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,
        },
    },

import os
from typing import Any, Dict, List

from pdm.backend.hooks import Context

TIANGOLO_BUILD_PACKAGE = os.getenv("TIANGOLO_BUILD_PACKAGE", "fastapi")


def pdm_build_initialize(context: Context) -> None:
    metadata = context.config.metadata
    # Get custom config for the current package, from the env var
    config: Dict[str, Any] = context.config.data["tool"]["tiangolo"][
        "_internal-slim-build"

import re
import warnings
from dataclasses import is_dataclass
from typing import (
    TYPE_CHECKING,
    Any,
    Dict,
    MutableMapping,
    Optional,
    Set,
    Type,
    Union,
    cast,
)
from weakref import WeakKeyDictionary

import fastapi
from fastapi._compat import (
    PYDANTIC_V2,
    BaseConfig,
    ModelField,
    PydanticSchemaGenerationError,
    Undefined,
    UndefinedType,

    <div class="termy">

    ```console
    $ pip install "uvicorn[standard]"

    ---> 100%
    ```

    </div>

    !!! tip
        By adding the `standard`, Uvicorn will install and use some recommended extra dependencies.

        That including `uvloop`, the high-performance drop-in replacement for `asyncio`, that provides the big concurrency performance boost.

```

!!! note
    Notice that as we communicate with the database using `await`, the *path operation function* is declared with `async`.

### Notice the `response_model=List[Note]`

It uses `typing.List`.

That documents (and validates, serializes, filters) the output data, as a `list` of `Note`s.

## Create notes

Create the *path operation function* to create notes:

```Python hl_lines="61-65"

from datetime import datetime, time, timedelta
from typing import 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: datetime = Body(),
    end_datetime: datetime = Body(),
    process_after: timedelta = Body(),
    repeat_at: Union[time, None] = Body(default=None),
):

    "Topic :: Software Development :: Libraries :: Python Modules",
    "Topic :: Software Development :: Libraries",
    "Topic :: Software Development",
    "Typing :: Typed",
    "Development Status :: 4 - Beta",
    "Environment :: Web Environment",
    "Framework :: AsyncIO",
    "Framework :: FastAPI",
    "Framework :: Pydantic",
    "Framework :: Pydantic :: 1",

## Mounting a **FastAPI** application

"Mounting" means adding a completely "independent" application in a specific path, that then takes care of handling everything under that path, with the _path operations_ declared in that sub-application.

### Top-level application

It will be defined in OpenAPI with `anyOf`.

To do that, use the standard Python type hint <a href="https://docs.python.org/3/library/typing.html#typing.Union" class="external-link" target="_blank">`typing.Union`</a>:

!!! note

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,
):