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Author SHA1 Message Date
anine09
5570cc5e5a 新年快乐 2024-01-10 03:58:30 +08:00
anine09
f2eab623fa init v2 textbook 2023-09-18 00:05:23 +08:00
33 changed files with 2974 additions and 5276 deletions
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.github/ISSUE_TEMPLATE/bug.yaml vendored Normal file
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name: 🐞 课程内容错误 / Bugs
description: 在此报告课程中发现的任何错误，以便教学团队及时勘误。
title: "格式：'章节名(Chap 3 | Talks 1): Bugs 概要标题'"
assignees:
- anine09
labels: "反馈问题"
body:
- type: markdown
attributes:
value: |
👏感谢你为 P2S 项目报告错误做出的贡献，为了便于我们了解你的问题，请填写以下信息~
- type: textarea
id: number
attributes:
label: "章节编号"
description: "请填写错误出现的章节号(Chap X | Talks X)"
validations:
required: true
- type: textarea
id: location
attributes:
label: "具体内容"
description: "请粘贴/描述/贴图错误的具体内容位置，方便我们排查~"
validations:
required: true
- type: textarea
id: reason
attributes:
label: "错误描述"
description: "请描述一下这个错误的出错原因~"
validations:
required: true
- type: textarea
id: suggestion
attributes:
label: "改进建议"
description: "请说明改进建议方案，感谢你为 P2S 项目做出的贡献~"
validations:
required: false

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blank_issues_enabled: true
contact_links:
- name: 💬 参与讨论
url: https://github.com/datawhalechina/learn-python-the-smart-way-v2/discussions
about: issues 暂时只接收教程内容问题反馈（内容错误、改进提案等），在教程学习过程中遇到的其他任何问题，欢迎移步到 Datawhale 聪明办法学 Python 社区的讨论。

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name: Build and Deploy Docs
on:
push:
branches:
- main
jobs:
build-docs:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: 3.11
- name: Install dependencies
run: |
pip install -r requirements.txt
- name: Build documentation
run: sphinx-build ./notebook docs
- name: Setup Git
run: |
git config user.name "GitHub Action"
git config user.email "action@github.com"
- name: Commit changes
run: |
git add -f ./docs
git commit -m "Build Docs"
- name: Push changes
uses: ad-m/github-push-action@master
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
branch: ${{ github.ref }}

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jupyter_execute/
docs/
# momodel
.idea/
*.pyc
*.swp
.DS_Store
.localenv/
datasets/
core.*
results/
_README.ipynb
_OVERVIEW.md
.ipynb_checkpoints/
coding_here.ipynb

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1. Python 安装及基本语法.ipynb
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2. Python 数据结构.ipynb
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4. Python 文件与模块.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"id": "a870e71d",
"metadata": {},
"source": [
"# Python 文件与模块"
]
},
{
"cell_type": "markdown",
"id": "1257bf93",
"metadata": {},
"source": [
"## 1.4.1 文件"
]
},
{
"cell_type": "markdown",
"id": "77a65ea6",
"metadata": {},
"source": [
"经过几百万年的演化，人类进化出了其他动物没有的“长期记忆”，进而拥有了语言、文化甚至发展出文明，走上了一条未曾设想的道路。在人类大脑中，“短期记忆”由海马体负责，“长期记忆”则由大脑皮层中的额叶负责；在计算机中也同样存在长短期记忆，短期记忆由程序中的变量负责，长期记忆则交给电脑中的文件系统。"
]
},
{
"cell_type": "markdown",
"id": "8199ed32",
"metadata": {},
"source": [
"### 1.4.1.1 Open 函数"
]
},
{
"cell_type": "markdown",
"id": "6638d46b",
"metadata": {},
"source": [
"Python `open( )` 函数用于打开一个文件，并返回文件对象，在对文件进行处理过程都需要使用到这个函数。"
]
},
{
"cell_type": "markdown",
"id": "508c28c5",
"metadata": {},
"source": [
"> 为了测试 Python 中的文件操作，我们先通过命令行在当前目录保存一个内容为 “hello world!” 的 test.txt 文件。\n",
"\n",
"- Mac / Linux: `echo Hello world >> test.txt`\n",
"- Windows: `echo Hello world > test.txt`\n",
"\n",
"<img style=\"float: center;\" src=\"./src/fig41.png\" width=\"50%\"> "
]
},
{
"cell_type": "markdown",
"id": "fd7d8214",
"metadata": {},
"source": [
"`open(file, mode)` 函数主要有 file 和 mode 两个参数，其中 file 为需要读写文件的路径。mode 为读取文件时的模式，常用的模式有以下几个：\n",
"\n",
"- r：以字符串的形式读取文件。\n",
"- rb：以二进制的形式读取文件。\n",
"- w：写入文件。\n",
"- a：追加写入文件。\n",
"\n",
"不同模式下返回的文件对象功能也会不同。"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "85581df5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class '_io.TextIOWrapper'>\n"
]
}
],
"source": [
"file = open('test.txt', 'r')\n",
"print(type(file))"
]
},
{
"cell_type": "markdown",
"id": "d4297989",
"metadata": {},
"source": [
"### 1.4.1.2 文件对象"
]
},
{
"cell_type": "markdown",
"id": "b2665bee",
"metadata": {},
"source": [
"`open` 函数会返回一个 文件对象。在进行文件操作前，我们首先需要了解文件对象提供了哪些常用的方法：\n",
"\n",
"- `close( )`: 关闭文件\n",
"- 在 r 与 rb 模式下：\n",
" - `read()`: 读取整个文件\n",
" - `readline()`: 读取文件的一行\n",
" - `readlines()`: 读取文件的所有行\n",
"- 在 w 与 a 模式下：\n",
" - `write()`: \n",
" - `writelines()`: "
]
},
{
"cell_type": "markdown",
"id": "0660d622",
"metadata": {},
"source": [
"下面我们通过实例学习这几种方法："
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "c42d7de4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"hello world\n",
"\n"
]
}
],
"source": [
"## 通过 read 方法读取整个文件\n",
"content = file.read()\n",
"print(content)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "0604c0d2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n"
]
}
],
"source": [
"## 通过 readline() 读取文件的一行\n",
"content = file.readline()\n",
"print(content)"
]
},
{
"cell_type": "markdown",
"id": "921fae61",
"metadata": {},
"source": [
"我们发现上面的代码竟然什么也没输出，这是为什么？\n",
"\n",
"你可以理解 open 函数返回的是一个指针，类似于你在 Microsolf Word 文档里编辑文档时闪烁的光标。在执行过 `file.read( )` 操作后，由于读取了整个文件，这个指针已经来到了文件末尾，因此 `file.readline( )` 没有获取到文件的内容。这种情况我们可以通过 close 方法关闭文件后再重新打开。"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "7d180532",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"hello world\n",
"\n"
]
}
],
"source": [
"## 关闭之前打开的 test.txt 文件\n",
"file.close()\n",
"## 重新打开\n",
"file = open('test.txt', 'r')\n",
"content = file.readline()\n",
"print(content)"
]
},
{
"cell_type": "markdown",
"id": "1ebaed11",
"metadata": {},
"source": [
"因此在操作文件时，我们一定要注意每次操作结束后，及时通过 `close( )` 方法关闭文件。"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "8388fe2d",
"metadata": {},
"outputs": [],
"source": [
"## 以 w 模式打开文件test.txt\n",
"file = open('test.txt', 'w')\n",
"## 创建需要写入的字符串变量 在字符串中 \\n 代表换行（也就是回车）\n",
"content = 'Hello world!\\nHello Python!!\\n'\n",
"## 写入到 test.txt 文件中\n",
"file.write(content)\n",
"## 关闭文件对象\n",
"file.close()"
]
},
{
"cell_type": "markdown",
"id": "a4726843",
"metadata": {},
"source": [
"<img style=\"float: center;\" src=\"./src/fig42.png\" width=\"50%\"> "
]
},
{
"cell_type": "markdown",
"id": "4db4bd05",
"metadata": {},
"source": [
"需要注意在上述操作中，w 模式会覆盖之前的文件。如果你想在文件后面追加内容，可以使用 a 模式操作。"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "f3352cfd",
"metadata": {},
"outputs": [],
"source": [
"## 以 w 模式打开文件test.txt\n",
"file = open('test.txt', 'a')\n",
"## 创建需要追加的字符串变量\n",
"content = 'Hello smart way!!!'\n",
"## 写入到 test.txt 文件中\n",
"file.write(content)\n",
"## 关闭文件对象\n",
"file.close()"
]
},
{
"cell_type": "markdown",
"id": "01915069",
"metadata": {},
"source": [
"<img style=\"float: center;\" src=\"./src/fig43.png\" width=\"50%\"> "
]
},
{
"cell_type": "markdown",
"id": "4d487fad",
"metadata": {},
"source": [
"## 1.4.2 模块"
]
},
{
"cell_type": "markdown",
"id": "a8bab259",
"metadata": {},
"source": [
"在普罗米修斯为人类带来火种后，人类制造出了各种各样的工具。工具的产生大大提高了人类的生产力，使人类从石器时代步入铁器时代、蒸汽时代以及现在的信息时代。\n",
"\n",
"在之前的学习中，为了更简洁高效地完成任务，我们引入了函数、数据结构以及面向对象编程等工具。但每次我们在这个代码写完后，在下一个代码中只能把代码复制粘贴过去，而模块可以帮助我们把一个代码添加到另一个代码中，真正实现了工具等复用性。"
]
},
{
"cell_type": "markdown",
"id": "ac5aa0a2",
"metadata": {},
"source": [
"编写模块的方式有很多，其中最简单的模块就是创建一个包含很多函数、变量以及类并以 .py 为后缀的文件。下面我们把上一节中实现的 class 类保存在 student.py 文件中："
]
},
{
"cell_type": "markdown",
"id": "46b45d90",
"metadata": {},
"source": [
"<img style=\"float: center;\" src=\"./src/fig44.png\" width=\"50%\"> "
]
},
{
"cell_type": "markdown",
"id": "575e38db",
"metadata": {},
"source": [
"> 为了方便读者，也可使用下面的代码来直接在当前目录生成 `student.py` 文件。"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "bc4a2658",
"metadata": {},
"outputs": [],
"source": [
"file = open('student.py', 'w',encoding=\"utf-8\")\n",
"file.write(\"\"\"class student():\n",
" def __init__(self, name, Math_score, Chinese_score):\n",
" self.name = name\n",
" self.Math_score = Math_score\n",
" self.Chinese_score = Chinese_score\n",
" \n",
" ## repr 函数用于定义对象被输出时的输出结果\n",
" def __repr__(self):\n",
" return str((self.name, self.Math_score, self.Chinese_score))\n",
" \n",
" def change_score(self, course_name, score):\n",
" if course_name == 'Math':\n",
" self.Math_score = score\n",
" elif course_name == 'Chinese':\n",
" self.Chinese_score = score\n",
" else:\n",
" print(course_name, \" course is still not in current system\")\n",
" \n",
" def print_name(self,):\n",
" print(self.name)\n",
" \n",
" name = 'Undefined'\n",
" Math_score = None\n",
" Chinese_score = None\"\"\")\n",
"file.close()"
]
},
{
"cell_type": "markdown",
"id": "ef0e6af7",
"metadata": {},
"source": [
"使用 `import` 关键字可以把一个模块引入到一个程序来使用它的功能。记得在上一节中我们说过一个程序也可以是一个对象，这时 student.py 程序就成了一个对象，而里面的 student 类便成了它的对象变量。"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "8de02c29",
"metadata": {},
"outputs": [],
"source": [
"import student"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "4c9f7a60",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('XiaoHu', 65, 55)\n"
]
}
],
"source": [
"xiaohu = student.student('XiaoHu', 65, 55)\n",
"print(xiaohu)"
]
},
{
"cell_type": "markdown",
"id": "2b91e95f",
"metadata": {},
"source": [
"通过 student.py 这个模块，我们不需要重复编写就可以在任何程序中使用 student 类！正是因为有了模块，才使得数据科学中复杂的算法与模型可以封装到模块中，用户只需要使用模块中定义好的函数与类。"
]
},
{
"cell_type": "markdown",
"id": "c422e8ea",
"metadata": {},
"source": [
"当我们只需要模块中的几个函数或类时，也可以采用 `from model_name import xxx` 的写法导入指定部分："
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "abf9e578",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('XiaoHu', 65, 55)\n"
]
}
],
"source": [
"## 仅导入 student 类\n",
"from student import student\n",
"## 这时直接通过类名，不需要使用模块名\n",
"xiaohu = student('XiaoHu', 65, 55)\n",
"print(xiaohu)"
]
},
{
"cell_type": "markdown",
"id": "3024271d",
"metadata": {},
"source": [
"在 Python 中内置了很多标准模块，例如用于数学操作的 math 模块与处理时间的 time 模块："
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "323741ef",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4.174387269895637\n"
]
}
],
"source": [
"import math\n",
"## 通过 math.log 计算数值的对数\n",
"print(math.log(xiaohu.Math_score))"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "67f56bad",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Tue Jul 12 21:37:51 2022\n"
]
}
],
"source": [
"import time\n",
"## 通过 time 库中多个方法获取当前时间\n",
"## time.time 获取当前时间的 unix 时间戳\n",
"## time.loacltime 把当前时间的 unix 时间戳按照时区划分\n",
"## time.asctime 把按时区划分的时间戳转化成标准日期格式\n",
"print(time.asctime(time.localtime(time.time())))"
]
},
{
"cell_type": "markdown",
"id": "389616ba",
"metadata": {},
"source": [
"除此之外，Python 还有很多标准库值得我们去探索。例如 re 库可以实现字符串正则表达式的匹配，random 用来生成随机数，urllib 用来访问互联网……"
]
},
{
"cell_type": "markdown",
"id": "77869207",
"metadata": {},
"source": [
"## 1.4.3 练习"
]
},
{
"cell_type": "markdown",
"id": "709140e5",
"metadata": {},
"source": [
"### 1.4.3.1 学生信息本地存储"
]
},
{
"cell_type": "markdown",
"id": "2d0897a3",
"metadata": {},
"source": [
"> 之前我们实现了学生信息的“增删查改”功能，现在希望通过文件系统保存学生的信息，每次打开程序时可以载入，关闭程序时可以保存。"
]
},
{
"cell_type": "markdown",
"id": "f0673d08",
"metadata": {},
"source": [
"### 1.4.3.2 Python 之禅"
]
},
{
"cell_type": "markdown",
"id": "7d95cc3f",
"metadata": {},
"source": [
"<blockquote>\n",
"\n",
"首先在这里恭喜各位同学完成了 Python 的全部学习内容！在这四章中希望你可以体会到本教程简洁明快的风格，这种风格与 Python 本身的代码设计风格是一致的。在 Tim Peters 编写的 “Python 之禅” 中的核心指导原则就是 “Simple is better than complex”。\n",
"\n",
"纵观历史，你会看到苹果创始人史蒂夫·乔布斯对 Less is More 的追求，看到无印良品“删繁就简，去其浮华”的核心设计理念，看到山下英子在《断舍离》中对生活做减法的观点，甚至看到苏东坡“竹杖芒鞋轻胜马，一蓑烟雨任平生”的人生态度。你会发现极简主义不只存在于 Python 编程中，它本就是这个世界优雅的一条运行法则。\n",
" \n",
"本练习让我们导入 this 模块，用心体会一下 Python 的设计原则。\n",
" \n",
"</blockquote>"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "d918ee0e",
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"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"
]
}
],
"source": [
"import this"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.9.7 ('base')",
"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": "3.9.7"
},
"toc": {
"base_numbering": 1,
"nav_menu": {},
"number_sections": false,
"sideBar": true,
"skip_h1_title": false,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": false,
"toc_position": {},
"toc_section_display": true,
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437
LICENSE
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@@ -1,437 +0,0 @@
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47
README.md
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@@ -1,47 +0,0 @@
# 聪明办法学Python
大家好，我是小雨姑娘。双非本科自学数据挖掘，曾两次获得数据挖掘比赛冠军，被选入2020数据挖掘竞赛十大开源贡献者，人工智能开源组织Datawhale成员，现于北美攻读计算机博士学位。创作本教程的初心是提供一个更快捷有效的 Python 入门途径，让大家在最短时间内补充需要的知识技能，从而更快完成自己的目标。
**学习完本教程你可以收获什么？**
1. 尝试使用Python完成项目解决问题的能力。
2. 对必备Python知识点的掌握。
3. 对经典理论与算法的了解。
**本教程适合哪类同学学习？**
1. 想要从0开始系统学习 Python 的同学。
2. 需要在最短时间内学习 Python 解决当下问题的同学。
3. 对 Python 感兴趣想要了解的同学。
**本教程不适合哪类同学学习？**
1. 希望精进 Python 高阶用法的同学。
2. 希望全面学习掌握 Python 知识点的同学。
*在开发本教程的同时，作者也在构思一套有上述需求同学适合的教程。*
**本教程相对市面其他材料的特点？**
1. 简明。专注 Python 编程的核心能力与技术，不涉及冷门/非必要相关知识。
2. 系统知识体系。从无到有一点点构建知识体系，拒绝琐碎知识点的堆叠。
3. 注重实践。通过代码讲解理论，辅以实例加以巩固。
柏拉图曾经说过：“良好的开端等于成功的一半”。大家选择本教程作为建起万丈高楼的地基，对于我而言便是莫大的荣幸。衷心希望大家在本教程陪伴下迈向未来的同时，也能享受学习过程中带来的乐趣。
## 如何使用这套教程？
1. 在 Github 网页版直接打开 ipynb 文件按顺序查看 (推荐)
2. 本地下载安装 jupyter notebook 运行 ipynb 文件，安装使用方法可参考这篇 [博客](https://www.jianshu.com/p/91365f343585/)
3. 在 [和鲸社区](https://www.heywhale.com) 创建项目，上传 .ipynb 文件可在线运行
4. 在 [Google Colab](https://www.colab.google.com) 上传 .ipynb 在线运行 （需要科学上网）
## 联系方式
知乎 [@小雨姑娘](https://www.zhihu.com/people/xuechuanyu)
Email: chuanyu.xue@uconn.edu
## 关注我们
<div align=center><img src="https://raw.githubusercontent.com/datawhalechina/pumpkin-book/master/res/qrcode.jpeg" width = "250" height = "270" alt="Datawhale是一个专注AI领域的开源组织，以“for the learner，和学习者一起成长”为愿景，构建对学习者最有价值的开源学习社区。关注我们，一起学习成长。"></div>
## LICENSE
<a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/"><img alt="知识共享许可协议" style="border-width:0" src="https://img.shields.io/badge/license-CC%20BY--NC--SA%204.0-lightgrey" /></a><br />本作品采用<a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/">知识共享署名-非商业性使用-相同方式共享 4.0 国际许可协议</a>进行许可。

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{
"cells": [
{
"cell_type": "markdown",
"id": "68e6c596",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Chapter 0 安装 Installation"
]
},
{
"cell_type": "markdown",
"id": "e3b9b6a8",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## 安装清单\n",
"- Miniconda: https://docs.conda.io/en/latest/miniconda.html\n",
"- Visual Studio Code: https://code.visualstudio.com/"
]
},
{
"cell_type": "markdown",
"id": "e3eb91af",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Miniconda 安装配置"
]
},
{
"cell_type": "markdown",
"id": "4585b342",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### 下载 Miniconda\n",
"\n",
"Miniconda 下载地址：<https://docs.conda.io/en/latest/miniconda.html>\n",
"\n",
"最新版 Miniconda For Windows 下载链接：\n",
"\n",
"<https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe>"
]
},
{
"cell_type": "markdown",
"id": "d9358602",
"metadata": {
"cell_style": "center",
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### Windows 下安装配置推荐\n",
"\n",
"- Just Me (recommended)\n",
"- Clear the package cache upon completion"
]
},
{
"cell_type": "markdown",
"id": "963b4fd9",
"metadata": {
"cell_style": "split"
},
"source": [
"![](./image/chap0/miniconda_installation_1.png)"
]
},
{
"cell_type": "markdown",
"id": "5d2168a7",
"metadata": {
"cell_style": "split"
},
"source": [
"![](./image/chap0/miniconda_installation_2.png)"
]
},
{
"cell_type": "markdown",
"id": "0312d547",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"## 修改 Powershell 执行策略（可选）\n",
"\n",
"在`开始`图标**右键单击**，选择 `Windows PowerShell（管理员）`\n",
"\n",
"先输入下面的内容，并回车：\n",
"```powershell\n",
"Set-ExecutionPolicy -Scope CurrentUser RemoteSigned\n",
"```\n",
"出现如下内容后，输入：`A`，回车：\n",
"\n",
"![](../resources/slides/chap0/pic/powershell.png)\n",
"\n",
"最后在 **Anaconda Powershell Prompt** 中输入：\n",
"```bash\n",
"conda init\n",
"```"
]
},
{
"cell_type": "markdown",
"id": "50b897f3",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## 更换镜像源\n",
"\n",
"- Pip 换源\n",
"- Conda 换源\n",
"\n",
"> 加快国内资源下载速度"
]
},
{
"cell_type": "markdown",
"id": "5ec52c36",
"metadata": {
"cell_style": "center",
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### 校园网联合镜像站\n",
"<https://help.mirrors.cernet.edu.cn/>\n",
"\n",
"### 阿里巴巴开源镜像站\n",
"\n",
"<https://developer.aliyun.com/mirror/>\n",
"\n",
"请避免使用代理，不合理的代理设置会导致下载失败"
]
},
{
"cell_type": "markdown",
"id": "02919362",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### Conda 更换镜像源\n",
"\n",
"清华大学开源软件镜像站：<https://help.mirrors.cernet.edu.cn/anaconda/>\n",
"\n",
"南方科技大学开源软件镜像站：<https://help.mirrors.cernet.edu.cn/anaconda-extra/>\n",
"\n",
"在 **Anaconda Powershell Prompt** 中输入：\n",
"\n",
"```bash\n",
"conda config --set show_channel_urls yes\n",
"```\n",
"\n",
"在镜像站复制文本后，在 **Anaconda Powershell Prompt** 中输入：\n",
"\n",
"```bash\n",
"notepad .condarc # 注意有个小点 \".\" 在 \"condarc\" 的前面\n",
"```\n",
"\n",
"粘贴刚刚复制的文本，保存文件后关闭\n",
"\n",
"最后在 **Anaconda Powershell Prompt** 中输入：\n",
"\n",
"```bash\n",
"conda clean -i # 清除源缓存，以启用镜像源\n",
"```"
]
},
{
"cell_type": "markdown",
"id": "0de0a2be",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"## PyPI 更换镜像源\n",
" \n",
"校园网联合镜像站：<https://help.mirrors.cernet.edu.cn/pypi/>\n",
"\n",
"复制文本后，在 **Anaconda Powershell Prompt** 中粘贴运行即可：\n",
"\n",
"```bash\n",
"# 设置 PyPI 镜像源\n",
"pip config set global.index-url https://mirrors.cernet.edu.cn/pypi/web/simple \n",
"```"
]
},
{
"cell_type": "markdown",
"id": "054f6cbc",
"metadata": {
"slideshow": {
"slide_type": "slide"
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},
"source": [
"## 课程环境搭建"
]
},
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"cell_type": "markdown",
"id": "d8028b9c",
"metadata": {
"slideshow": {
"slide_type": "subslide"
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"source": [
"### 创建与激活 Conda 环境\n",
"\n",
"创建 Conda 环境\n",
"\n",
"```bash\n",
"conda create -n Datawhale python=3.10 # conda 环境创建\n",
"```\n",
"\n",
"其中 ***-n*** 代表创建的环境名称，这里是 ***Datawhale***，并指定 ***Python 版本为 3.10***\n",
"\n",
"激活刚刚创建的 Conda 环境：\n",
"\n",
"```bash\n",
"conda activate Datawhale # 激活 Datawhale 环境，不同环境的 Python 包版本不同！\n",
"```\n",
"\n",
"如果需要删除某个 Conda 环境：\n",
"\n",
"```bash\n",
"conda deactivate # 退出该环境\n",
"conda remove -n Datawhale --all # 删除整个环境\n",
"```"
]
},
{
"cell_type": "markdown",
"id": "4cac85fe",
"metadata": {
"cell_style": "split",
"slideshow": {
"slide_type": "subslide"
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},
"source": [
"## Pip 安装与展示\n",
"\n",
"Pip 安装课程所需第三方库\n",
"\n",
"```bash\n",
"pip install jupyter\n",
"```\n",
"\n",
"在指定路径输入：\n",
"\n",
"```bash\n",
"jupyter-notebook # 会自动跳转到浏览器\n",
"```\n",
"\n",
"结束学习时使用：\n",
"\n",
"```bash\n",
"Ctrl + C # 关闭 Jupyter Notebook 服务\n",
"```"
]
},
{
"cell_type": "markdown",
"id": "708d553e",
"metadata": {
"cell_style": "split",
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
"### 安装清单\n",
"\n",
"数据挖掘：\n",
"- scikit-learn\n",
"- numpy\n",
"- pandas\n",
"- tqdm\n",
"- lightgbm (数据挖掘模型)\n",
"\n",
"CV：\n",
"- nibabel\n",
"- pillow"
]
},
{
"cell_type": "markdown",
"id": "8aedd2d4",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### Conda 安装与展示\n",
"\n",
"首先在 **Anaconda Powershell Prompt** 中输入：\n",
"\n",
"```bash\n",
"nvidia-smi # 查看当前 GPU 支持的最高 CUDA 版本\n",
"```\n",
"\n",
"![](../resources/slides/chap0/pic/CUDA_info.png)\n",
"\n",
"**Pytorch** 安装： <https://pytorch.org/get-started/locally/>\n",
"\n",
"```bash\n",
"conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia\n",
"```\n",
"\n",
"**PaddlePaddle** 安装：<https://www.paddlepaddle.org.cn>\n",
"```bash\n",
"conda install paddlepaddle-gpu==2.4.2 cudatoolkit=11.7 -c Paddle -c conda-forge\n",
"```"
]
},
{
"cell_type": "markdown",
"id": "109adde7",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"## CUDA 验证"
]
},
{
"cell_type": "markdown",
"id": "5651891e",
"metadata": {},
"source": [
"在 **Anaconda Powershell Prompt** 中输入：\n",
"\n",
"```bash\n",
"ipython # 交互 Python 运行环境\n",
"```\n",
"\n",
"使用 `exit` 或 `exit()` 来退出 **IPython**"
]
},
{
"cell_type": "markdown",
"id": "f6021cd5",
"metadata": {
"cell_style": "split",
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
"PaddlePaddle:\n",
"\n",
"```python\n",
">>> import paddle\n",
">>> paddle.utils.run_check()\n",
"```\n",
"\n",
"正确输出：\n",
"```plain\n",
"PaddlePaddle works well on 1 GPU.\n",
"PaddlePaddle is installed successfully! Let's start deep learning with PaddlePaddle now.\n",
"```"
]
},
{
"cell_type": "markdown",
"id": "de874521",
"metadata": {
"cell_style": "split",
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
"Pytorch:\n",
"\n",
"```python\n",
">>> import torch\n",
">>> torch.cuda.is_available()\n",
"```\n",
"\n",
"正常输出：\n",
"\n",
"```python\n",
"True\n",
"```"
]
},
{
"cell_type": "markdown",
"id": "0d011cdf",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## 云端环境的使用\n",
"- 百度飞桨 AI Studio https://aistudio.baidu.com/aistudio/index\n",
"- 阿里天池 PAI DSW https://tianchi.aliyun.com/notebook-ai\n",
"- Kaggle https://www.kaggle.com/code\n",
"- Google Colab https://colab.research.google.com/\n",
"- Sagemaker Studio Lab https://studiolab.sagemaker.aws/"
]
}
],
"metadata": {
"celltoolbar": "Slideshow",
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
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"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.5"
},
"rise": {
"overlay": "<div class='my-top-right'><img height=40px src='../resources/datawhale_logo.png'/></div><div class='my-top-left'></div>"
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"toc": {
"base_numbering": 1,
"nav_menu": {},
"number_sections": true,
"sideBar": true,
"skip_h1_title": false,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": false,
"toc_position": {},
"toc_section_display": true,
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"python": {
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"delete_cmd_postfix": ") ",
"delete_cmd_prefix": "rm(",
"library": "var_list.r",
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"types_to_exclude": [
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"builtin_function_or_method",
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"_Feature"
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"window_display": false
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"nbformat": 4,
"nbformat_minor": 5
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extensions = [
"myst_nb",
'sphinx_copybutton', # sphinx-copybutton.readthedocs.io
'sphinx_design', # github.com/executablebooks/sphinx-design
'sphinx_togglebutton', # sphinx-togglebutton.readthedocs.io
"sphinx.ext.githubpages",
]
myst_enable_extensions = ['colon_fence', 'deflist', 'dollarmath', 'html_image', 'substitution']
master_doc = "index"
project = "聪明办法学 Python"
copyright = "2022 - 2024 Datawhale P2S Team"
author = "P2S Team"
exclude_patterns = ["_build", "Thumbs.db", ".DS_Store", "**.ipynb_checkpoints"]
nitpicky = True
language = "zh_CN"
html_theme = "furo"
html_title = "<div align=center><small>聪明办法学 Python</small></div>"
html_logo = "./image/datawhale_logo.png"
html_theme_options = {
"announcement": "聪明办法学 Python 在线文档 Beta 测试",
"source_repository": "https://github.com/anine09/p2s-book",
"source_branch": "main",
"source_directory": "docs/",
}
nb_number_source_lines = True
nb_execution_mode = 'off'
nb_execution_in_temp = True

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1. AI Master —— 李宏毅 机器学习
![](chap1_1_AIMaster.jpg)
2. [Brian Kernighan](https://en.wikipedia.org/wiki/Brian_Kernighan#/media/File:Brian-Kernighan-2017.png)
![](chap1_1_464px-Brian-Kernighan-2017.png)

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---
sd_hide_title: true
---
# sphinx-design
::::::{div} landing-title
:style: "padding: 0.1rem 0.5rem 0.6rem 0; background-image: linear-gradient(315deg, #438ff9 0%, #1572f4 74%); clip-path: polygon(0px 0px, 100% 0%, 100% 100%, 0% calc(100% - 1.5rem)); -webkit-clip-path: polygon(0px 0px, 100% 0%, 100% 100%, 0% calc(100% - 1.5rem));"
::::{grid}
:reverse:
:gutter: 2 3 3 3
:margin: 4 4 1 2
:::{grid-item}
:columns: 12 4 4 4
```{image} ./image/white_datawhale_logo.png
:width: 300px
:class: sd-m-auto sd-animate-grow50-rot20
```
:::
:::{grid-item}
:columns: 12 8 8 8
:child-align: justify
:class: sd-text-white sd-fs-3
简明且系统的 Python 入门教程
```{button-link} https://datawhalechina.github.io/learn-python-the-smart-way-v2/
:ref-type: doc
:outline:
:color: white
:class: sd-px-4 sd-fs-5
课程主页
```
:::
::::
::::::
:::::{tab-set}
::::{tab-item} 基础部分
:::{dropdown} Chapter 0 安装 Installation
:animate: fade-in-slide-down
:color: primary
```{toctree}
:maxdepth: 2
:caption: 目录
chapter_0-Installation.ipynb
```
:::
:::{dropdown} Chapter 1 启航 Getting Started
:animate: fade-in-slide-down
:color: primary
<p>目录</p>
```{toctree}
:maxdepth: 2
chapter_1-Getting_Started.ipynb
```
:::
::::
::::{tab-item} 进阶部分
筹划中，敬请期待。
::::
:::::

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