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Alexander Hess 2020-04-16 05:37:52 +02:00
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8
01_elements_00_content.ipynb
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@ -1343,7 +1343,7 @@
"source": [
"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",
"\n",
"Formally, we call such type-specific functionalities **methods** (i.e., as opposed to functions) and we look at them in detail in Chapter 10. 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."
"Formally, we call such type-specific functionalities **methods** (i.e., as opposed to functions) and we look at them in detail 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/master/10_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."
]
},
{
@ -2474,7 +2474,7 @@
}
},
"source": [
"Some variables magically exist when a Python process is started or are added by Jupyter. We may safely ignore the former until Chapter 10 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 10 <img height=\"12\" style=\"display: inline-block\" src=\"static/link_to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/master/10_classes_00_content.ipynb) and the latter for good."
]
},
{
@ -2898,7 +2898,7 @@
}
},
"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 10. 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 10 <img height=\"12\" style=\"display: inline-block\" src=\"static/link_to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/master/10_classes_00_content.ipynb). We must *not* use this style for variables!"
]
},
{
@ -3734,7 +3734,7 @@
" - 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 10)\n",
" - built-in objects (incl. **literals**) vs. user-defined objects (cf., [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/master/10_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",

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02_functions_00_content.ipynb
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@ -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 10 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/master/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/master/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 10 <img height=\"12\" style=\"display: inline-block\" src=\"static/link_to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/master/10_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/master/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/master/03_conditionals_00_content.ipynb#Relational-Operators))."
]
},
{
@ -3599,7 +3599,7 @@
}
},
"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 10, 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 10 <img height=\"12\" style=\"display: inline-block\" src=\"static/link_to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/master/10_classes_00_content.ipynb), while the latter is explained further below."
]
},
{
@ -4519,7 +4519,7 @@
}
},
"source": [
"Packages are a generalization of modules, and we look at one in detail in Chapter 10. You may, however, already look at a [sample package <img height=\"12\" style=\"display: inline-block\" src=\"static/link_to_gh.png\">](https://github.com/webartifex/intro-to-python/tree/master/sample_package) in the repository, which is nothing but a folder with *.py* files in it.\n",
"Packages are a generalization of modules, and we look at one in detail 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/master/10_classes_00_content.ipynb). You may, however, already look at a [sample package <img height=\"12\" style=\"display: inline-block\" src=\"static/link_to_gh.png\">](https://github.com/webartifex/intro-to-python/tree/master/sample_package) in the repository, which is nothing but a folder with *.py* files in it.\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)."
]

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04_iteration_00_content.ipynb
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@ -5562,7 +5562,7 @@
"\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/master/07_sequences_00_content.ipynb#Collections-vs.-Sequences), we formalize these two concepts and introduce many more. Finally, Chapter 10 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/master/07_sequences_00_content.ipynb#Collections-vs.-Sequences), we formalize these two concepts and introduce many more. Finally, [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/master/10_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."
]

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05_numbers_00_content.ipynb
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@ -34,7 +34,7 @@
"\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/master/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/master/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/master/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/master/08_mfr_00_content.ipynb), 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/master/09_mappings_00_content.ipynb) then cover the more \"complex\" data types, including, for example, the `list` type. Finally, Chapter 10 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/master/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/master/08_mfr_00_content.ipynb), 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/master/09_mappings_00_content.ipynb) then cover the more \"complex\" data types, including, for example, the `list` type. Finally, [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/master/10_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",

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06_text_00_content.ipynb
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@ -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 10 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 10 <img height=\"12\" style=\"display: inline-block\" src=\"static/link_to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/master/10_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)."
]
},
{

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07_sequences_00_content.ipynb
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"\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",
"\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 10."
"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 10 <img height=\"12\" style=\"display: inline-block\" src=\"static/link_to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/master/10_classes_00_content.ipynb)."
]
},
{
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"source": [
"We implicitly assume that the first element represents the $x$ and the second the $y$ coordinate. While that follows intuitively from convention in math, we should at least add comments somewhere in the code to document this assumption.\n",
"\n",
"A better way is to create a *custom* data type. While that is covered in depth in Chapter 10, 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 10 <img height=\"12\" style=\"display: inline-block\" src=\"static/link_to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/master/10_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."
]
},
{

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09_mappings_00_content.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "skip"
}
},
"source": [
"**Important**: Click on \"*Kernel*\" > \"*Restart Kernel and Clear All Outputs*\" *before* reading this chapter in [JupyterLab <img height=\"12\" style=\"display: inline-block\" src=\"static/link_to_jp.png\">](https://jupyterlab.readthedocs.io/en/stable/) (e.g., in the cloud on [MyBinder <img height=\"12\" style=\"display: inline-block\" src=\"static/link_to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/master?urlpath=lab/tree/09_mappings_00_content.ipynb))"
]
},
{
"cell_type": "markdown",
"metadata": {
@ -8,7 +19,7 @@
}
},
"source": [
"# Chapter 8: Mappings & Sets"
"# Chapter 9: Mappings & Sets"
]
},
{

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pyproject.toml
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[tool.poetry]
name = "intro-to-python"
version = "0.6.8"
version = "0.7.0"
description = "An introduction to Python and programming for wanna-be data scientists"
authors = ["Alexander Hess <alexander@webartifex.biz>"]
license = "MIT"