# Summary * [介绍](README.md) ## Python语言相关 - [Python Common](./Python Common/README.md) - [3.5.1](./Python Common/3.5.1/README.md) - [What's New in Python xx](./Python Common/What's New in Python xx/README.md) - [New In Python：变量注解语法](./Python Common/What's New in Python xx/New In Python：变量注解语法.md) - [New in Python：数字字面量中的下划线](./Python Common/What's New in Python xx/New in Python：数字字面量中的下划线.md) - [Python 2和3中的异常泄漏](./Python Common/Python 2和3中的异常泄漏.md) - [为什么存在Python 3](./Python Common/为什么存在Python 3.md) - [Python async-await教程](./Python Common/Python async-await教程.md) - [hasattr()是有害的](./Python Common/hasattr()是有害的.md) - [异常 - 原力的黑暗面](./Python Common/异常 - 原力的黑暗面.md) - [Python Cookbook 3rd Edition Documentation(中文版)](http://python3-cookbook.readthedocs.org/zh_CN/latest/index.html) - [什么是stackless](./Python Common/什么是stackless.md) - [2016年的Python 3](./Python Common/2016年的Python 3.md) - [合并Python中的字典的惯用方法](./Python Common/合并Python中的字典的惯用方法.md) - [惯用Python：推导](./Python Common/惯用Python：推导.md) - [在Python 3中比较类型](./Python Common/在Python 3中比较类型.md) - [Python 201 – 什么是双端队列(deque)](./Python Common/Python 201 – 什么是双端队列(deque).md) - [高级asyncio测试](./Python Common/高级asyncio测试.md) - [惯用Python：布尔表达式](./Python Common/惯用Python：布尔表达式.md) - [base64-使用ASCII编码二进制数据](./Python Common/base64-使用ASCII编码二进制数据.md) - [Lists和Tuples大对决](./Python Common/Lists和Tuples大对决.md) - [解释python中的*args和**kwargs](./Python Common/解释python中的*args和**kwargs.md) - [深度探索Python：让我们审查dict模块](./Python Common/深度探索Python：让我们审查dict模块.md) - [不可不知的一点Python陷阱](./Python Common/不可不知的一点Python陷阱.md) - [Python：声明动态属性](./Python Common/Python：声明动态属性.md) - [了解Python类实例化](./Python Common/了解Python类实例化.md) - [Python中的assert语句](./Python Common/Python中的assert语句.md) - [Python新增的secrets模块](./Python Common/Python新增的secrets模块.md) - [Python中的lambda表达式](./Python Common/Python中的lambda表达式.md) - [我是如何修复 Python 3.7 中一个非常老的 GIL 竞争条件的](./Python Common/python37-gil-change.md) ## Web框架 - [Django](./Django/README.md) - [1.9](./Django/1.9/README.md) Django 1.9版本官方文档 - [使用Django进行原型化](./Django/使用Django进行原型化.md) - [使用Kubernetes使Django应用变得可扩展并具有弹性](./Django/使用Kubernetes使Django应用变得可扩展并具有弹性.md) - [Django, ELB健康检查和持续交付](./Django/Django, ELB健康检查和持续交付.md) - [带django教程的Facebook聊天机器人，又名笑话机器人](./Django/带django教程的Facebook聊天机器人，又名笑话机器人.md) - [在Django中，如何为提高页面加载速度优化图像](./Django/在Django中，如何为提高页面加载速度优化图像.md) - [Django Channels和Celery示例](./Django/Django Channels和Celery示例.md) - [如何扩展Django User模型](./Django/如何扩展Django User模型.md) - [Django中正确处理数据库并发的方法](./Django/Django中正确处理数据库并发的方法.md) - [Flask](./Flask/README.md) ## web爬取 - [Scrapy](./Scrapy/README.md) - [Scrapinghub的Scrapy技巧系列](./Scrapy/Scrapinghub的Scrapy技巧系列/README.md) - [跟着高手学习Scrapy技巧：第一部分](./Scrapy/Scrapinghub的Scrapy技巧系列/跟着高手学习Scrapy技巧：第一部分.md) - [Scrapy技巧：2016年三月版](./Scrapy/Scrapinghub的Scrapy技巧系列/Scrapy技巧：2016年三月版.md) - [Scrapy技巧：2016年四月版](./Scrapy/Scrapinghub的Scrapy技巧系列/Scrapy技巧：2016年四月版.md) - [Scrapy技巧：2016年五月版](./Scrapy/Scrapinghub的Scrapy技巧系列/Scrapy技巧：2016年五月版.md) - [Scrapy技巧：2016年六月版](./Scrapy/Scrapinghub的Scrapy技巧系列/Scrapy技巧：2016年六月版.md) - [Scrapy技巧：2016年七月版](./Scrapy/Scrapinghub的Scrapy技巧系列/Scrapy技巧：2016年七月版.md) ## DevOps工具 - Fabric: [中文版](http://fabric-chs.readthedocs.org/zh_CN/chs/) | [英文版](http://docs.fabfile.org/en/1.11/index.html) - [Glances](https://github.com/nicolargo/glances)：[中文版](http://glances-zh.readthedocs.io/en/latest/) | [英文版](https://glances.readthedocs.io/en/latest/) ## 测试 - [Testing](./Testing/README.md) - [Python Mock：简单介绍 —— 第一部分](./Testing/Python Mock：简单介绍 —— 第一部分.md) - [在Python中使用Behave来开始行为测试](./Testing/在Python中使用Behave来开始行为测试.md) - [基于属性的测试，hypothesis以及查找bug](./Testing/基于属性的测试，hypothesis以及查找bug.md) ## 硬件 - [Hardware](./Hardware/README.md) - 用Python玩转Worcester Wave恒温器 * [第一部分](./Hardware/用Python玩转Worcester Wave恒温器-第一部分.md) * [第二部分](./Hardware/用Python玩转Worcester Wave恒温器-第二部分.md) * [第三部分](./Hardware/用Python玩转Worcester Wave恒温器-第三部分.md) - [使用Python构建一个（半）自动无人机](./Hardware/使用Python构建一个（半）自动无人机.md) - [旅程中带着Ipad Pro和Raspberry Pi备份照片](./Hardware/旅程中带着Ipad Pro和Raspberry Pi备份照片.md) ## 科学计算和数据分析 - [Science and Data Analysis](./Science and Data Analysis/README.md) - [如何使用Python和Pandas处理大量的JSON数据集](./Science and Data Analysis/如何使用Python和Pandas处理大量的JSON数据集.md) - [新闻标题分析](./Science and Data Analysis/新闻标题分析.md) - [使用矩阵分解找到相似歌曲](./Science and Data Analysis/使用矩阵分解找到相似歌曲.md) - [Python中的并行处理](./Science and Data Analysis/Python中的并行处理.md) - [Matplotlib教程 - 绘制提到Trump, Clinton & Sanders的推特](./Science and Data Analysis/Matplotlib教程 - 绘制提到Trump, Clinton & Sanders的推特.md) - [使用Pandas, Docker和OS(R)M来猜测神秘的旅行地](./Science and Data Analysis/使用Pandas, Docker和OS(R)M来猜测神秘的旅行地.md) - [使用BigQuery和TensorFlow进行需求预测](./Science and Data Analysis/使用BigQuery和TensorFlow进行需求预测.md) - [Python中一个简单的基于内容的推荐引擎](./Science and Data Analysis/Python中一个简单的基于内容的推荐引擎.md) - [在Python中实现你自己的推荐系统](./Science and Data Analysis/在Python中实现你自己的推荐系统.md) - [分析权力游戏图表](./Science and Data Analysis/分析权力游戏图表.md) - [使用Python探索NFL选秀](./Science and Data Analysis/使用Python探索NFL选秀.md) - [用于格式化和数据清理的便捷Python库](./Science and Data Analysis/用于格式化和数据清理的便捷Python库.md) - [分析iPhone步数数据](./Science and Data Analysis/分析iPhone步数数据.md) - [使用Python，分析23AndMe数据，获取遗传起源](./Science and Data Analysis/使用Python，分析23AndMe数据，获取遗传起源.md) - [用Python进行股票市场数据分析概述 (第一部分)](./Science and Data Analysis/用Python进行股票市场数据分析概述 (第一部分).md) ## 自然语言处理 - [NLP](./NLP/README.md) - [003构建一个播客推荐算法](./NLP/003构建一个播客推荐算法.md) ## 机器学习 - [Machine Learning](./Machine Learning/README.md) - [使用非常少的数据构建强大的图像分类模型](./Machine Learning/使用非常少的数据构建强大的图像分类模型.md) - [在有限预算上计算最佳公路旅行](./Machine Learning/在有限预算上计算最佳公路旅行.md) - [对超过1M的酒店点评进行机器学习，发现有趣的见解](./Machine Learning/对超过1M的酒店点评进行机器学习，发现有趣的见解.md) - [Python，机器学习和语言之争](./Machine Learning/Python，机器学习和语言之争.md) - [使用预测算法追踪实时健康趋势](./Machine Learning/使用预测算法追踪实时健康趋势.md) ## 函数式编程 - [Functional Programming](./Functional Programming/README.md) - Henry Kupty的函数式编程扫盲系列 - [函数式编程：概念，惯用语和理念](./Functional Programming/函数式编程：概念，惯用语和理念.md) - [了解函数式编程背后的属性：单子(Monad)](./Functional Programming/了解函数式编程背后的属性：单子(Monad).md) ## 图像处理 - [Image Processing](./Image Processing/README.md) - [压缩和增强手写笔记](./Image Processing/压缩和增强手写笔记.md) ## 资源 - [Python Weekly](./Python Weekly/README.md) - [Issue 243](./Python Weekly/Python_Weekly_Issue_243.md) - [Issue 244](./Python Weekly/Python_Weekly_Issue_244.md) - [Issue 245](./Python Weekly/Python_Weekly_Issue_245.md) - [Issue 246](./Python Weekly/Python_Weekly_Issue_246.md) - [Issue 247](./Python Weekly/Python_Weekly_Issue_247.md) - [Issue 248](./Python Weekly/Python_Weekly_Issue_248.md) - [Issue 249](./Python Weekly/Python_Weekly_Issue_249.md) - [Issue 250](./Python Weekly/Python_Weekly_Issue_250.md) - [Issue 251](./Python Weekly/Python_Weekly_Issue_251.md) - [Issue 252](./Python Weekly/Python_Weekly_Issue_252.md) - [Issue 253](./Python Weekly/Python_Weekly_Issue_253.md) - [Issue 254](./Python Weekly/Python_Weekly_Issue_254.md) - [Issue 255](./Python Weekly/Python_Weekly_Issue_255.md) - [Issue 256](./Python Weekly/Python_Weekly_Issue_256.md) - [Issue 257](./Python Weekly/Python_Weekly_Issue_257.md) - [Issue 258](./Python Weekly/Python_Weekly_Issue_258.md) - [Issue 259](./Python Weekly/Python_Weekly_Issue_259.md) - [Issue 260](./Python Weekly/Python_Weekly_Issue_260.md) - [Issue 261](./Python Weekly/Python_Weekly_Issue_261.md) - [Issue 262](./Python Weekly/Python_Weekly_Issue_262.md) - [Issue 263](./Python Weekly/Python_Weekly_Issue_263.md) - [Issue 264](./Python Weekly/Python_Weekly_Issue_264.md) - [Issue 265](./Python Weekly/Python_Weekly_Issue_265.md) - [Issue 266](./Python Weekly/Python_Weekly_Issue_266.md) - [Issue 267](./Python Weekly/Python_Weekly_Issue_267.md) - [Issue 268](./Python Weekly/Python_Weekly_Issue_268.md) - [Issue 269](./Python Weekly/Python_Weekly_Issue_269.md) - [Issue 270](./Python Weekly/Python_Weekly_Issue_270.md) - [Issue 271](./Python Weekly/Python_Weekly_Issue_271.md) - [Issue 272](./Python Weekly/Python_Weekly_Issue_272.md) - [Issue 273](./Python Weekly/Python_Weekly_Issue_273.md) - [Issue 274](./Python Weekly/Python_Weekly_Issue_274.md) - [Issue 275](./Python Weekly/Python_Weekly_Issue_275.md) - [Issue 276](./Python Weekly/Python_Weekly_Issue_276.md) - [Issue 277](./Python Weekly/Python_Weekly_Issue_277.md) - [Issue 278](./Python Weekly/Python_Weekly_Issue_278.md) - [Issue 279](./Python Weekly/Python_Weekly_Issue_279.md) - [Issue 280](./Python Weekly/Python_Weekly_Issue_280.md) - [Issue 281](./Python Weekly/Python_Weekly_Issue_281.md) - [Issue 282](./Python Weekly/Python_Weekly_Issue_282.md) - [Issue 283](./Python Weekly/Python_Weekly_Issue_283.md) - [Issue 284](./Python Weekly/Python_Weekly_Issue_284.md) - [Issue 285](./Python Weekly/Python_Weekly_Issue_285.md) - [Issue 286](./Python Weekly/Python_Weekly_Issue_286.md) - [Issue 287](./Python Weekly/Python_Weekly_Issue_287.md) - [Issue 288](./Python Weekly/Python_Weekly_Issue_288.md) - [Issue 289](./Python Weekly/Python_Weekly_Issue_289.md) - [Issue 290](./Python Weekly/Python_Weekly_Issue_290.md) - [Issue 291](./Python Weekly/Python_Weekly_Issue_291.md) - [Issue 292](./Python Weekly/Python_Weekly_Issue_292.md) - [Issue 293](./Python Weekly/Python_Weekly_Issue_293.md) - [Issue 294](./Python Weekly/Python_Weekly_Issue_294.md) - [Issue 295](./Python Weekly/Python_Weekly_Issue_295.md) - [Issue 296](./Python Weekly/Python_Weekly_Issue_296.md) - [Issue 297](./Python Weekly/Python_Weekly_Issue_297.md) - [Issue 298](./Python Weekly/Python_Weekly_Issue_298.md) - [Issue 299](./Python Weekly/Python_Weekly_Issue_299.md) - [Issue 300](./Python Weekly/Python_Weekly_Issue_300.md) - [Issue 301](./Python Weekly/Python_Weekly_Issue_301.md) - [Issue 302](./Python Weekly/Python_Weekly_Issue_302.md) - [Issue 303](./Python Weekly/Python_Weekly_Issue_303.md) - [Issue 304](./Python Weekly/Python_Weekly_Issue_304.md) - [Issue 305](./Python Weekly/Python_Weekly_Issue_305.md) - [Issue 306](./Python Weekly/Python_Weekly_Issue_306.md) - [Issue 307](./Python Weekly/Python_Weekly_Issue_307.md) - [Issue 308](./Python Weekly/Python_Weekly_Issue_308.md) - [Issue 309](./Python Weekly/Python_Weekly_Issue_309.md) - [Issue 310](./Python Weekly/Python_Weekly_Issue_310.md) - [Issue 311](./Python Weekly/Python_Weekly_Issue_311.md) - [Issue 312](./Python Weekly/Python_Weekly_Issue_312.md) - [Issue 313](./Python Weekly/Python_Weekly_Issue_313.md) - [Issue 314](./Python Weekly/Python_Weekly_Issue_314.md) - [Issue 315](./Python Weekly/Python_Weekly_Issue_315.md) - [Issue 316](./Python Weekly/Python_Weekly_Issue_316.md) - [Issue 317](./Python Weekly/Python_Weekly_Issue_317.md) - [Issue 318](./Python Weekly/Python_Weekly_Issue_318.md) - [Issue 319](./Python Weekly/Python_Weekly_Issue_319.md) - [Issue 320](./Python Weekly/Python_Weekly_Issue_320.md) - [Issue 321](./Python Weekly/Python_Weekly_Issue_321.md) - [Issue 322](./Python Weekly/Python_Weekly_Issue_322.md) - [Issue 323](./Python Weekly/Python_Weekly_Issue_323.md) - [Issue 324](./Python Weekly/Python_Weekly_Issue_324.md) - [Issue 325](./Python Weekly/Python_Weekly_Issue_325.md) - [Issue 326](./Python Weekly/Python_Weekly_Issue_326.md) - [Issue 327](./Python Weekly/Python_Weekly_Issue_327.md) - [Issue 328](./Python Weekly/Python_Weekly_Issue_328.md) - [Issue 329](./Python Weekly/Python_Weekly_Issue_329.md) - [Issue 330](./Python Weekly/Python_Weekly_Issue_330.md) - [Issue 331](./Python Weekly/Python_Weekly_Issue_331.md) - [Issue 332](./Python Weekly/Python_Weekly_Issue_332.md) - [Issue 333](./Python Weekly/Python_Weekly_Issue_333.md) - [Issue 334](./Python Weekly/Python_Weekly_Issue_334.md) - [Issue 335](./Python Weekly/Python_Weekly_Issue_335.md) - [Issue 336](./Python Weekly/Python_Weekly_Issue_336.md) - [Issue 337](./Python Weekly/Python_Weekly_Issue_337.md) - [Issue 338](./Python Weekly/Python_Weekly_Issue_338.md) - [Issue 339](./Python Weekly/Python_Weekly_Issue_339.md) - [Issue 340](./Python Weekly/Python_Weekly_Issue_340.md) - [Issue 341](./Python Weekly/Python_Weekly_Issue_341.md) - [Issue 342](./Python Weekly/Python_Weekly_Issue_342.md) - [Issue 343](./Python Weekly/Python_Weekly_Issue_343.md) - [Issue 344](./Python Weekly/Python_Weekly_Issue_344.md) - [Issue 345](./Python Weekly/Python_Weekly_Issue_345.md) - [Issue 346](./Python Weekly/Python_Weekly_Issue_346.md) - [Issue 347](./Python Weekly/Python_Weekly_Issue_347.md) - [Issue 348](./Python Weekly/Python_Weekly_Issue_348.md) - [Issue 349](./Python Weekly/Python_Weekly_Issue_349.md) - [Issue 350](./Python Weekly/Python_Weekly_Issue_350.md) - [Issue 351](./Python Weekly/Python_Weekly_Issue_351.md) - [Issue 352](./Python Weekly/Python_Weekly_Issue_352.md) - [Issue 353](./Python Weekly/Python_Weekly_Issue_353.md) - [Issue 354](./Python Weekly/Python_Weekly_Issue_354.md) - [Issue 355](./Python Weekly/Python_Weekly_Issue_355.md) - [Issue 356](./Python Weekly/Python_Weekly_Issue_356.md) - [Issue 357](./Python Weekly/Python_Weekly_Issue_357.md) - Pycoder's Weekly * 中文版：[蟒周刊](http://weekly.pychina.org/) ## 无法归类的 - [Others](./Others/README.md) - [使用图像特征的库存图像相似性(程序是如何比我更时尚的)](./Others/程序是如何比我更时尚的.md) - [如何在Python中使用Twilio Lookup API验证电话号码](./Others/如何在Python中使用Twilio Lookup API验证电话号码.md) - [psutil 4.0.0以及如何获得Python中“真正的”进程内存和环境](./Others/psutil 4.0.0以及如何获得Python中“真正的”进程内存和环境.md) - [Python依赖关系分析](./Others/Python依赖关系分析.md) - [创造你自己的类IPython服务器](./Others/创造你自己的类IPython服务器.md) - [为部署Python web应用程序构建一个更好的用户体验](./Others/为部署Python web应用程序构建一个更好的用户体验.md) - [在Python中导入一个Docker容器](./Others/在Python中导入一个Docker容器.md) - [好吧，你发布了一个损坏的包到PyPI上。那么你现在要怎么办？](./Others/好吧，你发布了一个损坏的包到PyPI上。那么你现在要怎么办？.md) - [Python中Meta类习语的起源](./Others/Python中Meta类习语的起源.md) - [复合构建器模式(Composite Builder Pattern)，一个声明式编程的例子](./Others/复合构建器模式(Composite Builder Pattern)，一个声明式编程的例子) - [将Python用于地理空间数据处理](./Others/将Python用于地理空间数据处理.md) - [使用Python和Excel进行交互式数据分析](./Others/使用Python和Excel进行交互式数据分析.md) - [RPython的魔力](./Others/RPython的魔力.md) - [使用gdb调试CPython进程](./Others/使用gdb调试CPython进程.md) - [使用Python Newspaper构建Read It Later应用](./Others/使用Python Newspaper构建Read It Later应用.md) - [Python lambda的源代码](./Others/Python lambda的源代码.md) - [如何在Python中创建绿噪音](./Others/如何在Python中创建绿噪音.md) - [你需要学习编写Python装饰器的五大理由](./Others/你需要学习编写Python装饰器的五大理由.md) - [逆向工程我的酒店中的一个神秘的UDP流](./Others/逆向工程我的酒店中的一个神秘的UDP流.md) - [记录每天数以百万计的请求以及需要采取哪些措施](./Others/记录每天数以百万计的请求以及需要采取哪些措施.md) - [教程：手把手教你构建一个基本的Facebook聊天机器人](./Others/教程：手把手教你构建一个基本的Facebook聊天机器人.md) - [我的自动化之旅：为人民服务的自动化](./Others/我的自动化之旅：为人民服务的自动化.md) - [实用Python：EAFP VS. LBYL](./Others/实用Python：EAFP VS. LBYL.md) - [使用str.encode和threads冻结你的Python](./Others/使用str.encode和threads冻结你的Python.md) - [Python, GIL, 和Pyston](./Others/Python, GIL, 和Pyston.md) - [我是如何构建一个Slack机器人来帮助我在San Francisco找房子的](./Others/我是如何构建一个Slack机器人来帮助我在San Francisco找房子的.md) - [中断两个循环](./Others/中断两个循环.md) - [一个模板引擎是如何工作的？](./Others/一个模板引擎是如何工作的？.md) - [设计Pythonic API](./Others/设计Pythonic API.md) - [Requests vs. urllib：它解决了什么问题？](./Others/Requests vs. urllib：它解决了什么问题？.md) - [更好的Python对象序列化方法](./Others/更好的Python对象序列化方法.md) - [使用列表推导式实现zip](./Others/使用列表推导式实现zip.md) - [Python项目中的Makefiles](./Others/Python项目中的Makefiles.md) - [婚礼规模：我是如何使用Twilio, Python和Google来自动化我的婚礼的](./Others/婚礼规模：我是如何使用Twilio, Python和Google来自动化我的婚礼的.md) # [小黑屋](./raw/README.md)