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Mastering Python

Mastering Python

By : Rick Hattem
4 (11)
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Mastering Python

Mastering Python

4 (11)
By: Rick Hattem

Overview of this book

Python is a dynamic programming language. It is known for its high readability and hence it is often the first language learned by new programmers. Python being multi-paradigm, it can be used to achieve the same thing in different ways and it is compatible across different platforms. Even if you find writing Python code easy, writing code that is efficient, easy to maintain, and reuse is not so straightforward. This book is an authoritative guide that will help you learn new advanced methods in a clear and contextualised way. It starts off by creating a project-specific environment using venv, introducing you to different Pythonic syntax and common pitfalls before moving on to cover the functional features in Python. It covers how to create different decorators, generators, and metaclasses. It also introduces you to functools.wraps and coroutines and how they work. Later on you will learn to use asyncio module for asynchronous clients and servers. You will also get familiar with different testing systems such as py.test, doctest, and unittest, and debugging tools such as Python debugger and faulthandler. You will learn to optimize application performance so that it works efficiently across multiple machines and Python versions. Finally, it will teach you how to access C functions with a simple Python call. By the end of the book, you will be able to write more advanced scripts and take on bigger challenges.
Table of Contents (17 chapters)
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6
6. Generators and Coroutines – Infinity, One Step at a Time
16
Index

Summary

When it comes to performance, there is no holy grail, no single thing you can do to ensure peak performance in all cases. This shouldn't worry you however, as in most cases you will never need to tune the performance and if you do, a single tweak could probably fix your problem. You should be able to find performance problems and memory leaks in your code now which is what matters most, so just try to contain yourself and only tweak when it's actually needed.

The most important outtakes from this chapter are:

  • Test before you invest any effort. Making some functions faster seems like a great achievement but it is only rarely needed.
  • Choosing the correct data structure/algorithm is much more effective than any other performance optimization.
  • Circular references drain the memory until the garbage collector starts cleaning.
  • Slots are not worth the effort.

The next chapter will discuss multiprocessing, a library which makes it trivial to employ multiple processors for your scripts...

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Mastering Python
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