python_how-to_-_63_techniques_to_improve_your_python_code_by_yong_cui

Python How-To - 63 techniques to improve your Python code by Yong Cui

Book Summary

“Have you ever asked yourself, “How do I do that in Python?” If so, you’ll love this practical collection of the most important Python techniques.” (PyHow2 2023)

Python How-To includes over 60 detailed answers to questions like:

  • How do I join and split strings?
  • How do I access dictionary keys, values, and items?
  • How do I set and use the return value in function calls?
  • How do I process JSON data?
  • How do I create lazy attributes to improve performance?
  • How do I change variables in a different namespace?

…and much more

Python How-To walks you through the most important coding techniques in Python. Whether you’re doing data science, building web applications, or writing admin scripts, you’ll find answers to your “how-to” questions in this book. Inside you’ll find important insights into both Python basics and deep-dive topics to help you skill-up at any stage of your Python career. Author Yong Cui’s clear and practical writing is instantly accessible and makes it easy to take advantage of Python’s versatile tools and libraries. Perfect to be read both from cover to cover, and whenever you need help troubleshooting your code.

About the Technology

Python How-To uses a simple but powerful method to lock in 63 core Python skills. You’ll start with a question, like “How do I find items in a sequence?” Next, you’ll see an example showing the basic solution in crystal-clear code. You’ll then explore interesting variations, such as finding substrings or identifying custom classes. Finally, you’ll practice with a challenge exercise before moving on to the next How-To.

About the Book

This practical guide covers all the language features you’ll need to get up and running with Python. As you go, you’ll explore best practices for writing great Python code. Practical suggestions and engaging graphics make each important technique come to life. Author Yong Cui’s careful cross-referencing reveals how you can reuse features and concepts in different contexts.

What’s Inside

How to:

  • Join and split strings
  • Access dictionary keys, values, and items
  • Set and use the return value in function calls
  • Process JSON data
  • Create lazy attributes to improve performance
  • Change variables in a different namespace

…and much more.

About the Reader

For beginning to intermediate Python programmers.

Brief Table of Contents

  • 1 Developing a pragmatic learning strategy

PART 1 - USING BUILT-IN DATA MODELS

  • 2 Processing and formatting strings
  • 3 Using built-in data containers
  • 4 Dealing with sequence data
  • 5 Iterables and iterations

PART 2 - DEFINING FUNCTIONS

  • 6 Defining user-friendly functions
  • 7 Using functions beyond the basics

PART 3 - DEFINING CLASSES

  • 8 Defining user-friendly classes
  • 9 Using classes beyond the basics

PART 4 - MANIPULATING OBJECTS AND FILES

  • 10 Fundamentals of objects
  • 11 Dealing with files

PART 5 - SAFEGUARDING THE CODEBASE

  • 12 Logging and exception handling
  • 13 Debugging and testing

PART 6 - BUILDING A WEB APP

  • 14 Completing a real project

About the Author

Dr. Yong Cui has been working with Python in bioscience for data analysis, machine learning, and tool development for over 15 years.

Product Details

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Fair Use Sources

Python: Python Fundamentals, Python Inventor: Python Language Designer: Guido van Rossum on 20 February 1991; PEPs, Python Scripting, Python Keywords, Python Data Structures - Python Algorithms, Python Syntax, Python OOP - Python Design Patterns, Python Module Index, pymotw.com, Python Package Manager (pip-PyPI), Python Virtualization (Conda, Miniconda, Virtualenv, Pipenv, Poetry), Python Interpreter, CPython, Python REPL, Python IDEs (PyCharm, Jupyter Notebook), Python Development Tools, Python Linter, Pythonista-Python User, Python Uses, List of Python Software, Python Popularity, Python Compiler, Python Transpiler, Python DevOps - Python SRE, Python Data Science - Python DataOps, Python Machine Learning, Python Deep Learning, Functional Python, Python Concurrency - Python GIL - Python Async (Asyncio), Python Standard Library, Python Testing (Pytest), Python Libraries (Flask), Python Frameworks (Django), Python History, Python Bibliography, Manning Python Series, Python Official Glossary - Python Glossary, Python Topics, Python Courses, Python Research, Python GitHub, Written in Python, Python Awesome List, Python Versions. (navbar_python - see also navbar_python_virtual_environments, navbar_numpy, navbar_datascience)

Manning Publications: Manning Books Purchased by Cloud Monk, Manning Books Series, Manning Bibliography, In a Month of Lunches, In Action, Manning API Series, Manning "Functional Programming in" Series, Manning Concurrency Async Multithreaded Parallel Programming Series, Manning Grokking Series, Manning Java-JVM Languages Series (Manning Java Series, Manning Kotlin Series), Manning JavaScript Series, Manning TypeScript Series, Manning Microservices Series, Manning Python Series, Manning Security Series, Manning Spring Series, Manning SQL Series, Manning Database Series, Manning Data Science Series, Manning Mistakes and How to Avoid Them Series, Manning Books that were Cancelled, MEAP, Cloud Monk's Book Purchases, Cloud Monk Library. (navbar_manning)


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