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Advanced Python Programming - Second Edition

You're reading from  Advanced Python Programming - Second Edition

Product type Book
Published in Mar 2022
Publisher Packt
ISBN-13 9781801814010
Pages 606 pages
Edition 2nd Edition
Languages
Author (1):
Quan Nguyen Quan Nguyen
Profile icon Quan Nguyen

Table of Contents (32) Chapters

Preface 1. Section 1: Python-Native and Specialized Optimization
2. Chapter 1: Benchmarking and Profiling 3. Chapter 2: Pure Python Optimizations 4. Chapter 3: Fast Array Operations with NumPy, Pandas, and Xarray 5. Chapter 4: C Performance with Cython 6. Chapter 5: Exploring Compilers 7. Chapter 6: Automatic Differentiation and Accelerated Linear Algebra for Machine Learning 8. Section 2: Concurrency and Parallelism
9. Chapter 7: Implementing Concurrency 10. Chapter 8: Parallel Processing 11. Chapter 9: Concurrent Web Requests 12. Chapter 10: Concurrent Image Processing 13. Chapter 11: Building Communication Channels with asyncio 14. Chapter 12: Deadlocks 15. Chapter 13: Starvation 16. Chapter 14: Race Conditions 17. Chapter 15: The Global Interpreter Lock 18. Section 3: Design Patterns in Python
19. Chapter 16: The Factory Pattern 20. Chapter 17: The Builder Pattern 21. Chapter 18: Other Creational Patterns 22. Chapter 19: The Adapter Pattern 23. Chapter 20: The Decorator Pattern 24. Chapter 21: The Bridge Pattern 25. Chapter 22: The Façade Pattern 26. Chapter 23: Other Structural Patterns 27. Chapter 24: The Chain of Responsibility Pattern 28. Chapter 25: The Command Pattern 29. Chapter 26: The Observer Pattern 30. Assessments 31. Other Books You May Enjoy

Preface

Advanced Python Programming serves as a guide for you to take your Python skills to the next level. To beginners, Python is a great option for fast prototyping and software development due to its simple syntax, but some tend to lean toward other languages when they want to speed up and scale their code. However, this mindset is not necessarily correct. As this book will show us, Python comes with a wide range of support for optimizing, scaling, and overall high-performance computing.

This second edition includes both updated and new content from the first. Many chapters with overlapping materials have been combined to make a succinct, logical flow throughout the text. Further, a new chapter on JAX, the state-of-the-art high-performance computing tool in machine learning, has been added. These adjustments promise to make the book a high-quality text for all Python users who are looking to get the most out of their programs.

By the end of this book, you will have been exposed to a variety of techniques and libraries that are designed to streamline, protect, and optimize your software. You will gain practical skills on how to make your Python applications robust, efficient, and scalable.

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