High Performance Python 2e: Practical Performant Programming for Humans

Gorelick, Micha Micha Gorelick, Ian Ozsvald,

ISBN 10: 1492055026 / ISBN 13: 9781492055020

Published by O†Reilly, 2020

About this Item

High Performance Python 2e: Practical Performant Programming for Humans This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .

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Bibliographic Details

• Title: High Performance Python 2e: Practical Performant Programming for Humans
• Publisher: Oâ Reilly
• Publication Date: 2020
• Language: English
• ISBN 10: 1492055026
• ISBN 13: 9781492055020
• Binding: paperback
• Edition: 2nd Edition
• Condition: Very Good

About this title

Synopsis

Your Python code may run correctly, but you need it to run faster. Updated for Python 3, this expanded edition shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. By exploring the fundamental theory behind design choices, High Performance Python helps you gain a deeper understanding of Python's implementation.

How do you take advantage of multicore architectures or clusters? Or build a system that scales up and down without losing reliability? Experienced Python programmers will learn concrete solutions to many issues, along with war stories from companies that use high-performance Python for social media analytics, productionized machine learning, and more.

• 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 local or remote clusters
• Deploy code faster using tools like Docker

About the Authors

Micha Gorelick cofounded Fast Forward Labs as resident mad scientist. The company was acquired by Cloudera in 2017. She works on many issues from machine learning to performant stream algorithms.

Ian is a chief data scientist and coach. He co-organizes the annual PyDataLondon conference with 700+ attendees and the associated 10,000+ member monthly meetup. He runs the established Mor Consulting Data Science consultancy in London and gives conference talks internationally, often as keynote speaker. He has 17 years of experience as a senior data science leader, trainer and team coach. For fun he's walked by his high-energy Springer Spaniel, surfs the Cornish coast and drinks fine coffee. Past talks and articles can be found at: https://ianozsvald.com/