To declare those types and the internal types, you can use the standard Python module `typing`. It exists specifically to support these type hints.

#### Newer versions of Python

The syntax using `typing` is **compatible** with all versions, from Python 3.6 to the latest ones, including Python 3.9, Python 3.10, etc.

### <a href="https://flask.palletsprojects.com" class="external-link" target="_blank">Flask</a>

Flask is a "microframework", it doesn't include database integrations nor many of the things that come by default in Django.

This simplicity and flexibility allow doing things like using NoSQL databases as the main data storage system.

As it is very simple, it's relatively intuitive to learn, although the documentation gets somewhat technical at some points.

Щоб оголосити ці типи та внутрішні типи, ви можете використовувати стандартний модуль Python `typing`. Він існує спеціально для підтримки анотацій типів.

#### Новіші версії Python

Синтаксис із використанням `typing` **сумісний** з усіма версіями, від Python 3.6 до останніх, включаючи Python 3.9, Python 3.10 тощо.

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})

import binascii
from base64 import b64decode
from typing import Optional

from fastapi.exceptions import HTTPException
from fastapi.openapi.models import HTTPBase as HTTPBaseModel
from fastapi.openapi.models import HTTPBearer as HTTPBearerModel
from fastapi.security.base import SecurityBase
from fastapi.security.utils import get_authorization_scheme_param
from pydantic import BaseModel
from starlette.requests import Request

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(title="Query string", min_length=3)] = None,
):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

from typing import Union

from fastapi import Cookie, Depends, FastAPI
from typing_extensions import Annotated

app = FastAPI()


def query_extractor(q: Union[str, None] = None):
    return q


def query_or_cookie_extractor(
    q: Annotated[str, Depends(query_extractor)],
    last_query: Annotated[Union[str, None], Cookie()] = None,
):
    if not q:
        return last_query
    return q


@app.get("/items/")

Um diese Typen und die inneren Typen zu deklarieren, können Sie Pythons Standardmodul `typing` verwenden. Es existiert speziell für die Unterstützung dieser Typhinweise.

#### Neuere Python-Versionen

Die Syntax, welche `typing` verwendet, ist **kompatibel** mit allen Versionen, von Python 3.6 aufwärts zu den neuesten, inklusive Python 3.9, Python 3.10, usw.

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()],

এই টাইপগুলি এবং অভ্যন্তরীণ টাইপগুলি ঘোষণা করতে, আপনি Python মডিউল `typing` ব্যবহার করতে পারেন। এটি বিশেষভাবে এই টাইপ হিন্টগুলি সমর্থন করার জন্য রয়েছে।

#### Python এর নতুন সংস্করণ

`typing` ব্যবহার করা সিনট্যাক্সটি Python 3.6 থেকে সর্বশেষ সংস্করণগুলি পর্যন্ত, অর্থাৎ Python 3.9, Python 3.10 ইত্যাদি সহ সকল সংস্করণের সাথে **সামঞ্জস্যপূর্ণ**।