!!! tip
    You'll see what other "things", apart from functions, can be used as dependencies in the next chapter.

Whenever a new request arrives, **FastAPI** will take care of:

* Calling your dependency ("dependable") function with the correct parameters.
* Get the result from your function.
* Assign that result to the parameter in your *path operation function*.

```mermaid
graph TB

    rect rgba(0, 255, 0, .1)
        code ->> function: say_hi(name="Camila")
        function ->> execute: führe Code der Funktion aus
        execute ->> code: gib das Resultat zurück
    end

    rect rgba(0, 255, 255, .1)
        code ->> function: say_hi(name="Camila")
        function ->> code: gib das gespeicherte Resultat zurück
    end

    rect rgba(0, 255, 0, .1)

{!../../../docs_src/custom_response/tutorial008.py!}
```

1. This is the generator function. It's a "generator function" because it contains `yield` statements inside.
2. By using a `with` block, we make sure that the file-like object is closed after the generator function is done. So, after it finishes sending the response.

### Other utility functions

Any other utility function that you call directly can be created with normal `def` or `async def` and FastAPI won't affect the way you call it.

This is in contrast to the functions that FastAPI calls for you: *path operation functions* and dependencies.

            token,
        )
    }
    add(FirErrors.FUNCTION_EXPECTED) { firDiagnostic ->
        FunctionExpectedImpl(
            firDiagnostic.a,
            firSymbolBuilder.typeBuilder.buildKtType(firDiagnostic.b),
            firDiagnostic as KtPsiDiagnostic,
            token,
        )
    }
    add(FirErrors.INTERFACE_AS_FUNCTION) { firDiagnostic ->
        InterfaceAsFunctionImpl(

The [Func] type, which represents a function or method symbol, now
has a [Func.Signature] method that returns the function's type, which

    Maybe you need to start a new version, or you just got tired of running it. 🤷

### Lifespan function

The first thing to notice, is that we are defining an async function with `yield`. This is very similar to Dependencies with `yield`.

```Python hl_lines="14-19"
{!../../../docs_src/events/tutorial003.py!}
```

The first part of the function, before the `yield`, will be executed **before** the application starts.

    override fun readWriteAccessWithFullExpressionByResolve(assignment: KtBinaryExpression): Pair<ReferenceAccess, KtExpression>? {
        val function = assignment.operationReference.mainReference.resolve() as? KtNamedFunction ?: return null
        val name = function.name ?: return null
        return if (Name.identifier(name) in OperatorConventions.ASSIGNMENT_OPERATIONS.values)
            ReferenceAccess.READ to assignment

participant code as Code
participant function as say_hi()
participant execute as Execute function

    rect rgba(0, 255, 0, .1)
        code ->> function: say_hi(name="Camila")
        function ->> execute: execute function code
        execute ->> code: return the result
    end

    rect rgba(0, 255, 255, .1)
        code ->> function: say_hi(name="Camila")
        function ->> code: return stored result
    end

# Response Model - Return Type

You can declare the type used for the response by annotating the *path operation function* **return type**.

You can use **type annotations** the same way you would for input data in function **parameters**, you can use Pydantic models, lists, dictionaries, scalar values like integers, booleans, etc.

=== "Python 3.10+"

    ```Python hl_lines="16  21"
    {!> ../../../docs_src/response_model/tutorial001_01_py310.py!}
    ```