from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(
    q: str | None = Query(
        default=None,
        title="Query string",
        description="Query string for the items to search in the database that have a good match",
        min_length=3,
    ),
):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

items = {}


@app.on_event("startup")
async def startup_event():
    items["foo"] = {"name": "Fighters"}
    items["bar"] = {"name": "Tenders"}


@app.get("/items/{item_id}")
async def read_items(item_id: str):
    return items[item_id]


def test_read_items():
    with TestClient(app) as client:
        response = client.get("/items/foo")
        assert response.status_code == 200

from typing import Annotated

from fastapi import Depends, FastAPI

app = FastAPI()


async def common_parameters(q: str | None = None, skip: int = 0, limit: int = 100):
    return {"q": q, "skip": skip, "limit": limit}


CommonsDep = Annotated[dict, Depends(common_parameters)]


@app.get("/items/")
async def read_items(commons: CommonsDep):
    return commons


@app.get("/users/")

///

## Tags { #tags }

Sie können Ihrer *Pfadoperation* Tags hinzufügen, indem Sie dem Parameter `tags` eine `list`e von `str`s übergeben (in der Regel nur ein `str`):

{* ../../docs_src/path_operation_configuration/tutorial002_py310.py hl[15,20,25] *}

Diese werden zum OpenAPI-Schema hinzugefügt und von den automatischen Dokumentations-Benutzeroberflächen verwendet:

///

## Tags { #tags }

You can add tags to your *path operation*, pass the parameter `tags` with a `list` of `str` (commonly just one `str`):

{* ../../docs_src/path_operation_configuration/tutorial002_py310.py hl[15,20,25] *}

They will be added to the OpenAPI schema and used by the automatic documentation interfaces:

from fastapi import FastAPI, Form
from fastapi.testclient import TestClient
from inline_snapshot import snapshot
from pydantic import BaseModel

app = FastAPI()


class ItemGroup(BaseModel):
    items: list[tuple[str, str]]


class Coordinate(BaseModel):
    x: float
    y: float


@app.post("/model-with-tuple/")
def post_model_with_tuple(item_group: ItemGroup):
    return item_group

from fastapi import FastAPI
from fastapi.testclient import TestClient
from inline_snapshot import snapshot
from pydantic import BaseModel

app = FastAPI()


class Product(BaseModel):
    name: str
    description: str = None  # type: ignore
    price: float


@app.get("/product")
async def create_item(product: Product):
    return product


client = TestClient(app)


def test_get_with_body():

from pydantic import BaseModel

app = FastAPI()


class JsonApiResponse(JSONResponse):
    media_type = "application/vnd.api+json"


class Error(BaseModel):
    status: str
    title: str


class JsonApiError(BaseModel):
    errors: list[Error]


@app.get(
    "/a",
    response_class=JsonApiResponse,
    responses={500: {"description": "Error", "model": JsonApiError}},
)

from fastapi.testclient import TestClient
from inline_snapshot import snapshot

app = FastAPI()


@app.get("/{repeated_alias}")
def get_parameters_with_repeated_aliases(
    path: str = Path(..., alias="repeated_alias"),
    query: str = Query(..., alias="repeated_alias"),
):
    return {"path": path, "query": query}


client = TestClient(app)


def test_get_parameters():

from enum import Enum

from fastapi import FastAPI


class ModelName(str, Enum):
    alexnet = "alexnet"
    resnet = "resnet"
    lenet = "lenet"


app = FastAPI()


@app.get("/models/{model_name}")
async def get_model(model_name: ModelName):
    if model_name is ModelName.alexnet:
        return {"model_name": model_name, "message": "Deep Learning FTW!"}

    if model_name.value == "lenet":