English | 2022 | ISBN: 1617297933 | 374 pages | PDF,EPUB | 12.45 MB

Master these effective techniques to reduce costs and run s, handle huge datasets, and implement complex machine learning applications efficiently in Python.

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 underperfog code with multithreading, and simplify your datasets without sacrificing accuracy.

about the technology

Fast, accurate systems are vital for handling the huge datasets and complex analytical algorithms that are common in modern data science. Python programmers need to boost performance by writing faster pure-Python programs, optimizing the use of libraries, and utilizing modern multi-processor hardware; Fast Python shows you how.

about the book

Fast Python is a hands-on guide to writing Python code that can process more data, faster, and with less resources. It takes a holistic approach to Python performance, showing you how your code, libraries, and computing architecture interact and can be optimized together.

Written for experienced practitioners, this book dives right into practical solutions for improving computation and storage efficiency. You'll expent with fun and interesting examples such as rewriting games in lower-level 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.

what's inside

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

about the reader

For intermediate Python programmers familiar with the basics of concurrency.