90 Essential Python Tips for Better Coding

This guide presents ninety concise Python suggestions organized into thematic sections such as basic concepts, idiomatic practices, core language features, standard library utilities, design patterns, internal mechanisms, tooling, and performance optimization.

1. Basics – Emphasize understanding the Pythonic philosophy, writing readable code, proper indentation, comment usage, function design principles, and constant naming conventions.

2. Coding Conventions – Recommend using assert, tuple unpacking, lazy evaluation, proper type checking with isinstance, avoiding eval, leveraging enumerate, distinguishing == vs is, and adopting Unicode.

3. Core Language Features – Advise selective imports, absolute imports, correct use of with, exception handling best practices, understanding None, string formatting, mutable defaults, and variable argument handling.

4. Standard Library – Cover string operations, sorting with sort() vs sorted(), deep copying, Counter, configuration parsing, argparse, CSV handling, pandas for large datasets, XML parsing, pickle vs JSON, logging, and multithreading utilities.

5. Design Patterns – Illustrate module‑based singleton, mixin, publish‑subscribe, and state patterns for cleaner architecture.

6. Internals – Explain built‑in objects, __init__ vs __new__, scope resolution, self, MRO, descriptors, attribute access methods, properties, metaclasses, object protocol, operator overloading, iterator and generator protocols, coroutines, GIL limitations, and garbage collection.

7. Tooling – Guide installing packages via PyPI, using pip and yolk, creating packages, unit testing, TDD, code style checking with Pylint, code review processes, CI integration, and generating documentation.

8. Performance Profiling & Optimization – Discuss profiling principles, using cProfile, memory profilers, reducing algorithmic complexity, loop optimizations, generator usage, appropriate data structures, set advantages, multiprocessing to bypass GIL, thread pools, and extending Python with Cython.