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Alexander Hess 2024-04-08 22:13:31 +02:00
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16
02_functions/02_content.ipynb
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@ -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)."
]
},
{
@ -434,7 +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)."
]
@ -615,7 +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."
]
},
{
@ -1027,7 +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."
]
@ -1332,7 +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",
@ -1418,7 +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",
@ -1469,7 +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."
]
},
{
@ -1585,7 +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)."
]