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Add data structure section
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‎source-code/README.md

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1. `oo_vs_functional.ipynb`: comparing object-oriented approach to
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functional approach, including coroutines.
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1. `metaclasses`: illustration of the use of metaclasses in Python.
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1. `data-structures`: illustration of Python and standard library data
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structures.

‎source-code/data-structures/README.md

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# Data structures
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Python as well as its standard library have many data structures that help you
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write elegant and efficient code. Here you will soe examples.
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## What is it?
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1. `defaultdict.ipynb`: Jupyter notebook that illustrates the use of
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`collections.defaultdict` with a default factory for a Python `list` and
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a `dataclasss`.

‎source-code/data-structures/defaultdict.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "2462a390-11a0-4d96-be42-a215460ee554",
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"metadata": {},
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"source": [
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"# Requirements"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "4012d44e-1e7f-488d-bb19-d40466a0b800",
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"metadata": {},
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"outputs": [],
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"source": [
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"from collections import defaultdict\n",
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"from dataclasses import dataclass"
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]
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},
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{
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"cell_type": "markdown",
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"id": "62c1100f-d14c-4773-a87d-9b7935d55dcd",
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"metadata": {},
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"source": [
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"# defaultdict"
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]
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},
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{
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"cell_type": "markdown",
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"id": "771384fa-293a-4f00-94f9-0c5d28f19ed5",
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"metadata": {},
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"source": [
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"The `defaultdict` class is quite convenient since you don't have to test whether a key is already in a dictionary. If it is not, a factory is used to create an initial entry."
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]
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},
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{
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"cell_type": "markdown",
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"id": "f3951a33-b671-4603-8349-61c1641ae405",
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"metadata": {},
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"source": [
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"## Simple example"
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]
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},
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{
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"cell_type": "markdown",
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"id": "a2630300-45fd-4d51-8a05-a05bad9ee9d6",
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"metadata": {},
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"source": [
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"Consider a dictionary that has lists as values. If a key is not in the dictionary, it should be initialized with an empty list. The factory function for an empty list is the `list` function."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "67799112-3eb0-4410-b260-5c4646adffa6",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"multiples = defaultdict(list)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "556ecf15-3003-49f8-aa9b-e9f3998f2855",
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"metadata": {},
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"source": [
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"Now we can add data to the dictionary, for each integer between 0 and 20, we check whether the number is divisible by 2, 3, 4, or 5, and append it to the list that is the value for the divisor (which is the key)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "34147d51-a265-46b8-9e22-10b81460c006",
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"metadata": {},
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"outputs": [],
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"source": [
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"for number in range(20):\n",
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" for divisor in range(2, 6):\n",
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" if number % divisor == 0:\n",
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" multiples[divisor].append(number)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "d533abb9-7fcc-4ddf-895b-a13a71af138a",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"defaultdict(list,\n",
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" {2: [0, 2, 4, 6, 8, 10, 12, 14, 16, 18],\n",
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" 3: [0, 3, 6, 9, 12, 15, 18],\n",
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" 4: [0, 4, 8, 12, 16],\n",
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" 5: [0, 5, 10, 15]})"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"multiples"
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]
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},
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{
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"cell_type": "markdown",
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"id": "4fb29e3d-4264-4030-b933-b101c115d923",
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"metadata": {},
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"source": [
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"## Arbitrary classes"
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]
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},
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{
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"cell_type": "markdown",
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"id": "667ee4ca-6b2f-4ec0-823e-beef80dbbe93",
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"metadata": {},
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"source": [
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"`defaultdict` also supports arbitrary objects as default values. Consider the following dataclass that represents a person."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "0d049fe8-5b12-4c35-a730-1ddb47db55e8",
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"metadata": {},
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"outputs": [],
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"source": [
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"@dataclass\n",
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"class Person:\n",
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" first_name: str = None\n",
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" last_name: str = None\n",
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" age: int = None"
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]
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},
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{
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"cell_type": "markdown",
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"id": "928778d2-6fd8-4662-bb31-857e3a87f2c5",
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"metadata": {},
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"source": [
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"The constructor is the default factory in this case."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "1eec5ce6-3d7e-4e64-abd1-86f5f92e1446",
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"metadata": {},
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"outputs": [],
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"source": [
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"people = defaultdict(Person)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "aa0d20b2-ef70-487f-8637-cc6060355c1f",
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"metadata": {},
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"source": [
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"When a new person turns up, a default `Person` is constructed with `None` for each attribute, and one of the attributes, `first_name` is assigned to below."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "6732bd91-c726-4603-b4c4-7c70fc5eae7d",
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"metadata": {},
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"outputs": [],
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"source": [
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"people['gjb'].first_name = 'Geert Jan'"
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]
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},
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{
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"cell_type": "markdown",
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"id": "63b5c683-0a51-45e1-9d65-c9527e75136d",
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"metadata": {},
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"source": [
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"The dictionary indeed contains a single entry, a `Person` with `first_name` initialized, and `liast_name` and `age` attributes still set to `None`."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "c510d857-6796-48c4-a181-9ce58828cc2f",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"defaultdict(__main__.Person,\n",
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" {'gjb': Person(first_name='Geert Jan', last_name=None, age=None)})"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"people"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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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": "3.9.5"
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},
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"toc-autonumbering": true
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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