High Performance Python

Micha Gorelick, Ian Ozsvald

ISBN 10: 1492055026 / ISBN 13: 9781492055020

Verlag: O'Reilly Media, US, 2020

Beschreibung

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 profilersLearn how Python abstracts the underlying computer architectureUse profiling to find bottlenecks in CPU time and memory usageWrite efficient programs by choosing appropriate data structuresSpeed up matrix and vector computationsUse tools to compile Python down to machine codeManage multiple I/O and computational operations concurrentlyConvert multiprocessing code to run on local or remote clustersDeploy code faster using tools like Docker.

Bestandsnummer des Verkäufers LU-9781492055020

Bibliografische Details

• Titel: High Performance Python
• Verlag: O'Reilly Media, US
• Erscheinungsjahr: 2020
• Sprache: Englisch
• ISBN-10: 1492055026
• ISBN-13: 9781492055020
• Einband: Paperback
• Auflage: 2. Auflage
• Zustand: New

Über diesen Titel

Inhaltsangabe

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

Über die Autorin bzw. den Autor

Ian is a chief data scientist and coach. He co-organizes the annualPyDataLondon 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 ofexperience as a senior data science leader, trainer and team coach.For fun he's walked by his high-energy Springer Spaniel, surfs theCornish coast and drinks fine coffee. Past talks and articles can befound at: https: //ianozsvald.com/