numbers--%28revisited%29).\n",
|
||||
"\n",
|
||||
"**Q7**: Execute the following code cells a couple of times to observe that!"
|
||||
]
|
||||
|
|
@ -227,7 +227,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/09_mappings/04_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/09_mappings/04_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -315,7 +315,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-10-4ac30fae8196>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;34m{\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[10], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m {\u001b[38;5;241m0\u001b[39m, [\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m2\u001b[39m], \u001b[38;5;241m3\u001b[39m}\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: unhashable type: 'list'"
|
||||
]
|
||||
}
|
||||
|
|
@ -419,7 +419,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-13-1095d1ef6c80>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mnumber\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mreversed\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnumbers\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnumber\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mend\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\" \"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[13], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m number \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28;43mreversed\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mnumbers\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28mprint\u001b[39m(number, end\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: 'set' object is not reversible"
|
||||
]
|
||||
}
|
||||
|
|
@ -646,7 +646,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-21-7486ea9d37bc>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnumbers\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[21], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mnumbers\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: 'set' object is not subscriptable"
|
||||
]
|
||||
}
|
||||
|
|
@ -671,7 +671,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-22-4de4c0f84e99>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnumbers\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[22], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mnumbers\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[43m]\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: 'set' object is not subscriptable"
|
||||
]
|
||||
}
|
||||
|
|
@ -829,7 +829,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-28-45d8b57b937d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnumbers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m999\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[28], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mnumbers\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mremove\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m999\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mKeyError\u001b[0m: 999"
|
||||
]
|
||||
}
|
||||
|
|
@ -1407,7 +1407,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Python provides a literal notation for `set` comprehensions that works exactly like the one for `dict` comprehensions described in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/00_content.ipynb#dict-Comprehensions) of this chapter except that they use a single loop variable instead of a key-value pair.\n",
|
||||
"Python provides a literal notation for `set` comprehensions that works exactly like the one for `dict` comprehensions described in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/00_content.ipynb#dict-Comprehensions) of this chapter except that they use a single loop variable instead of a key-value pair.\n",
|
||||
"\n",
|
||||
"For example, let's create a new `set` object that consists of the squares of all the elements of `numbers`."
|
||||
]
|
||||
|
|
@ -1573,7 +1573,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/09_mappings/05_appendix.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/09_mappings/05_appendix.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -463,11 +463,11 @@
|
|||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"Counter({'Müller': 1,\n",
|
||||
" 'Klose': 1,\n",
|
||||
" 'Kroos': 2,\n",
|
||||
" 'Khedira': 1,\n",
|
||||
"Counter({'Kroos': 2,\n",
|
||||
" 'Schürrle': 2,\n",
|
||||
" 'Müller': 1,\n",
|
||||
" 'Klose': 1,\n",
|
||||
" 'Khedira': 1,\n",
|
||||
" 'Oscar': 1})"
|
||||
]
|
||||
},
|
||||
|
|
@ -647,11 +647,11 @@
|
|||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"Counter({'Müller': 1,\n",
|
||||
" 'Klose': 1,\n",
|
||||
" 'Kroos': 2,\n",
|
||||
" 'Khedira': 1,\n",
|
||||
"Counter({'Kroos': 2,\n",
|
||||
" 'Schürrle': 2,\n",
|
||||
" 'Müller': 1,\n",
|
||||
" 'Klose': 1,\n",
|
||||
" 'Khedira': 1,\n",
|
||||
" 'Oscar': 1,\n",
|
||||
" 'Lahm': 1})"
|
||||
]
|
||||
|
|
@ -701,11 +701,11 @@
|
|||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"Counter({'Müller': 1,\n",
|
||||
" 'Klose': 1,\n",
|
||||
" 'Kroos': 2,\n",
|
||||
" 'Khedira': 1,\n",
|
||||
"Counter({'Kroos': 2,\n",
|
||||
" 'Schürrle': 2,\n",
|
||||
" 'Müller': 1,\n",
|
||||
" 'Klose': 1,\n",
|
||||
" 'Khedira': 1,\n",
|
||||
" 'Oscar': 1,\n",
|
||||
" 'Lahm': 1,\n",
|
||||
" 'L': 1,\n",
|
||||
|
|
@ -910,9 +910,9 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-28-25fb5b5b2e5f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mchain\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m~/.pyenv/versions/3.8.6/lib/python3.8/collections/__init__.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 896\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 897\u001b[0m \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 898\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__missing__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# support subclasses that define __missing__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 899\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 900\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdefault\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;32m~/.pyenv/versions/3.8.6/lib/python3.8/collections/__init__.py\u001b[0m in \u001b[0;36m__missing__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 888\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 889\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__missing__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 890\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 891\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 892\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__getitem__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[28], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mchain\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m10\u001b[39;49m\u001b[43m]\u001b[49m\n",
|
||||
"File \u001b[0;32m/usr/lib64/python3.12/collections/__init__.py:1014\u001b[0m, in \u001b[0;36mChainMap.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1012\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m:\n\u001b[1;32m 1013\u001b[0m \u001b[38;5;28;01mpass\u001b[39;00m\n\u001b[0;32m-> 1014\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__missing__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"File \u001b[0;32m/usr/lib64/python3.12/collections/__init__.py:1006\u001b[0m, in \u001b[0;36mChainMap.__missing__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1005\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__missing__\u001b[39m(\u001b[38;5;28mself\u001b[39m, key):\n\u001b[0;32m-> 1006\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key)\n",
|
||||
"\u001b[0;31mKeyError\u001b[0m: 10"
|
||||
]
|
||||
}
|
||||
|
|
@ -938,7 +938,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -45,7 +45,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -11,7 +11,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/00_content.ipynb), [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/02_content.ipynb), and [third <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/04_content.ipynb) part of Chapter 9.\n",
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/00_content.ipynb), [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/02_content.ipynb), and [third <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/04_content.ipynb) part of Chapter 9.\n",
|
||||
"\n",
|
||||
"Be concise in your answers! Most questions can be answered in *one* sentence."
|
||||
]
|
||||
|
|
@ -99,7 +99,7 @@
|
|||
"source": [
|
||||
"**Q6**: **Memoization** is an essential concept to know to solve problems in the real world. Together with the idea of **recursion**, it enables us to solve problems in a \"backwards\" fashion *effectively*.\n",
|
||||
"\n",
|
||||
"Compare the **recursive** formulation of `fibonacci()` in [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/02_content.ipynb#\"Easy-at-second-Glance\"-Example:-Fibonacci-Numbers--(revisited)), the \"*Easy at second Glance*\" example, with the **iterative** version in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/02_content.ipynb#\"Hard-at-first-Glance\"-Example:-Fibonacci-Numbers-%28revisited%29), the \"*Hard at first Glance*\" example!\n",
|
||||
"Compare the **recursive** formulation of `fibonacci()` in [Chapter 9 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/02_content.ipynb#\"Easy-at-second-Glance\"-Example:-Fibonacci-Numbers--(revisited)), the \"*Easy at second Glance*\" example, with the **iterative** version in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/02_content.ipynb#\"Hard-at-first-Glance\"-Example:-Fibonacci-Numbers-%28revisited%29), the \"*Hard at first Glance*\" example!\n",
|
||||
"\n",
|
||||
"How are they similar and how do they differ? Also consider how the flow of execution behaves when the functions are being executed."
|
||||
]
|
||||
|
|
@ -226,7 +226,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/09_mappings/08_resources.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/09_mappings/08_resources.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -67,6 +67,7 @@
|
|||
" src=\"https://www.youtube.com/embed/C4Kc8xzcA68\"\n",
|
||||
" frameborder=\"0\"\n",
|
||||
" allowfullscreen\n",
|
||||
" \n",
|
||||
" ></iframe>\n",
|
||||
" "
|
||||
],
|
||||
|
|
@ -104,6 +105,7 @@
|
|||
" src=\"https://www.youtube.com/embed/66P5FMkWoVU\"\n",
|
||||
" frameborder=\"0\"\n",
|
||||
" allowfullscreen\n",
|
||||
" \n",
|
||||
" ></iframe>\n",
|
||||
" "
|
||||
],
|
||||
|
|
@ -163,6 +165,7 @@
|
|||
" src=\"https://www.youtube.com/embed/npw4s1QTmPg\"\n",
|
||||
" frameborder=\"0\"\n",
|
||||
" allowfullscreen\n",
|
||||
" \n",
|
||||
" ></iframe>\n",
|
||||
" "
|
||||
],
|
||||
|
|
@ -196,7 +199,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
1
10_arrays/TODO.md
Normal file
1
10_arrays/TODO.md
Normal file
|
|
@ -0,0 +1 @@
|
|||
Here, a new section on `numpy` Arrays and, maybe, `pandas` DataFrames will be added.
|
||||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/11_classes/00_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/11_classes/00_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -34,7 +34,7 @@
|
|||
"\n",
|
||||
"Classes and instances follow the **[object-oriented programming <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Object-oriented_programming)** (OOP) paradigm where a *large program* is broken down into many *small components* (i.e., the objects) that *reuse* code. This way, a program that is too big for a programmer to fully comprehend as a whole becomes maintainable via its easier to understand individual pieces.\n",
|
||||
"\n",
|
||||
"Often, we see the terminology \"classes & objects\" used instead of \"classes & instances\" in Python related texts. In this book, we are more precise as *both* classes and instances are objects as specified already in the \"*Objects vs. Types vs. Values*\" section in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#Objects-vs.-Types-vs.-Values)."
|
||||
"Often, we see the terminology \"classes & objects\" used instead of \"classes & instances\" in Python related texts. In this book, we are more precise as *both* classes and instances are objects as specified already in the \"*Objects vs. Types vs. Values*\" section in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#Objects-vs.-Types-vs.-Values)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -56,7 +56,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Neither core Python nor the standard library offer an implementation of common [linear algebra <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Linear_algebra) functionalities. While we introduce the popular third-party library [numpy](http://www.numpy.org/) in [Chapter 10 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/10_arrarys/00_content.ipynb) as the de-facto standard for that and recommend to use it in real-life projects, we show how one could use Python's object-oriented language features to implement common matrix and vector operations throughout this chapter. Once we have achieved that, we compare our own library with [numpy](http://www.numpy.org/).\n",
|
||||
"Neither core Python nor the standard library offer an implementation of common [linear algebra <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Linear_algebra) functionalities. While we introduce the popular third-party library [numpy](http://www.numpy.org/) in [Chapter 10 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/10_arrarys/00_content.ipynb) as the de-facto standard for that and recommend to use it in real-life projects, we show how one could use Python's object-oriented language features to implement common matrix and vector operations throughout this chapter. Once we have achieved that, we compare our own library with [numpy](http://www.numpy.org/).\n",
|
||||
"\n",
|
||||
"Without classes, we could model a vector, for example, with a `tuple` or a `list` object, depending on if we want it to be mutable or not.\n",
|
||||
"\n",
|
||||
|
|
@ -212,7 +212,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-5-fd81d962f516>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mA\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[5], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mA\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mx\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: can't multiply sequence by non-int of type 'tuple'"
|
||||
]
|
||||
}
|
||||
|
|
@ -326,7 +326,7 @@
|
|||
"source": [
|
||||
"Its type is `type` indicating that it represents a user-defined data type and it evaluates to its fully qualified name (i.e., `__main__` as it is defined in this Jupyter notebook).\n",
|
||||
"\n",
|
||||
"We have seen the type `type` before in the \"*Constructors*\" section in [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb#Constructors) and also in the \"*The `namedtuple` Type*\" section in [Chapter 7's Appendix <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/05_appendix.ipynb#The-namedtuple-Type). In the latter case, we could also use a `Point` class but the [namedtuple() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.html#collections.namedtuple) function from the [collections <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.html) module in the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html) is a convenient shortcut to create custom data types that can be derived out of a plain `tuple`.\n",
|
||||
"We have seen the type `type` before in the \"*Constructors*\" section in [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/00_content.ipynb#Constructors) and also in the \"*The `namedtuple` Type*\" section in [Chapter 7's Appendix <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/05_appendix.ipynb#The-namedtuple-Type). In the latter case, we could also use a `Point` class but the [namedtuple() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.html#collections.namedtuple) function from the [collections <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.html) module in the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html) is a convenient shortcut to create custom data types that can be derived out of a plain `tuple`.\n",
|
||||
"\n",
|
||||
"In all examples, if an object's type is `type`, we can simply view it as a blueprint for a \"family\" of objects."
|
||||
]
|
||||
|
|
@ -405,7 +405,7 @@
|
|||
"\u001b[0;31mInit signature:\u001b[0m \u001b[0mVector\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;31mDocstring:\u001b[0m A one-dimensional vector from linear algebra.\n",
|
||||
"\u001b[0;31mType:\u001b[0m type\n",
|
||||
"\u001b[0;31mSubclasses:\u001b[0m \n"
|
||||
"\u001b[0;31mSubclasses:\u001b[0m "
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
|
|
@ -433,24 +433,24 @@
|
|||
"\n",
|
||||
"class Vector(builtins.object)\n",
|
||||
" | A one-dimensional vector from linear algebra.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Methods defined here:\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | dummy_method(self)\n",
|
||||
" | A dummy method for illustration purposes.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | ----------------------------------------------------------------------\n",
|
||||
" | Data descriptors defined here:\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __dict__\n",
|
||||
" | dictionary for instance variables (if defined)\n",
|
||||
" | \n",
|
||||
" | dictionary for instance variables\n",
|
||||
" |\n",
|
||||
" | __weakref__\n",
|
||||
" | list of weak references to the object (if defined)\n",
|
||||
" | \n",
|
||||
" | list of weak references to the object\n",
|
||||
" |\n",
|
||||
" | ----------------------------------------------------------------------\n",
|
||||
" | Data and other attributes defined here:\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | dummy_variable = 'I am a vector'\n",
|
||||
"\n"
|
||||
]
|
||||
|
|
@ -521,6 +521,7 @@
|
|||
" '__format__',\n",
|
||||
" '__ge__',\n",
|
||||
" '__getattribute__',\n",
|
||||
" '__getstate__',\n",
|
||||
" '__gt__',\n",
|
||||
" '__hash__',\n",
|
||||
" '__init__',\n",
|
||||
|
|
@ -632,13 +633,13 @@
|
|||
"outputs": [
|
||||
{
|
||||
"ename": "TypeError",
|
||||
"evalue": "dummy_method() missing 1 required positional argument: 'self'",
|
||||
"evalue": "Vector.dummy_method() missing 1 required positional argument: 'self'",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-16-829638f9c7cf>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mVector\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdummy_method\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m: dummy_method() missing 1 required positional argument: 'self'"
|
||||
"Cell \u001b[0;32mIn[16], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mVector\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdummy_method\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: Vector.dummy_method() missing 1 required positional argument: 'self'"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -859,13 +860,13 @@
|
|||
"outputs": [
|
||||
{
|
||||
"ename": "TypeError",
|
||||
"evalue": "__init__() missing 1 required positional argument: 'data'",
|
||||
"evalue": "Vector.__init__() missing 1 required positional argument: 'data'",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-23-bcda4006949f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mVector\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m: __init__() missing 1 required positional argument: 'data'"
|
||||
"Cell \u001b[0;32mIn[22], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mVector\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: Vector.__init__() missing 1 required positional argument: 'data'"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -884,13 +885,13 @@
|
|||
"outputs": [
|
||||
{
|
||||
"ename": "TypeError",
|
||||
"evalue": "__init__() takes 2 positional arguments but 4 were given",
|
||||
"evalue": "Vector.__init__() takes 2 positional arguments but 4 were given",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-24-e00314c6a560>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mVector\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m: __init__() takes 2 positional arguments but 4 were given"
|
||||
"Cell \u001b[0;32mIn[23], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mVector\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m3\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: Vector.__init__() takes 2 positional arguments but 4 were given"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -925,8 +926,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-25-7261658e317e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mVector\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-17-441d7f5df856>\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_entries\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfloat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 17\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_entries\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 18\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"a vector must have at least one entry\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[24], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mVector\u001b[49m\u001b[43m(\u001b[49m\u001b[43m[\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[17], line 18\u001b[0m, in \u001b[0;36mVector.__init__\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_entries \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(\u001b[38;5;28mfloat\u001b[39m(x) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m data)\n\u001b[1;32m 17\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_entries) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m---> 18\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124ma vector must have at least one entry\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
|
||||
"\u001b[0;31mValueError\u001b[0m: a vector must have at least one entry"
|
||||
]
|
||||
}
|
||||
|
|
@ -1293,7 +1294,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"From a theoretical point of view, the text representation provided by `.__repr__()` contains all the information (i.e., the $0$s and $1$s in memory) that is needed to model something in a computer. In a way, it is a natural extension from the binary (cf., [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/00_content.ipynb#Binary-Representations)), hexadecimal (cf., [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/00_content.ipynb#Hexadecimal-Representations)), and `bytes` (cf., [Chapter 6 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/02_content.ipynb#The-bytes-Type)) representations of information. After all, just like Unicode characters are encoded in `bytes`, the more \"complex\" objects in this chapter are encoded in Unicode characters via their text representations."
|
||||
"From a theoretical point of view, the text representation provided by `.__repr__()` contains all the information (i.e., the $0$s and $1$s in memory) that is needed to model something in a computer. In a way, it is a natural extension from the binary (cf., [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/00_content.ipynb#Binary-Representations)), hexadecimal (cf., [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/00_content.ipynb#Hexadecimal-Representations)), and `bytes` (cf., [Chapter 6 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/02_content.ipynb#The-bytes-Type)) representations of information. After all, just like Unicode characters are encoded in `bytes`, the more \"complex\" objects in this chapter are encoded in Unicode characters via their text representations."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1589,8 +1590,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-46-87c8bd55bdc1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mMatrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-37-2c8575833cd9>\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"rows must have the same number of entries\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_entries\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"a matrix must have at least one entry\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__repr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[45], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mMatrix\u001b[49m\u001b[43m(\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[36], line 9\u001b[0m, in \u001b[0;36mMatrix.__init__\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrows must have the same number of entries\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 8\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_entries) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m----> 9\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124ma matrix must have at least one entry\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
|
||||
"\u001b[0;31mValueError\u001b[0m: a matrix must have at least one entry"
|
||||
]
|
||||
}
|
||||
|
|
@ -1615,8 +1616,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-47-359f87edecdf>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mMatrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;36m4\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-37-2c8575833cd9>\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mrow\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_entries\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrow\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_entries\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"rows must have the same number of entries\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 8\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_entries\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"a matrix must have at least one entry\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[46], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mMatrix\u001b[49m\u001b[43m(\u001b[49m\u001b[43m[\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m3\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m4\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[36], line 7\u001b[0m, in \u001b[0;36mMatrix.__init__\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m row \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_entries[\u001b[38;5;241m1\u001b[39m:]:\n\u001b[1;32m 6\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(row) \u001b[38;5;241m!=\u001b[39m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_entries[\u001b[38;5;241m0\u001b[39m]):\n\u001b[0;32m----> 7\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrows must have the same number of entries\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 8\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_entries) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 9\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124ma matrix must have at least one entry\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
|
||||
"\u001b[0;31mValueError\u001b[0m: rows must have the same number of entries"
|
||||
]
|
||||
}
|
||||
|
|
@ -1648,7 +1649,7 @@
|
|||
"\n",
|
||||
"An example of an instance method from linear algebra is the `.transpose()` method below that switches the rows and columns of an *existing* `Matrix` instance and returns a *new* `Matrix` instance based off that. It is implemented by passing the *iterator* created with the [zip() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#zip) built-in as the `data` argument to the `Matrix` constructor: The expression `zip(*self._entries)` may be a bit hard to understand because of the involved unpacking but simply flips a `Matrix`'s rows and columns. The built-in [list() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-list) constructor within the `.__init__()` method then materializes the iterator into the `._entries` attribute. Without a concrete `Matrix`'s rows and columns, `.transpose()` does not make sense, conceptually speaking.\n",
|
||||
"\n",
|
||||
"Also, we see that it is ok to reference a class from within one of its methods. While this seems trivial to some readers, others may find this confusing. The final versions of the `Vector` and `Matrix` classes in the [fourth part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/04_content.ipynb#The-final-Vector-and-Matrix-Classes) of this chapter show how this \"hard coded\" redundancy can be avoided."
|
||||
"Also, we see that it is ok to reference a class from within one of its methods. While this seems trivial to some readers, others may find this confusing. The final versions of the `Vector` and `Matrix` classes in the [fourth part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/04_content.ipynb#The-final-Vector-and-Matrix-Classes) of this chapter show how this \"hard coded\" redundancy can be avoided."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -2083,13 +2084,13 @@
|
|||
"outputs": [
|
||||
{
|
||||
"ename": "AttributeError",
|
||||
"evalue": "can't set attribute",
|
||||
"evalue": "property 'n_rows' of 'Matrix' object has no setter",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-62-f4cc4767ae11>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mn_rows\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;31mAttributeError\u001b[0m: can't set attribute"
|
||||
"Cell \u001b[0;32mIn[61], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mm\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mn_rows\u001b[49m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m3\u001b[39m\n",
|
||||
"\u001b[0;31mAttributeError\u001b[0m: property 'n_rows' of 'Matrix' object has no setter"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -2114,7 +2115,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/11_classes/01_exercises.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/11_classes/01_exercises.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -18,7 +18,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The exercises below assume that you have read the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/00_content.ipynb) of Chapter 11.\n",
|
||||
"The exercises below assume that you have read the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/00_content.ipynb) of Chapter 11.\n",
|
||||
"\n",
|
||||
"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
|
||||
]
|
||||
|
|
@ -1476,7 +1476,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/11_classes/02_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/11_classes/02_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -52,7 +52,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"As discussed in detail in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/00_content.ipynb#Collections-vs.-Sequences), a sequence is any finite and iterable container type with a *predictable* order of its elements such that we can label each element with an index in the range `0 <= index < len(sequence)`.\n",
|
||||
"As discussed in detail in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/00_content.ipynb#Collections-vs.-Sequences), a sequence is any finite and iterable container type with a *predictable* order of its elements such that we can label each element with an index in the range `0 <= index < len(sequence)`.\n",
|
||||
"\n",
|
||||
"To make `Vector` and `Matrix` instances emulate sequences, we implement the `.__len__()` (cf., [reference <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/reference/datamodel.html#object.__len__)) and `.__getitem__()` (cf., [reference <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/reference/datamodel.html#object.__getitem__)) methods. While the former returns the total number of elements in a container and is automatically invoked on any object passed to the built-in [len() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#len) function, the latter is invoked by the interpreter behind the scenes when we use the indexing operator `[]`.\n",
|
||||
"\n",
|
||||
|
|
@ -346,7 +346,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-10-ac550dc2349d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mv\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m99\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[10], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mv\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m99\u001b[39m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: 'Vector' object does not support item assignment"
|
||||
]
|
||||
}
|
||||
|
|
@ -714,7 +714,7 @@
|
|||
"\n",
|
||||
"The collection of all such behaviors a programming language offers is commonly referred to as its **object model**. In Python, the term **data model** is used instead and all possible behaviors are documented in the [language reference <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/reference/datamodel.html), in particular, in the section on special methods. We can think of the data model as the collection of all the behaviors we can make our user-defined data types follow. Pythonistas also use the term **protocol** instead of behavior, for example, we may say that \"the `Vector` and `Matrix` classes follow the sequence protocol.\"\n",
|
||||
"\n",
|
||||
"So, merely defining the *two* `.__len__()` and `.__getitem__()` methods is enough to make instances of any user-defined type behave like the built-in sequences in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/00_content.ipynb). Yet, there we defined sequences as all objects having the *four* properties of being finite, iterable, and ordered container types. And, these properties correspond to special methods by the names of `.__len__()`, `.__iter__()`, `.__reversed__()`, and `.__contains__()` as we see in the next section. Thus, Python \"magically\" knows how to derive the logic for the `.__iter__()`, `.__reversed__()`, and `.__contains__()` methods from the combination of the `.__len__()` and `.__getitem__()` methods. In general, while some special methods are related, others are not. Understanding these relationships means understanding the Python data model and vice versa. That is what every aspiring data scientist should aim for.\n",
|
||||
"So, merely defining the *two* `.__len__()` and `.__getitem__()` methods is enough to make instances of any user-defined type behave like the built-in sequences in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/00_content.ipynb). Yet, there we defined sequences as all objects having the *four* properties of being finite, iterable, and ordered container types. And, these properties correspond to special methods by the names of `.__len__()`, `.__iter__()`, `.__reversed__()`, and `.__contains__()` as we see in the next section. Thus, Python \"magically\" knows how to derive the logic for the `.__iter__()`, `.__reversed__()`, and `.__contains__()` methods from the combination of the `.__len__()` and `.__getitem__()` methods. In general, while some special methods are related, others are not. Understanding these relationships means understanding the Python data model and vice versa. That is what every aspiring data scientist should aim for.\n",
|
||||
"\n",
|
||||
"On the contrary, we could also look at special methods individually. Whereas `.__len__()` is invoked on the object passed to [len() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#len), Python \"translates\" the indexing operator applied on any name like `a[i]`, for example, into the method invocation `a.__getitem__(i)`. So, in both cases, the special methods are executed according to a deterministic rule of the language. In that sense, they act as some sort of syntactic sugar. Thus, they even work if only one of them is defined. For example, without `.__len__()`, iteration with a `for`-loop still works but only in forward direction."
|
||||
]
|
||||
|
|
@ -1047,7 +1047,7 @@
|
|||
"source": [
|
||||
"In the above implementations, the instance attribute `._entries` on a `Vector` or `Matrix` instance references either a `list` or a `list` of row `list`s , which is by the convention of the leading underscore `_` an implementation detail. If users of our classes adhere to this convention, `Vector` and `Matrix` instances can be regarded as *immutable*.\n",
|
||||
"\n",
|
||||
"In line with the implied immutability, we implemented the `.transpose()` method such that it returns a *new* `Matrix` instance. Instead, we could make the method change the internal `self._entries` attribute *in place* as we do in the next example. To indicate this mutation to the user of the `Matrix` class clearly, the revised `.transpose()` method returns `None`. That mirrors, for example, how the mutating methods of the built-in `list` type behave (cf., [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/01_content.ipynb#List-Methods)).\n",
|
||||
"In line with the implied immutability, we implemented the `.transpose()` method such that it returns a *new* `Matrix` instance. Instead, we could make the method change the internal `self._entries` attribute *in place* as we do in the next example. To indicate this mutation to the user of the `Matrix` class clearly, the revised `.transpose()` method returns `None`. That mirrors, for example, how the mutating methods of the built-in `list` type behave (cf., [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/01_content.ipynb#List-Methods)).\n",
|
||||
"\n",
|
||||
"Such decisions are better made consciously when designing a custom data type. The main trade-off is that immutable data types are typically easier to reason about when reading code whereas mutable data types tend to be more memory efficient and make programs faster as less copying operations take place in memory. However, this trade-off only becomes critical when we deal with big amounts of data."
|
||||
]
|
||||
|
|
@ -1200,7 +1200,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-37-21b8354a80f8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranspose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranspose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[37], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mm\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtranspose\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtranspose\u001b[49m()\n",
|
||||
"\u001b[0;31mAttributeError\u001b[0m: 'NoneType' object has no attribute 'transpose'"
|
||||
]
|
||||
}
|
||||
|
|
@ -1577,7 +1577,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"After this discussion of mutable `Vector` and `Matrix` classes, we continue with immutable implementations in the rest of this chapter. To lower the chance that we accidently design parts of our classes to be mutable, we replace the built-in [list() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-list) constructor with [tuple() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-tuple) in the `.__init__()` methods. As we learn in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/03_content.ipynb#Tuples-are-like-%22Immutable-Lists%22), `tuple`s are like immutable `list`s."
|
||||
"After this discussion of mutable `Vector` and `Matrix` classes, we continue with immutable implementations in the rest of this chapter. To lower the chance that we accidently design parts of our classes to be mutable, we replace the built-in [list() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-list) constructor with [tuple() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-tuple) in the `.__init__()` methods. As we learn in [Chapter 7 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/03_content.ipynb#Tuples-are-like-%22Immutable-Lists%22), `tuple`s are like immutable `list`s."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1599,7 +1599,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"A function is considered **polymorphic** if it can work with *different* data types. The main advantage is reuse of the function's code. Polymorphism goes hand in hand with the concept of [duck typing <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Duck_typing), first mentioned in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/00_content.ipynb#Duck-Typing) in the context of input validation.\n",
|
||||
"A function is considered **polymorphic** if it can work with *different* data types. The main advantage is reuse of the function's code. Polymorphism goes hand in hand with the concept of [duck typing <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Duck_typing), first mentioned in [Chapter 4 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/00_content.ipynb#Duck-Typing) in the context of input validation.\n",
|
||||
"\n",
|
||||
"We know polymorphic functions already: The built-in [sum() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#sum) function is a trivial example that works with all kinds of `iterable` arguments."
|
||||
]
|
||||
|
|
@ -1951,7 +1951,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/11_classes/03_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/11_classes/03_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -415,8 +415,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-14-625d8ddab141>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mas_vector\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-2-3a6f1abfe70b>\u001b[0m in \u001b[0;36mas_vector\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 22\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mas_vector\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 23\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mn_rows\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m1\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mn_cols\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 24\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mRuntimeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"one dimension (m or n) must be 1\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 25\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mVector\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mm\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mas_vector\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[2], line 24\u001b[0m, in \u001b[0;36mMatrix.as_vector\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 22\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mas_vector\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m 23\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mn_rows \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m1\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mn_cols \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m1\u001b[39m):\n\u001b[0;32m---> 24\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mone dimension (m or n) must be 1\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 25\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m Vector(x \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m)\n",
|
||||
"\u001b[0;31mRuntimeError\u001b[0m: one dimension (m or n) must be 1"
|
||||
]
|
||||
}
|
||||
|
|
@ -446,7 +446,7 @@
|
|||
"source": [
|
||||
"By implementing special methods such as `.__add__()`, `.__sub__()`, `.__mul__()`, and some others, we can make user-defined data types emulate how numeric types operate with each other (cf., [reference <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/reference/datamodel.html#emulating-numeric-types)): Then, `Vector` and `Matrix` instances can be added together, subtracted from one another, or be multiplied together. We use them to implement the arithmetic rules from linear algebra.\n",
|
||||
"\n",
|
||||
"The OOP concept behind this is **[operator overloading <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Operator_overloading)** as first mentioned in the context of `str` concatenation in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb#Operator-Overloading)."
|
||||
"The OOP concept behind this is **[operator overloading <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Operator_overloading)** as first mentioned in the context of `str` concatenation in [Chapter 1 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb#Operator-Overloading)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -599,7 +599,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"To check if `other` is a scalar, we need to specify what data type constitutes a scalar. We use a goose typing strategy as explained in [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/02_content.ipynb#Goose-Typing): Any object that behaves like a `numbers.Number` from the [numbers <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/numbers.html) module in the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html) is considered a scalar.\n",
|
||||
"To check if `other` is a scalar, we need to specify what data type constitutes a scalar. We use a goose typing strategy as explained in [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/02_content.ipynb#Goose-Typing): Any object that behaves like a `numbers.Number` from the [numbers <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/numbers.html) module in the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html) is considered a scalar.\n",
|
||||
"\n",
|
||||
"For example, the integer `1` is an instance of the built-in `int` type. At the same time, [isinstance() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#isinstance) also confirms that it is a `numbers.Number` in the abstract sense."
|
||||
]
|
||||
|
|
@ -889,8 +889,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-27-21fab2d5f12e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mv\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mw\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-21-e7b5dd8e219a>\u001b[0m in \u001b[0;36m__mul__\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 45\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;31m# dot product\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 46\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 47\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"vectors must be of the same length\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 48\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0my\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 49\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnumbers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mNumber\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;31m# scalar multiplication\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[27], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mv\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mw\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[21], line 47\u001b[0m, in \u001b[0;36mVector.__mul__\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 45\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(other, Vector): \u001b[38;5;66;03m# dot product\u001b[39;00m\n\u001b[1;32m 46\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m!=\u001b[39m \u001b[38;5;28mlen\u001b[39m(other):\n\u001b[0;32m---> 47\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvectors must be of the same length\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 48\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28msum\u001b[39m(x \u001b[38;5;241m*\u001b[39m y \u001b[38;5;28;01mfor\u001b[39;00m (x, y) \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(\u001b[38;5;28mself\u001b[39m, other))\n\u001b[1;32m 49\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(other, numbers\u001b[38;5;241m.\u001b[39mNumber): \u001b[38;5;66;03m# scalar multiplication\u001b[39;00m\n",
|
||||
"\u001b[0;31mValueError\u001b[0m: vectors must be of the same length"
|
||||
]
|
||||
}
|
||||
|
|
@ -1009,8 +1009,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-31-490ee3f2b9e8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mv\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mw\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-21-e7b5dd8e219a>\u001b[0m in \u001b[0;36m__add__\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 18\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;31m# vector addition\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 19\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 20\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"vectors must be of the same length\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 21\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mVector\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0my\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 22\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnumbers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mNumber\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;31m# broadcasting addition\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[31], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mv\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mw\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[21], line 20\u001b[0m, in \u001b[0;36mVector.__add__\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 18\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(other, Vector): \u001b[38;5;66;03m# vector addition\u001b[39;00m\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m!=\u001b[39m \u001b[38;5;28mlen\u001b[39m(other):\n\u001b[0;32m---> 20\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvectors must be of the same length\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 21\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m Vector(x \u001b[38;5;241m+\u001b[39m y \u001b[38;5;28;01mfor\u001b[39;00m (x, y) \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(\u001b[38;5;28mself\u001b[39m, other))\n\u001b[1;32m 22\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(other, numbers\u001b[38;5;241m.\u001b[39mNumber): \u001b[38;5;66;03m# broadcasting addition\u001b[39;00m\n",
|
||||
"\u001b[0;31mValueError\u001b[0m: vectors must be of the same length"
|
||||
]
|
||||
}
|
||||
|
|
@ -1098,6 +1098,7 @@
|
|||
" src=\"https://www.youtube.com/embed/OMA2Mwo0aZg\"\n",
|
||||
" frameborder=\"0\"\n",
|
||||
" allowfullscreen\n",
|
||||
" \n",
|
||||
" ></iframe>\n",
|
||||
" "
|
||||
],
|
||||
|
|
@ -1404,9 +1405,9 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-41-b57a49d097c9>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mm\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-35-def82d7b791b>\u001b[0m in \u001b[0;36m__mul__\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 72\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_matrix_multiply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mas_matrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mas_vector\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 73\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 74\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_matrix_multiply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 75\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mNotImplemented\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 76\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;32m<ipython-input-35-def82d7b791b>\u001b[0m in \u001b[0;36m_matrix_multiply\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 63\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_matrix_multiply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 64\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mn_cols\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mn_rows\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 65\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"matrices must have compatible dimensions\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 66\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mMatrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrv\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mcv\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mcv\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcols\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mrv\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrows\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 67\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[41], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mm\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mn\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[35], line 74\u001b[0m, in \u001b[0;36mMatrix.__mul__\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 72\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_matrix_multiply(other\u001b[38;5;241m.\u001b[39mas_matrix())\u001b[38;5;241m.\u001b[39mas_vector()\n\u001b[1;32m 73\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(other, Matrix):\n\u001b[0;32m---> 74\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_matrix_multiply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mother\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 75\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mNotImplemented\u001b[39m\n",
|
||||
"Cell \u001b[0;32mIn[35], line 65\u001b[0m, in \u001b[0;36mMatrix._matrix_multiply\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 63\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_matrix_multiply\u001b[39m(\u001b[38;5;28mself\u001b[39m, other):\n\u001b[1;32m 64\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mn_cols \u001b[38;5;241m!=\u001b[39m other\u001b[38;5;241m.\u001b[39mn_rows:\n\u001b[0;32m---> 65\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmatrices must have compatible dimensions\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 66\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m Matrix((rv \u001b[38;5;241m*\u001b[39m cv \u001b[38;5;28;01mfor\u001b[39;00m cv \u001b[38;5;129;01min\u001b[39;00m other\u001b[38;5;241m.\u001b[39mcols()) \u001b[38;5;28;01mfor\u001b[39;00m rv \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrows())\n",
|
||||
"\u001b[0;31mValueError\u001b[0m: matrices must have compatible dimensions"
|
||||
]
|
||||
}
|
||||
|
|
@ -1514,9 +1515,9 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-45-9faf2ee0ae54>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mv\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-35-def82d7b791b>\u001b[0m in \u001b[0;36m__rmul__\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 79\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 80\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mVector\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 81\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mas_matrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcolumn\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_matrix_multiply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mas_vector\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 82\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mNotImplemented\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 83\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;32m<ipython-input-35-def82d7b791b>\u001b[0m in \u001b[0;36m_matrix_multiply\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 63\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_matrix_multiply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 64\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mn_cols\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mn_rows\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 65\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"matrices must have compatible dimensions\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 66\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mMatrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrv\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mcv\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mcv\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcols\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mrv\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrows\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 67\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[45], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mv\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mn\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[35], line 81\u001b[0m, in \u001b[0;36mMatrix.__rmul__\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 79\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m \u001b[38;5;241m*\u001b[39m other\n\u001b[1;32m 80\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(other, Vector):\n\u001b[0;32m---> 81\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mother\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mas_matrix\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcolumn\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_matrix_multiply\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mas_vector()\n\u001b[1;32m 82\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mNotImplemented\u001b[39m\n",
|
||||
"Cell \u001b[0;32mIn[35], line 65\u001b[0m, in \u001b[0;36mMatrix._matrix_multiply\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 63\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_matrix_multiply\u001b[39m(\u001b[38;5;28mself\u001b[39m, other):\n\u001b[1;32m 64\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mn_cols \u001b[38;5;241m!=\u001b[39m other\u001b[38;5;241m.\u001b[39mn_rows:\n\u001b[0;32m---> 65\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmatrices must have compatible dimensions\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 66\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m Matrix((rv \u001b[38;5;241m*\u001b[39m cv \u001b[38;5;28;01mfor\u001b[39;00m cv \u001b[38;5;129;01min\u001b[39;00m other\u001b[38;5;241m.\u001b[39mcols()) \u001b[38;5;28;01mfor\u001b[39;00m rv \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrows())\n",
|
||||
"\u001b[0;31mValueError\u001b[0m: matrices must have compatible dimensions"
|
||||
]
|
||||
}
|
||||
|
|
@ -1611,9 +1612,9 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-48-356d02c93f11>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mm\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mv\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-21-12852bd26164>\u001b[0m in \u001b[0;36m__radd__\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 25\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 26\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__radd__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 27\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 28\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 29\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__sub__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;32m<ipython-input-35-f4e0bb37caf6>\u001b[0m in \u001b[0;36m__radd__\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 40\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__radd__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 41\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mVector\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 42\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"vectors and matrices cannot be added\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 43\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 44\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[48], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mm\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mv\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[21], line 27\u001b[0m, in \u001b[0;36mVector.__radd__\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 26\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__radd__\u001b[39m(\u001b[38;5;28mself\u001b[39m, other):\n\u001b[0;32m---> 27\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mother\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[35], line 42\u001b[0m, in \u001b[0;36mMatrix.__radd__\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 40\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__radd__\u001b[39m(\u001b[38;5;28mself\u001b[39m, other):\n\u001b[1;32m 41\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(other, Vector):\n\u001b[0;32m---> 42\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvectors and matrices cannot be added\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 43\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m \u001b[38;5;241m+\u001b[39m other\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: vectors and matrices cannot be added"
|
||||
]
|
||||
}
|
||||
|
|
@ -1714,7 +1715,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"We implement the `.__eq__()` (cf., [reference <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/reference/datamodel.html#object.__eq__)) method to control how the comparison operator `==` is carried out. For brevity, we show this only for the `Vector` class. The `.__eq__()` method exits early as soon as the first pair of entries does not match. Also, for reasons discussed in [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/01_content.ipynb#Imprecision), we compare the absolute difference of two corresponding entries to a very small `zero_threshold` that is stored as a class attribute shared among all `Vector` instances. If the `Vector`s differ in their numbers of entries, we fail loudly and raise a `ValueError`."
|
||||
"We implement the `.__eq__()` (cf., [reference <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/reference/datamodel.html#object.__eq__)) method to control how the comparison operator `==` is carried out. For brevity, we show this only for the `Vector` class. The `.__eq__()` method exits early as soon as the first pair of entries does not match. Also, for reasons discussed in [Chapter 5 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/01_content.ipynb#Imprecision), we compare the absolute difference of two corresponding entries to a very small `zero_threshold` that is stored as a class attribute shared among all `Vector` instances. If the `Vector`s differ in their numbers of entries, we fail loudly and raise a `ValueError`."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1933,7 +1934,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-59-c01df863c5f8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;34m-\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[59], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;241;43m-\u001b[39;49m\u001b[43mv\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: bad operand type for unary -: 'Vector'"
|
||||
]
|
||||
}
|
||||
|
|
@ -1969,7 +1970,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-60-09d4e6f30397>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mabs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[60], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;43mabs\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mv\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: bad operand type for abs(): 'Vector'"
|
||||
]
|
||||
}
|
||||
|
|
@ -2238,7 +2239,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Only an all `0`s `Vector` is `False` in a boolean context. As mentioned in [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/03_conditionals/00_content.ipynb#Truthy-vs.-Falsy), commonly we view an *empty* sequence as falsy; however, as we do not allow `Vector`s without any entries, we choose the all `0`s alternative. In that regard, the `Vector` class does not behave like the built-in sequence types."
|
||||
"Only an all `0`s `Vector` is `False` in a boolean context. As mentioned in [Chapter 3 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/03_conditionals/00_content.ipynb#Truthy-vs.-Falsy), commonly we view an *empty* sequence as falsy; however, as we do not allow `Vector`s without any entries, we choose the all `0`s alternative. In that regard, the `Vector` class does not behave like the built-in sequence types."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -2353,8 +2354,8 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-75-8369cec552f3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfloat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-63-67b90fc89e7c>\u001b[0m in \u001b[0;36m__float__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 29\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__float__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 30\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 31\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mRuntimeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"vector must have exactly one entry to become a scalar\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 32\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_entries\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"Cell \u001b[0;32mIn[75], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;43mfloat\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mv\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"Cell \u001b[0;32mIn[63], line 31\u001b[0m, in \u001b[0;36mVector.__float__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 29\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__float__\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m 30\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[0;32m---> 31\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvector must have exactly one entry to become a scalar\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 32\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_entries[\u001b[38;5;241m0\u001b[39m]\n",
|
||||
"\u001b[0;31mRuntimeError\u001b[0m: vector must have exactly one entry to become a scalar"
|
||||
]
|
||||
}
|
||||
|
|
@ -2380,7 +2381,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/11_classes/04_content.ipynb)."
|
||||
"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *before* reading this notebook to reset its output. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/11_classes/04_content.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -52,13 +52,13 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"In [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/02_content.ipynb#Local-Modules-and-Packages), we introduce the concept of a Python module that is imported with the `import` statement. Essentially, a **module** is a single plain text \\*.py file on disk that contains Python code (e.g., [*sample_module.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/02_functions/sample_module.py) in [Chapter 2's folder <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/tree/develop/02_functions)).\n",
|
||||
"In [Chapter 2 <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/02_content.ipynb#Local-Modules-and-Packages), we introduce the concept of a Python module that is imported with the `import` statement. Essentially, a **module** is a single plain text \\*.py file on disk that contains Python code (e.g., [*sample_module.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/02_functions/sample_module.py) in [Chapter 2's folder <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/tree/main/02_functions)).\n",
|
||||
"\n",
|
||||
"Conceptually, a **package** is a generalization of a module whose code is split across several \\*.py to achieve a better organization of the individual parts. The \\*.py files are stored within a folder (e.g., [*sample_package* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/tree/develop/11_classes/sample_package) in [Chapter 11's folder <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/tree/develop/11_classes)). In addition to that, a \"*\\_\\_init\\_\\_.py*\" file that may be empty must be put inside the folder. The latter is what the Python interpreter looks for to decide if a folder is a package or not.\n",
|
||||
"Conceptually, a **package** is a generalization of a module whose code is split across several \\*.py to achieve a better organization of the individual parts. The \\*.py files are stored within a folder (e.g., [*sample_package* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/tree/main/11_classes/sample_package) in [Chapter 11's folder <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/tree/main/11_classes)). In addition to that, a \"*\\_\\_init\\_\\_.py*\" file that may be empty must be put inside the folder. The latter is what the Python interpreter looks for to decide if a folder is a package or not.\n",
|
||||
"\n",
|
||||
"Let's look at an example with the final version of our `Vector` and `Matrix` classes.\n",
|
||||
"\n",
|
||||
"`!pwd` shows the location of this Jupyter notebook on the computer you are running [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) on: It is the local equivalent of [Chapter 11's folder <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/tree/develop/11_classes) in this book's [GitHub repository <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python)."
|
||||
"`!pwd` shows the location of this Jupyter notebook on the computer you are running [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) on: It is the local equivalent of [Chapter 11's folder <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/tree/main/11_classes) in this book's [GitHub repository <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -74,7 +74,7 @@
|
|||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"/home/webartifex/repos/intro-to-python/11_classes\n"
|
||||
"/home/alexander/Repositories/intro-to-python/11_classes\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -90,7 +90,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"`!ls` lists all the files and folders in the current location: These are Chapter 11's Jupyter notebooks (i.e., the \\*.ipynb files) and the [*sample_package* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/tree/develop/11_classes/sample_package) folder. "
|
||||
"`!ls` lists all the files and folders in the current location: These are Chapter 11's Jupyter notebooks (i.e., the \\*.ipynb files) and the [*sample_package* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/tree/main/11_classes/sample_package) folder. "
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -106,8 +106,8 @@
|
|||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"00_content.ipynb 02_content.ipynb 04_content.ipynb\n",
|
||||
"01_exercises.ipynb 03_content.ipynb sample_package\n"
|
||||
"00_content.ipynb 02_content.ipynb 04_content.ipynb\t06_review.ipynb\n",
|
||||
"01_exercises.ipynb 03_content.ipynb 05_summary.ipynb\tsample_package\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -155,11 +155,11 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"The package is organized such that the [*matrix.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/11_classes/sample_package/matrix.py) and [*vector.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/11_classes/sample_package/vector.py) modules each define just one class, `Matrix` and `Vector`. That is intentional as both classes consist of several hundred lines of code and comments.\n",
|
||||
"The package is organized such that the [*matrix.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/11_classes/sample_package/matrix.py) and [*vector.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/11_classes/sample_package/vector.py) modules each define just one class, `Matrix` and `Vector`. That is intentional as both classes consist of several hundred lines of code and comments.\n",
|
||||
"\n",
|
||||
"The [*utils.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/11_classes/sample_package/utils.py) module contains code that is shared by both classes. Such code snippets are commonly called \"utilities\" or \"helpers,\" which explains the module's name.\n",
|
||||
"The [*utils.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/11_classes/sample_package/utils.py) module contains code that is shared by both classes. Such code snippets are commonly called \"utilities\" or \"helpers,\" which explains the module's name.\n",
|
||||
"\n",
|
||||
"Finally, the [*\\_\\_init\\_\\_.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/11_classes/sample_package/__init__.py) file contains mostly meta information and defines what objects should be importable from the package's top level.\n",
|
||||
"Finally, the [*\\_\\_init\\_\\_.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/11_classes/sample_package/__init__.py) file contains mostly meta information and defines what objects should be importable from the package's top level.\n",
|
||||
"\n",
|
||||
"With the `import` statement, we can import the entire package just as we would import a module from the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html)."
|
||||
]
|
||||
|
|
@ -185,7 +185,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"The above cell runs the code in the [*\\_\\_init\\_\\_.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/11_classes/sample_package/__init__.py) file from top to bottom, which in turn runs the [*matrix.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/11_classes/sample_package/matrix.py), [*utils.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/11_classes/sample_package/utils.py), and [*vector.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/11_classes/sample_package/vector.py) modules (cf., look at the `import` statements in the four \\*.py files to get the idea). As both [*matrix.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/11_classes/sample_package/matrix.py) and [*vector.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/11_classes/sample_package/vector.py) depend on each other (i.e., the `Matrix` class needs the `Vector` class to work and vice versa), understanding the order in that the modules are executed is not trivial. Without going into detail, we mention that Python guarantees that each \\*.py file is run only once and figures out the order on its own. If Python is unable to do that, for example, due to unresolvable cirular imports, it aborts with an `ImportError`.\n",
|
||||
"The above cell runs the code in the [*\\_\\_init\\_\\_.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/11_classes/sample_package/__init__.py) file from top to bottom, which in turn runs the [*matrix.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/11_classes/sample_package/matrix.py), [*utils.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/11_classes/sample_package/utils.py), and [*vector.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/11_classes/sample_package/vector.py) modules (cf., look at the `import` statements in the four \\*.py files to get the idea). As both [*matrix.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/11_classes/sample_package/matrix.py) and [*vector.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/11_classes/sample_package/vector.py) depend on each other (i.e., the `Matrix` class needs the `Vector` class to work and vice versa), understanding the order in that the modules are executed is not trivial. Without going into detail, we mention that Python guarantees that each \\*.py file is run only once and figures out the order on its own. If Python is unable to do that, for example, due to unresolvable cirular imports, it aborts with an `ImportError`.\n",
|
||||
"\n",
|
||||
"Below, `pkg` is an object of type `module` ..."
|
||||
]
|
||||
|
|
@ -202,7 +202,7 @@
|
|||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"<module 'sample_package' from '/home/webartifex/repos/intro-to-python/11_classes/sample_package/__init__.py'>"
|
||||
"<module 'sample_package' from '/home/alexander/Repositories/intro-to-python/11_classes/sample_package/__init__.py'>"
|
||||
]
|
||||
},
|
||||
"execution_count": 5,
|
||||
|
|
@ -297,7 +297,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"The package's meta information and documentation are automatically parsed from the [*\\_\\_init\\_\\_.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/11_classes/sample_package/__init__.py) file."
|
||||
"The package's meta information and documentation are automatically parsed from the [*\\_\\_init\\_\\_.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/11_classes/sample_package/__init__.py) file."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -324,9 +324,9 @@
|
|||
" - vector: defines the Vector class\n",
|
||||
" - utils: defines the norm() function that is shared by Matrix and Vector\n",
|
||||
" and package-wide constants\n",
|
||||
" \n",
|
||||
"\n",
|
||||
" The classes implement arithmetic operations involving vectors and matrices.\n",
|
||||
" \n",
|
||||
"\n",
|
||||
" See the docstrings in the modules and classes for further info.\n",
|
||||
"\n",
|
||||
"PACKAGE CONTENTS\n",
|
||||
|
|
@ -338,14 +338,14 @@
|
|||
" builtins.object\n",
|
||||
" sample_package.matrix.Matrix\n",
|
||||
" sample_package.vector.Vector\n",
|
||||
" \n",
|
||||
"\n",
|
||||
" class Matrix(builtins.object)\n",
|
||||
" | Matrix(data)\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | An m-by-n-dimensional matrix from linear algebra.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | All entries are converted to floats, or whatever is set in the typing attribute.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Attributes:\n",
|
||||
" | storage (callable): data type used to store the entries internally;\n",
|
||||
" | defaults to tuple\n",
|
||||
|
|
@ -354,63 +354,63 @@
|
|||
" | vector_cls (vector.Vector): a reference to the Vector class to work with\n",
|
||||
" | zero_threshold (float): max. tolerance when comparing an entry to zero;\n",
|
||||
" | defaults to 1e-12\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Methods defined here:\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __abs__(self)\n",
|
||||
" | The Frobenius norm of a Matrix.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __add__(self, other)\n",
|
||||
" | Handle `self + other` and `other + self`.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | This may be either matrix addition or broadcasting addition.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Example Usage:\n",
|
||||
" | >>> Matrix([(1, 2), (3, 4)]) + Matrix([(2, 3), (4, 5)])\n",
|
||||
" | Matrix(((3.0, 5.0,), (7.0, 9.0,)))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> Matrix([(1, 2), (3, 4)]) + 5\n",
|
||||
" | Matrix(((6.0, 7.0,), (8.0, 9.0,)))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> 10 + Matrix([(1, 2), (3, 4)])\n",
|
||||
" | Matrix(((11.0, 12.0,), (13.0, 14.0,)))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __bool__(self)\n",
|
||||
" | A Matrix is truthy if its Frobenius norm is strictly positive.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __eq__(self, other)\n",
|
||||
" | Handle `self == other`.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Compare two Matrix instances for equality.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Example Usage:\n",
|
||||
" | >>> Matrix([(1, 2), (3, 4)]) == Matrix([(1, 2), (3, 4)])\n",
|
||||
" | True\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> Matrix([(1, 2), (3, 4)]) == Matrix([(5, 6), (7, 8)])\n",
|
||||
" | False\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __float__(self)\n",
|
||||
" | Cast a Matrix as a scalar.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Returns:\n",
|
||||
" | scalar (float)\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Raises:\n",
|
||||
" | RuntimeError: if the Matrix has more than one entry\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __getitem__(self, index)\n",
|
||||
" | Obtain an individual entry of a Matrix.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Args:\n",
|
||||
" | index (int / tuple of int's): if index is an integer,\n",
|
||||
" | the Matrix is viewed as a sequence in row-major order;\n",
|
||||
" | if index is a tuple of integers, the first one refers to\n",
|
||||
" | the row and the second one to the column of the entry\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Returns:\n",
|
||||
" | entry (Matrix.typing)\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Example Usage:\n",
|
||||
" | >>> m = Matrix([(1, 2), (3, 4)])\n",
|
||||
" | >>> m[0]\n",
|
||||
|
|
@ -419,226 +419,228 @@
|
|||
" | 4.0\n",
|
||||
" | >>> m[0, 1]\n",
|
||||
" | 2.0\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __init__(self, data)\n",
|
||||
" | Create a new matrix.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Args:\n",
|
||||
" | data (sequence of sequences): the matrix's entries;\n",
|
||||
" | viewed as a sequence of the matrix's rows (i.e., row-major order);\n",
|
||||
" | use the .from_columns() class method if the data come as a sequence\n",
|
||||
" | of the matrix's columns (i.e., column-major order)\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Raises:\n",
|
||||
" | ValueError:\n",
|
||||
" | - if no entries are provided\n",
|
||||
" | - if the number of columns is inconsistent across the rows\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Example Usage:\n",
|
||||
" | >>> Matrix([(1, 2), (3, 4)])\n",
|
||||
" | Matrix(((1.0, 2.0,), (3.0, 4.0,)))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __iter__(self)\n",
|
||||
" | Loop over a Matrix's entries.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | See .entries() for more customization options.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __len__(self)\n",
|
||||
" | Number of entries in a Matrix.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __mul__(self, other)\n",
|
||||
" | Handle `self * other` and `other * self`.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | This may be either scalar multiplication, matrix-vector multiplication,\n",
|
||||
" | vector-matrix multiplication, or matrix-matrix multiplication.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Example Usage:\n",
|
||||
" | >>> Matrix([(1, 2), (3, 4)]) * Matrix([(1, 2), (3, 4)])\n",
|
||||
" | Matrix(((7.0, 10.0,), (15.0, 22.0,)))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> 2 * Matrix([(1, 2), (3, 4)])\n",
|
||||
" | Matrix(((2.0, 4.0,), (6.0, 8.0,)))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> Matrix([(1, 2), (3, 4)]) * 3\n",
|
||||
" | Matrix(((3.0, 6.0,), (9.0, 12.0,)))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Matrix-vector and vector-matrix multiplication are not commutative.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> from sample_package import Vector\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> Matrix([(1, 2), (3, 4)]) * Vector([5, 6])\n",
|
||||
" | Vector((17.0, 39.0))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> Vector([5, 6]) * Matrix([(1, 2), (3, 4)])\n",
|
||||
" | Vector((23.0, 34.0))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __neg__(self)\n",
|
||||
" | Handle `-self`.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Negate all entries of a Matrix.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __pos__(self)\n",
|
||||
" | Handle `+self`.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | This is simply an identity operator returning the Matrix itself.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __radd__(self, other)\n",
|
||||
" | See docstring for .__add__().\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __repr__(self)\n",
|
||||
" | Text representation of a Matrix.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __reversed__(self)\n",
|
||||
" | Loop over a Matrix's entries in reverse order.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | See .entries() for more customization options.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __rmul__(self, other)\n",
|
||||
" | See docstring for .__mul__().\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __rsub__(self, other)\n",
|
||||
" | See docstring for .__sub__().\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __str__(self)\n",
|
||||
" | Human-readable text representation of a Matrix.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __sub__(self, other)\n",
|
||||
" | Handle `self - other` and `other - self`.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | This may be either matrix subtraction or broadcasting subtraction.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Example Usage:\n",
|
||||
" | >>> Matrix([(2, 3), (4, 5)]) - Matrix([(1, 2), (3, 4)])\n",
|
||||
" | Matrix(((1.0, 1.0,), (1.0, 1.0,)))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> Matrix([(1, 2), (3, 4)]) - 1\n",
|
||||
" | Matrix(((0.0, 1.0,), (2.0, 3.0,)))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> 10 - Matrix([(1, 2), (3, 4)])\n",
|
||||
" | Matrix(((9.0, 8.0,), (7.0, 6.0,)))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __truediv__(self, other)\n",
|
||||
" | Handle `self / other`.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Divide a Matrix by a scalar.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Example Usage:\n",
|
||||
" | >>> Matrix([(1, 2), (3, 4)]) / 4\n",
|
||||
" | Matrix(((0.25, 0.5,), (0.75, 1.0,)))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | as_vector(self)\n",
|
||||
" | Get a Vector representation of a Matrix.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Returns:\n",
|
||||
" | vector (vector.Vector)\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Raises:\n",
|
||||
" | RuntimeError: if one of the two dimensions, .n_rows or .n_cols, is not 1\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Example Usage:\n",
|
||||
" | >>> Matrix([(1, 2, 3)]).as_vector()\n",
|
||||
" | Vector((1.0, 2.0, 3.0))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | cols(self)\n",
|
||||
" | Loop over a Matrix's columns.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Returns:\n",
|
||||
" | columns (generator): produces a Matrix's columns as Vectors\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | entries(self, *, reverse=False, row_major=True)\n",
|
||||
" | Loop over a Matrix's entries.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Args:\n",
|
||||
" | reverse (bool): flag to loop backwards; defaults to False\n",
|
||||
" | row_major (bool): flag to loop in row-major order; defaults to True\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Returns:\n",
|
||||
" | entries (generator): produces a Matrix's entries\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | rows(self)\n",
|
||||
" | Loop over a Matrix's rows.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Returns:\n",
|
||||
" | rows (generator): produces a Matrix's rows as Vectors\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | transpose(self)\n",
|
||||
" | Switch the rows and columns of a Matrix.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Returns:\n",
|
||||
" | matrix (Matrix)\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Example Usage:\n",
|
||||
" | >>> m = Matrix([(1, 2), (3, 4)])\n",
|
||||
" | >>> m\n",
|
||||
" | Matrix(((1.0, 2.0,), (3.0, 4.0,)))\n",
|
||||
" | >>> m.transpose()\n",
|
||||
" | Matrix(((1.0, 3.0,), (2.0, 4.0,)))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | ----------------------------------------------------------------------\n",
|
||||
" | Class methods defined here:\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | from_columns(data) from builtins.type\n",
|
||||
" | Create a new matrix.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | This is an alternative constructor for data provided in column-major order.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Args:\n",
|
||||
" | data (sequence of sequences): the matrix's entries;\n",
|
||||
" | viewed as a sequence of the matrix's columns (i.e., column-major order);\n",
|
||||
" | use the normal constructor method if the data come as a sequence\n",
|
||||
" | of the matrix's rows (i.e., row-major order)\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Raises:\n",
|
||||
" | ValueError:\n",
|
||||
" | - if no entries are provided\n",
|
||||
" | - if the number of rows is inconsistent across the columns\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Example Usage:\n",
|
||||
" | >>> Matrix.from_columns([(1, 2), (3, 4)])\n",
|
||||
" | Matrix(((1.0, 3.0,), (2.0, 4.0,)))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | from_rows(data) from builtins.type\n",
|
||||
" | See docstring for .__init__().\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | ----------------------------------------------------------------------\n",
|
||||
" | Readonly properties defined here:\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | n_cols\n",
|
||||
" | Number of columns in a Matrix.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | n_rows\n",
|
||||
" | Number of rows in a Matrix.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | ----------------------------------------------------------------------\n",
|
||||
" | Data descriptors defined here:\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __dict__\n",
|
||||
" | dictionary for instance variables (if defined)\n",
|
||||
" | \n",
|
||||
" | dictionary for instance variables\n",
|
||||
" |\n",
|
||||
" | __weakref__\n",
|
||||
" | list of weak references to the object (if defined)\n",
|
||||
" | \n",
|
||||
" | list of weak references to the object\n",
|
||||
" |\n",
|
||||
" | ----------------------------------------------------------------------\n",
|
||||
" | Data and other attributes defined here:\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __hash__ = None\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | storage = <class 'tuple'>\n",
|
||||
" | Built-in immutable sequence.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | If no argument is given, the constructor returns an empty tuple.\n",
|
||||
" | If iterable is specified the tuple is initialized from iterable's items.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | If the argument is a tuple, the return value is the same object.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" |\n",
|
||||
" | typing = <class 'float'>\n",
|
||||
" | Convert a string or number to a floating point number, if possible.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" |\n",
|
||||
" | vector_cls = <class 'sample_package.vector.Vector'>\n",
|
||||
" | A one-dimensional vector from linear algebra.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | All entries are converted to floats, or whatever is set in the typing attribute.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Attributes:\n",
|
||||
" | matrix_cls (matrix.Matrix): a reference to the Matrix class to work with\n",
|
||||
" | storage (callable): data type used to store the entries internally;\n",
|
||||
|
|
@ -647,16 +649,17 @@
|
|||
" | defaults to float\n",
|
||||
" | zero_threshold (float): max. tolerance when comparing an entry to zero;\n",
|
||||
" | defaults to 1e-12\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" |\n",
|
||||
" | zero_threshold = 1e-12\n",
|
||||
" \n",
|
||||
"\n",
|
||||
" class Vector(builtins.object)\n",
|
||||
" | Vector(data)\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | A one-dimensional vector from linear algebra.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | All entries are converted to floats, or whatever is set in the typing attribute.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Attributes:\n",
|
||||
" | matrix_cls (matrix.Matrix): a reference to the Matrix class to work with\n",
|
||||
" | storage (callable): data type used to store the entries internally;\n",
|
||||
|
|
@ -665,179 +668,179 @@
|
|||
" | defaults to float\n",
|
||||
" | zero_threshold (float): max. tolerance when comparing an entry to zero;\n",
|
||||
" | defaults to 1e-12\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Methods defined here:\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __abs__(self)\n",
|
||||
" | The Euclidean norm of a vector.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __add__(self, other)\n",
|
||||
" | Handle `self + other` and `other + self`.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | This may be either vector addition or broadcasting addition.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Example Usage:\n",
|
||||
" | >>> Vector([1, 2, 3]) + Vector([2, 3, 4])\n",
|
||||
" | Vector((3.0, 5.0, 7.0))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> Vector([1, 2, 3]) + 4\n",
|
||||
" | Vector((5.0, 6.0, 7.0))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> 10 + Vector([1, 2, 3])\n",
|
||||
" | Vector((11.0, 12.0, 13.0))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __bool__(self)\n",
|
||||
" | A Vector is truthy if its Euclidean norm is strictly positive.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __eq__(self, other)\n",
|
||||
" | Handle `self == other`.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Compare two Vectors for equality.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Example Usage:\n",
|
||||
" | >>> Vector([1, 2, 3]) == Vector([1, 2, 3])\n",
|
||||
" | True\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> Vector([1, 2, 3]) == Vector([4, 5, 6])\n",
|
||||
" | False\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __float__(self)\n",
|
||||
" | Cast a Vector as a scalar.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Returns:\n",
|
||||
" | scalar (float)\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Raises:\n",
|
||||
" | RuntimeError: if the Vector has more than one entry\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __getitem__(self, index)\n",
|
||||
" | Obtain an individual entry of a Vector.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __init__(self, data)\n",
|
||||
" | Create a new vector.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Args:\n",
|
||||
" | data (sequence): the vector's entries\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Raises:\n",
|
||||
" | ValueError: if no entries are provided\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Example Usage:\n",
|
||||
" | >>> Vector([1, 2, 3])\n",
|
||||
" | Vector((1.0, 2.0, 3.0))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> Vector(range(3))\n",
|
||||
" | Vector((0.0, 1.0, 2.0))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __iter__(self)\n",
|
||||
" | Loop over a Vector's entries.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __len__(self)\n",
|
||||
" | Number of entries in a Vector.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __mul__(self, other)\n",
|
||||
" | Handle `self * other` and `other * self`.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | This may be either the dot product of two vectors or scalar multiplication.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Example Usage:\n",
|
||||
" | >>> Vector([1, 2, 3]) * Vector([2, 3, 4])\n",
|
||||
" | 20.0\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> 2 * Vector([1, 2, 3])\n",
|
||||
" | Vector((2.0, 4.0, 6.0))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> Vector([1, 2, 3]) * 3\n",
|
||||
" | Vector((3.0, 6.0, 9.0))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __neg__(self)\n",
|
||||
" | Handle `-self`.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Negate all entries of a Vector.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __pos__(self)\n",
|
||||
" | Handle `+self`.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | This is simply an identity operator returning the Vector itself.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __radd__(self, other)\n",
|
||||
" | See docstring for .__add__().\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __repr__(self)\n",
|
||||
" | Text representation of a Vector.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __reversed__(self)\n",
|
||||
" | Loop over a Vector's entries in reverse order.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __rmul__(self, other)\n",
|
||||
" | See docstring for .__mul__().\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __rsub__(self, other)\n",
|
||||
" | See docstring for .__sub__().\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __str__(self)\n",
|
||||
" | Human-readable text representation of a Vector.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __sub__(self, other)\n",
|
||||
" | Handle `self - other` and `other - self`.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | This may be either vector subtraction or broadcasting subtraction.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Example Usage:\n",
|
||||
" | >>> Vector([7, 8, 9]) - Vector([1, 2, 3])\n",
|
||||
" | Vector((6.0, 6.0, 6.0))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> Vector([1, 2, 3]) - 1\n",
|
||||
" | Vector((0.0, 1.0, 2.0))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | >>> 10 - Vector([1, 2, 3])\n",
|
||||
" | Vector((9.0, 8.0, 7.0))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __truediv__(self, other)\n",
|
||||
" | Handle `self / other`.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Divide a Vector by a scalar.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Example Usage:\n",
|
||||
" | >>> Vector([9, 6, 12]) / 3\n",
|
||||
" | Vector((3.0, 2.0, 4.0))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | as_matrix(self, *, column=True)\n",
|
||||
" | Get a Matrix representation of a Vector.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Args:\n",
|
||||
" | column (bool): if the vector is interpreted as a\n",
|
||||
" | column vector or a row vector; defaults to True\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Returns:\n",
|
||||
" | matrix (matrix.Matrix)\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Example Usage:\n",
|
||||
" | >>> v = Vector([1, 2, 3])\n",
|
||||
" | >>> v.as_matrix()\n",
|
||||
" | Matrix(((1.0,), (2.0,), (3.0,)))\n",
|
||||
" | >>> v.as_matrix(column=False)\n",
|
||||
" | Matrix(((1.0, 2.0, 3.0,)))\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | ----------------------------------------------------------------------\n",
|
||||
" | Data descriptors defined here:\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __dict__\n",
|
||||
" | dictionary for instance variables (if defined)\n",
|
||||
" | \n",
|
||||
" | dictionary for instance variables\n",
|
||||
" |\n",
|
||||
" | __weakref__\n",
|
||||
" | list of weak references to the object (if defined)\n",
|
||||
" | \n",
|
||||
" | list of weak references to the object\n",
|
||||
" |\n",
|
||||
" | ----------------------------------------------------------------------\n",
|
||||
" | Data and other attributes defined here:\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | __hash__ = None\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | matrix_cls = <class 'sample_package.matrix.Matrix'>\n",
|
||||
" | An m-by-n-dimensional matrix from linear algebra.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | All entries are converted to floats, or whatever is set in the typing attribute.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | Attributes:\n",
|
||||
" | storage (callable): data type used to store the entries internally;\n",
|
||||
" | defaults to tuple\n",
|
||||
|
|
@ -846,18 +849,21 @@
|
|||
" | vector_cls (vector.Vector): a reference to the Vector class to work with\n",
|
||||
" | zero_threshold (float): max. tolerance when comparing an entry to zero;\n",
|
||||
" | defaults to 1e-12\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" |\n",
|
||||
" | storage = <class 'tuple'>\n",
|
||||
" | Built-in immutable sequence.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | If no argument is given, the constructor returns an empty tuple.\n",
|
||||
" | If iterable is specified the tuple is initialized from iterable's items.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" | If the argument is a tuple, the return value is the same object.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" |\n",
|
||||
" | typing = <class 'float'>\n",
|
||||
" | Convert a string or number to a floating point number, if possible.\n",
|
||||
" | \n",
|
||||
" |\n",
|
||||
" |\n",
|
||||
" | zero_threshold = 1e-12\n",
|
||||
"\n",
|
||||
"DATA\n",
|
||||
|
|
@ -870,7 +876,7 @@
|
|||
" Alexander Hess\n",
|
||||
"\n",
|
||||
"FILE\n",
|
||||
" /home/webartifex/repos/intro-to-python/11_classes/sample_package/__init__.py\n",
|
||||
" /home/alexander/Repositories/intro-to-python/11_classes/sample_package/__init__.py\n",
|
||||
"\n",
|
||||
"\n"
|
||||
]
|
||||
|
|
@ -1006,7 +1012,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"A common practice by package authors is to put all the objects on the package's top level that they want the package users to work with directly. That is achieved via the `import` statements in the [*\\_\\_init\\_\\_.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/11_classes/sample_package/__init__.py) file.\n",
|
||||
"A common practice by package authors is to put all the objects on the package's top level that they want the package users to work with directly. That is achieved via the `import` statements in the [*\\_\\_init\\_\\_.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/11_classes/sample_package/__init__.py) file.\n",
|
||||
"\n",
|
||||
"However, users can always reach into a package and work with its internals.\n",
|
||||
"\n",
|
||||
|
|
@ -1069,7 +1075,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Also, let's import the [*utils.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/11_classes/sample_package/utils.py) module with the `norm()` function into the global scope. As this function is integrated into the `Vector.__abs__()` and `Matrix.__abs__()` methods, there is actually no need to work with it explicitly."
|
||||
"Also, let's import the [*utils.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/11_classes/sample_package/utils.py) module with the `norm()` function into the global scope. As this function is integrated into the `Vector.__abs__()` and `Matrix.__abs__()` methods, there is actually no need to work with it explicitly."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1102,15 +1108,15 @@
|
|||
"\n",
|
||||
"norm(vec_or_mat)\n",
|
||||
" Calculate the Frobenius or Euclidean norm of a matrix or vector.\n",
|
||||
" \n",
|
||||
"\n",
|
||||
" Find more infos here: https://en.wikipedia.org/wiki/Matrix_norm#Frobenius_norm\n",
|
||||
" \n",
|
||||
"\n",
|
||||
" Args:\n",
|
||||
" vec_or_mat (Vector / Matrix): object whose entries are squared and summed up\n",
|
||||
" \n",
|
||||
"\n",
|
||||
" Returns:\n",
|
||||
" norm (float)\n",
|
||||
" \n",
|
||||
"\n",
|
||||
" Example Usage:\n",
|
||||
" As Vector and Matrix objects are by design non-empty sequences,\n",
|
||||
" norm() may be called, for example, with `[3, 4]` as the argument:\n",
|
||||
|
|
@ -1134,7 +1140,7 @@
|
|||
"source": [
|
||||
"Many tutorials on the internet begin by importing \"everything\" from a package into the global scope with `from ... import *`.\n",
|
||||
"\n",
|
||||
"That is commonly considered a *bad* practice as it may overwrite already existing variables. However, if the package's [*\\_\\_init\\_\\_.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/11_classes/sample_package/__init__.py) file defines an `__all__` attribute, a `list` with all the names to be \"exported,\" the **star import** is safe to be used, in particular, in *interactive* sessions like Jupyter notebooks. We emphasize that the star import should *not* be used *within* packages and modules as then it is not directly evident from a name where the corresponding object is defined.\n",
|
||||
"That is commonly considered a *bad* practice as it may overwrite already existing variables. However, if the package's [*\\_\\_init\\_\\_.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/11_classes/sample_package/__init__.py) file defines an `__all__` attribute, a `list` with all the names to be \"exported,\" the **star import** is safe to be used, in particular, in *interactive* sessions like Jupyter notebooks. We emphasize that the star import should *not* be used *within* packages and modules as then it is not directly evident from a name where the corresponding object is defined.\n",
|
||||
"\n",
|
||||
"For more best practices regarding importing we refer to, among others, [Google's Python Style Guide](https://google.github.io/styleguide/pyguide.html#22-imports).\n",
|
||||
"\n",
|
||||
|
|
@ -1232,9 +1238,9 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"The final implementations of the `Vector` and `Matrix` classes are in the [*matrix.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/11_classes/sample_package/matrix.py) and [*vector.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/11_classes/sample_package/vector.py) files: They integrate all of the functionalities introduced in this chapter. In addition, the code is cleaned up and fully documented, including examples of common usages.\n",
|
||||
"The final implementations of the `Vector` and `Matrix` classes are in the [*matrix.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/11_classes/sample_package/matrix.py) and [*vector.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/11_classes/sample_package/vector.py) files: They integrate all of the functionalities introduced in this chapter. In addition, the code is cleaned up and fully documented, including examples of common usages.\n",
|
||||
"\n",
|
||||
"We strongly suggest the eager student go over the files in the [*sample_package* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/tree/develop/11_classes/sample_package) in detail at some point to understand what well-written and (re-)usable code looks like."
|
||||
"We strongly suggest the eager student go over the files in the [*sample_package* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/tree/main/11_classes/sample_package) in detail at some point to understand what well-written and (re-)usable code looks like."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1453,8 +1459,8 @@
|
|||
"\u001b[0;34m\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_entries\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstorage\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtyping\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n",
|
||||
"\u001b[0;34m\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\n",
|
||||
"\u001b[0;34m\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"a vector must have at least one entry\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;31mFile:\u001b[0m ~/repos/intro-to-python/11_classes/sample_package/vector.py\n",
|
||||
"\u001b[0;31mType:\u001b[0m function\n"
|
||||
"\u001b[0;31mFile:\u001b[0m ~/Repositories/intro-to-python/11_classes/sample_package/vector.py\n",
|
||||
"\u001b[0;31mType:\u001b[0m function"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
|
|
@ -1473,7 +1479,7 @@
|
|||
}
|
||||
},
|
||||
"source": [
|
||||
"Both `Matrix/Vector.storage` and `Matrix/Vector.typing` themselves reference the `DEFAULT_ENTRIES_STORAGE` and `DEFAULT_ENTRY_TYPE` constants in the [*utils.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/develop/11_classes/sample_package/utils.py) module. This way, we could, for example, change only the constants and thereby also change how the `._entries` are stored internally in both classes. Also, this single **[single source of truth <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Single_source_of_truth)** ensures that both classes are consistent with each other at all times."
|
||||
"Both `Matrix/Vector.storage` and `Matrix/Vector.typing` themselves reference the `DEFAULT_ENTRIES_STORAGE` and `DEFAULT_ENTRY_TYPE` constants in the [*utils.py* <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com/webartifex/intro-to-python/blob/main/11_classes/sample_package/utils.py) module. This way, we could, for example, change only the constants and thereby also change how the `._entries` are stored internally in both classes. Also, this single **[single source of truth <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Single_source_of_truth)** ensures that both classes are consistent with each other at all times."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1635,8 +1641,8 @@
|
|||
"\u001b[0;34m Matrix(((1.0, 3.0,), (2.0, 4.0,)))\u001b[0m\n",
|
||||
"\u001b[0;34m \"\"\"\u001b[0m\u001b[0;34m\u001b[0m\n",
|
||||
"\u001b[0;34m\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_entries\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;31mFile:\u001b[0m ~/repos/intro-to-python/11_classes/sample_package/matrix.py\n",
|
||||
"\u001b[0;31mType:\u001b[0m function\n"
|
||||
"\u001b[0;31mFile:\u001b[0m ~/Repositories/intro-to-python/11_classes/sample_package/matrix.py\n",
|
||||
"\u001b[0;31mType:\u001b[0m function"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
|
|
@ -1748,9 +1754,9 @@
|
|||
"\u001b[0;34m\u001b[0m \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\", \"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n",
|
||||
"\u001b[0;34m\u001b[0m \u001b[0;34m\"(\"\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m\", \"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrepr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mc\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m\",)\"\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mr\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_entries\u001b[0m\u001b[0;34m\u001b[0m\n",
|
||||
"\u001b[0;34m\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n",
|
||||
"\u001b[0;34m\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;34mf\"{name}(({args}))\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;31mFile:\u001b[0m ~/repos/intro-to-python/11_classes/sample_package/matrix.py\n",
|
||||
"\u001b[0;31mType:\u001b[0m function\n"
|
||||
"\u001b[0;34m\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;34mf\"\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m((\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m))\u001b[0m\u001b[0;34m\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;31mFile:\u001b[0m ~/Repositories/intro-to-python/11_classes/sample_package/matrix.py\n",
|
||||
"\u001b[0;31mType:\u001b[0m function"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
|
|
@ -1865,8 +1871,8 @@
|
|||
"\u001b[0;34m\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mcolumn\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\n",
|
||||
"\u001b[0;34m\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmatrix_cls\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n",
|
||||
"\u001b[0;34m\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmatrix_cls\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;31mFile:\u001b[0m ~/repos/intro-to-python/11_classes/sample_package/vector.py\n",
|
||||
"\u001b[0;31mType:\u001b[0m function\n"
|
||||
"\u001b[0;31mFile:\u001b[0m ~/Repositories/intro-to-python/11_classes/sample_package/vector.py\n",
|
||||
"\u001b[0;31mType:\u001b[0m function"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
|
|
@ -2122,7 +2128,7 @@
|
|||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Vector(11378937.3105893, ..., 13593029.305789862)[100]\n"
|
||||
"Vector(11378937.310589302, ..., 13593029.305789862)[100]\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -2167,7 +2173,7 @@
|
|||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Matrix((14370711.265265431, ...), ..., (..., 16545418.239505699))[100x100]\n"
|
||||
"Matrix((14370711.26526542, ...), ..., (..., 16545418.239505697))[100x100]\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -2201,7 +2207,7 @@
|
|||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Matrix((32618511.50703142, ...), ..., (..., 32339164.77803234))[50x50]\n"
|
||||
"Matrix((32618511.507031415, ...), ..., (..., 32339164.778032355))[50x50]\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -2232,7 +2238,7 @@
|
|||
"\n",
|
||||
"If we feel like sharing our linear algebra library with the world, we could easily do so on either [GitHub <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_gh.png\">](https://github.com) or [PyPI](https://pypi.org). However, for the domain of linear algebra this would be rather pointless as there is already a widely adopted library with [numpy](https://www.numpy.org/) that not only has a lot more features than ours but also is implemented in C, which makes it a lot faster with big data.\n",
|
||||
"\n",
|
||||
"Let's model the example in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/00_content.ipynb#Example:-Vectors-&-Matrices) with both [numpy](https://www.numpy.org/) and our own DSL and compare them."
|
||||
"Let's model the example in the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/00_content.ipynb#Example:-Vectors-&-Matrices) with both [numpy](https://www.numpy.org/) and our own DSL and compare them."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -2265,7 +2271,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-55-fd81d962f516>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mA\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[55], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mA\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mx\u001b[49m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: can't multiply sequence by non-int of type 'tuple'"
|
||||
]
|
||||
}
|
||||
|
|
@ -2916,7 +2922,7 @@
|
|||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-79-032c970f8cfc>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mA_arr\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mA_mat\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"Cell \u001b[0;32mIn[79], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mA_arr\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mA_mat\u001b[49m\n",
|
||||
"\u001b[0;31mValueError\u001b[0m: operands could not be broadcast together with shapes (3,3) (9,) "
|
||||
]
|
||||
}
|
||||
|
|
@ -2953,7 +2959,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -68,7 +68,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"livereveal": {
|
||||
"auto_select": "code",
|
||||
|
|
|
|||
|
|
@ -11,7 +11,7 @@
|
|||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/00_content.ipynb), [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/02_content.ipynb), [third <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/03_content.ipynb), and [fourth <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/04_content.ipynb) part of Chapter 11.\n",
|
||||
"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/00_content.ipynb), [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/02_content.ipynb), [third <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/03_content.ipynb), and [fourth <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/04_content.ipynb) part of Chapter 11.\n",
|
||||
"\n",
|
||||
"Be concise in your answers! Most questions can be answered in *one* sentence."
|
||||
]
|
||||
|
|
@ -250,7 +250,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.6"
|
||||
"version": "3.12.2"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
|
|
|
|||
251
CONTENTS.md
251
CONTENTS.md
|
|
@ -24,270 +24,271 @@ It is recommended
|
|||
|
||||
If this is not possible,
|
||||
the files can be viewed in a web browser
|
||||
either statically (i.e., read-only) on [nbviewer <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/tree/develop/)
|
||||
or interactively (i.e., code can be executed) on [Binder <img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab).
|
||||
either statically (i.e., read-only) on [nbviewer <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/tree/main/)
|
||||
or interactively (i.e., code can be executed) on [Binder <img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab).
|
||||
|
||||
- *Chapter 0*: Introduction
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/00_intro/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/00_intro/00_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/00_intro/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/00_intro/00_content.ipynb)
|
||||
(Python's History & Background;
|
||||
Open-source & Communities;
|
||||
JupyterLab;
|
||||
Programming vs. Computer Science;
|
||||
Learning Tips)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/00_intro/01_exercises.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/00_intro/01_exercises.ipynb)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/00_intro/01_exercises_markdown.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/00_intro/01_exercises_markdown.ipynb)
|
||||
(Mastering Markdown)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/00_intro/02_review.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/00_intro/02_review.ipynb)
|
||||
- **Part A: Expressing Logic**
|
||||
- *Chapter 1*: Elements of a Program
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/01_elements/00_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/01_elements/00_content.ipynb)
|
||||
(A first Example: Averaging Even Numbers;
|
||||
Operators;
|
||||
Objects & Data Types;
|
||||
Errors)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/01_exercises.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/01_elements/01_exercises.ipynb)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/01_exercises_print.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/01_elements/01_exercises_print.ipynb)
|
||||
(Printing Output)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/02_exercises.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/01_elements/02_exercises.ipynb)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/02_exercises_for-loops.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/01_elements/02_exercises_for-loops.ipynb)
|
||||
(Simple `for`-loops)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/03_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/01_elements/03_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/03_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/01_elements/03_content.ipynb)
|
||||
(Memory in Detail;
|
||||
Variables & References;
|
||||
Mutability;
|
||||
Expressions & Statements)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/04_exercises.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/01_elements/04_exercises.ipynb)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/04_exercises_calculator.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/01_elements/04_exercises_calculator.ipynb)
|
||||
(Python as a Calculator)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/05_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/06_review.ipynb)
|
||||
- [further resources <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/01_elements/07_resources.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/01_elements/07_resources.ipynb)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/05_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/06_review.ipynb)
|
||||
- [further resources <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/01_elements/07_resources.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/01_elements/07_resources.ipynb)
|
||||
- *Chapter 2*: Functions & Modularization
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/02_functions/00_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/02_functions/00_content.ipynb)
|
||||
(Built-in Functions & Constructors;
|
||||
Function Definitions;
|
||||
Function Calls & Scoping Rules;
|
||||
Positional vs. Keyword Arguments;
|
||||
Modularization)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/01_exercises.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/02_functions/01_exercises.ipynb)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/01_exercises_sphere-volume.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/02_functions/01_exercises_sphere-volume.ipynb)
|
||||
(Volume of a Sphere)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/02_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/02_functions/02_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/02_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/02_functions/02_content.ipynb)
|
||||
(Standard Library: `math` & `random` Modules;
|
||||
Third-party Packages: `numpy` Library;
|
||||
Writing one's own Modules)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/03_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/04_review.ipynb)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/03_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/02_functions/04_review.ipynb)
|
||||
- *Chapter 3*: Conditionals & Exceptions
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/03_conditionals/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/03_conditionals/00_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/03_conditionals/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/03_conditionals/00_content.ipynb)
|
||||
(Boolean Expressions;
|
||||
Relational Operators;
|
||||
Logical Operators;
|
||||
`if` statement;
|
||||
Exception Handling)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/03_conditionals/01_exercises.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/03_conditionals/01_exercises.ipynb)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/03_conditionals/01_exercises_discounts.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/03_conditionals/01_exercises_discounts.ipynb)
|
||||
(Discounting Customer Orders)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/03_conditionals/02_exercises.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/03_conditionals/02_exercises.ipynb)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/03_conditionals/02_exercises_fizz-buzz.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/03_conditionals/02_exercises_fizz-buzz.ipynb)
|
||||
(Fizz Buzz)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/03_conditionals/03_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/03_conditionals/04_review.ipynb)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/03_conditionals/03_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/03_conditionals/04_review.ipynb)
|
||||
- *Chapter 4*: Recursion & Looping
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/04_iteration/00_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/04_iteration/00_content.ipynb)
|
||||
(Recursion;
|
||||
Examples: Factorial, Euclid's Algorithm, & Fibonacci;
|
||||
Duck Typing;
|
||||
Type Casting & Checking;
|
||||
Input Validation)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/01_exercises.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/04_iteration/01_exercises.ipynb)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/01_exercises_hanoi-towers.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/04_iteration/01_exercises_hanoi-towers.ipynb)
|
||||
(Towers of Hanoi)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/02_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/04_iteration/02_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/02_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/04_iteration/02_content.ipynb)
|
||||
(Looping with `while` & `for`;
|
||||
Examples: Collatz Conjecture, Factorial, Euclid's Algorithm, & Fibonacci;
|
||||
Containers vs. Iterables)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/03_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/04_iteration/03_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/03_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/04_iteration/03_content.ipynb)
|
||||
(Customizing Loops with `break` and `continue`;
|
||||
Indefinite Loops)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/04_exercises.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/04_iteration/04_exercises.ipynb)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/04_exercises_dice.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/04_iteration/04_exercises_dice.ipynb)
|
||||
(Throwing Dice)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/05_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/04_iteration/06_review.ipynb)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/05_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/04_iteration/06_review.ipynb)
|
||||
- **Part B: Managing Data and Memory**
|
||||
- *Chapter 5*: Numbers & Bits
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/05_numbers/00_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/05_numbers/00_content.ipynb)
|
||||
(`int` Type;
|
||||
Binary & Hexadecimal Representations;
|
||||
Bit Arithmetic;
|
||||
Bitwise Operators)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/01_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/05_numbers/01_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/01_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/05_numbers/01_content.ipynb)
|
||||
(`float` Type;
|
||||
Floating-point Standard;
|
||||
Special Values;
|
||||
Imprecision;
|
||||
Binary & Hexadecimal Representations)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/02_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/05_numbers/02_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/02_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/05_numbers/02_content.ipynb)
|
||||
(`complex` Type;
|
||||
Numerical Tower;
|
||||
Duck vs. Goose Typing)
|
||||
- [appendix <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/03_appendix.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/05_numbers/03_appendix.ipynb)
|
||||
- [appendix <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/03_appendix.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/05_numbers/03_appendix.ipynb)
|
||||
(`Decimal` Type;
|
||||
`Fraction` Type)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/04_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/05_review.ipynb)
|
||||
- [further resources <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/05_numbers/06_resources.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/05_numbers/06_resources.ipynb)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/04_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/05_review.ipynb)
|
||||
- [further resources <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/05_numbers/06_resources.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/05_numbers/06_resources.ipynb)
|
||||
- *Chapter 6*: Text & Bytes
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/06_text/00_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/06_text/00_content.ipynb)
|
||||
(`str` Type;
|
||||
Reading Files;
|
||||
Sequences;
|
||||
Indexing & Slicing;
|
||||
String Methods & Operations;
|
||||
String Interpolation)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/01_exercises.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/06_text/01_exercises.ipynb)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/01_exercises_palindromes.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/06_text/01_exercises_palindromes.ipynb)
|
||||
(Detecting Palindromes)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/02_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/06_text/02_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/02_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/06_text/02_content.ipynb)
|
||||
(Special Characters;
|
||||
ASCII & Unicode;
|
||||
Multi-line Strings;
|
||||
`bytes` Type;
|
||||
Character Encodings)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/03_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/04_review.ipynb)
|
||||
- [further resources <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/06_text/05_resources.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/06_text/05_resources.ipynb)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/03_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/04_review.ipynb)
|
||||
- [further resources <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/06_text/05_resources.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/06_text/05_resources.ipynb)
|
||||
- *Chapter 7*: Sequential Data
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/07_sequences/00_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/07_sequences/00_content.ipynb)
|
||||
(Collections vs. Sequences;
|
||||
ABCs: `Container`, `Iterable`, `Sized`, & `Reversible`)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/01_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/07_sequences/01_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/01_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/07_sequences/01_content.ipynb)
|
||||
(`list` Type;
|
||||
Indexing & Slicing;
|
||||
Shallow vs. Deep Copies;
|
||||
List Methods & Operations)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/02_exercises.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/07_sequences/02_exercises.ipynb)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/02_exercises_lists.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/07_sequences/02_exercises_lists.ipynb)
|
||||
(Working with Lists)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/03_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/07_sequences/03_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/03_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/07_sequences/03_content.ipynb)
|
||||
(Modifiers vs. Pure Functions;
|
||||
`tuple` Type;
|
||||
Packing & Unpacking;
|
||||
`*args` in Function Definitions)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/04_exercises.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/07_sequences/04_exercises.ipynb)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/04_exercises_un-packing.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/07_sequences/04_exercises_un-packing.ipynb)
|
||||
(Packing & Unpacking with Functions)
|
||||
- [appendix <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/05_appendix.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/07_sequences/05_appendix.ipynb)
|
||||
- [appendix <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/05_appendix.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/07_sequences/05_appendix.ipynb)
|
||||
(`namedtuple` Type)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/06_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/07_sequences/07_review.ipynb)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/06_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/07_sequences/07_review.ipynb)
|
||||
- *Chapter 8*: Map, Filter, & Reduce
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/08_mfr/00_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/08_mfr/00_content.ipynb)
|
||||
(Mapping;
|
||||
Filtering;
|
||||
Reducing;
|
||||
`lambda` Expression)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/01_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/08_mfr/01_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/01_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/08_mfr/01_content.ipynb)
|
||||
(`list` Comprehension;
|
||||
`generator` Expression;
|
||||
Streams of Data;
|
||||
Boolean Reducers)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/02_exercises.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/08_mfr/02_exercises.ipynb)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/02_exercises_outliers.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/08_mfr/02_exercises_outliers.ipynb)
|
||||
(Removing Outliers in Streaming Data)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/03_exercises.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/08_mfr/03_exercises.ipynb)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/03_exercises_un-packing.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/08_mfr/03_exercises_un-packing.ipynb)
|
||||
(Packing & Unpacking with Functions, continued)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/04_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/08_mfr/04_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/04_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/08_mfr/04_content.ipynb)
|
||||
(Iterators vs. Iterables;
|
||||
Example: `sorted()` vs. `reversed()`)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/05_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/08_mfr/06_review.ipynb)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/05_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/08_mfr/06_review.ipynb)
|
||||
- *Chapter 9*: Mappings & Sets
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/09_mappings/00_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/09_mappings/00_content.ipynb)
|
||||
(`dict` Type;
|
||||
Nested Data;
|
||||
Hash Tables;
|
||||
`dict` Methods & Behavior;
|
||||
`dict` Comprehension)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/01_exercises.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/09_mappings/01_exercises.ipynb)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/01_exercises_nested-data.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/09_mappings/01_exercises_nested-data.ipynb)
|
||||
(Working with Nested Data)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/02_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/09_mappings/02_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/02_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/09_mappings/02_content.ipynb)
|
||||
(`**kwargs` in Function Definitions;
|
||||
Memoization)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/03_exercises.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/09_mappings/03_exercises.ipynb)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/03_exercises_fibonacci.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/09_mappings/03_exercises_fibonacci.ipynb)
|
||||
(Memoization without Side Effects)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/04_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/09_mappings/04_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/04_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/09_mappings/04_content.ipynb)
|
||||
(`set` Type;
|
||||
`set` Methods & Operations;
|
||||
`set` Comprehension;
|
||||
`frozenset` Type)
|
||||
- [appendix <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/05_appendix.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/09_mappings/05_appendix.ipynb)
|
||||
- [appendix <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/05_appendix.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/09_mappings/05_appendix.ipynb)
|
||||
(`defaultdict` Type;
|
||||
`Counter` Type;
|
||||
`ChainMap` Type)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/06_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/07_review.ipynb)
|
||||
- [further resources <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/09_mappings/08_resources.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/09_mappings/08_resources.ipynb)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/06_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/07_review.ipynb)
|
||||
- [further resources <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/09_mappings/08_resources.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/09_mappings/08_resources.ipynb)
|
||||
- *Chapter 10*: Arrays & Dataframes
|
||||
- *Chapter 11*: Classes & Instances
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/11_classes/00_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/00_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/11_classes/00_content.ipynb)
|
||||
(`class` Statement;
|
||||
Instantiation;
|
||||
Text Representations;
|
||||
Instance Methods vs. Class Methods;
|
||||
Computed Properties)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/01_exercises.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/11_classes/01_exercises.ipynb)
|
||||
- [exercises <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/01_exercises_tsp.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/11_classes/01_exercises_tsp.ipynb)
|
||||
(A Traveling Salesman Problem)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/02_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/11_classes/02_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/02_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/11_classes/02_content.ipynb)
|
||||
(Sequence Emulation & Iteration;
|
||||
Python's Data Model;
|
||||
(Im)mutable Data Types;
|
||||
Method Chaining;
|
||||
Polymorphism)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/03_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/11_classes/03_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/03_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/11_classes/03_content.ipynb)
|
||||
(Operator Overloading: Arithmetic & Relational Operators;
|
||||
Number Emulation)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/04_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/11_classes/04_content.ipynb)
|
||||
- [content <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/04_content.ipynb)
|
||||
[<img height="12" style="display: inline-block" src="static/link/to_mb.png">](https://mybinder.org/v2/gh/webartifex/intro-to-python/main?urlpath=lab/tree/11_classes/04_content.ipynb)
|
||||
(Writing one's own Packages;
|
||||
The final `Vector` & `Matrix` Classes;
|
||||
Comparison with `numpy`)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/05_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/06_review.ipynb)
|
||||
- [summary <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/05_summary.ipynb)
|
||||
- [review questions <img height="12" style="display: inline-block" src="static/link/to_nb.png">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/main/11_classes/06_review.ipynb)
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
MIT License
|
||||
|
||||
Copyright (c) 2018-2020 Alexander Hess [alexander@webartifex.biz]
|
||||
Copyright (c) 2018-2024 Alexander Hess [alexander@webartifex.biz]
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to deal
|
||||
|
|
|
|||
40
README.md
40
README.md
|
|
@ -22,12 +22,13 @@ For a more *detailed version* with **clickable links**
|
|||
- *Chapter 7*: Sequential Data
|
||||
- *Chapter 8*: Map, Filter, & Reduce
|
||||
- *Chapter 9*: Mappings & Sets
|
||||
- *Chapter 10*: Arrays & Dataframes
|
||||
- *Chapter 11*: Classes & Instances
|
||||
|
||||
|
||||
#### Videos
|
||||
|
||||
Presentations of the chapters are available on this [YouTube playlist <img height="12" style="display: inline-block" src="static/link/to_yt.png">](https://www.youtube.com/playlist?list=PL-2JV1G3J10lQ2xokyQowcRJI5jjNfW7f).
|
||||
Presentations of the chapters are available on this [YouTube playlist <img height="12" style="display: inline-block" src="static/link/to_yt.png">](https://www.youtube.com/playlist?list=PL-2JV1G3J10kRUPgP7EwLhyeN5lOZW2kH).
|
||||
The recordings are about 25 hours long in total
|
||||
and were made in spring 2020
|
||||
after a corresponding in-class Bachelor course was cancelled due to Corona.
|
||||
|
|
@ -75,21 +76,21 @@ If you are familiar with
|
|||
|
||||
### Installation
|
||||
|
||||
To follow this course, an installation of **Python 3.8** or higher is expected.
|
||||
To follow this course, an installation of **Python 3.11** or higher is expected.
|
||||
|
||||
A popular and beginner friendly way is
|
||||
to install the [Anaconda Distribution](https://www.anaconda.com/products/individual)
|
||||
to install the [Anaconda Distribution](https://www.anaconda.com/download)
|
||||
that not only ships Python itself
|
||||
but also comes pre-packaged with a lot of third-party libraries.
|
||||
|
||||
<img src="static/anaconda_download.png" width="50%">
|
||||
|
||||
Scroll down to the [download](https://www.anaconda.com/products/individual#Downloads) section
|
||||
Scroll down to the "Anaconda Installers" section
|
||||
and install the latest version for your operating system
|
||||
(i.e., *2020-07* with Python 3.8 at the time of this writing).
|
||||
(i.e., *2024-02* with Python 3.11 at the time of this writing).
|
||||
|
||||
After installation,
|
||||
you find an entry "[Anaconda Navigator](https://docs.anaconda.com/anaconda/navigator/)"
|
||||
you find an entry "[Anaconda Navigator](https://docs.anaconda.com/free/navigator/)"
|
||||
in your start menu.
|
||||
Click on it.
|
||||
|
||||
|
|
@ -138,7 +139,7 @@ Then, unpack the ZIP file into a folder of your choice,
|
|||
<img src="static/repo_download.png" width="50%">
|
||||
|
||||
|
||||
### Alternative Installation (for Instructors)
|
||||
### Alternative Installation (for Instructors using Linux)
|
||||
|
||||
Python can also be installed in a "pure" way
|
||||
obtained directly from its core development team [here](https://www.python.org/downloads/).
|
||||
|
|
@ -231,31 +232,6 @@ The command-line interface stays open in the background,
|
|||
<img src="static/cli_jupyter_lab.png" width="50%" align="center">
|
||||
|
||||
|
||||
#### Interactive Presentation Mode & Live Coding
|
||||
|
||||
`poetry install` also installs the
|
||||
[RISE <img height="12" style="display: inline-block" src="static/link/to_gh.png">](https://github.com/damianavila/RISE)
|
||||
extension for Jupyter.
|
||||
With that, the instructor can execute code in *presentation* mode during a class session.
|
||||
However, the RISE extension does *not* work in the more recent
|
||||
[JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) app
|
||||
but only in the older [Jupyter Notebook](https://jupyter-notebook.readthedocs.io/en/stable/) app,
|
||||
which comes with less features
|
||||
and a simpler [GUI <img height="12" style="display: inline-block" src="static/link/to_gh.png">](https://en.wikipedia.org/wiki/Graphical_user_interface).
|
||||
The instructor can start the latter with:
|
||||
|
||||
- `poetry run jupyter notebook`
|
||||
|
||||
This also opens a new tab in the web browser.
|
||||
After opening a notebook,
|
||||
clicking on the button highlighted below
|
||||
starts the presentation mode.
|
||||
|
||||
<img src="static/presentation_mode.png" width="50%" align="center">
|
||||
|
||||
Not all notebooks are designed for this presentation mode.
|
||||
|
||||
|
||||
## Contributing
|
||||
|
||||
Feedback **is highly encouraged** and will be incorporated.
|
||||
|
|
|
|||
17
noxfile.py
17
noxfile.py
|
|
@ -46,11 +46,6 @@ def init_project(session):
|
|||
):
|
||||
session.run("poetry", "run", "pre-commit", "install", f"--hook-type={type_}")
|
||||
|
||||
# Copy the extensions' JavaScript and CSS files into Jupyter's search directory.
|
||||
session.run(
|
||||
"poetry", "run", "jupyter", "contrib", "nbextension", "install", "--user"
|
||||
)
|
||||
|
||||
|
||||
@nox.session(venv_backend="none")
|
||||
def doctests(session):
|
||||
|
|
@ -92,23 +87,23 @@ def fix_branch_references(_session):
|
|||
{
|
||||
"name": "github",
|
||||
"pattern": re.compile(
|
||||
fr"((((http)|(https))://github\.com/{REPOSITORY}/((blob)|(tree))/)([\w-]+)/)"
|
||||
rf"((((http)|(https))://github\.com/{REPOSITORY}/((blob)|(tree))/)([\w-]+)/)"
|
||||
),
|
||||
"replacement": fr"\2{branch}/",
|
||||
"replacement": rf"\2{branch}/",
|
||||
},
|
||||
{
|
||||
"name": "nbviewer",
|
||||
"pattern": re.compile(
|
||||
fr"((((http)|(https))://nbviewer\.jupyter\.org/github/{REPOSITORY}/((blob)|(tree))/)([\w-]+)/)",
|
||||
rf"((((http)|(https))://nbviewer\.jupyter\.org/github/{REPOSITORY}/((blob)|(tree))/)([\w-]+)/)",
|
||||
),
|
||||
"replacement": fr"\2{branch}/",
|
||||
"replacement": rf"\2{branch}/",
|
||||
},
|
||||
{
|
||||
"name": "mybinder",
|
||||
"pattern": re.compile(
|
||||
fr"((((http)|(https))://mybinder\.org/v2/gh/{REPOSITORY}/)([\w-]+)\?)",
|
||||
rf"((((http)|(https))://mybinder\.org/v2/gh/{REPOSITORY}/)([\w-]+)\?)",
|
||||
),
|
||||
"replacement": fr"\2{branch}?",
|
||||
"replacement": rf"\2{branch}?",
|
||||
},
|
||||
]
|
||||
|
||||
|
|
|
|||
2809
poetry.lock
generated
2809
poetry.lock
generated
File diff suppressed because it is too large
Load diff
|
|
@ -1,29 +1,26 @@
|
|||
[build-system]
|
||||
requires = ["poetry>=0.12"]
|
||||
build-backend = "poetry.masonry.api"
|
||||
requires = ["poetry-core"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[tool.poetry]
|
||||
name = "intro-to-python"
|
||||
version = "0.1.0.dev0"
|
||||
version = "0.1.0"
|
||||
package-mode = false
|
||||
|
||||
authors = ["Alexander Hess <alexander@webartifex.biz>"]
|
||||
description = "An intro to Python & programming for wanna-be data scientists"
|
||||
license = "MIT"
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.8"
|
||||
python = "^3.11"
|
||||
|
||||
jupyterlab = "^2.2.8"
|
||||
numpy = "^1.19.2"
|
||||
jupyterlab = "^4.1.0"
|
||||
numpy = "^1.26.0"
|
||||
|
||||
[tool.poetry.dev-dependencies]
|
||||
# Task runners
|
||||
nox = "^2020.8.22"
|
||||
pre-commit = "^2.7.1"
|
||||
nox = "^2024.3.2"
|
||||
pre-commit = "^3.7.0"
|
||||
|
||||
# Testing
|
||||
xdoctest = "^0.15.0"
|
||||
|
||||
# Live coding during presentation mode
|
||||
jupyter-contrib-nbextensions = "^0.5.1"
|
||||
rise = "^5.6.1"
|
||||
xdoctest = "^1.1.0"
|
||||
|
|
|
|||
Loading…
Reference in a new issue