python-patterns

Choosing between FastAPI and Django depends on your project needs. This guidance provides a decision tree comparing Python web frameworks to help you select the most suitable option for your new API based on specific project requirements.

Use async programming in Python when managing high-concurrency I/O operations. This guidance provides clear criteria for deciding when to use asynchronous or synchronous code based on your application's specific workload and context.

The best way to structure a scalable Python project is by adopting scalable templates. This guidance offers project structure patterns tailored for different project sizes to ensure maintainability and efficient development.

Implement type hints and data validation using Pydantic by following established best practices. This guidance emphasizes the importance of type hinting strategies and using Pydantic to validate data efficiently in your Python applications.

Manage background tasks and error handling in Python frameworks by applying robust strategies. This guidance recommends specific solutions for handling background tasks and outlines strategies for robust error management and testing methodologies.