name: Test

on:
  push:
    branches:
      - master
  pull_request:
    types:
      - opened
      - synchronize
  schedule:
    # cron every week on monday
    - cron: "0 0 * * 1"

jobs:
  lint:
    runs-on: ubuntu-latest
    steps:
      - name: Dump GitHub context
        env:
          GITHUB_CONTEXT: ${{ toJson(github) }}
        run: echo "$GITHUB_CONTEXT"
      - uses: actions/checkout@v4

            "name": "The Baz"
        }
    ]
}
```

!!! info
    Notice how the `images` key now has a list of image objects.

## Deeply nested models

You can define arbitrarily deeply nested models:

=== "Python 3.10+"

    ```Python hl_lines="7  12  18  21  25"
    {!> ../../../docs_src/body_nested_models/tutorial007_py310.py!}
    ```

=== "Python 3.9+"

> What’s the history of this project? It seems to have come from nowhere to awesome in a few weeks [...]

Here's a little bit of that history.

## Alternatives

Just functions that look the same as the *path operation functions*.

But still, it is very powerful, and allows you to declare arbitrarily deeply nested dependency "graphs" (trees).

!!! tip
    All this might not seem as useful with these simple examples.

    But you will see how useful it is in the chapters about **security**.

    * Use of hierarchical Pydantic models, Python `typing`’s `List` and `Dict`, etc.
    * 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.

* Editor support, including:
    * Completion.
    * Type checks.
* Validation of data:
    * Automatic and clear errors when the data is invalid.
    * Validation even for deeply nested JSON objects.
* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of input data: coming from the network to Python data and types. Reading from:
    * JSON.
    * Path parameters.

                },
                "x-aperture-labs-portal": "blue"
            }
        }
    }
}
```

### Custom OpenAPI *path operation* schema

The dictionary in `openapi_extra` will be deeply merged with the automatically generated OpenAPI schema for the *path operation*.

So, you could add additional data to the automatically generated schema.

That way, you can create a token with an expiration of, let's say, 1 week. And then when the user comes back the next day with the token, you know that user is still logged in to your system.

* ⬆ Bump black from 23.3.0 to 24.3.0. PR [#11325](https://github.com/tiangolo/fastapi/pull/11325) by [@dependabot[bot]](https://github.com/apps/dependabot).
* 👷 Add cron to run test once a week on monday. PR [#11377](https://github.com/tiangolo/fastapi/pull/11377) by [@estebanx64](https://github.com/estebanx64).

* Editor support, including:
    * Completion.
    * Type checks.
* Validation of data:
    * Automatic and clear errors when the data is invalid.
    * Validation even for deeply nested JSON objects.
* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of input data: coming from the network to Python data and types. Reading from:
    * JSON.
    * Path parameters.