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<p>Numpy与Pandas是两个强有力的数据分析工具包，它在机器学习与深度学习里都会用到。它们的运算速度快，其中numpy是由C语言编写，而pandas又是在numpy基础上实现的，另外，它们采用矩阵运算，消耗资源少，比python缺省的字典或者列表快多了。</p>
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<p>现在的数据处理，特别在互联网领域中，很大部分是字符类数据的处理。而该类数据一个主要处理就是：字符或字符串的匹配处理。我们知道这种匹配处理正是正规则表达式的用武之地。同样在Python的标准库中，有re模块正是用于字符串匹配发现。<br>这里我们并不打算对正则表达式进行太细的讨论，正则表达式中规则多，各种操作千变万化，我们也记不清。这里主要讲讲python中正则表达式的主体流程，细的匹配规则，可以查找下类似下面的文档或手册：<br>[Python正则表达式指南]<a href="https://www.cnblogs.com/huxi/archive/2010/07/04/1771073.html" target="_blank" rel="noopener">https://www.cnblogs.com/huxi/archive/2010/07/04/1771073.html</a></p>
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<p>数据除了要保存在内存，有时，还需要进行序列化，保存到磁盘上。python标准库中的pickle模块，就提供了文件的压缩、保存与提取功能。</p>
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<p>threading让程序更灵活，但在数据处理效率上，并不能提高太多。而multiprocessing，可以充分利用当下计算机多处理器的特性，可以让任务执行分摊至各个处理器，从而成倍地提高效率。</p>
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