"detail": [
            {
                "type": "int_parsing",
                "loc": ["path", "item_id"],
                "msg": "Input should be a valid integer, unable to parse string as an integer",
                "input": "foobar",
            }
        ]
    }


def test_path_int_True():
    response = client.get("/path/int/True")
    assert response.status_code == 422

                "msg": "Input should be a valid integer, unable to parse string as an integer",
                "input": "five",
            },
            {
                "type": "int_parsing",
                "loc": ["query", "q", 1],
                "msg": "Input should be a valid integer, unable to parse string as an integer",
                "input": "six",
            },
        ]
    }

            {
                "item_id": "foo",
                "description": "This is an amazing item that has a long description",
            },
        ),
        (
            "/items/bar?q=somequery",
            {
                "item_id": "bar",
                "q": "somequery",
                "description": "This is an amazing item that has a long description",
            },
        ),
        (

                "owner_id": 123,
                "description": "This is an amazing item that has a long description",
            },
        ),
        (
            "/users/1/items/bar?q=somequery",
            {
                "item_id": "bar",
                "owner_id": 1,
                "q": "somequery",
                "description": "This is an amazing item that has a long description",
            },
        ),

@pytest.fixture(name="client")
def client_fixture() -> TestClient:
    from pydantic import BaseModel

    class Address(BaseModel):
        """
        This is a public description of an Address
        \f
        You can't see this part of the docstring, it's private!
        """

        line_1: str
        city: str
        state_province: str

    class Facility(BaseModel):

```JSON
{"item_id": 5, "q": "somequery"}
```

You already created an API that:

* Receives HTTP requests in the _paths_ `/` and `/items/{item_id}`.
* Both _paths_ take `GET` operations (also known as HTTP _methods_).
* The _path_ `/items/{item_id}` has a _path parameter_ `item_id` that should be an `int`.
* The _path_ `/items/{item_id}` has an optional `str` _query parameter_ `q`.

### Interactive API docs

            """
            Pydantic's `by_alias` parameter, passed to Pydantic models to define if
            the output should use the alias names (when provided) or the Python
            attribute names. In an API, if you set an alias, it's probably because you
            want to use it in the result, so you probably want to leave this set to
            `True`.
            """
        ),
    ] = True,
    exclude_unset: Annotated[

    return form_data


@app.get("/users/me")
def read_users_me(current_user: Optional[User] = Depends(get_current_user)):
    if current_user is None:
        return {"msg": "Create an account first"}
    return current_user


client = TestClient(app)


def test_security_oauth2():
    response = client.get("/users/me", headers={"Authorization": "Bearer footokenbar"})

class EndpointContext(TypedDict, total=False):
    function: str
    path: str
    file: str
    line: int


class HTTPException(StarletteHTTPException):
    """
    An HTTP exception you can raise in your own code to show errors to the client.

    This is for client errors, invalid authentication, invalid data, etc. Not for server
    errors in your code.

    Read more about it in the

                * Serialization: you could return an arbitrary object and the
                    `response_model` would be used to serialize that object into the
                    corresponding JSON.
                * Filtering: the JSON sent to the client will only contain the data
                    (fields) defined in the `response_model`. If you returned an object
                    that contains an attribute `password` but the `response_model` does