Python High Performance, 2nd Edition

Book Description

Learn how to use Python to create efficient applications

Key Features

• Identify the bottlenecks in your applications and solve them using the best profiling techniques
• Write efficient numerical code in NumPy, Cython, and Pandas
• Adapt your programs to run on multiple processors and machines with parallel programming

Book Description

Python is a versatile language that has found applications in many industries. The clean syntax, rich standard library, and vast selection of third-party libraries make Python a wildly popular language.

Python High Performance is a practical guide that shows how to leverage the power of both native and third-party Python libraries to build robust applications.

The book explains how to use various profilers to find performance bottlenecks and apply the correct algorithm to fix them. The reader will learn how to effectively use NumPy and Cython to speed up numerical code. The book explains concepts of concurrent programming and how to implement robust and responsive applications using Reactive programming. Readers will learn how to write code for parallel architectures using Tensorflow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark.

By the end of the book, readers will have learned to achieve performance and scale from their Python applications.

What you will learn

• Write efficient numerical code with the NumPy and Pandas libraries
• Use Cython and Numba to achieve native performance
• Find bottlenecks in your Python code using profilers
• Write asynchronous code using Asyncio and RxPy
• Use Tensorflow and Theano for automatic parallelism in Python
• Set up and run distributed algorithms on a cluster using Dask and PySpark

Table of Contents

1. Benchmarking and profiling
2. Pure Python Optimization techniques
3. Fast array operations
4. C performance with Cython
5. Exploring Compilers
6. Implementing concurrency
7. Parallel processing
8. Distributed Processing
9. Designing for High Performance

中文：

书名：Python High Performance, 2nd Edition

了解如何使用Python创建高效的应用程序

Key Features

• 找出应用程序中的瓶颈，并使用最佳的性能分析技术解决它们
• Write efficient numerical code in NumPy, Cython, and Pandas
• 通过并行编程使您的程序能够在多个处理器和机器上运行

Book Description

Python是一种多用途语言，已在许多行业中得到应用。干净的语法、丰富的标准库和大量的第三方库选择使Python成为一种广受欢迎的语言。

PythonHigh Performance是一个实用指南，它展示了如何利用本机和第三方Python库的强大功能来构建健壮的应用程序。

这本书解释了如何使用各种分析器来发现性能瓶颈并应用正确的算法来修复它们。读者将学习如何有效地使用NumPy和Cython来加速数字代码。这本书解释了并发编程的概念，以及如何使用反应式编程实现健壮和响应迅速的应用程序。读者将学习如何使用TensorFlow和Theano为并行体系结构编写代码，并使用DASK和PySpark等技术使用计算机集群进行大规模计算。

在本书的最后，读者将学会从他们的Python应用程序中获得性能和伸缩性。

你将学到什么

• 用NumPy和Pandas库编写高效的数值代码
• 使用Cython和Numba实现原生性能
• 使用探查器查找您的Python代码中的瓶颈
• 使用Asyncio和RxPy编写异步代码
• 在Python中使用TensorFlow和Theano实现自动并行
• 使用DASK和PySpark在群集上设置和运行分布式算法

Table of Contents

1. Benchmarking and profiling
2. 纯Python优化技术
3. 快速阵列操作
4. C performance with Cython
5. 探索编译器
6. 实现并发性
7. Parallel processing
8. 分布式处理
9. Designing for High Performance