feat: 新增技能扩展 N3 一章相关示例源码

code/newsletter/N3/collections.ipynb

@@ -0,0 +1,330 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# namedtuple"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## namedtuple 使用示例"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Point 1: Point(x=1, y=1), Point 2: Point(x=2, y=3)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from collections import namedtuple\n",
+    "\n",
+    "Point = namedtuple(\"Point\", [\"x\", \"y\"])\n",
+    "p1 = Point(x=1, y=1)\n",
+    "p2 = Point(2, 3)\n",
+    "print(f\"Point 1: {p1}, Point 2: {p2}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'x': 3, 'y': 4}"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "p3 = Point(p1.x + p2.x, p1.y + p2.y)\n",
+    "p3._asdict()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 自定义 `Point` 类"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class Point:\n",
+    "    def __init__(self, x: int, y: int):\n",
+    "        self.x = x\n",
+    "        self.y = y\n",
+    "\n",
+    "    def __repr__(self):\n",
+    "        return f\"{self.__class__.__name__}(x={self.x}, y={self.y})\"\n",
+    "\n",
+    "\n",
+    "p = Point(x=3, y=4)\n",
+    "p\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 使用 `NamedTuple` 类"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Point(x=0, y=0)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from typing import NamedTuple\n",
+    "\n",
+    "\n",
+    "class Point(NamedTuple):\n",
+    "    x: int = 0\n",
+    "    y: int = 0\n",
+    "\n",
+    "    def __repr__(self):\n",
+    "        return f\"{self.__class__.__name__}(x={self.x}, y={self.y})\"\n",
+    "\n",
+    "\n",
+    "p = Point()\n",
+    "p"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Counter"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[('is', 10),\n",
+       " ('better', 8),\n",
+       " ('than', 8),\n",
+       " ('to', 5),\n",
+       " ('the', 5),\n",
+       " ('of', 3),\n",
+       " ('Although', 3),\n",
+       " ('be', 3),\n",
+       " ('should', 2),\n",
+       " ('never', 2)]"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from collections import Counter\n",
+    "from itertools import chain\n",
+    "\n",
+    "poem = \"\"\"\n",
+    "The Zen of Python, by Tim Peters\n",
+    "\n",
+    "Beautiful is better than ugly.\n",
+    "Explicit is better than implicit.\n",
+    "Simple is better than complex.\n",
+    "Complex is better than complicated.\n",
+    "Flat is better than nested.\n",
+    "Sparse is better than dense.\n",
+    "Readability counts.\n",
+    "Special cases aren't special enough to break the rules.\n",
+    "Although practicality beats purity.\n",
+    "Errors should never pass silently.\n",
+    "Unless explicitly silenced.\n",
+    "In the face of ambiguity, refuse the temptation to guess.\n",
+    "There should be one-- and preferably only one --obvious way to do it.\n",
+    "Although that way may not be obvious at first unless you're Dutch.\n",
+    "Now is better than never.\n",
+    "Although never is often better than *right* now.\n",
+    "If the implementation is hard to explain, it's a bad idea.\n",
+    "If the implementation is easy to explain, it may be a good idea.\n",
+    "Namespaces are one honking great idea -- let's do more of those!\n",
+    "\"\"\"\n",
+    "split = [line.split() for line in poem.splitlines()]\n",
+    "words = list(chain(*[elem for elem in split if elem]))\n",
+    "words[1:10]\n",
+    "\n",
+    "counter = Counter(words)\n",
+    "counter.most_common(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# deque "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "deque([])"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from collections import deque\n",
+    "\n",
+    "queue = deque()\n",
+    "queue"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "deque(['foo'])"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "queue.append(\"foo\")\n",
+    "queue"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "deque(['bar', 'bar', 'foo'])"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "queue.appendleft(\"bar\")\n",
+    "queue"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "queue.extendleft([\"zoo\", \"fuzz\"])\n",
+    "queue"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "deque(['foo', 'bar', 'baz'])"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "queue.rotate(1)\n",
+    "queue"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.9.0 ('pandas-startup')",
+   "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": "3.9.0"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "13977d4cc82dee5f9d9535ceb495bd0ab12a43c33c664e5f0d53c24cf634b67f"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}