Book Image

Mastering Python 2E - Second Edition

By : Rick van Hattem
5 (1)
Book Image

Mastering Python 2E - Second Edition

5 (1)
By: Rick van Hattem

Overview of this book

Even if you find writing Python code easy, writing code that is efficient, maintainable, and reusable is not so straightforward. Many of Python’s capabilities are underutilized even by more experienced programmers. Mastering Python, Second Edition, is an authoritative guide to understanding advanced Python programming so you can write the highest quality code. This new edition has been extensively revised and updated with exercises, four new chapters and updates up to Python 3.10. Revisit important basics, including Pythonic style and syntax and functional programming. Avoid common mistakes made by programmers of all experience levels. Make smart decisions about the best testing and debugging tools to use, optimize your code’s performance across multiple machines and Python versions, and deploy often-forgotten Python features to your advantage. Get fully up to speed with asyncio and stretch the language even further by accessing C functions with simple Python calls. Finally, turn your new-and-improved code into packages and share them with the wider Python community. If you are a Python programmer wanting to improve your code quality and readability, this Python book will make you confident in writing high-quality scripts and taking on bigger challenges
Table of Contents (21 chapters)
19
Other Books You May Enjoy
20
Index

Generator examples

Now that you know how generators can be created, let’s look at a few useful generators and examples of how to use them.

Before you start writing a generator for your project, always make sure to look at the Python itertools module. It features a host of useful generators that cover a vast array of use cases. The following sections show some custom generators and a few of the most useful generators in the standard library.

These generators work on all iterables, not just generators. So, you could also apply them to a list, tuple, string, or other kinds of iterables.

Breaking an iterable up into chunks/groups

When executing large amounts of queries in a database or when running tasks via multiple processes, it is often more efficient to chunk the operations. Having a single huge operation could result in out-of-memory issues; having many tiny operations can be slow due to start-up/teardown sequences.

To make things more efficient...