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
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20
Index

Exercises

Many of the topics discussed in this chapter already gave full examples, leaving little room for exercises. There are additional resources to discover, however.

Reading the Python Enhancement Proposals (PEPs)

A good way to learn more about the topics discussed in this chapter (and all the following chapters) is to read the PEP pages. These proposals were written before the changes were accepted into the Python core. Note that not all of the PEPs on the Python site have been accepted, but they will remain on the Python site:

Combining pyenv and poetry or pipenv

Even though the chapter did not cover it, there is nothing stopping you from telling poetry or pipenv to use a pyenv-based Python interpreter. Give it a try!

Converting an existing project to a poetry project

Part of this exercise should be to either create a brand new pyproject.toml or to convert an existing requirements.txt file to a pyproject.toml.