implementation-design-patterns-python

name

implementation-design-patterns-python

description

Implementation guide for the 22 Gang of Four design patterns in idiomatic modern Python (3.10+), distilled from refactoring.guru. Use when writing, refactoring, or reviewing Python with a pattern-shaped problem — class-explosion from inheritance, conditionals switching on type, tight coupling to concrete classes, tree-shaped models, runtime algorithm selection, undo/redo, state-dependent behavior, or hiding subsystem complexity. Each entry leads with the Pythonic form (functions, dataclasses, Protocol, singledispatch, match, generators, copy/replace) and falls back to the class-based GoF structure only when identity, state, or dispatch require it. Includes intent, applicability (when to use AND when NOT to), a runnable example, steps, pros/cons, and relations. Trigger even when no pattern is named — cues like "too many constructor params," "giant if/elif," "swap behavior at runtime," "need undo," or "walk a tree" are pattern-shaped. Covers all 5 Creational, 7 Structural, and 10 Behavioral GoF patterns.

Python Design Patterns Best Practices (Refactoring Guru)

Implementation reference for the 22 Gang of Four design patterns in idiomatic modern Python (3.10+), distilled from refactoring.guru. Each of the 22 pattern files across 3 categories captures intent, problem, solution, applicability (when to use AND when NOT to), a runnable Python example with output, implementation steps, pros/cons, and relations to sibling patterns.

This is the Pythonic-first companion to the TypeScript design-patterns skill. Most GoF patterns shrink to a language feature in Python — a function, a generator, a dataclass, functools.singledispatch, a match statement. Every entry leads with that idiomatic form and keeps the class-based GoF structure only where identity, stored state, runtime registration, or polymorphic dispatch genuinely earn it.

The patterns are a vocabulary for structural decisions, not a prescription. Reach for one only when its applicability criteria match — every entry includes a When NOT to Use section to guard against over-engineering, which is the more common failure with this catalog in Python.