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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
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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

The possibilities with external libraries are endless, so perhaps you already have some ideas about what to implement. If not, here’s some inspiration:

  • Try to sort a list of numbers using ctypes, CFFI, and with a native extension. You can use the qsort function in stdlib.
  • Try to make the custom_sum function we created safer by adding proper errors for overflow/underflow issues. Additionally, catch the errors when summing multiple numbers that only overflow or underflow in summation.

These exercises should be a nice starting point for doing something useful with your newly acquired knowledge. If you are looking for more of the native C/C++ examples, I would recommend looking through the CPython source. There are many examples available: https://github.com/python/cpython/tree/main/Modules. I would suggest starting with a relatively simple one such as the bisect module.

Example answers for these exercises can be found on GitHub: https...

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