Easy interview questions in Python & FastAPI
Explain Python type hints and their importance in FastAPI
Python type hints describe expected data, but Python itself does not enforce them. FastAPI reads those annotations with Pydantic to parse and validate requests and generate OpenAPI documentation. A strong answer separates language syntax from framework behavior.
What is the difference between def and async def in Python and FastAPI?
Tests event-loop boundaries: async def yields control via await for non-blocking I/O, def runs in a threadpool. Use async def only with async libraries; def covers blocking calls. Red flag: claiming async is automatically faster or awaiting inside def.
What is the purpose of @app.get("/") in FastAPI?
Tests your understanding of FastAPI routing. A strong answer explains that the decorator binds an HTTP method and path to a Python function, registers it in the app's route table, and builds OpenAPI metadata.
How do you define and access a FastAPI path parameter?
Tests FastAPI route-to-function binding. Good answer: curly-brace syntax in the decorator path, a matching typed function argument, and awareness that FastAPI auto-extracts and converts the value.
How do you define a Pydantic model for FastAPI request body validation?
Subclass BaseModel with id int, email str, full_name str|None; pass it as a route param so FastAPI validates JSON and returns 422s.
How does Pydantic handle extra JSON fields, and how to configure it?
This tests Pydantic's data filtering behavior and configuration. By default, Pydantic ignores extra fields silently. Set model_config = ConfigDict(extra='forbid' or 'allow') to change it. A red flag is claiming FastAPI 422s by default on unknown fields.
What is the difference between a Pydantic default and Optional field?
Both forms are non-required; str = 'guest' rejects None, Optional[str] = None accepts it.
How do you define a Pydantic model and use it in FastAPI?
Subclass BaseModel with name str and age int, then type-hint the parameter with the model.
How would you use a Pydantic response_model to enforce output structure?
Tests separation of internal models from API contracts. Define a Pydantic output model with only safe fields, set it as the endpoint response_model, and let FastAPI filter and validate.
Define a FastAPI endpoint with path and query parameters
Tests if you know FastAPI infers parameter location from the route string. Good answer: route with {item_id}, signature item_id: int, q: str | None = None, noting any param not in the path becomes a query param.
How do you declare a function as a dependency, and why?
Tests FastAPI dependency injection basics. Answer: create a function, import Depends, and add it to path operation parameters so FastAPI injects it. Purpose: routes declare what they need instead of hard-coding shared logic.
What is the purpose of yield in a dependency function?
Tests teardown logic in FastAPI dependencies. Yield splits setup from cleanup: code before yield runs pre-request, after yield runs post-response to close resources like DB sessions. Red flag: confusing it with return or thinking yield is only for generators.
How do you apply a dependency to an APIRouter without per-endpoint signatures?
Pass Depends() to APIRouter dependencies parameter; runs before every route in that router and shows in docs.
What is APIRouter in FastAPI and why use it?
It tests your grasp of modular architecture in FastAPI. APIRouter splits routes into separate modules so you include them in the main app with prefixes, tags, and dependencies.
Describe a common FastAPI project structure and key directories
Main module holds the FastAPI app; domain files (users, items) expose APIRouters; dependencies in their own module; pyproject.toml as entrypoint.
How do you include a router in your main FastAPI app?
Create APIRouter in another file, import it into main.py, then call app.include_router(router).
What is the difference between async def and regular functions?
This tests async def call semantics. A strong answer contrasts regular functions, which execute immediately, with async def, which returns a coroutine object that does nothing until awaited or wrapped in create_task.
Explain await's purpose, awaitable types, and event loop signaling
This tests whether you understand await as a yield point. A strong answer lists three awaitables (coroutines, Tasks, Futures), explains await yields control to the event loop until completion, and warns that a bare coroutine call does not run it.
Describe SQLAlchemy setup in FastAPI from database config to endpoint
Tests FastAPI dependency injection and SQLAlchemy session lifecycle. Good answers cover: engine with pooling, declarative models, a yield-based session dependency, and endpoint queries. Red flag: engine per request or global session shared everywhere.
Explain SQLAlchemy ORM vs Pydantic models in FastAPI
This tests separation of database schema from API contracts. A strong answer distinguishes SQLAlchemy table rows from Pydantic validation and OpenAPI generation, and notes that create schemas exclude auto-generated IDs.
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