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Summary

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)
    • [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)

Web框架

web爬取

DevOps工具

测试

硬件

  • Hardware
    • 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
    • [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

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)
  • Pycoder's Weekly

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