# Conditional OpenAPI

If you needed to, you could use settings and environment variables to configure OpenAPI conditionally depending on the environment, and even disable it entirely.

## About security, APIs, and docs

Hiding your documentation user interfaces in production *shouldn't* be the way to protect your API.

That doesn't add any extra security to your API, the *path operations* will still be available where they are.

An <a href="https://en.wikipedia.org/wiki/Environment_variable" class="external-link" target="_blank">environment variable</a> (also known as "env var") is a variable that lives outside of the Python code, in the operating system, and could be read by your Python code (or by other programs as well).

) -> Dict[str, Any]:
    headers = {"Authorization": f"token {settings.input_token.get_secret_value()}"}
    # some fields are only used by one query, but GraphQL allows unused variables, so
    # keep them here for simplicity
    variables = {
        "after": after,
        "category_id": category_id,
        "discussion_number": discussion_number,
        "discussion_id": discussion_id,
        "comment_id": comment_id,

    # category_id is only used by one query, but GraphQL allows unused variables, so
    # keep it here for simplicity
    variables = {"after": after, "category_id": category_id}
    response = httpx.post(
        github_graphql_url,
        headers=headers,
        timeout=settings.httpx_timeout,
        json={"query": query, "variables": variables, "operationName": "Q"},
    )
    if response.status_code != 200:

Estos **type hints** son una nueva sintaxis, desde Python 3.6+, que permite declarar el <abbr title="por ejemplo: str, int, float, bool">tipo</abbr> de una variable.

Usando las declaraciones de tipos para tus variables, los editores y otras herramientas pueden proveerte un soporte mejor.

### Memory per Process

Now, when the program loads things in memory, for example, a machine learning model in a variable, or the contents of a large file in a variable, all that **consumes a bit of the memory (RAM)** of the server.

These **"type hints"** or annotations are a special syntax that allow declaring the <abbr title="for example: str, int, float, bool">type</abbr> of a variable.

By declaring types for your variables, editors and tools can give you better support.

### Classes en tant que types

Vous pouvez aussi déclarer une classe comme type d'une variable.

Disons que vous avez une classe `Person`, avec une variable `name` :

```Python hl_lines="1-3"
{!../../../docs_src/python_types/tutorial010.py!}
```

Vous pouvez ensuite déclarer une variable de type `Person` :

```Python hl_lines="6"
{!../../../docs_src/python_types/tutorial010.py!}
```

Doing that in separated functions that don't share logic or variables together is more difficult as you would need to store values in global variables or similar tricks.

Because of that, it's now recommended to instead use the `lifespan` as explained above.

## Technical Details

        "bar",
        "foo"
    ]
}
```

## Recap

Declare headers with `Header`, using the same common pattern as `Query`, `Path` and `Cookie`.