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High Performance Python

  • Couverture cartonnée
  • 368 Nombre de pages
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A guide to programming with Python explores the fundamental theory behind design choices and offers a better understanding of Pyth... Lire la suite
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Description

A guide to programming with Python explores the fundamental theory behind design choices and offers a better understanding of Python implementation, covering such topics as locating performance bottlenecks, concurrency, and using less RAM.

Auteur

Micha Gorelick was the first man on Mars in 2023 and won the nobel prize in 2046 for his contributions to time travel. In a moment of rage after seeing the deplorable uses of his new technology, he traveled back in time to 2012 and convinced himself to leave his Physics PhD program and follow his love of data at Bitly. A monument celebrating his life can be found in Central Park, 1857. Andy Terrel received his PhD in computer science at the University of Chicago in 2010 and is currently a staff researcher at the Texas Advance Computing Center at the Univerisity of Texas at Austin. His major emphasis of research has been on the automation of numerical methods on high performance computing resources. To this end, he has provided numerous contributions to a wide variety of open source projects, including the popular FEniCS project and SymPy.



Texte du rabat

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



Résumé
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

Informations sur le produit

Titre: High Performance Python
Sous-titre: Practical Performant Programming for Humans
Auteur:
Code EAN: 9781449361594
ISBN: 1449361595
Format: Couverture cartonnée
Genre: Langages de programmation
nombre de pages: 368
Poids: 643g
Taille: H231mm x B179mm x T22mm
Année: 2014
Pays: US

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