𝔖 Scriptorium
✦   LIBER   ✦

πŸ“

Pythonic Programming: Tips for Becoming an Idiomatic Python Programmer

✍ Scribed by Dmitry Zinoviev


Publisher
Pragmatic Bookshelf
Year
2021
Tongue
English
Leaves
152
Edition
1
Category
Library

⬇  Acquire This Volume

No coin nor oath required. For personal study only.

✦ Synopsis


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.


πŸ“œ SIMILAR VOLUMES


Cython: a guide for Python programmers
✍ Smith, Kurt W πŸ“‚ Library πŸ“… 2015 πŸ› O'Reilly Media 🌐 English

<p>Build software that combines Python's expressivity with the performance and control of C (and C++). It's possible with Cython, the compiler and hybrid programming language used by foundational packages such as NumPy, and prominent in projects including Pandas, h5py, and scikits-learn. In this pra

Cython: A Guide for Python Programmers
✍ Kurt W Smith πŸ“‚ Library πŸ“… 2015 πŸ› O'Reilly 🌐 English

Cython can yield massive performance improvements over pure Python--speedups of 3000X are easily attainable for certain patterns. With this book, Kurt Smith shows you how to use Cython to easily wrap C and C++ libraries in Python, handling all the details of memory management for you. By removing th

Cython- A guide for Python programmers
✍ Kurt W. Smith πŸ“‚ Library πŸ“… 2015 πŸ› O'Reilly 🌐 English

Build software that combines Python’s expressivity with the performance and control of C (and C++). It’s possible with Cython, the compiler and hybrid programming language used by foundational packages such as NumPy, and prominent in projects including Pandas, h5py, and scikits-learn. In this practi

Cython: A Guide for Python Programmers
✍ Kurt W. Smith πŸ“‚ Library πŸ“… 2015 πŸ› O’Reilly Media 🌐 English

<div><p>Build software that combines Python’s expressivity with the performance and control of C (and C++). It’s possible with Cython, the compiler and hybrid programming language used by foundational packages such as NumPy, and prominent in projects including Pandas, h5py, and scikits-learn. In thi