Add initial version of chapter 09's appendix
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09_mappings/05_appendix.ipynb
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09_mappings/05_appendix.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/develop?urlpath=lab/tree/09_mappings/05_appendix.ipynb)."
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"cell_type": "markdown",
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"slide_type": "slide"
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"source": [
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"# Chapter 9: Mappings & Sets (Appendix)"
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]
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"cell_type": "markdown",
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"slideshow": {
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"slide_type": "skip"
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"source": [
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"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 specialized mapping types for common use cases."
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"cell_type": "markdown",
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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},
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"source": [
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"## The `defaultdict` Type"
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]
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{
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"cell_type": "markdown",
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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"source": [
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"The [defaultdict <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.html#collections.defaultdict) type allows us to define a factory function that creates default values whenever we look up a key that does not yet exist. Ordinary `dict` objects would throw a `KeyError` exception in such situations.\n",
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"\n",
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"Let's say we have a `list` with *records* of goals scored during a soccer game. The records consist of the fields \"Country,\" \"Player,\" and the \"Time\" when a goal was scored. Our task is to group the goals by player and/or country."
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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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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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},
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"outputs": [],
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"source": [
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"goals = [\n",
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" (\"Germany\", \"Müller\", 11), (\"Germany\", \"Klose\", 23),\n",
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" (\"Germany\", \"Kroos\", 24), (\"Germany\", \"Kroos\", 26),\n",
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" (\"Germany\", \"Khedira\", 29), (\"Germany\", \"Schürrle\", 69),\n",
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" (\"Germany\", \"Schürrle\", 79), (\"Brazil\", \"Oscar\", 90),\n",
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"]"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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},
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"source": [
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"Using a normal `dict` object, we have to tediously check if a player has already scored a goal before. If not, we must create a *new* `list` object with the first time the player scored. Otherwise, we append the goal to an already existing `list` object."
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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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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'Müller': [11],\n",
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" 'Klose': [23],\n",
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" 'Kroos': [24, 26],\n",
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" 'Khedira': [29],\n",
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" 'Schürrle': [69, 79],\n",
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" 'Oscar': [90]}"
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]
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},
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"execution_count": 2,
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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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"goals_by_player = {}\n",
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"\n",
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"for _, player, minute in goals:\n",
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" if player not in goals_by_player:\n",
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" goals_by_player[player] = [minute]\n",
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" else:\n",
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" goals_by_player[player].append(minute)\n",
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"\n",
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"goals_by_player"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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},
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"source": [
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"Instead, with a `defaultdict` object, we can portray the code fragment's intent in a concise form. We pass a reference to 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) built-in to `defaultdict`."
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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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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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},
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"outputs": [],
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"source": [
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"from collections import defaultdict"
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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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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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},
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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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" {'Müller': [11],\n",
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" 'Klose': [23],\n",
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" 'Kroos': [24, 26],\n",
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" 'Khedira': [29],\n",
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" 'Schürrle': [69, 79],\n",
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" 'Oscar': [90]})"
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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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"goals_by_player = defaultdict(list)\n",
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"\n",
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"for _, player, minute in goals:\n",
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" goals_by_player[player].append(minute)\n",
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"\n",
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"goals_by_player"
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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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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"collections.defaultdict"
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]
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},
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"execution_count": 5,
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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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"type(goals_by_player)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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},
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"source": [
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"A reference to the factory function is stored in the `default_factory` attribute."
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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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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"list"
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]
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},
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"execution_count": 6,
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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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"goals_by_player.default_factory"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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},
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"source": [
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"If we want this code to produce a normal `dict` object, we pass `goals_by_player` to the [dict() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-dict) constructor."
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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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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'Müller': [11],\n",
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" 'Klose': [23],\n",
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" 'Kroos': [24, 26],\n",
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" 'Khedira': [29],\n",
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" 'Schürrle': [69, 79],\n",
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" 'Oscar': [90]}"
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]
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},
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"execution_count": 7,
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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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"dict(goals_by_player)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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},
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"source": [
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"Being creative, we use a factory function, created with a `lambda` expression, that returns another [defaultdict <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.html#collections.defaultdict) 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 its factory to group on the country and the player level simultaneously."
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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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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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},
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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(<function __main__.<lambda>()>,\n",
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" {'Germany': defaultdict(list,\n",
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" {'Müller': [11],\n",
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" 'Klose': [23],\n",
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" 'Kroos': [24, 26],\n",
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" 'Khedira': [29],\n",
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" 'Schürrle': [69, 79]}),\n",
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" 'Brazil': defaultdict(list, {'Oscar': [90]})})"
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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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"goals_by_country_and_player = defaultdict(lambda: defaultdict(list))\n",
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"\n",
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"for country, player, minute in goals:\n",
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" goals_by_country_and_player[country][player].append(minute)\n",
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"\n",
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"goals_by_country_and_player"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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},
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"source": [
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"Conversion into a normal and nested `dict` object is now a bit tricky but can be achieved in one line with a comprehension."
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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": 9,
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'Germany': {'Müller': [11],\n",
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" 'Klose': [23],\n",
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" 'Kroos': [24, 26],\n",
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" 'Khedira': [29],\n",
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" 'Schürrle': [69, 79]},\n",
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" 'Brazil': {'Oscar': [90]}}"
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]
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},
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"execution_count": 9,
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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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"{country: dict(by_player) for country, by_player in goals_by_country_and_player.items()}"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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},
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"source": [
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"## The `Counter` Type"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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},
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"source": [
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"A common task is to count the number of occurrences of elements in an iterable.\n",
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"\n",
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"The [Counter <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.html#collections.Counter) type provides an easy-to-use interface that can be called with any iterable and returns a `dict`-like object of type `Counter` that maps each unique elements to the number of times it occurs.\n",
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"\n",
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|
"To continue the previous example, let's create an overview that shows how many goals a player scorred. We use a generator expression as the argument to `Counter`."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 10,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"[('Germany', 'Müller', 11),\n",
|
||||||
|
" ('Germany', 'Klose', 23),\n",
|
||||||
|
" ('Germany', 'Kroos', 24),\n",
|
||||||
|
" ('Germany', 'Kroos', 26),\n",
|
||||||
|
" ('Germany', 'Khedira', 29),\n",
|
||||||
|
" ('Germany', 'Schürrle', 69),\n",
|
||||||
|
" ('Germany', 'Schürrle', 79),\n",
|
||||||
|
" ('Brazil', 'Oscar', 90)]"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 10,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"goals"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 11,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"from collections import Counter"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 12,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"scorers = Counter(x[1] for x in goals)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 13,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"Counter({'Müller': 1,\n",
|
||||||
|
" 'Klose': 1,\n",
|
||||||
|
" 'Kroos': 2,\n",
|
||||||
|
" 'Khedira': 1,\n",
|
||||||
|
" 'Schürrle': 2,\n",
|
||||||
|
" 'Oscar': 1})"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 13,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"scorers"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 14,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"collections.Counter"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 14,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"type(scorers)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"Now we can look up individual players. `scores` behaves like a normal dictionary with regard to key look-ups."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 15,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"1"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 15,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"scorers[\"Müller\"]"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"By default, it returns `0` if a key is not found. So, we do not have to handle a `KeyError`."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 16,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"0"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 16,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"scorers[\"Lahm\"]"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"`Counter` objects have a [.most_common() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.html#collections.Counter.most_common) method that returns a `list` object containing $2$-element `tuple` objects, where the first element is the element from the original iterable and the second the number of occurrences. The `list` object is sorted in descending order of occurrences."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 17,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"[('Kroos', 2), ('Schürrle', 2)]"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 17,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"scorers.most_common(2)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"We can increase the count of individual entries with the [.update() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.html#collections.Counter.update) method: That takes an *iterable* of the elements we want to count.\n",
|
||||||
|
"\n",
|
||||||
|
"Imagine if [Philipp Lahm <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Philipp_Lahm) had also scored against Brazil."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 18,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"scorers.update([\"Lahm\"])"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 19,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"Counter({'Müller': 1,\n",
|
||||||
|
" 'Klose': 1,\n",
|
||||||
|
" 'Kroos': 2,\n",
|
||||||
|
" 'Khedira': 1,\n",
|
||||||
|
" 'Schürrle': 2,\n",
|
||||||
|
" 'Oscar': 1,\n",
|
||||||
|
" 'Lahm': 1})"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 19,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"scorers"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"If we use a `str` object as the argument instead, each individual character is treated as an element to be updated. That is most likely not what we want."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 20,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"scorers.update(\"Lahm\")"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 21,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"Counter({'Müller': 1,\n",
|
||||||
|
" 'Klose': 1,\n",
|
||||||
|
" 'Kroos': 2,\n",
|
||||||
|
" 'Khedira': 1,\n",
|
||||||
|
" 'Schürrle': 2,\n",
|
||||||
|
" 'Oscar': 1,\n",
|
||||||
|
" 'Lahm': 1,\n",
|
||||||
|
" 'L': 1,\n",
|
||||||
|
" 'a': 1,\n",
|
||||||
|
" 'h': 1,\n",
|
||||||
|
" 'm': 1})"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 21,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"scorers"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"## The `ChainMap` Type"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"Consider `to_words`, `more_words`, and `even_more_words` below. Instead of merging the items of the three `dict` objects together into a *new* one, we want to create an object that behaves as if it contained all the unified items in it without materializing them in memory a second time."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 22,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"to_words = {\n",
|
||||||
|
" 0: \"zero\",\n",
|
||||||
|
" 1: \"one\",\n",
|
||||||
|
" 2: \"two\",\n",
|
||||||
|
"}"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 23,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"more_words = {\n",
|
||||||
|
" 2: \"TWO\", # to illustrate a point\n",
|
||||||
|
" 3: \"three\",\n",
|
||||||
|
" 4: \"four\",\n",
|
||||||
|
"}"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 24,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"even_more_words = {\n",
|
||||||
|
" 4: \"FOUR\", # to illustrate a point\n",
|
||||||
|
" 5: \"five\",\n",
|
||||||
|
" 6: \"six\",\n",
|
||||||
|
"}"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"The [ChainMap <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/collections.html#collections.ChainMap) type allows us to do precisely that."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 25,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"from collections import ChainMap"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"We simply pass all mappings as positional arguments to `ChainMap` and obtain a **proxy** object that occupies almost no memory but gives us access to the union of all the items."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 26,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"chain = ChainMap(to_words, more_words, even_more_words)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"Let's loop over the items in `chain` and see what is \"in\" it. The order is obviously *unpredictable* but all seven items we expected are there. Keys of later mappings do *not* overwrite earlier keys."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 27,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"4 four\n",
|
||||||
|
"5 five\n",
|
||||||
|
"6 six\n",
|
||||||
|
"2 two\n",
|
||||||
|
"3 three\n",
|
||||||
|
"0 zero\n",
|
||||||
|
"1 one\n"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"for number, word in chain.items():\n",
|
||||||
|
" print(number, word)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"When looking up a non-existent key, `ChainMap` objects raise a `KeyError` just like normal `dict` objects would."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 28,
|
||||||
|
"metadata": {
|
||||||
|
"slideshow": {
|
||||||
|
"slide_type": "skip"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"ename": "KeyError",
|
||||||
|
"evalue": "10",
|
||||||
|
"output_type": "error",
|
||||||
|
"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",
|
||||||
|
"\u001b[0;31mKeyError\u001b[0m: 10"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"chain[10]"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"kernelspec": {
|
||||||
|
"display_name": "Python 3",
|
||||||
|
"language": "python",
|
||||||
|
"name": "python3"
|
||||||
|
},
|
||||||
|
"language_info": {
|
||||||
|
"codemirror_mode": {
|
||||||
|
"name": "ipython",
|
||||||
|
"version": 3
|
||||||
|
},
|
||||||
|
"file_extension": ".py",
|
||||||
|
"mimetype": "text/x-python",
|
||||||
|
"name": "python",
|
||||||
|
"nbconvert_exporter": "python",
|
||||||
|
"pygments_lexer": "ipython3",
|
||||||
|
"version": "3.8.6"
|
||||||
|
},
|
||||||
|
"livereveal": {
|
||||||
|
"auto_select": "code",
|
||||||
|
"auto_select_fragment": true,
|
||||||
|
"scroll": true,
|
||||||
|
"theme": "serif"
|
||||||
|
},
|
||||||
|
"toc": {
|
||||||
|
"base_numbering": 1,
|
||||||
|
"nav_menu": {},
|
||||||
|
"number_sections": false,
|
||||||
|
"sideBar": true,
|
||||||
|
"skip_h1_title": true,
|
||||||
|
"title_cell": "Table of Contents",
|
||||||
|
"title_sidebar": "Contents",
|
||||||
|
"toc_cell": false,
|
||||||
|
"toc_position": {
|
||||||
|
"height": "calc(100% - 180px)",
|
||||||
|
"left": "10px",
|
||||||
|
"top": "150px",
|
||||||
|
"width": "384px"
|
||||||
|
},
|
||||||
|
"toc_section_display": false,
|
||||||
|
"toc_window_display": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 4
|
||||||
|
}
|
||||||
|
|
@ -253,3 +253,8 @@ If this is not possible,
|
||||||
`set` Methods & Operations;
|
`set` Methods & Operations;
|
||||||
`set` Comprehension;
|
`set` Comprehension;
|
||||||
`frozenset` Type)
|
`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)
|
||||||
|
(`defaultdict` Type;
|
||||||
|
`Counter` Type;
|
||||||
|
`ChainMap` Type)
|
||||||
|
|
|
||||||
Loading…
Reference in a new issue