{ "cells": [ { "cell_type": "markdown", "id": "737e79eb", "metadata": {}, "source": [ "# Dictionaries" ] }, { "cell_type": "code", "execution_count": 1, "id": "200584f6", "metadata": { "tags": [ "hide-input" ] }, "outputs": [], "source": [ "import sys\n", "from pathlib import Path\n", "\n", "current = Path.cwd()\n", "for parent in [current, *current.parents]:\n", " if (parent / '_config.yml').exists():\n", " project_root = parent # ← Add project root, not chapters\n", " break\n", "else:\n", " project_root = Path.cwd().parent.parent\n", "\n", "sys.path.insert(0, str(project_root))\n", "\n", "from shared import thinkpython, diagram, jupyturtle\n", "from shared.download import download\n", "\n", "# Register as top-level modules so direct imports work in subsequent cells\n", "sys.modules['thinkpython'] = thinkpython\n", "sys.modules['diagram'] = diagram\n", "sys.modules['jupyturtle'] = jupyturtle\n" ] }, { "cell_type": "markdown", "id": "9963a57e", "metadata": {}, "source": [ "This chapter presents a built-in type called a dictionary.\n", "\n", "It is one of Python's best features -- and the building block of many efficient and elegant algorithms.\n" ] }, { "cell_type": "markdown", "id": "be7467bb", "metadata": {}, "source": [ "## What Is a Dictionary?\n", "\n", "A dictionary in Python is a built-in data type used to store data in key–value pairs. A Python dictionary is like a real world dictionary, where you look up a word for its definition. In Python dictionary, you look up a **key** for the **value**. \n", "\n", "The key characteristics of a dictionary are:\n", "\n", "1. Dictionaries are **mutable** (can be changed)\n", "2. Keys must be **immutable** (strings, numbers, tuples)\n", "3. A dictionary represents a **mapping** from **keys** to **values**. \n", "4. **Keys** must be **unique**\n", "5. **Values** can be any data type\n", "\n", "In terms formatting, \n", "- Each dictionary item consists of a **key** and a **value** separated by a **colon**. \n", "- Dictionary items are separated by **commas** and enclosed in **curly braces**." ] }, { "cell_type": "markdown", "id": "3a94f8ae", "metadata": {}, "source": [ "A **dictionary** is like a list, but more general. In a list, the indices have to be integers; in a dictionary they can be (almost) any type.\n", "\n", "| Feature | List | Dictionary |\n", "| --------- | ---------------- | ----------------- |\n", "| Access by | Index (0,1,2) | Key |\n", "| Structure | Ordered sequence | Key-value mapping |\n", "| Best for | Ordered data | Labeled data |\n" ] }, { "cell_type": "markdown", "id": "bb0fdc15", "metadata": {}, "source": [ "As seen in the example below: \n", "\n", "- A **list** of number words can be accessed using an integer as an **index**. \n", "- A **dictionary** goes in the other direction, and look up a word to get the corresponding integer; in other words, using the keys to look up the values." ] }, { "cell_type": "code", "execution_count": 2, "id": "20dd9f32", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['zero', 'one', 'two']\n", "one\n", "{'zero': 0, 'one': 1, 'two': 2}\n", "1\n" ] } ], "source": [ "nums_lst = ['zero', 'one', 'two']\n", "print(nums_lst)\n", "print(nums_lst[1])\n", "\n", "nums_dic = {'zero': 0, 'one': 1, 'two': 2}\n", "print(nums_dic)\n", "print(nums_dic['one'])" ] }, { "cell_type": "markdown", "id": "2c2f6f79", "metadata": {}, "source": [ "In mathematical language, a dictionary represents a **mapping** from keys to values, so you can also say that each key \"maps to\" a value.\n", "In this example, each number word maps to the corresponding integer.\n", "\n", "The following figure shows the state diagram for `numbers`.\n", "A dictionary is represented by a box with the word \"dict\" outside and the items inside.\n", "Each item is represented by a key and an arrow pointing to a value.\n", "The quotation marks indicate that the keys here are strings, not variable names." ] }, { "cell_type": "code", "execution_count": 3, "id": "e9004edf", "metadata": { "tags": [ "remove-input" ] }, "outputs": [], "source": [ "from shared.diagram import make_dict, Binding, Value\n", "\n", "numbers = {'zero': 0, 'one': 1, 'two': 2}\n", "\n", "d1 = make_dict(numbers, dy=-0.3, offsetx=0.37)\n", "binding1 = Binding(Value('numbers'), d1)" ] }, { "cell_type": "code", "execution_count": 4, "id": "3b05ed1f", "metadata": { "tags": [ "remove-input" ] }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from shared.diagram import diagram, adjust, Bbox\n", "\n", "width, height, x, y = [1.83, 1.24, 0.49, 0.85]\n", "ax = diagram(width, height)\n", "bbox = binding1.draw(ax, x, y)\n", "# adjust(x, y, bbox)" ] }, { "cell_type": "markdown", "id": "fc778385", "metadata": {}, "source": [ "## When to Use a Dictionary\n", "\n", "You use a dictionary when:\n", "- You need labeled data\n", "- You want fast lookups by name\n", "- You need a mapping relationship\n", "\n", "Examples of dictionaries:\n", "\n", "- Student records\n", "- **Configuration** settings\n", "- Word counts\n", "- **JSON** data" ] }, { "cell_type": "markdown", "id": "6ef15bbc", "metadata": {}, "source": [ "## Creating Dictionaries\n", "\n", "Python provides several ways to create a dictionary, depending on whether you already have the data or are building it incrementally. T \n", "\n", "1. **dict literal**: the most common approach to create a dictionary\n", "2. `dict()` constructor: to turn sequences into dictionaries\n", "3. dictionary comprehensions: are useful when keys and values come from other sources" ] }, { "cell_type": "markdown", "id": "657c28ae", "metadata": {}, "source": [ "Python also has a `dict.fromkeys()` method, which is a special case in creating dictionaries. Overall, common ways ways to create a dictionary include:\n", "\n", "| # | Method | Syntax | Notes |\n", "|---|---|---|---|\n", "| 1 | Empty dict literal | `{}` | Fastest way to create an empty dict |\n", "| 2 | Dict literal | `{'a': 1, 'b': 2}` | Keys and values known up front |\n", "| 3 | `dict()` constructor | `dict(a=1, b=2)` | Keys must be valid identifiers |\n", "| 4 | From list of tuples | `dict([('a', 1), ('b', 2)])` | Useful when pairs are already in a sequence |\n", "| 5 | `dict.fromkeys()` | `dict.fromkeys(['a', 'b'], 0)` | All keys share the same default value |\n", "| 6 | Dict comprehension | `{k: v for k, v in items}` | Build from any iterable with an expression |" ] }, { "cell_type": "markdown", "id": "9e3f77f0", "metadata": {}, "source": [ "Pay attention to ways 2, 3, and 4. We usually use dict literal for creating dictionaries but you should know how to use the `dict()` constructor to turn a sequence into a dictionary. Also, try to transfer your skill in list comprehension and tuple comprehension to dictionary comprehension. " ] }, { "cell_type": "code", "execution_count": 5, "id": "fe26184b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Empty literal: {}\n", "Dict literal: {'zero': 0, 'one': 1, 'two': 2}\n", "dict() keywords: {'zero': 0, 'one': 1, 'two': 2}\n", "dict() from tuples: {'zero': 0, 'one': 1, 'two': 2}\n", "dict.fromkeys(): {'zero': 0, 'one': 0, 'two': 0}\n", "Dict comprehension: {'zero': 0, 'one': 1, 'two': 2}\n" ] } ], "source": [ "# 1. Empty dict literal\n", "d1 = {}\n", "\n", "# 2. Dict literal with items\n", "d2 = {'zero': 0, 'one': 1, 'two': 2}\n", "\n", "# 3. dict() constructor with keyword arguments (keys must be valid identifiers)\n", "d3 = dict(zero=0, one=1, two=2)\n", "\n", "# 4. dict() from a list of (key, value) tuples\n", "d4 = dict([('zero', 0), ('one', 1), ('two', 2)])\n", "\n", "# 5. dict.fromkeys() — all keys share the same default value\n", "d5 = dict.fromkeys(['zero', 'one', 'two'], 0)\n", "\n", "# 6. Dict comprehension\n", "words = ['zero', 'one', 'two']\n", "d6 = {word: idx for idx, word in enumerate(words)} # note the two variables\n", "\n", "print(\"Empty literal: \", d1)\n", "print(\"Dict literal: \", d2)\n", "print(\"dict() keywords: \", d3)\n", "print(\"dict() from tuples: \", d4)\n", "print(\"dict.fromkeys(): \", d5)\n", "print(\"Dict comprehension: \", d6)" ] }, { "cell_type": "markdown", "id": "e5909815", "metadata": {}, "source": [ "To give some details about dictionary creation, let's use the dictionary literal to create a dictionary, which is to put the items inside curly braces. " ] }, { "cell_type": "code", "execution_count": 6, "id": "d73e8aab", "metadata": {}, "outputs": [], "source": [ "numbers = {'zero': 0, 'one': 1, 'two': 2}" ] }, { "cell_type": "markdown", "id": "b79066d8", "metadata": {}, "source": [ "Each item consists of a **key** and a **value** separated by a **colon**.\n", "The items are separated by commas and enclosed in curly braces.\n", "\n", "Another way to create a dictionary is to use the `dict` function.\n", "We can make an empty dictionary like this." ] }, { "cell_type": "code", "execution_count": 7, "id": "f597dc41", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{}" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "empty = dict()\n", "empty" ] }, { "cell_type": "markdown", "id": "991fb3e2", "metadata": {}, "source": [ "Or, if you have a list like [ \"zero\", \"one\", \"two\"], you can use `enumerate()` to create a dictionary." ] }, { "cell_type": "code", "execution_count": 8, "id": "888528e3", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'zero': 0, 'one': 1, 'two ': 2}\n" ] } ], "source": [ "lst = [\"zero\", \"one\", \"two \"]\n", "\n", "dict_words = {}\n", "for idx, word in enumerate(lst):\n", " dict_words[word] = idx\n", "\n", "print(dict_words)" ] }, { "cell_type": "markdown", "id": "d5cbea30", "metadata": {}, "source": [ "And we can make a copy of a dictionary like this." ] }, { "cell_type": "code", "execution_count": 9, "id": "88f7eab1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'zero': 0, 'one': 1, 'two': 2}" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "numbers_copy = dict(numbers)\n", "numbers_copy" ] }, { "cell_type": "markdown", "id": "959ce6d9", "metadata": {}, "source": [ "It is often useful to make a copy before performing operations that modify dictionaries." ] } ], "metadata": { "celltoolbar": "Tags", "kernelspec": { "display_name": ".venv", "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": "3.13.7" } }, "nbformat": 4, "nbformat_minor": 5 }