FastAPI stands out for speed, async support, and built-in validation, making it ideal for modern high-traffic APIs.
Interviewers focus on concepts like ASGI, async behavior, and dependency injection, not just syntax.
Real understanding of non-blocking code, JWT auth, and deployment is key to cracking FastAPI interviews.
FastAPI has earned its place in serious backend development. Companies running high-traffic APIs increasingly choose it over older Python frameworks. Interview rounds have caught up with this shift. Candidates applying for Python backend roles now face FastAPI questions regularly, sometimes as the main focus of the technical round.
Most people go in underprepared. They know Flask or Django, have a surface-level understanding of FastAPI, and assume that will be enough. It rarely is. Interviewers want to see that a candidate understands why the framework works the way it does, not just what it does. The ten questions below reflect what consistently comes up, along with answers that hold up under follow-up questions.
FastAPI is a Python framework built for building APIs. It runs on Starlette and uses Pydantic for data validation. It supports Python 3.7 and above. Flask needs third-party libraries for validation and documentation. FastAPI handles both automatically.
Django is a full-stack framework suited for web apps. FastAPI stays focused on API delivery with far less overhead. That focus is the core difference.
ASGI stands for Asynchronous Server Gateway Interface. It allows Python web servers to handle async operations properly. FastAPI runs on Uvicorn, which is an ASGI server.
A single Uvicorn worker can manage thousands of concurrent connections. WSGI, used by Flask and Django traditionally, cannot do this. That is why FastAPI benchmarks rank it among the fastest Python frameworks available.
With async def, FastAPI runs the route inside the event loop. This lets other requests continue while one waits on I/O, such as a database call or an external API.
With plain def, FastAPI offloads the function to a thread pool. Both work. The mistake is writing blocking code inside an async def route. That kills concurrency entirely.
Pydantic is a validation library that uses Python type hints to define data schemas. FastAPI uses it to validate request bodies and serialize response data.
It also generates JSON Schema for the automatic API documentation. If a request body does not match the defined model, FastAPI returns a 422 error automatically. No extra code is needed for that behavior.
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Dependency injection is a way to share logic across multiple routes without repeating it. In FastAPI, a shared function like a database session or an auth check is declared separately. It is then passed into a route using Depends().
This keeps routes clean. It also makes testing easier, since dependencies can be swapped out during tests using override_dependency.
Path parameters sit inside the URL itself. /users/{user_id} is an example. The value is part of the route. Query parameters come after a ? in the URL. /items?skip=0&limit=10 uses query parameters for filtering.
FastAPI reads both from the function signature and validates them automatically against the declared types.
FastAPI has built-in support for OAuth2. The common approach uses OAuth2PasswordBearer and JWT tokens. A user logs in, receives a token, and sends it with each request.
A dependency validates the token on protected routes. The token carries an expiry claim. FastAPI checks both the token structure and the expiry before granting access.
FastAPI generates two documentation interfaces at startup. Swagger UI loads at /docs. ReDoc loads at /redoc. Both are built from OpenAPI specifications that FastAPI compiles from route definitions and Pydantic models. Nothing extra needs to be configured.
Developers can test endpoints directly from the browser, which speeds up development considerably.
FastAPI returns a 422 status code. The response body is a structured JSON object. It lists every field that failed, the location of the error, and the reason. This is handled internally by Pydantic.
Custom error messages can be added inside the Pydantic model. The entire error handler can also be replaced globally using app.add_exception_handler().
The standard setup uses Uvicorn as the ASGI server. Gunicorn manages multiple Uvicorn workers across CPU cores. The application is containerized with Docker for consistent behavior across environments.
Nginx typically sits at the front to handle SSL termination and route traffic. For scaling, Kubernetes manages container instances across multiple machines.
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FastAPI interviews are not won by memorizing definitions. Interviewers probe for understanding. They want to know whether a candidate would make sound decisions with the framework in a real codebase. Knowing that async endpoints only help when the underlying operations are non-blocking is worth more than any syntax recall.
These ten questions cover the ground that matters most before walking into a technical round. Each answer here is a foundation, not a ceiling. Topics like dependency injection, JWT flow, and ASGI behavior go much deeper. The candidates who explore that depth are the ones who leave the room with an offer.
What is FastAPI used for?
Ans. FastAPI is used to build REST APIs with Python. It is a popular choice for backend development, ML model serving, and microservices where speed and documentation matter.
Is FastAPI better than Flask?
Ans. FastAPI handles async requests natively and generates documentation automatically. Flask works well for simpler projects where those features are not needed.
What Python version does FastAPI require?
Ans. FastAPI requires Python 3.7 or higher. Most teams today run Python 3.10 or 3.11 in production.
What server does FastAPI run on?
Ans. FastAPI runs on Uvicorn. Gunicorn is added in production to manage multiple Uvicorn workers across available CPU cores.
Is FastAPI good for beginners?
Ans. It is approachable for anyone who knows Python basics. Type hints and automatic validation reduce boilerplate, which helps beginners write cleaner code from the start.