from typing import Union

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(
    q: Union[str, None] = Query(default=None, min_length=3, max_length=50),
):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

from typing import Annotated

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(
    q: Annotated[str | None, Query(min_length=3, max_length=50)] = None,
):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

from typing import Union

from fastapi import FastAPI, Query
from typing_extensions import Annotated

app = FastAPI()


@app.get("/items/")
async def read_items(
    q: Annotated[Union[str, None], Query(min_length=3, max_length=50)] = None,
):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

from typing import Annotated, Union

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(
    q: Annotated[Union[str, None], Query(min_length=3, max_length=50)] = None,
):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

```

...使得参数可选，等同于：

```Python
q: str = None
```

但是 `Query` 显式地将其声明为查询参数。

然后，我们可以将更多的参数传递给 `Query`。在本例中，适用于字符串的 `max_length` 参数：

```Python
q: Union[str, None] = Query(default=None, max_length=50)
```

将会校验数据，在数据无效时展示清晰的错误信息，并在 OpenAPI 模式的*路径操作*中记录该参​​数。

## 添加更多校验

你还可以添加 `min_length` 参数：

```Python hl_lines="10"

    return item_id


@app.get("/path/param-maxlength/{item_id}")
def get_path_param_max_length(item_id: str = Path(max_length=3)):
    return item_id


@app.get("/path/param-min_maxlength/{item_id}")
def get_path_param_min_max_length(item_id: str = Path(max_length=3, min_length=2)):
    return item_id


@app.get("/path/param-gt/{item_id}")

    default_pydantic_max_size = 2**16
    path = tmp_path / "test.txt"
    path.write_bytes(b"x" * (default_pydantic_max_size + 1))

    client = TestClient(app)
    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": default_pydantic_max_size + 1}

    default_pydantic_max_size = 2**16
    path = tmp_path / "test.txt"
    path.write_bytes(b"x" * (default_pydantic_max_size + 1))

    client = TestClient(app)
    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": default_pydantic_max_size + 1}

 * @version 0.0.1
 * @license MIT
 */

:root {
    --color-bg: #252a33;
    --color-text: #eee;
    --color-text-subtle: #a2a2a2;
}

[data-termynal] {
    width: 750px;
    max-width: 100%;
    background: var(--color-bg);
    color: var(--color-text);
    /* font-size: 18px; */
    font-size: 15px;
    /* font-family: 'Fira Mono', Consolas, Menlo, Monaco, 'Courier New', Courier, monospace; */

* Validation for most (or all?) Python **data types**, including:
    * JSON objects (`dict`).
    * JSON array (`list`) defining item types.
    * String (`str`) fields, defining min and max lengths.
    * Numbers (`int`, `float`) with min and max values, etc.

* Validation for more exotic types, like:
    * URL.
    * Email.
    * UUID.
    * ...and others.