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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


This chapter has shown us how multiprocessing works, how we can pool a lot of jobs, and how we should share data between multiple processes. But more interestingly, it has also shown how we can distribute processing across multiple machines which helps a lot in speeding up heavy calculations.

The most important lesson you can learn from this chapter is that you should always try to avoid data sharing and synchronisation between multiple processes or servers, as it is slow and will thus slow down your applications a lot. Whenever possible, keep your calculations and data local.

In the next chapter we will learn about creating extensions in C/C++ to increase performance and allow low-level access to memory and other hardware resources. While Python will generally protect you from silly mistakes, C and C++ most certainly won't.

 

"C makes it easy to shoot yourself in the foot; C++ makes it harder, but when you do, it blows away your whole leg."

 
 --Bjarne Stroustrup (the creator of C++)
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Mastering Python
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