And of course, it supports the same:

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

This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.

/// info

Keep in mind that dataclasses can't do everything Pydantic models can do.

@GwtCompatible
public abstract class DiscreteDomain<C extends Comparable> {

  /**
   * Returns the discrete domain for values of type {@code Integer}.
   *
   * <p>This method always returns the same object. That object is serializable; deserializing it
   * results in the same object too.
   *
   * @since 14.0 (since 10.0 as {@code DiscreteDomains.integers()})
   */
  public static DiscreteDomain<Integer> integers() {
    return IntegerDomain.INSTANCE;

 *     their equivalent on the result of {@code Traverser.forTree(tree)} where {@code tree}
 *     implements {@code SuccessorsFunction}, which has a similar API as {@link #children} or can be
 *     the same lambda function as passed into {@link #using(Function)}.
 *     <p>This class is scheduled to be removed in October 2019.
 */
// TODO(b/68134636): Remove by 2019-10
@Deprecated
@Beta
@GwtCompatible

        map sigbuild-r2.12-python3.9 2.12-python3.9
        map sigbuild-r2.12-python3.10 2.12-python3.10
        map sigbuild-r2.12-python3.11 2.12-python3.11
        # TF 2.12 + Clang (containers are the same, but env vars in configs.bzl are different)
        map sigbuild-r2.12-clang 2.12-python3.9
        map sigbuild-r2.12-clang-python3.8 2.12-python3.8
        map sigbuild-r2.12-clang-python3.9 2.12-python3.9

**FastAPI** knows what to do in each case and how to reuse the same object, so that all the background tasks are merged together and are run in the background afterwards:


{* ../../docs_src/background_tasks/tutorial002_an_py310.py hl[13,15,22,25] *}

If you pass a "callable" as a dependency in **FastAPI**, it will analyze the parameters for that "callable", and process them in the same way as the parameters for a *path operation function*. Including sub-dependencies.

That also applies to callables with no parameters at all. The same as it would be for *path operation functions* with no parameters.

  ]
}
```

because the path parameter `item_id` had a value of `"foo"`, which is not an `int`.

The same error would appear if you provided a `float` instead of an `int`, as in: <a href="http://127.0.0.1:8000/items/4.2" class="external-link" target="_blank">http://127.0.0.1:8000/items/4.2</a>

/// check

So, with the same Python type declaration, **FastAPI** gives you data validation.

    }
  }

  /**
   * Returns a hash code, having the same bit length as each of the input hash codes, that combines
   * the information of these hash codes in an ordered fashion. That is, whenever two equal hash
   * codes are produced by two calls to this method, it is <i>as likely as possible</i> that each
   * was computed from the <i>same</i> input hash codes in the <i>same</i> order.
   *

Then you declare your data model as a class that inherits from `BaseModel`.

Use standard Python types for all the attributes:

{* ../../docs_src/body/tutorial001_py310.py hl[5:9] *}


The same as when declaring query parameters, when a model attribute has a default value, it is not required. Otherwise, it is required. Use `None` to make it just optional.

You can use the same dependency *functions* you use normally.

### Dependency requirements { #dependency-requirements }

They can declare request requirements (like headers) or other sub-dependencies:

{* ../../docs_src/dependencies/tutorial006_an_py39.py hl[8,13] *}

### Raise exceptions { #raise-exceptions }

These dependencies can `raise` exceptions, the same as normal dependencies: