So far, we have only executed our scripts on multiple local processors, but we can actually expand this further. Using the multiprocessing library, it's actually very easy to execute jobs on remote servers, but the documentation is currently still a bit cryptic. There are actually a few ways of executing processes in a distributed way, but the most obvious one isn't the easiest one. The multiprocessing.connection module has both the Client and Listener classes, which facilitate secure communication between the clients and servers in a simple way. Communication is not the same as process management and queue management however, those features requires some extra effort. The multiprocessing library is still a bit bare in this regard, but it's most certainly possible given a few different processes.
Mastering Python
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Mastering Python
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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.
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Table of Contents (22 chapters)
Mastering Python
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Getting Started – One Environment per Project
Pythonic Syntax, Common Pitfalls, and Style Guide
Containers and Collections – Storing Data the Right Way
Functional Programming – Readability Versus Brevity
Decorators – Enabling Code Reuse by Decorating
Generators and Coroutines – Infinity, One Step at a Time
Async IO – Multithreading without Threads
Metaclasses – Making Classes (Not Instances) Smarter
Documentation – How to Use Sphinx and reStructuredText
Testing and Logging – Preparing for Bugs
Debugging – Solving the Bugs
Performance – Tracking and Reducing Your Memory and CPU Usage
Multiprocessing – When a Single CPU Core Is Not Enough
Extensions in C/C++, System Calls, and C/C++ Libraries
Packaging – Creating Your Own Libraries or Applications
Index
Customer Reviews