Detailed Explanation of FastAPI Dependency Injection: Basic and Advanced Usage of Depends

Dependency Injection (DI) core is to inject dependencies (such as database connections) into functions automatically by the system, rather than having the functions acquire them themselves, thereby enhancing code reusability and decoupling. FastAPI implements this through `Depends`, which involves two steps: defining a dependency function (to produce a dependency object, e.g., simulating a database connection), and declaring the dependency in the path function using `Depends(dependency_function)`, where FastAPI automatically calls and injects the result. Dependency functions can accept path/query parameters, such as querying a user based on a `user_id`. Advanced usages include: nested dependencies (dependencies on other dependencies), caching dependencies with `lru_cache` (singleton), asynchronous dependencies (adapting to asynchronous path functions), and combining with Pydantic for parameter validation. Core advantages: code reusability, decoupling (path functions only focus on business logic), testability (dependencies can be replaced with mocks), and extensibility (adding new dependencies only requires modifying the dependency function). Mastering `Depends` enables a clearer and more robust API structure.