Python How-To

63 techniques to improve your Python code

Yong Cui

• Publisher: Manning
• Year: 2023
• eBook ISBN: 9781638352037
• Edition: 0
• Topic: Computer Science
• Subtopic: Data Processing
• Index: Computer Science

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. 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 BookThis 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 InsideHow 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 ReaderFor beginning to intermediate Python programmers.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. 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

Table of contents

• inside front cover
• Python How-To
• Copyright
• dedication
• contents
• front matter
• 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
• Appendix A. Learning Python with REPL in IDLE
• Appendix B. Managing Python packages with pip
• Appendix C. Using Jupyter Notebook: A web-based interactive Python editor
• Appendix D. Integrating version control into your project
• Appendix E. Preparing your package for public distribution
• Appendix F. solutions to the challenges
• index
• inside back cover