!!! info
    Keep in mind that dataclasses can't do everything Pydantic models can do.

    So, you might still need to use Pydantic models.

    But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

## Dataclasses in `response_model`

You can also use `dataclasses` in the `response_model` parameter:

```Python hl_lines="1  7-13  19"

## Recap

Having **HTTPS** is very important, and quite **critical** in most cases. Most of the effort you as a developer have to put around HTTPS is just about **understanding these concepts** and how they work.

* Automatic data model documentation with <a href="https://json-schema.org/" class="external-link" target="_blank"><strong>JSON Schema</strong></a> (as OpenAPI itself is based on JSON Schema).
* Designed around these standards, after a meticulous study. Instead of an afterthought layer on top.
* This also allows using automatic **client code generation** in many languages.

### Automatic docs

logins:
  - jina-ai
  - deta
  - investsuite
  - mikeckennedy
  - deepset-ai
  - cryptapi
  - xoflare
  - DropbaseHQ
  - VincentParedes
  - BLUE-DEVIL1134
  - ObliviousAI
  - Doist
  - nihpo
  - armand-sauzay
  - databento-bot
  - databento
  - nanram22
  - Flint-company
  - porter-dev
  - fern-api
  - ndimares
  - svixhq
  - Alek99
  - codacy
  - zanfaruqui
  - scalar
  - bump-sh

    return client


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"

<img src="/img/tutorial/body/image03.png">

You also get error checks for incorrect type operations:

<img src="/img/tutorial/body/image04.png">

This is not by chance, the whole framework was built around that design.

And it was thoroughly tested at the design phase, before any implementation, to ensure it would work with all the editors.

There were even some changes to Pydantic itself to support this.

    if x_token != fake_secret_token:
        raise HTTPException(status_code=400, detail="Invalid X-Token header")
    if item_id not in fake_db:
        raise HTTPException(status_code=404, detail="Item not found")
    return fake_db[item_id]


@app.post("/items/", response_model=Item)
async def create_item(item: Item, x_token: str = Header()):
    if x_token != fake_secret_token:

    * So, by using FastAPI you are saving development time, bugs, lines of code, and you would probably get the same performance (or better) you would if you didn't use it (as you would have to implement it all...

    response = client.get(
        "/items/bar?token=jessica", headers={"X-Token": "fake-super-secret-token"}
    )
    assert response.status_code == 404
    assert response.json() == {"detail": "Item not found"}


def test_items_plumbus_with_no_token(client: TestClient):
    response = client.get(
        "/items/plumbus", headers={"X-Token": "fake-super-secret-token"}
    )
    assert response.status_code == 422

    response = client.get(
        "/items/bar?token=jessica", headers={"X-Token": "fake-super-secret-token"}
    )
    assert response.status_code == 404
    assert response.json() == {"detail": "Item not found"}


@needs_py39
def test_items_plumbus_with_no_token(client: TestClient):
    response = client.get(
        "/items/plumbus", headers={"X-Token": "fake-super-secret-token"}
    )