from typing import Annotated, Union

import pytest
from dirty_equals import IsOneOf, IsPartialDict
from fastapi import Body, FastAPI
from fastapi.testclient import TestClient
from pydantic import BaseModel, Field

from .utils import get_body_model_name

app = FastAPI()

# =====================================================================================
# Without aliases

from typing import Annotated, Optional

import pytest
from fastapi import Body, FastAPI
from fastapi.testclient import TestClient
from pydantic import BaseModel, Field

from .utils import get_body_model_name

app = FastAPI()

# =====================================================================================
# Without aliases


@app.post("/optional-str", operation_id="optional_str")

```

</div>

**Note**: Make sure you put `"fastapi[standard]"` in quotes to ensure it works in all terminals.

## Example

### Create it

Create a file `main.py` with:

```Python
from typing import Union

from fastapi import FastAPI

app = FastAPI()


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")

To achieve that, first import:

* `Query` from `fastapi`
* `Annotated` from `typing`

{* ../../docs_src/query_params_str_validations/tutorial002_an_py310.py hl[1,3] *}

/// info

FastAPI added support for `Annotated` (and started recommending it) in version 0.95.0.

If you have an older version, you would get errors when trying to use `Annotated`.

import warnings
from collections.abc import Sequence
from dataclasses import dataclass
from enum import Enum
from typing import Annotated, Any, Callable, Optional, Union

from fastapi.exceptions import FastAPIDeprecationWarning
from fastapi.openapi.models import Example
from pydantic import AliasChoices, AliasPath
from pydantic.fields import FieldInfo
from typing_extensions import Literal, deprecated

from ._compat import (
    Undefined,
)

* Valida **estruturas complexas**:
    * Use modelos hierárquicos do Pydantic, `List` e `Dict` do `typing` do Python, etc.
    * Validadores permitem que esquemas de dados complexos sejam limpos e facilmente definidos, conferidos e documentados como JSON Schema.

### Імпорт `Query` та `Annotated`

Щоб це зробити, спочатку імпортуємо:

* `Query` з `fastapi`
* `Annotated` з `typing`

{* ../../docs_src/query_params_str_validations/tutorial002_an_py310.py hl[1,3] *}

/// info | Інформація

FastAPI додав підтримку `Annotated` (і почав рекомендувати його) у версії 0.95.0.

Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_112)
Type in expressions to have them evaluated.
Type :help for more information.

scala>
```

- At the _scala>_ prompt, submit the job by typing the following commands, Replace node names, file name, and file location with your values:

```
scala> val file = sc.textFile("s3a://testbucket/testdata")

### 型パラメータを持つジェネリック型

データ構造の中には、`dict`、`list`、`set`、そして`tuple`のように他の値を含むことができるものがあります。また内部の値も独自の型を持つことができます。

これらの型や内部の型を宣言するには、Pythonの標準モジュール`typing`を使用します。

これらの型ヒントをサポートするために特別に存在しています。

#### `List`

例えば、`str`の`list`の変数を定義してみましょう。

`typing`から`List`をインポートします（大文字の`L`を含む）:

{* ../../docs_src/python_types/tutorial006.py hl[1] *}


同じようにコロン（`:`）の構文で変数を宣言します。

型として、`List`を入力します。

import os
import re
import shutil
import subprocess
from html.parser import HTMLParser
from http.server import HTTPServer, SimpleHTTPRequestHandler
from multiprocessing import Pool
from pathlib import Path
from typing import Any, Optional, Union

import mkdocs.utils
import typer
import yaml
from jinja2 import Template
from ruff.__main__ import find_ruff_bin
from slugify import slugify as py_slugify