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Learn how to effectively validate `GET` parameters using `FastAPI` and `Pydantic` by incorporating regex without needing a model.
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How to Validate a FastAPI GET Parameter with Pydantic Without a Model

In the ever-evolving world of web development, keeping your API both functional and secure is crucial. When using FastAPI, one common requirement might be to validate GET parameters, ensuring they conform to specific formats. Here, we will address the problem of validating a mandatory GET parameter using Pydantic in a FastAPI application without invoking a model.

The Challenge

Imagine you have a simple FastAPI endpoint that uses the following URL structure:

[[See Video to Reveal this Text or Code Snippet]]

In this case, the foo parameter must adhere to a specific regex. In earlier versions of Pydantic (like v1.9), this task was straightforward. However, after migrating to Pydantic 2.5, developers have run into issues with parameter validation, as regex was replaced by pattern, and validation no longer functions as expected.

Previous Working Example

The previous implementation in Pydantic 1.9 looked like this:

[[See Video to Reveal this Text or Code Snippet]]

Here, the foo parameter is enforced to match the defined regex pattern, ensuring input validation.

The Problem with Pydantic 2.5

After the upgrade, however, the expected validation ceased to work when simply changing regex to pattern, leaving developers perplexed:

[[See Video to Reveal this Text or Code Snippet]]

Other suggested implementations, like using Annotated with StringConstraints, also fell short in terms of validation:

[[See Video to Reveal this Text or Code Snippet]]

Finding a Solution

Fortunately, there is a clean and effective solution to restore validation functionality without creating unnecessary complexity. By leveraging the Query type provided by FastAPI, we can validate GET parameters succinctly.

Implementing the Fix

Here’s how to structure your endpoint with Query:

[[See Video to Reveal this Text or Code Snippet]]

Benefits of This Approach

Simplicity: This method keeps your code clean without adding optional or final restrictions to the parameter.

Validation: The parameter foo will adhere to the defined regex pattern, ensuring that it matches the required format upon request.

Conclusion

By following this guide, you can effectively validate GET parameters in FastAPI using Pydantic without the need for complex models. With a few modifications involving the Query type, you can maintain the robustness of your API and ensure proper input validation for a seamless user experience.

Now you can confidently move forward with your FastAPI project and ensure that your parameters are validated correctly—no messy workarounds required!