Python运行速度慢？是你孤陋寡闻了？5个优化办法提速百分百
<h1 style="color: black; text-align: left; margin-bottom: 10px;">Python运行速度慢？是你孤陋寡闻了？5个优化<span style="color: black;">方法</span>提速百分百</h1>
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<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">北漂编程<span style="color: black;">2021-04-23 21:47</span></p>
<h1 style="color: black; text-align: left; margin-bottom: 10px;">速度慢</h1>
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<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">Python之<span style="color: black;">因此</span>速度慢，<span style="color: black;">重点</span>是<span style="color: black;">因为</span>动态性和多功能性。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">Python 的运行过程是虚拟机读入 Python 代码（文本），词法分析，编译成虚拟机认识的 opcode，<span style="color: black;">而后</span>虚拟机解释 opcode 执行。但这<span style="color: black;">并不</span>是最<span style="color: black;">重点</span>的<span style="color: black;">原由</span>，Python import 之后会缓存编译后的 opcode，<span style="color: black;">因此</span>读入、词法分析和编译并<span style="color: black;">无</span>占用太多的时间。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">那样</span>真正的慢的是哪一步分呢？<span style="color: black;">便是</span>后面的虚拟机解释 opcode 执行的部分。前期的编译是将 Python 代码编译成解释器<span style="color: black;">能够</span>理解的中间代码，解释器再将中间代码翻译成 CPU <span style="color: black;">能够</span>理解的指令。相比于 AOT（提前编译型语言，<span style="color: black;">例如</span>C）直接编译成<span style="color: black;">设备</span>码，肯定是慢的。</p>
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<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">下面是五种已有的<span style="color: black;">方法</span>，<span style="color: black;">帮忙</span>你<span style="color: black;">加强</span>Python的性能。</p>
<h1 style="color: black; text-align: left; margin-bottom: 10px;">Cython</h1>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">是Python的C语言扩展，cPython是一门单独的语言，专门用来写在Python里面的import用的扩展库。CPython跟Python语法基本一致，而CPython有专门的编译器。</p>
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://p26-sign.toutiaoimg.com/pgc-image/8c1a48f328a4430893541c9635a6aca0~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723895544&x-signature=iuivvC0KgOca3glbtvwhZVqyIXQ%3D" style="width: 50%; margin-bottom: 20px;"></div>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">据述</span>，Cython<span style="color: black;">供给</span>了<span style="color: black;">有些</span>特性来让代码更<span style="color: black;">有效</span>，<span style="color: black;">例如</span>变量类型化，这本质上是C<span style="color: black;">需求</span>的。<span style="color: black;">有些</span>科学计算的包，如scikit-learn依赖Cython的<span style="color: black;">有些</span>特性来保持操作简洁快速。</p>
<h1 style="color: black; text-align: left; margin-bottom: 10px;">Pyston</h1>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">Pyston，由Dropbox<span style="color: black;">帮助</span>，<span style="color: black;">运用</span>LLVM编译器架构来加速Python，<span style="color: black;">一样</span>的它<span style="color: black;">亦</span><span style="color: black;">运用</span>了适时编译。相比于PyPy，Pyston还<span style="color: black;">处在</span><span style="color: black;">初期</span><span style="color: black;">周期</span>，它只支持Python的部分特性。Pyston把工作分成两个部分，一部分是语言的核心特性，另一部分是把性能<span style="color: black;">提高</span>到可接受的程度。Pyston距离<span style="color: black;">能够</span>在生产环境<span style="color: black;">运用</span>还有一段距离</p>
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<h1 style="color: black; text-align: left; margin-bottom: 10px;">Nuitka</h1>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">是一个Python的替代品，它<span style="color: black;">能够</span>将Python代码转换为C++代码，<span style="color: black;">而后</span>编译为可执行文件，并且<span style="color: black;">经过</span>调用Python的API的方式实现从解析语言到编译语言的转换，在转换到C++的过程中直接<span style="color: black;">运用</span>python的解释器，<span style="color: black;">能够</span><span style="color: black;">保准</span>100%的语法兼容。</p>
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://p3-sign.toutiaoimg.com/pgc-image/b52806b8e1b24864abd0974f9c31576a~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723895544&x-signature=LZIm06KkOv9Eaf0a00W5PEkJ23o%3D" style="width: 50%; margin-bottom: 20px;"></div>
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<h1 style="color: black; text-align: left; margin-bottom: 10px;">Numba</h1>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">Numba结合了上面几个项目的想法。学习了Cython，Numba<span style="color: black;">亦</span>采用了部分加速的策略，只加速CPU密集型的任务；<span style="color: black;">同期</span>它又学习了PyPy和Pyston，<span style="color: black;">经过</span>LLVM运行Python。你<span style="color: black;">能够</span>用一个装饰器指定你要用Numba编译的函数，Numba继承Numpy来加速函数的执行，Numba不做适时编译，它的代码是预先编译的。</p>
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://p26-sign.toutiaoimg.com/pgc-image/52b57d8ea5554021a865fb52d5360d14~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723895544&x-signature=9%2FbPb%2BeVOd9QRZgwjZDJ9Rqpbmk%3D" style="width: 50%; margin-bottom: 20px;"></div>
<h1 style="color: black; text-align: left; margin-bottom: 10px;">PyPy</h1>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">在<span style="color: black;">选取</span>CPython的简易替代语言时，pypy无疑时最佳之选，与现有Python代码保持高度兼容性，pypy<span style="color: black;">亦</span>是默认程序运行时的一个很好<span style="color: black;">选取</span>。PyPy<span style="color: black;">运用</span>了Just-in-Time即时编译器，动态编译器与静态编译器<span style="color: black;">区别</span>，利用程序运行的过程的数据进行优化。</p>
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://p3-sign.toutiaoimg.com/pgc-image/3aa14dee7c8a498bad317dabaa631bac~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723895544&x-signature=fIoR1Nvuvhwxy%2BLUMGEGhGm5XZ8%3D" style="width: 50%; margin-bottom: 20px;"></div>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">PyPy<span style="color: black;">运用</span>适时编译来加速Python，这项技术Google<span style="color: black;">亦</span>在<span style="color: black;">运用</span>，Google在V8引擎中<span style="color: black;">运用</span>它加速Javascript。<span style="color: black;">近期</span>的版本PyPy2.5<span style="color: black;">增多</span>了<span style="color: black;">有些</span><span style="color: black;">提高</span>性能的特性，其中有一项很受欢迎，它集<span style="color: black;">成为了</span>Numpy，Numpy之前<span style="color: black;">亦</span><span style="color: black;">始终</span>被用来加速Python的运行。</p>
<h1 style="color: black; text-align: left; margin-bottom: 10px;">结语</h1>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">Python之父说：大部分觉得Python慢的应用都是<span style="color: black;">无</span>正确地<span style="color: black;">运用</span>Python。<span style="color: black;">针对</span>CPU密集型的任务有多种<span style="color: black;">办法</span>来提升性能--<span style="color: black;">运用</span>Numpy来做计算，调用<span style="color: black;">外边</span>C代码，以及<span style="color: black;">尽可能</span>避免GIL锁。<span style="color: black;">因为</span>GIL锁<span style="color: black;">日前</span>还<span style="color: black;">没法</span>被替代，</p>
<h1 style="color: black; text-align: left; margin-bottom: 10px;">彩蛋！！！</h1>
<h1 style="color: black; text-align: left; margin-bottom: 10px;"><span style="color: black;">必须</span>下面的资料的，还有<span style="color: black;">更加多</span>课件资源的，请私信我“666”领取！！！</h1>
<h1 style="color: black; text-align: left; margin-bottom: 10px;">私信我还有<span style="color: black;">更加多</span>惊喜哦！！！</h1>
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