* Both _paths_ take `GET` operations (also known as HTTP _methods_).
* The _path_ `/items/{item_id}` has a _path parameter_ `item_id` that should be an `int`.
* The _path_ `/items/{item_id}` has an optional `str` _query parameter_ `q`.

### Interactive API docs { #interactive-api-docs }

Now go to [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs).

from fastapi import FastAPI, Path, Query

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(
    item_id: int = Path(title="The ID of the item to get"),
    q: str | None = Query(default=None, alias="item-query"),
):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})

import org.opensearch.index.query.RangeQueryBuilder;
import org.opensearch.index.query.RegexpQueryBuilder;
import org.opensearch.index.query.SpanTermQueryBuilder;
import org.opensearch.index.query.TermQueryBuilder;
import org.opensearch.index.query.TermsQueryBuilder;
import org.opensearch.index.query.WildcardQueryBuilder;
import org.opensearch.index.query.functionscore.FunctionScoreQueryBuilder;

## 요약 { #recap }

`Query`, `Path`(아직 보지 못한 다른 것들도)를 사용하면 [쿼리 매개변수와 문자열 검증](query-params-str-validations.md)에서와 마찬가지로 메타데이터와 문자열 검증을 선언할 수 있습니다.

그리고 숫자 검증 또한 선언할 수 있습니다:

* `gt`: `g`reater `t`han
* `ge`: `g`reater than or `e`qual
* `lt`: `l`ess `t`han
* `le`: `l`ess than or `e`qual

/// info | 정보

`Query`, `Path`, 그리고 나중에 보게 될 다른 클래스들은 공통 `Param` 클래스의 서브클래스입니다.

## 总结 { #recap }

你能够以与[查询参数和字符串校验](query-params-str-validations.md)相同的方式使用 `Query`、`Path`（以及其他你还没见过的类）声明元数据和字符串校验。

而且你还可以声明数值校验：

* `gt`：大于（`g`reater `t`han）
* `ge`：大于等于（`g`reater than or `e`qual）
* `lt`：小于（`l`ess `t`han）
* `le`：小于等于（`l`ess than or `e`qual）

/// info | 信息

`Query`、`Path` 以及你后面会看到的其他类，都是一个通用 `Param` 类的子类。

它们都共享相同的参数，用于你已看到的额外校验和元数据。

///

from dirty_equals import IsPartialDict
from fastapi import Cookie, FastAPI, Header, Query
from fastapi.testclient import TestClient
from pydantic import BaseModel, Field

app = FastAPI()


class Model(BaseModel):
    param: str = Field(alias="param_alias")


@app.get("/query")
async def query_model(data: Model = Query()):
    return {"param": data.param}


@app.get("/header")
async def header_model(data: Model = Header()):

from fastapi import Body, FastAPI, Query
from fastapi.testclient import TestClient

app = FastAPI()


@app.get("/query")
def read_query(q: str | None):
    return q


@app.get("/explicit-query")
def read_explicit_query(q: str | None = Query()):
    return q


@app.post("/body-embed")
def send_body_embed(b: str | None = Body(embed=True)):
    return b


client = TestClient(app)

        }

        return resultBuf.toString();
    }

    /**
     * Sets the query builder for filtering documents.
     *
     * @param queryBuilder the query builder to filter documents
     * @return this UpdateLabelJob instance for method chaining
     */
    public UpdateLabelJob query(final QueryBuilder queryBuilder) {
        this.queryBuilder = queryBuilder;
        return this;
    }

    /**
     * Performs a search operation using the specified query and parameters.
     *
     * @param query the search query string
     * @param params the search request parameters
     * @param userBean the optional user bean for access control
     * @return the search result containing documents and metadata
     */
    @Override

func parsePreSignV4(query url.Values, region string, stype serviceType) (psv preSignValues, aec APIErrorCode) {
	// verify whether the required query params exist.
	aec = doesV4PresignParamsExist(query)
	if aec != ErrNone {
		return psv, aec
	}

	// Verify if the query algorithm is supported or not.
	if query.Get(xhttp.AmzAlgorithm) != signV4Algorithm {