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Bibliografische Details

Titel: The Hacker's Guide to Scaling Python
Verlag: Lulu.com
Ver�ffentlichungsdatum: 2017
Sprache: Englisch
ISBN-10: 1387379321
ISBN-13: 9781387379323
Bindung: Softcover
Zustand: good

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Inhaltsangabe

Python is an excellent programming language that allows to write applications quickly. But how do you make those applications scale for thousands of users and requests? It takes years of practice, research, trial and errors to build experience and knowledge along the way. Simple questions such as "How do I make my code faster?", "How do I make sure there is no bottleneck?" or "How do I run this application on several computers?" cost hours to find satisfying answers. Without enough background on the topic, you'll never be sure that any solution you'll come up with will be correct. In The Hacker's Guide to Scaling Python, you will learn how to solve these issues. This book provides guidelines, tips and best practice on how to build high performing Python applications. Adding a few interview of experts on the subject, you will learn how you can distribute your Python application so it can process thousands of requests.

Rese�a del editor

Python is an excellent programming language that allows to write applications quickly. But how do you make those applications scale for thousands of users and requests? It takes years of practice, research, trial and errors to build experience and knowledge along the way. Simple questions such as ""How do I make my code faster?"", ""How do I make sure there is no bottleneck?"" or ""How do I run this application on several computers?"" cost hours to find satisfying answers. Without enough background on the topic, you'll never be sure that any solution you'll come up with will be correct. In The Hacker's Guide to Scaling Python, you will learn how to solve these issues. This book provides guidelines, tips and best practice on how to build high performing Python applications. Adding a few interview of experts on the subject, you will learn how you can distribute your Python application so it can process thousands of requests.

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