You can also use regular `def` functions (without `async`), and use `yield` the same way.

{* ../../docs_src/stream_data/tutorial001_py310.py ln[26:29] hl[27] *}

### No Annotation { #no-annotation }

You don't really need to declare the return type annotation for streaming binary data.

      Runnable task, @ParametricNullness T result);

  /**
   * {@inheritDoc}
   *
   * <p>All elements in the returned list must be {@link ListenableFuture} instances. The easiest
   * way to obtain a {@code List<ListenableFuture<T>>} from this method is an unchecked (but safe)
   * cast:
   *
   * <pre>
   *   {@code @SuppressWarnings("unchecked") // guaranteed by invokeAll contract}

 limitations under the License.
-->
Contributing to Apache Maven
======================

You have found a bug or you have an idea for a cool new feature? Contributing
code is a great way to give something back to the open source community. Before
you dig right into the code, there are a few guidelines that we need
contributors to follow so that we can have a chance of keeping on top of
things.

We can do better...

## What makes a dependency { #what-makes-a-dependency }

Up to now you have seen dependencies declared as functions.

But that's not the only way to declare dependencies (although it would probably be the more common).

The key factor is that a dependency should be a "callable".

A "**callable**" in Python is anything that Python can "call" like a function.

I can reach the key; and if it makes me grow smaller, I can creep
under the door; so either way I'll get into the garden, and I
don't care which happens!'

  She ate a little bit, and said anxiously to herself, `Which
way?  Which way?', holding her hand on the top of her head to
feel which way it was growing, and she was quite surprised to
find that she remained the same size:  to be sure, this generally

But that is still not that useful.

Let's make it give us the current user.

## Create a user model { #create-a-user-model }

First, let's create a Pydantic user model.

The same way we use Pydantic to declare bodies, we can use it anywhere else:

{* ../../docs_src/security/tutorial002_an_py310.py hl[5,12:6] *}

## Create a `get_current_user` dependency { #create-a-get-current-user-dependency }

```

It is not encrypted, so, anyone could recover the information from the contents.

But it's signed. So, when you receive a token that you emitted, you can verify that you actually emitted it.

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.

# Global Dependencies { #global-dependencies }

For some types of applications you might want to add dependencies to the whole application.

Similar to the way you can [add `dependencies` to the *path operation decorators*](dependencies-in-path-operation-decorators.md), you can add them to the `FastAPI` application.

In that case, they will be applied to all the *path operations* in the application:

{* ../../docs_src/dependencies/tutorial012_an_py310.py hl[17] *}

   * or extract a variable, and put the suppression on that. However, a local variable typically
   * doesn't work: Because nullness analyses typically infer the nullness of local variables,
   * there's no way to assign a {@code @Nullable T} to a field {@code T foo;} and instruct the
   * analysis that that means "plain {@code T}" rather than the inferred type {@code @Nullable T}.

# Body - Fields { #body-fields }

The same way you can declare additional validation and metadata in *path operation function* parameters with `Query`, `Path` and `Body`, you can declare validation and metadata inside of Pydantic models using Pydantic's `Field`.

## Import `Field` { #import-field }

First, you have to import it:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}


/// warning