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

* Then it returns the **response**.

!!! note "Technical Details"
    If you have dependencies with `yield`, the exit code will run *after* the middleware.

    If there were any background tasks (documented later), they will run *after* all the middleware.

## Create a middleware

To create a middleware you use the decorator `@app.middleware("http")` on top of a function.

# 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
```

    This makes sure that if you use a terminal program installed by that package, you use the one from your local environment and not any other that could be installed globally.

### Install requirements using pip

After activating the environment as described above:

<div class="termy">

```console
$ pip install -r requirements.txt

---> 100%
```

</div>

    if response.status_code != 200:
        logging.error(
            f"Response was not 200, after: {after}, category_id: {category_id}"
        )
        logging.error(response.text)
        raise RuntimeError(response.text)
    data = response.json()
    if "errors" in data:
        logging.error(f"Errors in response, after: {after}, category_id: {category_id}")
        logging.error(data["errors"])

    * 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.

    if response.status_code != 200:
        logging.error(
            f"Response was not 200, after: {after}, category_id: {category_id}"
        )
        logging.error(response.text)
        raise RuntimeError(response.text)
    data = response.json()
    if "errors" in data:
        logging.error(f"Errors in response, after: {after}, category_id: {category_id}")
        logging.error(response.text)

    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,

  },
  "author": "",
  "license": "",
  "devDependencies": {
    "@hey-api/openapi-ts": "^0.27.38",
    "typescript": "^4.6.2"
  }
}
```

After having that NPM `generate-client` script there, you can run it with:

<div class="termy">

```console
$ npm run generate-client

frontend-app@1.0.0 generate-client /home/user/code/frontend-app

You could want to set up a different database for testing, rollback the data after the tests, pre-fill it with some testing data, etc.

The main idea is exactly the same you saw in that previous chapter.

## Add tests for the SQL app