50 Practical Tips for Writing Python Code

This article compiles fifty practical recommendations for Python developers, covering coding style, function design, module organization, error handling, library usage, design patterns, and internal language mechanisms to help beginners and intermediate programmers write cleaner, more efficient, and safer Python code.

Programming preface : Emphasize understanding the Pythonic philosophy and avoid non‑standard code such as confusing variable names or excessive case sensitivity.

Coding conventions : Use clear variable names, appropriate whitespace, and comments; add blank lines for readability; keep functions short, simple, and focused on a single task; design functions with four principles (short, simple, compatible arguments, consistent granularity).

Common idioms : Use assert for debugging, swap variables with a, b = b, a , leverage lazy evaluation, prefer enumerate() over manual indexing, distinguish == from is , and avoid unsafe eval() .

Basic usage : Limit from … import statements, prefer absolute imports, use else with loops for clean exception handling, follow best practices for try/except blocks, avoid pitfalls with finally , understand None checks, and use consistent container literals ( [], {}, () ).

Function arguments : Recognize that arguments are passed by object reference, avoid mutable default arguments, limit use of *args and **kwargs , and understand the role of self .

Class and method design : Distinguish static methods, class methods, and instance methods; understand method resolution order (MRO) and multiple inheritance; know when to use mixins, singleton modules, and publish‑subscribe patterns; and grasp descriptor protocols.

Library usage : Master string operations, choose between sort() and sorted() , use ConfigParser , argparse , pandas for large CSVs, ElementTree for XML, and understand serialization with pickle and json . Also employ traceback , logging , threading , and Queue for robust applications.

Design patterns : Implement singleton modules, mixins, publish‑subscribe, and state patterns to achieve loose coupling and flexible code structures.

Internal mechanisms : Understand built‑in objects, the difference between __init__ and __new__ , variable scope (local, global, nested, built‑in), the purpose of self , MRO, and descriptor methods like __getattr__ vs __getattribute__ .