python-patterns
Python-specific design patterns and best practices including protocols, dataclasses, context managers, decorators, async/await, type hints, and package organization. Use when working with Python code to apply Pythonic patterns.
Target: Software development & testing. Automatically collected · unverified.
Excerpt from the author’s documentation
Extracted from a fixed version of SKILL.md in its original language. This is the author’s documentation; installation, compatibility and runtime results have not been verified by this site.
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Topics in the source
- Python Patterns
- Protocol (Duck Typing)
- Dataclasses as DTOs
- Context Managers
- Generators
- Decorators
- Function Decorators
- Class Decorators
This skill provides comprehensive Python patterns extending common design principles with Python-specific idioms. Use Protocol for structural subtyping (duck typing with type hints): Benefits: Type safety without inheritance Flexible, loosely coupled code Easy testing and mocking Use dataclass for data transfer objects and value objects: Features: Auto-generated init, repr, eq frozen=True for immutability field() for complex defaults Type hints for validation Use context managers (with statement) for resource management: Class-based context manager: Use generators for lazy evaluation and memory-efficient iteration: Generator expressions: Designing Python APIs and packages Implementing async/concurrent systems Structuring Python projects Writing Pythonic code Refactoring Python codebases Type-safe Python development
- Source repository
- affaan-m/ECC
- Source file
- .kiro/skills/python-patterns/SKILL.md
- Fixed revision
- d2ef2680594f9a17526a6e1a2e18b3d242c5d17b
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This record was collected automatically. Its documentation, suitability and runtime behavior have not been manually verified.
Author: affaan-m/ECC · original repository metadata. Documentation review: Not reviewed. Last source check: 2026-11-09T14:01:48.645Z.
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