```JSON hl_lines="4-8"
{
    "openapi": "3.1.0",
    // More stuff here
    "servers": [
        {
            "url": "/api/v1"
        }
    ],
    "paths": {
            // More stuff here
    }
}
```

```Python hl_lines="3"
{!../../../docs_src/first_steps/tutorial001.py!}
```

Here the `app` variable will be an "instance" of the class `FastAPI`.

This will be the main point of interaction to create all your API.

### Step 3: create a *path operation*

#### Path

"Path" here refers to the last part of the URL starting from the first `/`.

So, in a URL like:

```

def test_get_no_item(client: TestClient):
    response = client.get("/items/foo")
    assert response.status_code == 404, response.text
    assert response.json() == {"detail": "Item not found, there's only a plumbus here"}


def test_get(client: TestClient):
    response = client.get("/items/plumbus")
    assert response.status_code == 200, response.text
    assert response.json() == "plumbus"

### Virtual environment with `venv`

You can create an isolated virtual local environment in a directory using Python's `venv` module. Let's do this in the cloned repository (where the `requirements.txt` is):

<div class="termy">

```console
$ python -m venv env
```

    In this case, it's a list of `Item` dataclasses.

6. Here we are returning a dictionary that contains `items` which is a list of dataclasses.

    FastAPI is still capable of <abbr title="converting the data to a format that can be transmitted">serializing</abbr> the data to JSON.

7. Here the `response_model` is using a type annotation of a list of `Author` dataclasses.

* It will **limit and filter** the output data to what is defined in the return type.
    * This is particularly important for **security**, we'll see more of that below.

## `response_model` Parameter

There are some cases where you need or want to return some data that is not exactly what the type declares.

This will help us inside of the function with all the completion and type checks.

!!! tip
    You might remember that request bodies are also declared with Pydantic models.

    Here **FastAPI** won't get confused because you are using `Depends`.

!!! check
    The way this dependency system is designed allows us to have different dependencies (different "dependables") that all return a `User` model.

The data is calculated each month, you can read the <a href="https://github.com/tiangolo/fastapi/blob/master/.github/actions/people/app/main.py" class="external-link" target="_blank">source code here</a>.

Here I'm also highlighting contributions from sponsors.

You can customize that function. It takes an `APIRoute` and outputs a string.

For example, here it is using the first tag (you will probably have only one tag) and the *path operation* name (the function name).

You can then pass that custom function to **FastAPI** as the `generate_unique_id_function` parameter:

    Notice that all this code is pure SQLAlchemy Core.

    `databases` is not doing anything here yet.

## Import and set up `databases`

* 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`.