In FastAPI, query parameters can be defined by adding function parameters with type annotations in the endpoint function. FastAPI automatically reads them from the query string and validates their types.
In depth
Query parameters in FastAPI allow clients to send additional information via the URL, which can modify the behavior of API endpoints. You define these parameters simply by listing them as function arguments in your route handler, and you can specify types for automatic validation. For example, an integer, string, or even a float can be specified, and FastAPI will return a 422 error if the type does not match. You can also provide default values which make them optional. If not provided, you can handle them accordingly in your logic.
It is essential to take care of edge cases, such as when a query parameter is missing or when the data does not meet the expected format. FastAPI provides helpful error messages in those situations, which is beneficial for both development and user experience. Additionally, FastAPI supports validation through Pydantic models, which can also include query parameters for more complex data structures. These features greatly enhance your API's robustness and usability.
Example scenario
In a project I worked on, we developed an API for a product catalog where users could filter products based on price and category. We defined query parameters for 'min_price' and 'max_price' in the endpoint. This allowed users to send requests like '/products?min_price=10&max_price=50'. FastAPI validated these parameters, ensuring they were numbers, and our application logic then filtered the results accordingly before sending the response.
Common mistakes
A common mistake is not using type annotations in the function parameters, which disables FastAPI's automatic validation and conversion. This could lead to type errors in the application. Another mistake is assuming that all parameters are required, which could lead to confusion if not handled properly. Developers should provide default values or use optional types to ensure that missing parameters do not cause application errors.
Follow-up questions
- How would you set default values for query parameters?
- Can you explain how to handle optional query parameters?
- What would you do if a client sends an invalid value for a query parameter?
- How can you leverage Pydantic for more complex query parameters?
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