Название: Fast Python: High performance techniques for large datasets (Final Release)
Автор: Tiago Rodriques Antao
Издательство: Manning Publications
Год: 2023
Страниц: 304
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Master Python techniques and libraries to reduce run times, efficiently handle huge datasets, and optimize execution for complex machine learning applications.

Fast Python is a toolbox of techniques for high performance Python including:

Writing efficient pure-Python code
Optimizing the NumPy and pandas libraries
Rewriting critical code in Cython
Designing persistent data structures
Tailoring code for different architectures
Implementing Python GPU computing

The purpose of this book is to help you write more efficient applications in the Python ecosystem. By more efficient, I mean that your code will use fewer CPU cycles, less storage space, and less network communication. The book takes a holistic approach to the problem of performance. We not only discuss code optimization techniques in pure Python, but we also consider the efficient use of widely used data libraries, like NumPy and Pandas. Because Python is not sufficiently performant in some cases, we also consider Cython when we need more speed. In line with this holistic approach, we also discuss the impact of hardware on code design: we analyze the impact of modern computer architectures on algorithm performance. We also examine the effect of network architectures on efficiency, and we explore the usage of GPU computing for fast data analysis.

Fast Python is your guide to optimizing every part of your Python-based data analysis process, from the pure Python code you write to managing the resources of modern hardware and GPUs. You'll learn to rewrite inefficient data structures, improve underperforming code with multithreading, and simplify your datasets without sacrificing accuracy.

Written for experienced practitioners, this book dives right into practical solutions for improving computation and storage efficiency. You'll experiment with fun and interesting examples such as rewriting games in Cython and implementing a MapReduce framework from scratch. Finally, you'll go deep into Python GPU computing and learn how modern hardware has rehabilitated some former antipatterns and made counterintuitive ideas the most efficient way of working.

About the Technology:
Face it. Slow code will kill a Big Data project. Fast pure-Python code, optimized libraries, and fully utilized multiprocessor hardware are the price of entry for machine learning and large-scale data analysis. What you need are reliable solutions that respond faster to computing requirements while using less resources, and saving money.

About the Book:
Fast Python is a toolbox of techniques for speeding up Python, with an emphasis on Big Data applications. Following the clear examples and precisely articulated details, you’ll learn how to use common libraries like NumPy and pandas in more performant ways and transform data for efficient storage and I/O. More importantly, Fast Python takes a holistic approach to performance, so you’ll see how to optimize the whole system, from code to architecture .

What’s Inside:

Rewriting critical code in Cython
Designing persistent data structures
Tailoring code for different architectures
Implementing Python GPU computing

About the Reader:
For intermediate Python programmers familiar with the basics of concurrency.