It used custom types in its declarations instead of standard Python types, but it was still a huge step forward.

It also was one of the first frameworks to generate a custom schema declaring the whole API in JSON.

For example, you might want to try <a href="https://speakeasyapi.dev/?utm_source=fastapi+repo&utm_medium=github+sponsorship" class="external-link" target="_blank">Speakeasy</a>.

There are also several other companies offering similar services that you can search and find online. 🤓

## Generate a TypeScript Frontend Client

Let's start with a simple FastAPI application:

=== "Python 3.9+"

First let's see how editors, mypy and other tools would see this.

`BaseUser` has the base fields. Then `UserIn` inherits from `BaseUser` and adds the `password` field, so, it will include all the fields from both models.

We annotate the function return type as `BaseUser`, but we are actually returning a `UserIn` instance.

!!! tip
    We are using port 9999 instead of the standard HTTP port 80 so that you don't have to run it with admin (`sudo`) privileges.

Now create that other file `routes.toml`:

```TOML hl_lines="5  12  20"
[http]
  [http.middlewares]

    [http.middlewares.api-stripprefix.stripPrefix]
      prefixes = ["/api/v1"]

  [http.routers]

    In our case, this decorator tells **FastAPI** that the function below corresponds to the **path** `/` with an **operation** `get`.

    It is the "**path operation decorator**".

You can also use the other operations:

* `@app.post()`
* `@app.put()`
* `@app.delete()`

And the more exotic ones:

* `@app.options()`
* `@app.head()`
* `@app.patch()`
* `@app.trace()`

!!! tip

    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

## Bodys mit beliebigen `dict`s

Sie können einen Body auch als `dict` deklarieren, mit Schlüsseln eines Typs und Werten eines anderen Typs.

So brauchen Sie vorher nicht zu wissen, wie die Feld-/Attribut-Namen lauten (wie es bei Pydantic-Modellen der Fall wäre).

Das ist nützlich, wenn Sie Schlüssel empfangen, deren Namen Sie nicht bereits kennen.

---

                    "msg": "value is not a valid dict",
                    "type": "type_error.dict",
                }
            ]
        }
    )


@needs_py310
def test_other_exceptions(client: TestClient):
    with patch("json.loads", side_effect=Exception):
        response = client.post("/items/", json={"test": "test2"})
        assert response.status_code == 400, response.text

                    "loc": ["body"],
                    "msg": "value is not a valid dict",
                    "type": "type_error.dict",
                }
            ]
        }
    )


def test_other_exceptions(client: TestClient):
    with patch("json.loads", side_effect=Exception):
        response = client.post("/items/", json={"test": "test2"})
        assert response.status_code == 400, response.text

            client_secret=client_secret,
        )


class OAuth2(SecurityBase):
    """
    This is the base class for OAuth2 authentication, an instance of it would be used
    as a dependency. All other OAuth2 classes inherit from it and customize it for
    each OAuth2 flow.

    You normally would not create a new class inheriting from it but use one of the