To get the most out of this book
This book presumes some familiarity with Python 3 and the general concept of application development. Because a project is a complete unit of work, it will go beyond the Python programming language. This book will often challenge you to learn more about specific Python tools and packages, including pytest, mypy, tox, and many others.
Most of these projects use exploratory data analysis (EDA) as a problem domain to show the value of functional programming. Some familiarity with basic probability and statistics will help with this. There are only a few examples that move into more serious data science.
Python 3.11 is expected. For data science purposes, it’s often helpful to start with the conda tool to create and manage virtual environments. It’s not required, however, and you should be able to use any available Python.
Additional packages are generally installed with pip. The command looks like this:
% python -m pip install pytext mypy tox beautifulsoup4
Complete the extras
Each chapter includes a number of “extras” that help you to extend the concepts in the chapter. The extra projects often explore design alternatives and generally lead you to create additional, more complete solutions to the given problem.
In many cases, the extras section will need even more unit test cases to confirm they actually solve the problem. Expanding the core test cases of the chapter to include the extra features is an important software development skill.
Download the example code files
The code bundle for the book is hosted on GitHub at https://github.com/PacktPublishing/Python-Real-World-Projects. We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!