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Mastering Python 2E

You're reading from   Mastering Python 2E Write powerful and efficient code using the full range of Python's capabilities

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Product type Paperback
Published in May 2022
Last Updated in May 2022
Publisher Packt
ISBN-13 9781800207721
Length 710 pages
Edition 2nd Edition
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Author (1):
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Rick Hattem Rick Hattem
Author Profile Icon Rick Hattem
Rick Hattem
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Table of Contents (21) Chapters Close

Preface 1. Getting Started – One Environment per Project FREE CHAPTER 2. Interactive Python Interpreters 3. Pythonic Syntax and Common Pitfalls 4. Pythonic Design Patterns 5. Functional Programming – Readability Versus Brevity 6. Decorators – Enabling Code Reuse by Decorating 7. Generators and Coroutines – Infinity, One Step at a Time 8. Metaclasses – Making Classes (Not Instances) Smarter 9. Documentation – How to Use Sphinx and reStructuredText 10. Testing and Logging – Preparing for Bugs 11. Debugging – Solving the Bugs 12. Performance – Tracking and Reducing Your Memory and CPU Usage 13. asyncio – Multithreading without Threads 14. Multiprocessing – When a Single CPU Core Is Not Enough 15. Scientific Python and Plotting 16. Artificial Intelligence 17. Extensions in C/C++, System Calls, and C/C++ Libraries 18. Packaging – Creating Your Own Libraries or Applications 19. Other Books You May Enjoy
20. Index

Exercises

Now that you have seen several testing and logging options, it’s time to try it yourself.

A few challenges:

  • Create a function that tests the doctests of a given function/class.
  • For a greater challenge, create a function that recursively tests all doctests of every function and class in a given module.
  • Create a py.test plugin that checks if all tested files have file-level documentation. Hint: use pytest_collect_file.
  • Create a custom tox environment to run flake8 or mypy on your project.
  • Create a LoggerAdapter that combines multiple messages into a single message based on some task ID. This can be useful when debugging long-running tasks.

Example answers for these exercises can be found on GitHub: https://github.com/mastering-python/exercises. You are encouraged to submit your own solutions and learn about alternative solutions from others.

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