@pytest.mark.parametrize(
    "path",
    ["/optional-str", "/model-optional-str"],
)
def test_optional_str_missing_empty_dict(path: str):
    client = TestClient(app)
    response = client.post(path, json={})
    assert response.status_code == 200, response.text
    assert response.json() == {"p": None}


@pytest.mark.parametrize(
    "path",
    ["/optional-str", "/model-optional-str"],
)
def test_optional_str(path: str):

from typing import Annotated

from fastapi import BackgroundTasks, Depends, FastAPI

app = FastAPI()


def write_log(message: str):
    with open("log.txt", mode="a") as log:
        log.write(message)


def get_query(background_tasks: BackgroundTasks, q: str | None = None):
    if q:
        message = f"found query: {q}\n"
        background_tasks.add_task(write_log, message)
    return q

from typing import Union

from fastapi import BackgroundTasks, Depends, FastAPI

app = FastAPI()


def write_log(message: str):
    with open("log.txt", mode="a") as log:
        log.write(message)


def get_query(background_tasks: BackgroundTasks, q: Union[str, None] = None):
    if q:
        message = f"found query: {q}\n"
        background_tasks.add_task(write_log, message)
    return q

# Without aliases


@app.post("/required-list-str", operation_id="required_list_str")
async def read_required_list_str(p: Annotated[list[str], Form()]):
    return {"p": p}


class FormModelRequiredListStr(BaseModel):
    p: list[str]


@app.post("/model-required-list-str", operation_id="model_required_list_str")

from fastapi import FastAPI
from fastapi.responses import JSONResponse
from pydantic import BaseModel


class Item(BaseModel):
    id: str
    value: str


class Message(BaseModel):
    message: str


app = FastAPI()


@app.get(
    "/items/{item_id}",
    response_model=Item,
    responses={
        404: {"model": Message, "description": "The item was not found"},
        200: {

class HeroBase(SQLModel):
    name: str = Field(index=True)
    age: Union[int, None] = Field(default=None, index=True)


class Hero(HeroBase, table=True):
    id: Union[int, None] = Field(default=None, primary_key=True)
    secret_name: str


class HeroPublic(HeroBase):
    id: int


class HeroCreate(HeroBase):
    secret_name: str


class HeroUpdate(HeroBase):

from fastapi import FastAPI, Header
from pydantic import BaseModel

app = FastAPI()


class CommonHeaders(BaseModel):
    host: str
    save_data: bool
    if_modified_since: str | None = None
    traceparent: str | None = None
    x_tag: list[str] = []


@app.get("/items/")
async def read_items(headers: CommonHeaders = Header()):

到目前为止，您一直在使用常见的数据类型，如:

* `int`
* `float`
* `str`
* `bool`

但是您也可以使用更复杂的数据类型。

您仍然会拥有现在已经看到的相同的特性:

* 很棒的编辑器支持。
* 传入请求的数据转换。
* 响应数据转换。
* 数据验证。
* 自动补全和文档。

## 其他数据类型

下面是一些你可以使用的其他数据类型:

* `UUID`:
    * 一种标准的 "通用唯一标识符" ，在许多数据库和系统中用作ID。
    * 在请求和响应中将以 `str` 表示。
* `datetime.datetime`:
    * 一个 Python `datetime.datetime`.
    * 在请求和响应中将表示为 ISO 8601 格式的 `str` ，比如: `2008-09-15T15:53:00+05:00`.

		}
	}
}

func TestParseKey(t *testing.T) {
	testCases := []struct {
		str         string
		expectedKey Key
	}{
		{
			str: "01894394-d046-4783-ba0d-f1c6885790dc.event",
			expectedKey: Key{
				Name:      "01894394-d046-4783-ba0d-f1c6885790dc",
				Extension: ".event",
				ItemCount: 1,
			},
		},
		{
			str: "100:01894394-d046-4783-ba0d-f1c6885790dc.event.snappy",
			expectedKey: Key{

from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: float = 10.5


items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The Bar fighters", "price": 62, "tax": 20.2},
    "baz": {
        "name": "Baz",