So, even with the code above that doesn't use Pydantic explicitly, FastAPI is using Pydantic to convert those standard dataclasses to Pydantic's own flavor of dataclasses.

And of course, it supports the same:

* data validation
* data serialization
* data documentation, etc.

                )
            },
            block = block
        )

    /**
     * Runs the binary compatibility check against two source trees.
     *
     * The fixture build supports both Java and Kotlin sources.
     *
     * @param v1 sources producer for V1, receiver is the `src/main` directory
     * @param v2 sources producer for V2, receiver is the `src/main` directory

In these cases, it could make sense to store the tags in an `Enum`.

**FastAPI** supports that the same way as with plain strings:

{* ../../docs_src/path_operation_configuration/tutorial002b_py39.py hl[1,8:10,13,18] *}

## Summary and description { #summary-and-description }

as in:

{* ../../docs_src/body_nested_models/tutorial008_py39.py hl[13] *}

## Editor support everywhere { #editor-support-everywhere }

And you get editor support everywhere.

Even for items inside of lists:

<img src="/img/tutorial/body-nested-models/image01.png">

You couldn't get this kind of editor support if you were working directly with `dict` instead of Pydantic models.

 *   <li>readTimeout - Read timeout in milliseconds (default: 10000)</li>
 * </ul>
 *
 * <p>The client supports URLs in the format: {@code gcs://bucket-name/object-path}
 *
 * <p>Features:
 * <ul>
 *   <li>Automatic initialization of GCS client</li>
 *   <li>Support for HEAD and GET operations</li>
 *   <li>Content length validation</li>
 *   <li>MIME type detection</li>

If you have an old FastAPI app, you might be using Pydantic version 1.

FastAPI version 0.100.0 had support for either Pydantic v1 or v2. It would use whichever you had installed.

FastAPI version 0.119.0 introduced partial support for Pydantic v1 from inside of Pydantic v2 (as `pydantic.v1`), to facilitate the migration to v2.

FastAPI 0.126.0 dropped support for Pydantic v1, while still supporting `pydantic.v1` for a little while.

/// warning

 * to register, retrieve, and discover available data stores.
 *
 * <p>Data stores are registered by name and class name, allowing flexible lookup.
 * The factory also supports dynamic discovery of data store plugins by scanning
 * JAR files for data store configurations.</p>
 *
 * <p>Thread-safe operations are supported for registration and retrieval of data stores.

    encoded as JSON before it is sent to the client.

    You can also use it yourself, for example to convert objects before saving them
    in a database that supports only JSON.

    Read more about it in the
    [FastAPI docs for JSON Compatible Encoder](https://fastapi.tiangolo.com/tutorial/encoder/).
    """
    custom_encoder = custom_encoder or {}
    if custom_encoder:

 *   <li>readTimeout - Read timeout in milliseconds (default: 10000)</li>
 * </ul>
 *
 * <p>The client supports URLs in the format: {@code s3://bucket-name/object-path}
 *
 * <p>Features:
 * <ul>
 *   <li>Automatic initialization of AWS S3 client</li>
 *   <li>Support for HEAD and GET operations</li>
 *   <li>Content length validation</li>
 *   <li>MIME type detection</li>

import software.amazon.awssdk.services.s3.model.Tag;
import software.amazon.awssdk.services.s3.model.Tagging;

/**
 * S3-compatible storage client implementation using AWS SDK v2.
 * Supports Amazon S3, MinIO, and other S3-compatible storage systems.
 */
public class S3StorageClient implements StorageClient {

    private static final Logger logger = LogManager.getLogger(S3StorageClient.class);