High Performance Python: Practical Performant Programming for Humans

Gorelick, Micha; Ozsvald, Ian

ISBN 10: 1492055026 / ISBN 13: 9781492055020

Verlag: O'Reilly Media, 2020

Beschreibung

Gently read. May have name of previous ownership, or ex-library edition. Binding tight; spine straight and smooth, with no creasing; covers clean and crisp. Minimal signs of handling or shelving. 100% GUARANTEE! Shipped with delivery confirmation, if youâ re not satisfied with purchase please return item for full refund. Ships USPS Media Mail.

Bestandsnummer des Verkäufers OTV.1492055026.VG

Bibliografische Details

• Titel: High Performance Python: Practical Performant Programming for Humans
• Verlag: O'Reilly Media
• Veröffentlichungsdatum: 2020
• Sprache: Englisch
• ISBN-10: 1492055026
• ISBN-13: 9781492055020
• Bindung: Softcover
• Ausgabe: 2. Auflage
• Zustand: very_good

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/