python-patterns

What problem does it solve?

Building robust Python applications requires adherence to modern patterns and best practices. Without clear guidance, Python projects can suffer from untyped code, inefficient async operations, and inconsistent error handling.

Core Features & Use Cases

• Type Hints: Master basic, generic, TypedDict, and Protocol types for more maintainable and error-free Python code.
• Dataclasses & Pydantic Models: Efficiently define data structures with immutability, default factories, and robust validation.
• Async Patterns: Implement asyncio for concurrent execution, async context managers, and async generators.
• Error Handling: Design custom exceptions and implement structured try-except blocks for graceful error management.
• Testing with Pytest: Write effective unit tests with fixtures, parametrized tests, and comprehensive mocking.
• Use Case: Add type hints to an existing Python function, implement an async context manager, or write a parametrized test with Pytest.

Quick Start

Refactor the given Python function to use type hints for all parameters and return values, and add a dataclass for its output.