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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


In this chapter, we saw how to use asynchronous I/O in Python using asyncio. For many scenarios, the asyncio module is still a bit raw and unfinished, but there should not be any obstacles in using it. Creating a fully functional server/client setup is still a tad complicated, but the most obvious use of asyncio is the handling of basic network I/O such as database connections and external resources such as websites. Especially, the latter takes only a few lines to implement with the use of asyncio, removing some very important bottlenecks from your code.

The point of this chapter is understanding how to tell Python to wait for results in the background instead of simply waiting or polling for them as usual. In Chapter 13, Multiprocessing – When a Single CPU Core Is Not Enough you will learn about multiprocessing, which is also an option for handling stalling resources. However, the goal of multiprocessing is actually to use multiple processors instead of handling stalling resources...

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Mastering Python
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