高性能Python(影印版第2版)(英文版)

你的Python代码也许运 行正确，但是你需要运行 得更快。本书经过拓展后 的新版向你展示了如何在 高数据量程序中定位性能 瓶颈，显著提高代码速度 。通过探索设计选择背后 的基础理论，《高性能 Python》将帮助你更深入 地理解Python的实现。该 如何利用多核架构和集群 ？或者该如何构建能够自 由伸缩同时又不失可靠性 的系统？有经验的Python 程序员会学到很多问题的 具体解决方案，了解到各 个公司如何将高性能 Python应用于社交媒体分 析、产品机器学习等场景 的曲折故事。

Foreword Preface 1.Understanding Performant Python The Fundamental Computer System Computing Units Memory Units Communications Layers Putting the Fundamental Elements Together Idealized Computing Versus the Python Virtual Machine So Why Use Python? How to Be a Highly Performant Programmer Good Working Practices Some Thoughts on Good Notebook Practice Getting the Joy Back into Your Work 2.Profiling to Find Bottlenecks. Profiling Efficiently Introducing the Julia Set Calculating the Full Julia Set Simple Approaches to Timing—print and a Decorator Simple Timing Using the Unix time Command Using the cProfile Module Visualizing cProfile Output with SnakeViz Using line_profiler for Line-by-Line Measurements Using memory_profiler to Diagnose Memory Usage Introspecting an Existing Process with PySpy Bytecode: Under the Hood Using the dis Module to Examine CPython Bytecode Different Approaches, Different Co mplexity Unit Testing During Optimization to Maintain Correctness No-op @profile Decorator Strategies to Profile Your Code Successfully Wrap-Up 3.Lists and Tuples A More Efficient Search Lists Versus Tuples Lists as Dynamic Arrays Tuples as Static Arrays Wrap-Up 4.Dictionaries and Sets. How Do Dictionaries and Sets Work? Inserting and Retrieving Deletion Resizing Hash Functions and Entropy Dictionaries and Namespaces Wrap-Up 5.Iterators and Generators. Iterators for Infinite Series Lazy Generator Evaluation Wrap-Up