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Learn Python Programming

You're reading from   Learn Python Programming A comprehensive, up-to-date, and definitive guide to learning Python

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Product type Paperback
Published in Nov 2024
Publisher Packt
ISBN-13 9781835882948
Length 616 pages
Edition 4th Edition
Languages
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Authors (2):
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Heinrich Kruger Heinrich Kruger
Author Profile Icon Heinrich Kruger
Heinrich Kruger
Fabrizio Romano Fabrizio Romano
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Fabrizio Romano
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Toc

Table of Contents (20) Chapters Close

Preface A Gentle Introduction to Python FREE CHAPTER Built-In Data Types Conditionals and Iteration Functions, the Building Blocks of Code Comprehensions and Generators OOP, Decorators, and Iterators Exceptions and Context Managers Files and Data Persistence Cryptography and Tokens Testing Debugging and Profiling Introduction to Type Hinting Data Science in Brief Introduction to API Development CLI Applications Packaging Python Applications Programming Challenges Other Books You May Enjoy
Index

Other Books You May Enjoy

If you enjoyed this book, you may be interested in these other books by Packt:

Modern Python Cookbook

Steven F. Lott

ISBN: 9781835466384

  • Master core Python data structures, algorithms, and design patterns
  • Implement object-oriented designs and functional programming features
  • Use type matching and annotations to make more expressive programs
  • Create useful data visualizations with Matplotlib and Pyplot
  • Manage project dependencies and virtual environments effectively
  • Follow best practices for code style and testing
  • Create clear and trustworthy documentation for your projects

Mastering Python 2E

Rick Hattem

ISBN: 9781800207721

  • Write beautiful Pythonic code and avoid common Python coding mistakes
  • Apply the power of decorators, generators, coroutines, and metaclasses
  • Use different testing systems like pytest, unittest, and doctest
  • Track and optimize application performance for both memory and CPU usage
  • Debug your applications with PDB, Werkzeug, and faulthandler
  • Improve your performance through asyncio, multiprocessing, and distributed computing
  • Explore popular libraries like Dask, NumPy, SciPy, pandas, TensorFlow, and scikit-learn
  • Extend Python’s capabilities with C/C++ libraries and system calls

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