This is to prevent accidentally sharing the same connection for different things (for different requests).

    But in FastAPI, using normal functions (`def`) more than one thread could interact with the database for the same request, so we need to make SQLite know that it should allow that with `connect_args={"check_same_thread": False}`.

            required_params=dependant.body_params, received_body=body
        )
        values.update(body_values)
        errors.extend(body_errors)
    if dependant.http_connection_param_name:
        values[dependant.http_connection_param_name] = request
    if dependant.request_param_name and isinstance(request, Request):
        values[dependant.request_param_name] = request

!!! tip

    Additionally, a background task is normally an independent set of logic that should be handled separately, with its own resources (e.g. its own database connection).

    So, this way you will probably have cleaner code.

This can be very useful for setting up **resources** that you need to use for the whole app, and that are **shared** among requests, and/or that you need to **clean up** afterwards. For example, a database connection pool, or loading a shared machine learning model.

## Use Case

Let's start with an example **use case** and then see how to solve it with this.

Additionally, a background task is normally an independent set of logic that should be handled separately, with its own resources (e.g. its own database connection).

* Import `databases`.
* Create a `DATABASE_URL`.
* Create a `database` object.

```Python hl_lines="3  9  12"
{!../../../docs_src/async_sql_databases/tutorial001.py!}
```

!!! tip
    If you were connecting to a different database (e.g. PostgreSQL), you would need to change the `DATABASE_URL`.

## Create the tables

They are generally all related to the same application.

The analogy in the relational database world would be a "database" (a specific database, not the database server).

The analogy in **MongoDB** would be a "collection".

In the code, a `Bucket` represents the main entrypoint of communication with the database.

This utility function will:

* Connect to a **Couchbase** cluster (that might be a single machine).

    ```
    from app.routers import items
    ```

* The `app` directory contains everything. And it has an empty file `app/__init__.py`, so it is a "Python package" (a collection of "Python modules"): `app`.
* It contains an `app/main.py` file. As it is inside a Python package (a directory with a file `__init__.py`), it is a "module" of that package: `app.main`.

This is the case for most of the web applications.

Many, many users, but your server is waiting 🕙 for their not-so-good connection to send their requests.

And then waiting 🕙 again for the responses to come back.

This "waiting" 🕙 is measured in microseconds, but still, summing it all, it's a lot of waiting in the end.

* **Automatic validation** even for *path operation* parameters defined in dependencies.
* Support for complex user authentication systems, **database connections**, etc.
* **No compromise** with databases, frontends, etc. But easy integration with all of them.

### Unlimited "plug-ins"

Or in other way, no need for them, import and use the code you need.