Micha Gorelick, Ian Ozsvald ... 370 pages- Publisher: O'Reilly Media; (September, 2014) ... Language: English - ISBN-10: 1449361595 - ISBN-13: 978-1449361594.
Your Python code may run correctly, but
you need it to run faster. By exploring the fundamental theory behind
design choices, this practical guide helps you gain a deeper
understanding of Python’s implementation. You’ll learn how to locate
performance bottlenecks and significantly speed up your code in
high-data-volume programs. How can you take advantage of
multi-core architectures or clusters? Or build a system that can scale
up and down without losing reliability? Experienced Python programmers
will learn concrete solutions to these and other issues, along with war
stories from companies that use high performance Python for social media
analytics, productionized machine learning, and other situations.
Get a better grasp of numpy, Cython and profilers + Learn how Python abstracts the underlying computer architecture + Use profiling to find bottlenecks in CPU time and memory usage + Write efficient programs by choosing appropriate data structures + Speed up matrix and vector computations + Use tools to compile Python down to machine code + Manage multiple I/O and computational operations concurrently + Convert multiprocessing code to run on a local or remote cluster + Solve large problems while using less RAM.
Get a better grasp of numpy, Cython and profilers + Learn how Python abstracts the underlying computer architecture + Use profiling to find bottlenecks in CPU time and memory usage + Write efficient programs by choosing appropriate data structures + Speed up matrix and vector computations + Use tools to compile Python down to machine code + Manage multiple I/O and computational operations concurrently + Convert multiprocessing code to run on a local or remote cluster + Solve large problems while using less RAM.