Mastering Python Write Powerful And Efficient Code Using The Full Range Of Pythons Capabilities 2nd Edition 2nd Edition Rick Van Hattem by Rick Van Hattem 9781800207721, 1800207727 instant download after payment.

Use advanced features of Python to write high-quality, readable code and packages
Even if you find writing Python code easy, writing code that is efficient, maintainable, and reusable is not so straightforward. Many of Python's capabilities are underutilized even by more experienced programmers. Mastering Python, Second Edition, is an authoritative guide to understanding advanced Python programming so you can write the highest quality code. This new edition has been extensively revised and updated with exercises, four new chapters and updates up to Python 3.10.
Revisit important basics, including Pythonic style and syntax and functional programming. Avoid common mistakes made by programmers of all experience levels. Make smart decisions about the best testing and debugging tools to use, optimize your code's performance across multiple machines and Python versions, and deploy often-forgotten Python features to your advantage. Get fully up to speed with asyncio and stretch the language even further by accessing C functions with simple Python calls. Finally, turn your new-and-improved code into packages and share them with the wider Python community.
If you are a Python programmer wanting to improve your code quality and readability, this Python book will make you confident in writing high-quality scripts and taking on bigger challenges.

What you will learn
• 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