from fastapi import FastAPI, Path
from typing_extensions import Annotated

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(
    item_id: Annotated[int, Path(title="The ID of the item to get")], q: str
):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})

from fastapi import FastAPI, Path

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(
    *,
    item_id: int = Path(title="The ID of the item to get", gt=0, le=1000),
    q: str,
):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})

                    "loc": ["path", "item_id"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "foo",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {
                    "loc": ["path", "item_id"],

@needs_py39
@pytest.mark.parametrize(
    "path,headers,expected_status,expected_response",
    [
        ("/items", None, 200, {"X-Token values": None}),
        ("/items", {"x-token": "foo"}, 200, {"X-Token values": ["foo"]}),
        # TODO: fix this, is it a bug?
        # ("/items", [("x-token", "foo"), ("x-token", "bar")], 200, {"X-Token values": ["foo", "bar"]}),
    ],
)

object, for example placed at `ALIAS/bucket/path/to/file.txt` append `/xl.meta`, for instance `mc support inspect ALIAS/bucket/path/to/file.txt/xl.meta`. All files can be collected, so this can also be used to retrieve `part.*` files, etc.

Wildcards can be used, for example `mc support inspect ALIAS/bucket/path/**/xl.meta` will collect all `xl.meta` recursively. `mc support inspect ALIAS/bucket/path/to/file.txt/*/part.*` will collect parts for all versions for the object located at `buc...

from typing import Annotated

from fastapi import FastAPI, Path

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(
    item_id: Annotated[int, Path(title="The ID of the item to get", ge=1)], q: str
):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})

@needs_py310
def test_post_file(tmp_path: Path, client: TestClient):
    path = tmp_path / "test.txt"
    path.write_bytes(b"<file content>")

    with path.open("rb") as file:
        response = client.post("/files/", files={"file": file})
    assert response.status_code == 200, response.text
    assert response.json() == {"file_size": 14}


@needs_py310
def test_post_upload_file(tmp_path: Path, client: TestClient):

client = TestClient(app)


@pytest.mark.parametrize(
    "path,expected_status,expected_response",
    [
        ("/", 200, {"message": "Hello World"}),
        ("/nonexistent", 404, {"detail": "Not Found"}),
    ],
)
def test_get_path(path, expected_status, expected_response):
    response = client.get(path)
    assert response.status_code == expected_status
    assert response.json() == expected_response

しかし、`Response` を直接返すと、データは自動的に変換されず、ドキュメントも自動生成されません (例えば、生成されるOpenAPIの一部としてHTTPヘッダー `Content-Type` に特定の「メディアタイプ」を含めるなど) 。

しかし、*path operationデコレータ* に、使いたい `Response` を宣言することもできます。

*path operation関数* から返されるコンテンツは、その `Response` に含まれます。

そしてもし、`Response` が、`JSONResponse` や `UJSONResponse` の場合のようにJSONメディアタイプ (`application/json`) ならば、データは *path operationデコレータ* に宣言したPydantic `response_model` により自動的に変換 (もしくはフィルタ) されます。

/// note | "備考"

from typing import Annotated

from fastapi import FastAPI, Path

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(
    item_id: Annotated[int, Path(title="The ID of the item to get", gt=0, le=1000)],
    q: str,
):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})