3DES cipher suites were removed from the default list used when
[Config.CipherSuites] is nil. The default can be reverted adding `tls3des=1` to

from datetime import datetime, time, timedelta
from typing import Annotated
from uuid import UUID

from fastapi import Body, FastAPI

app = FastAPI()


@app.put("/items/{item_id}")
async def read_items(
    item_id: UUID,
    start_datetime: Annotated[datetime, Body()],
    end_datetime: Annotated[datetime, Body()],
    process_after: Annotated[timedelta, Body()],
    repeat_at: Annotated[time | None, Body()] = None,
):

from datetime import datetime, time, timedelta
from typing import Union
from uuid import UUID

from fastapi import Body, FastAPI
from typing_extensions import Annotated

app = FastAPI()


@app.put("/items/{item_id}")
async def read_items(
    item_id: UUID,
    start_datetime: Annotated[datetime, Body()],
    end_datetime: Annotated[datetime, Body()],
    process_after: Annotated[timedelta, Body()],

### Importe `List` do typing

Primeiramente, importe `List` do módulo `typing` que já vem por padrão no Python:

```Python hl_lines="1"
{!../../../docs_src/body_nested_models/tutorial002.py!}
```

### Declare a `List` com um parâmetro de tipo

Para declarar tipos que têm parâmetros de tipo(tipos internos), como `list`, `dict`, `tuple`:

* Importe os do modulo `typing`

   
     * If you have above configuration and using _**Windows**_ platform -
       * Try adding the CUDA, CUPTI, and cuDNN installation directories to the %PATH% environment variable.
       * Refer [windows setup guide](https://www.tensorflow.org/install/gpu#windows_setup).
     * If you have above configuration and using _**Ubuntu/Linux**_ platform -
       * Try adding the CUDA, CUPTI, and cuDNN installation directories to the $LD_LIBRARY_PATH environment variable.

}

// All is the table of known settings, sorted by Name.
//
// Note: After adding entries to this table, run 'go generate runtime/metrics'
// to update the runtime/metrics doc comment.
// (Otherwise the runtime/metrics test will fail.)
//
// Note: After adding entries to this table, update the list in doc/godebug.md as well.
// (Otherwise the test in this package will fail.)
var All = []Info{

from datetime import datetime, time, timedelta
from typing import Annotated, Union
from uuid import UUID

from fastapi import Body, FastAPI

app = FastAPI()


@app.put("/items/{item_id}")
async def read_items(
    item_id: UUID,
    start_datetime: Annotated[datetime, Body()],
    end_datetime: Annotated[datetime, Body()],
    process_after: Annotated[timedelta, Body()],
    repeat_at: Annotated[Union[time, None], Body()] = None,
):

from typing import Any, Dict, Optional, Sequence, Type, Union

from pydantic import BaseModel, create_model
from starlette.exceptions import HTTPException as StarletteHTTPException
from starlette.exceptions import WebSocketException as StarletteWebSocketException
from typing_extensions import Annotated, Doc


class HTTPException(StarletteHTTPException):
    """
    An HTTP exception you can raise in your own code to show errors to the client.

     *
     *  1. In general, considering an error type equal to all other types is unintuitive. It essentially turns error types into dynamic `Any`
     *     or `Nothing` types (depending on the typing position). This can produce a lot of typing relationships which do not make any sense,
     *     such as `Int = UnresolvedClass`.
     *  2. It forces the user to handle error types explicitly, which reduces the risk of false positives.

from typing import List

import yaml
from fastapi import FastAPI, HTTPException, Request
from pydantic import BaseModel, ValidationError

app = FastAPI()


class Item(BaseModel):
    name: str
    tags: List[str]


@app.post(
    "/items/",
    openapi_extra={
        "requestBody": {
            "content": {"application/x-yaml": {"schema": Item.model_json_schema()}},
            "required": True,
        },
    },