FastAPI uses PythonA high-level language known for readability — dominant in data science, scripting, and web backends. type hints and Pydantic for validation, Starlette for async I/O, and auto-generates Swagger UIUser interface — the parts of software people see and interact with. docs. Used for ML inferenceRunning a trained model to produce predictions — as opposed to the training phase that learns weights. APIs, microservicesAn architecture splitting applications into small independent services — each deployed and scaled separately., and high-throughput backends. Example: `async def read_item(item_id: int)` with request/response schemas enforced at runtime and documented for free.

FastAPI became the default for new PythonA high-level language known for readability — dominant in data science, scripting, and web backends. APIs when async and OpenAPI docs mattered.

It showed type hints could drive validation, serialization, and documentation in one cohesive framework.