"format": "time",
                            }
                        ),
                        "process_after": IsDict(
                            {
                                "title": "Process After",
                                "type": "string",
                                "format": "duration",
                            }
                        )

# Background Tasks - `BackgroundTasks`

You can declare a parameter in a *path operation function* or dependency function with the type `BackgroundTasks`, and then you can use it to schedule the execution of background tasks after the response is sent.

You can import it directly from `fastapi`:

```python
from fastapi import BackgroundTasks
```

    * If you are comparing Uvicorn, compare it against Daphne, Hypercorn, uWSGI, etc. Application servers.
* **Starlette**:
    * Will have the next best performance, after Uvicorn. In fact, Starlette uses Uvicorn to run. So, it probably can only get "slower" than Uvicorn by having to execute more code.
    * But it provides you the tools to build simple web applications, with routing based on paths, etc.

## Run it

After that, you just need to install `pytest`:

<div class="termy">

```console
$ pip install pytest

---> 100%
```

</div>

    end_datetime: datetime = Body(),
    process_after: timedelta = Body(),
    repeat_at: Union[time, None] = Body(default=None),
):
    start_process = start_datetime + process_after
    duration = end_datetime - start_process
    return {
        "item_id": item_id,
        "start_datetime": start_datetime,
        "end_datetime": end_datetime,
        "process_after": process_after,
        "repeat_at": repeat_at,

* <a href="https://docs.porter.run/language-specific-guides/fastapi" class="external-link" target="_blank">Porter</a>

                                "format": "time",
                            }
                        ),
                        "process_after": IsDict(
                            {
                                "title": "Process After",
                                "type": "string",
                                "format": "duration",
                            }
                        )

    # TODO: remove after upgrading SQLAlchemy to a version that includes the following changes
    # https://github.com/sqlalchemy/sqlalchemy/commit/59521abcc0676e936b31a523bd968fc157fef0c2
    'ignore:datetime\.datetime\.utcfromtimestamp\(\) is deprecated and scheduled for removal in a future version\..*:DeprecationWarning:sqlalchemy',

participant handler as Exception handler
participant dep as Dep with yield
participant operation as Path Operation
participant tasks as Background tasks

    Note over client,tasks: Can raise exception for dependency, handled after response is sent
    Note over client,operation: Can raise HTTPException and can change the response
    client ->> dep: Start request
    Note over dep: Run code up to yield
    opt raise

Doing this, our `GzipRequest` will take care of decompressing the data (if necessary) before passing it to our *path operations*.

After that, all of the processing logic is the same.

But because of our changes in `GzipRequest.body`, the request body will be automatically decompressed when it is loaded by **FastAPI** when needed.