## Documentation Response description - OpenAPI

To define the description of the response, shown in the docs UI, read the docs for [Tutorial - Path Operation Configurations - Response description](../tutorial/path-operation-configuration.md#response-description){.internal-link target=_blank}.

    ```

=== "Python 3.8+"

    ```Python hl_lines="9-11  14-15  18  19  23"
    {!> ../../../docs_src/generate_clients/tutorial001.py!}
    ```

Notice that the *path operations* define the models they use for request payload and response payload, using the models `Item` and `ResponseMessage`.

### API Docs

If you can use the **latest versions of Python**, use the examples for the latest version, those will have the **best and simplest syntax**, for example, "**Python 3.10+**".

#### List

For example, let's define a variable to be a `list` of `str`.

=== "Python 3.9+"

    Declare the variable, with the same colon (`:`) syntax.

    As the type, put `list`.

### OpenAPI support

OpenAPI doesn't support a way to declare a *path parameter* to contain a *path* inside, as that could lead to scenarios that are difficult to test and define.

Nevertheless, you can still do it in **FastAPI**, using one of the internal tools from Starlette.

And the docs would still work, although not adding any documentation telling that the parameter should contain a path.

**FastAPI** will know that it can use this dependency to define a "security scheme" in the OpenAPI schema (and the automatic API docs).

!!! info "Technical Details"

# Body - Nested Models

With **FastAPI**, you can define, validate, document, and use arbitrarily deeply nested models (thanks to Pydantic).

## List fields

You can define an attribute to be a subtype. For example, a Python `list`:

=== "Python 3.10+"

    ```Python hl_lines="12"
    {!> ../../../docs_src/body_nested_models/tutorial001_py310.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="14"

=== "Python 3.8+"

    ```Python hl_lines="31  37"
    {!> ../../../docs_src/response_model/tutorial006.py!}
    ```

## Recap

Use the *path operation decorator's* parameter `response_model` to define response models and especially to ensure private data is filtered out.

    {!> ../../../docs_src/query_params_str_validations/tutorial003_py310.py!}
    ```

## 🚮 🥔 🧬

👆 💪 🔬 <abbr title="A regular expression, regex or regexp is a sequence of characters that define a search pattern for strings.">🥔 🧬</abbr> 👈 🔢 🔜 🏏:

=== "🐍 3️⃣.6️⃣ &amp; 🔛"

    ```Python hl_lines="11"
    {!> ../../../docs_src/query_params_str_validations/tutorial004.py!}
    ```

## Import Couchbase components

For now, don't pay attention to the rest, only the imports:

```Python hl_lines="3-5"
{!../../../docs_src/nosql_databases/tutorial001.py!}
```

## Define a constant to use as a "document type"

We will use it later as a fixed field `type` in our documents.

This is not required by Couchbase, but is a good practice that will help you afterwards.

```Python hl_lines="9"

    * Because pydantic data structures are just instances of classes you define; auto-completion, linting, mypy and your intuition should all work properly with your validated data.
* Validate **complex structures**:
    * 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.