* L'apprentissage automatique (ou **Machine Learning**) : cela nécessite de nombreuses multiplications de matrices et vecteurs. Imaginez une énorme feuille de calcul remplie de nombres que vous multiplierez entre eux tous au même moment.

```Python
    return {"item_name": item.name, "item_id": item_id}
```

...da:

```Python
        ... "item_name": item.name ...
```

...a:

```Python
        ... "item_price": item.price ...
```

...e osserva come il tuo editor di testo autocompleterà gli attributi e sarà in grado di riconoscere i loro tipi:

![editor support](https://fastapi.tiangolo.com/img/vscode-completion.png)

    response = client.post("/items/", json={"name": "Foo", "price": 50.5})
    assert response.status_code == 200
    assert response.json() == {
        "name": "Foo",
        "price": 50.5,
        "description": None,
        "tax": None,
    }


@needs_py310
def test_post_with_str_float(client: TestClient):
    response = client.post("/items/", json={"name": "Foo", "price": "50.5"})
    assert response.status_code == 200

    response = client.post("/items/", json={"name": "Foo", "price": 50.5})
    assert response.status_code == 200
    assert response.json() == {
        "name": "Foo",
        "price": 50.5,
        "description": None,
        "tax": None,
    }


def test_post_with_str_float(client: TestClient):
    response = client.post("/items/", json={"name": "Foo", "price": "50.5"})
    assert response.status_code == 200

        "description": None,
        "price": 50.2,
        "tax": 10.5,
        "tags": [],
    }


@needs_py39
def test_put(client: TestClient):
    response = client.put(
        "/items/bar", json={"name": "Barz", "price": 3, "description": None}
    )
    assert response.json() == {
        "name": "Barz",
        "description": None,
        "price": 3,
        "tax": 10.5,
        "tags": [],

```Python
    return {"item_name": item.name, "item_id": item_id}
```

...de:

```Python
        ... "item_name": item.name ...
```

...para:

```Python
        ... "item_price": item.price ...
```

...e veja como seu editor irá auto-completar os atributos e saberá os tipos:

![editor support](https://fastapi.tiangolo.com/img/vscode-completion.png)

        "name": "Baz",
        "description": None,
        "price": 50.2,
        "tax": 10.5,
        "tags": [],
    }


def test_put(client: TestClient):
    response = client.put(
        "/items/bar", json={"name": "Barz", "price": 3, "description": None}
    )
    assert response.json() == {
        "name": "Barz",
        "description": None,
        "price": 3,
        "tax": 10.5,
        "tags": [],
    }

        "description": None,
        "price": 50.2,
        "tax": 10.5,
        "tags": [],
    }


@needs_py310
def test_put(client: TestClient):
    response = client.put(
        "/items/bar", json={"name": "Barz", "price": 3, "description": None}
    )
    assert response.json() == {
        "name": "Barz",
        "description": None,
        "price": 3,
        "tax": 10.5,
        "tags": [],

                        "price": IsDict(
                            {
                                "title": "Price",
                                "anyOf": [{"type": "number"}, {"type": "null"}],
                            }
                        )
                        # TODO: remove when deprecating Pydantic v1
                        | IsDict({"title": "Price", "type": "number"}),
                    },

                "Item": {
                    "title": "Item",
                    "required": ["name", "price"],
                    "type": "object",
                    "properties": {
                        "name": {"title": "Name", "type": "string"},
                        "price": {"title": "Price", "type": "number"},
                    },
                },
                "User": {