new_field.key_field = create_cloned_field(  # type: ignore[attr-defined]
            field.key_field,  # type: ignore[attr-defined]
            cloned_types=cloned_types,
        )
    new_field.validators = field.validators  # type: ignore[attr-defined]
    new_field.pre_validators = field.pre_validators  # type: ignore[attr-defined]
    new_field.post_validators = field.post_validators  # type: ignore[attr-defined]

@needs_pydanticv1
def test_union_scalar_list():
    # For coverage
    # TODO: there might not be a current valid code path that uses this, it would
    # potentially enable query parameters defined as both a scalar and a list
    # but that would require more refactors, also not sure it's really useful
    from fastapi._compat import is_pv1_scalar_field

    field_info = FieldInfo()
    field = ModelField(

      - coverage-combine
    runs-on: ubuntu-latest
    steps:
      - name: Dump GitHub context
        env:
          GITHUB_CONTEXT: ${{ toJson(github) }}
        run: echo "$GITHUB_CONTEXT"
      - name: Decide whether the needed jobs succeeded or failed
        uses: re-actors/alls-green@release/v1
        with:

If you want to secure your API, there are several better things you can do, for example:

* Make sure you have well defined Pydantic models for your request bodies and responses.
* Configure any required permissions and roles using dependencies.
* Never store plaintext passwords, only password hashes.

asynchrone Funktionsaufrufe in Ihre Tests integrieren (z. B. bei Verwendung von <a href="https://stackoverflow.com/questions/41584243/runtimeerror-task-attached-to-a-different-loop" class="external-link" target="_blank">MongoDBs MotorClient</a>), dann denken Sie daran, Objekte zu instanziieren, die einen Event Loop nur innerhalb asynchroner Funktionen benötigen, z. B. einen `@app.on_event("startup")`-Callback....

## Singular values in body

The same way there is a `Query` and `Path` to define extra data for query and path parameters, **FastAPI** provides an equivalent `Body`.

For example, extending the previous model, you could decide that you want to have another key `importance` in the same body, besides the `item` and `user`.

If you declare it as is, because it is a singular value, **FastAPI** will assume that it is a query parameter.

And it can also be used by yourself, to debug, check and test the same application.

## The `password` flow

Now let's go back a bit and understand what is all that.

The `password` "flow" is one of the ways ("flows") defined in OAuth2, to handle security and authentication.

OAuth2 was designed so that the backend or API could be independent of the server that authenticates the user.

All in a way that provided the best development experience for all the developers.

## Requirements

After testing several alternatives, I decided that I was going to use <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">**Pydantic**</a> for its advantages.

    * And validators allow complex data schemas to be clearly and easily defined, checked and documented as JSON Schema.
    * You can have deeply **nested JSON** objects and have them all validated and annotated.
* **Extensible**:
    * Pydantic allows custom data types to be defined or you can extend validation with methods on a model decorated with the validator decorator.

    You can use a closing code from the <a href="https://tools.ietf.org/html/rfc6455#section-7.4.1" class="external-link" target="_blank">valid codes defined in the specification</a>.

### Try the WebSockets with dependencies

If your file is named `main.py`, run your application with:

<div class="termy">

```console
$ fastapi dev main.py