Make your good Python code even better by following proven and effective pythonic programming tips. Avoid logical errors that usually go undetected by Python linters and code formatters, such as frequent data look-ups in long lists, improper use of local and global variables, and mishandled user input. Discover rare language features, like rational numbers, set comprehensions, counters, and pickling, that may boost your productivity. Discover how to apply general programming patterns, including caching, in your Python code. Become a better-than-average Python programmer, and develop self-documented, maintainable, easy-to-understand programs that are fast to run and hard to break.

Python is one of the most popular and rapidly growing modern programming languages. With more than 200 standard libraries and even more third-party libraries, it reaches into the software development areas as diverse as artificial intelligence, bioinformatics, natural language processing, and computer vision. Find out how to improve your understanding of the spirit of the language by using one hundred pythonic tips to make your code safer, faster, and better documented.

This programming style manual is a quick reference of helpful hints and a random source of inspiration. Choose the suitable data structures for searching and sorting jobs and become aware of how a wrong choice may cause your application to be completely ineffective. Understand global and local variables, class and instance attributes, and information-hiding techniques. Create functions with flexible interfaces. Manage intermediate computation results by caching them in files and memory to improve performance and reliability. Polish your documentation skills to make your code easy for other programmers to understand. As a bonus, discover Easter eggs cleverly planted in the standard library by its developers.

Polish, secure, and speed-up your Python applications, and make them easier to maintain by following pythonic programming tips.

What You Need:

You will need a Python interpreter (ideally, version 3.4 or above) and the standard Python library that usually comes with the interpreter.

Contents

1. Documentation Tips

2. General Tips

3. Data Types and Data Structures Tips

4. Function Tips

5. Performance Tips

6. Safety Tips

7. Wrapping Up

About this Book

Welcome, reader! Let me briefly introduce myself. I am a computer science professor, and I have been teaching Python since 2012—that is, for the last nine years. I have been teaching Python 2.7 and Python 3.4. I have been teaching undergraduate and graduate students. I have been teaching adults in their fifties, and teenagers, and everyone in between. I have even been teaching my twin cats in my dreams, and they were not the worst learners.

Over those nine years, I answered hundreds of questions and graded hundreds of programming assignments ranging from print (’Hello, world!’) to several-pages-long data acquisition and analysis scripts. I am not exaggerating: literally hundreds.

Besides, in the last three years, I have answered close to 2,000 Python-related questions on StackOverflow. That’s a lot of questions. I wonder what took me so long to start seeing patterns in the questions and the students’ programs; most questions were the same, and most programs had the same programming errors.

That’s when I decided to select one hundred Pythonic tips—solutions to the most common errors and answers to the most common questions—and compile them into a book.

And that is how this book was born.

About the Author

Dmitry Zinoviev is a professor of Computer Science at Suffolk University in Boston and has a dual degree in Physics and Computer Science. He is passionate about C and Python programming, complex network analysis, computational social science, and digital humanities.