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Learn how to format API responses in `FastAPI` using Pydantic models for better structure and documentation.
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How to Customize API Responses in FastAPI: A Comprehensive Guide

In developing APIs using FastAPI, you may often find that the default response format does not meet your requirements. For instance, you might want your endpoints to return data in a structured way, rather than the standard list or dictionary response types. This guide examines a common scenario encountered when working with FastAPI and provides practical solutions to help you achieve the desired response format.

The Problem

In FastAPI, you may be querying data from a database and want to return it in a specific format. Consider the following code snippet:

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This code returns a list of queried posts, but the response looks like:

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However, you aim to format the response like this:

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In other words, you want to wrap your data response inside a dictionary with a key of "response". Let’s explore how to achieve that.

Solution Overview

There are two primary methods to structure your FastAPI response as desired:

Quick and Dirty Solution: Return a dictionary with your data.

Proper Solution: Use Pydantic models to define and structure your API responses.

Quick and Dirty Solution

If you are looking for a quick fix without worrying about documentation or proper structuring, you can simply return a dictionary that maps to your desired structure:

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The Proper Solution with Pydantic

Using Pydantic models allows for better validation and documentation of your API responses, which is especially useful for larger applications. Here’s how you can set this up:

Step 1: Define Your Pydantic Models

First, define the Pydantic models that describe the schema of your response. This lets FastAPI know what to expect and helps with validation.

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Step 2: Update Your API Endpoint

Then, modify your FastAPI endpoint to use this new model for the response. You will specify the response_model parameter to tell FastAPI how you want the output formatted:

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Conclusion

By following these steps, you can ensure your API responses are not just structured according to your requirements but are also well-documented and validated. Whether you choose the quick solution or the full Pydantic model approach, you now have the tools to control how your FastAPI application responds to requests.

With clear formatting, your API can provide a better developer experience for all who consume your service. Happy coding!