Interviewing for a FastAPI developer position can be a challenging process, as the framework comes with its own set of complexities and nuances. To help you prepare for your interview, we have put together a list of the top 25 FastAPI interview questions and answers that can help you showcase your knowledge and skills. Let’s dive in!
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What is FastAPI?
FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints. -
What are the key features of FastAPI?
- Fast: FastAPI is one of the fastest web frameworks available for Python.
- Easy to use: It is easy to learn and use, especially for developers familiar with Python.
- Type checking: It uses Python type hints for validating and providing documentation for your API.
- Automatic OpenAPI and JSON Schema generation.
- Dependency Injection: FastAPI supports automatic dependency injection to manage dependencies in your application.
- Async support: It is built on top of Starlette and Pydantic, both of which support asynchronous programming in Python.
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How does FastAPI handle request routing?
FastAPI uses path operations to define endpoints in your application. These path operations are based on standard Python functions with decorators that specify the HTTP method and URL path. -
How does FastAPI handle request parameters?
FastAPI allows you to define request parameters directly in the path operation function signature using Python type hints. For example, you can define query parameters using regular arguments and path parameters using annotated arguments. -
How does FastAPI handle response types?
FastAPI uses Pydantic models to define response types for your API endpoints. You can annotate your path operation function with a Pydantic model, and FastAPI will automatically validate the response data against the model schema. -
How does FastAPI handle request validation?
FastAPI automatically validates incoming requests against the defined request parameter types. If the request data does not match the expected types, FastAPI will return an error response with details about the validation error. -
How does FastAPI support authentication and authorization?
FastAPI provides built-in support for authentication and authorization using dependency injection. You can define dependencies to handle user authentication and authorization logic, and FastAPI will automatically inject these dependencies into your path operation functions. -
How does FastAPI handle error handling?
FastAPI provides built-in support for error handling using standard Python exceptions. You can raise exceptions in your path operation functions, and FastAPI will automatically handle these exceptions and return appropriate error responses. -
How does FastAPI generate API documentation?
FastAPI automatically generates OpenAPI documentation for your API based on the defined path operations, request parameters, response types, and error handling logic. You can access the generated documentation by visiting the "/docs" endpoint in your FastAPI application. -
How does FastAPI handle background tasks?
FastAPI supports background tasks using thebackground_taskdecorator. You can define background tasks that run asynchronously in the background and do not affect the main request/response cycle. -
How does FastAPI handle file uploads?
FastAPI provides built-in support for handling file uploads using theFiletype from thefastapi.UploadFileclass. You can define endpoint parameters of typeFileto handle file uploads in your API. -
How does FastAPI handle request validation with Pydantic models?
FastAPI uses Pydantic models to define request and response data schemas for your API endpoints. You can define Pydantic models to validate incoming request data and generate API documentation automatically. -
How does FastAPI handle CORS (Cross-Origin Resource Sharing)?
FastAPI provides built-in support for handling CORS requests using thefastapi.middleware.corsmiddleware. You can enable CORS for your FastAPI application by adding the middleware to your application configuration. -
How does FastAPI handle request dependencies?
FastAPI supports dependency injection to manage request dependencies in your API endpoints. You can define dependencies as function parameters or as decorators on your path operation functions. -
How does FastAPI handle HTTP middleware?
FastAPI supports HTTP middleware for processing requests and responses before they reach the path operation functions. You can define middleware functions to intercept and modify incoming requests or outgoing responses. -
How does FastAPI handle data validation with Pydantic models?
FastAPI uses Pydantic models to validate incoming request data against defined data schemas. You can define Pydantic models to enforce data validation rules and generate API documentation automatically. -
How does FastAPI handle WebSocket connections?
FastAPI supports WebSocket connections using theWebSocketclass from thefastapi.WebSocketmodule. You can define WebSocket routes in your FastAPI application to handle WebSocket connections and communication. -
How does FastAPI handle automatic API validation and serialization?
FastAPI automatically validates incoming requests against defined request parameter types and serializes response data based on defined response types. You can use Pydantic models to define request and response data schemas that FastAPI will validate and serialize automatically. -
How does FastAPI handle pagination in API responses?
FastAPI supports pagination in API responses using query parameters to specify the page size and page number. You can define query parameters for pagination in your API endpoints to control the number of results returned in each paginated response. -
How does FastAPI handle dependency injection for request dependencies?
FastAPI supports automatic dependency injection for request dependencies using theDependsclass. You can define a dependency as a function that returns the dependency, and FastAPI will automatically inject the dependency into your path operation functions. -
How does FastAPI handle response serialization with Pydantic models?
FastAPI uses Pydantic models to define response types for your API endpoints. You can annotate your path operation function with a Pydantic model, and FastAPI will automatically serialize the response data according to the model schema. -
How does FastAPI handle data validation for incoming requests?
FastAPI automatically validates incoming requests against the defined request parameter types using Python type hints. If the request data does not match the expected types, FastAPI will return an error response with details about the validation error. -
How does FastAPI handle request parsing and data extraction?
FastAPI automatically parses incoming requests and extracts data based on the defined request parameter types. You can access the parsed request data directly in your path operation functions with the defined parameter names. -
How does FastAPI handle dependency injection for authentication and authorization?
FastAPI supports dependency injection for authentication and authorization dependencies using theDependsclass. You can define dependencies to handle user authentication and authorization logic, and FastAPI will automatically inject these dependencies into your path operation functions. - How does FastAPI handle middleware for request processing?
FastAPI supports HTTP middleware for processing incoming requests and outgoing responses before they reach the path operation functions. You can define middleware functions to intercept and modify the request and response data as needed.
In conclusion, mastering FastAPI requires a good understanding of its key features, including request routing, request validation, response serialization, authentication, authorization, error handling, documentation generation, and more. By preparing for these top 25 FastAPI interview questions and answers, you can demonstrate your expertise in using FastAPI to build high-performance APIs with Python. Good luck with your FastAPI interview!
