FastAPI Interview Questions — Easy

• A modern Python framework for building APIs on standard type hints (ASGI-based, via Starlette + Pydantic).
• Headline features: automatic validation from annotations, interactive docs (Swagger/ReDoc) generated free, async-first performance, dependency injection system.
• Popularity drivers: near-Node throughput with Python ergonomics, minimal boilerplate, editor autocompletion because everything is typed.

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• They ARE the framework contract: parameters annotated int, UUID, Pydantic models drive parsing, validation, serialization and the OpenAPI schema.
• Wrong types yield automatic 422 responses with precise error locations - no manual checking code.
• Editors autocomplete everything; mypy catches mismatches pre-runtime. Interview line: "In FastAPI you don't validate inputs; you DECLARE them."

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@app.get("/items/{item_id}")
async def read_item(item_id: int, q: str | None = None):
    return {"item_id": item_id, "q": q}

• Decorator binds HTTP method + path to function (@app.get/post/put/delete).
• Path parameter typed int → auto-conversion/validation.
• Optional query param q defaults None; return dict auto-serialized to JSON.

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• Function params not in path become query params: def list(skip: int = 0, limit: int = Query(default=10, le=100)).
• Constraints via Query(gt=0, max_length=...); alias support maps external names to pythonic ones.
• Multiple values: tags: list[str] = Query([]) accepts ?tags=a&tags=b.

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class ItemIn(BaseModel):
    name: str
    price: float = Field(gt=0)
    tags: set[str] = set()

@app.post("/items")
async def create(item: ItemIn): ...

• POST/PUT body parsed into the model automatically; nested models validated recursively.
• Extra fields forbidden/configurable (model_config = ConfigDict(extra="forbid")).
• Response model (response_model=ItemOut) filters output shape separately from input.

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