# Python Tiplerine Giriş { #python-types-intro }

Python, isteğe bağlı "type hints" (diğer adıyla "type annotations") desteğine sahiptir.

Bu **"type hints"** veya annotations, bir değişkenin <dfn title="örneğin: str, int, float, bool">tip</dfn>'ini bildirmeye yarayan özel bir sözdizimidir.

Değişkenleriniz için tip bildirerek, editörler ve araçlar size daha iyi destek sağlayabilir.

Python підтримує додаткові «підказки типів» (також звані «анотаціями типів»).

Ці **«підказки типів»** або анотації — це спеціальний синтаксис, що дозволяє оголошувати <dfn title="наприклад: str, int, float, bool">тип</dfn> змінної.

За допомогою оголошення типів для ваших змінних редактори та інструменти можуть надати вам кращу підтримку.

                title="<la:message key="labels.dashboard_plugin" />"></iframe>
    </main>

    <jsp:include page="/WEB-INF/view/common/admin/footer.jsp"></jsp:include>
</div>
<jsp:include page="/WEB-INF/view/common/admin/foot.jsp"></jsp:include>
</body>

    @Override
    protected String getQueryClassName() {
        return BoostQuery.class.getSimpleName();
    }

    @Override
    public QueryBuilder execute(final QueryContext context, final Query query, final float boost) {
        if (query instanceof final BoostQuery boostQuery) {
            if (logger.isDebugEnabled()) {
                logger.debug("BoostQuery: query={}, boost={}", query, boost);
            }

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float


class ResponseMessage(BaseModel):
    message: str


class User(BaseModel):
    username: str
    email: str


@app.post("/items/", response_model=ResponseMessage, tags=["items"])
async def create_item(item: Item):
    return {"message": "Item received"}

    byte[] data = {0x12, 0x34, 0x56, 0x78, 0x76, 0x54, 0x32, 0x10};
    ByteArrayDataInput in = ByteStreams.newDataInput(data);
    assertThat(in.readFloat()).isEqualTo(Float.intBitsToFloat(0x12345678));
    assertThat(in.readFloat()).isEqualTo(Float.intBitsToFloat(0x76543210));
  }

  public void testNewDataInput_readDouble() {
    byte[] data = {0x12, 0x34, 0x56, 0x78, 0x76, 0x54, 0x32, 0x10};

    @Override
    protected String getQueryClassName() {
        return MatchAllDocsQuery.class.getSimpleName();
    }

    @Override
    public QueryBuilder execute(final QueryContext context, final Query query, final float boost) {
        if (logger.isDebugEnabled()) {
            logger.debug("MatchAllQuery: query={}, boost={}", query, boost);
        }
        return QueryBuilders.matchAllQuery().boost(boost);
    }

from fastapi import FastAPI, Header
from fastapi.sse import EventSourceResponse, ServerSentEvent
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float


items = [
    Item(name="Plumbus", price=32.99),
    Item(name="Portal Gun", price=999.99),
    Item(name="Meeseeks Box", price=49.99),
]


@app.get("/items/stream", response_class=EventSourceResponse)

Python has support for optional "type hints" (also called "type annotations").

These **"type hints"** or annotations are a special syntax that allow declaring the <dfn title="for example: str, int, float, bool">type</dfn> of a variable.

By declaring types for your variables, editors and tools can give you better support.

    @Override
    protected String getQueryClassName() {
        return WildcardQuery.class.getSimpleName();
    }

    @Override
    public QueryBuilder execute(final QueryContext context, final Query query, final float boost) {
        if (query instanceof final WildcardQuery wildcardQuery) {
            if (logger.isDebugEnabled()) {
                logger.debug("WildcardQuery: query={}, boost={}", query, boost);
            }