你也可以同時宣告**本文**、**路徑**與**查詢**參數。

**FastAPI** 會分別辨識並從正確的位置取得資料。

{* ../../docs_src/body/tutorial004_py310.py hl[16] *}

函式參數的辨識方式如下：

- 如果參數同時在**路徑**中宣告，則作為路徑參數。
- 如果參數是**單一型別**（像是 `int`、`float`、`str`、`bool` 等），會被視為**查詢**參數。
- 如果參數宣告為 **Pydantic 模型** 型別，會被視為請求**本文**。

/// note

FastAPI 會因為預設值 `= None` 而知道 `q` 的值不是必填。

`str | None` 並非 FastAPI 用來判斷是否必填的依據；它會因為有預設值 `= None` 而知道不是必填。

 *  New: `ConnectionPool.setPolicy()` configures a minimum connection pool size for a target
    address. Use this to proactively open HTTP connections.

    Connections opened to fulfill this policy are subject to the connection pool's
    `keepAliveDuration` but do not count against the pool-wide `maxIdleConnections` limit.

        final List<InstanceInfo> instances = new ArrayList<>();
        final long now = System.currentTimeMillis();
        final String query = toJson(Map.of( //
                "query", Map.of("bool", Map.of("must", List.of( //
                        Map.of("term", Map.of("type", TYPE_HEARTBEAT)), //
                        Map.of("range", Map.of("expiredTime", Map.of("gte", now)))))), //
                "size", 100));

Puedes usar las mismas declaraciones de tipo con `str`, `float`, `bool` y muchos otros tipos de datos complejos.

Varios de estos se exploran en los siguientes capítulos del tutorial.

## El orden importa { #order-matters }

All the data validation is performed under the hood by [Pydantic](https://docs.pydantic.dev/), so you get all the benefits from it. And you know you are in good hands.

You can use the same type declarations with `str`, `float`, `bool` and many other complex data types.

Several of these are explored in the next chapters of the tutorial.

## Order matters { #order-matters }

}

TF_Function* TF_FunctionImportFunctionDef(const void* proto, size_t proto_len,
                                          TF_Status* status) {
  tensorflow::FunctionDef fdef;
  bool success = fdef.ParseFromArray(proto, proto_len);
  if (!success) {
    status->status = InvalidArgument(
        "Invalid FunctionDef given to TF_FunctionImportFunctionDef");
    return nullptr;
  }

pkg go/build/constraint, method (*NotExpr) String() string
pkg go/build/constraint, method (*OrExpr) Eval(func(string) bool) bool
pkg go/build/constraint, method (*OrExpr) String() string
pkg go/build/constraint, method (*SyntaxError) Error() string
pkg go/build/constraint, method (*TagExpr) Eval(func(string) bool) bool
pkg go/build/constraint, method (*TagExpr) String() string
pkg go/build/constraint, type AndExpr struct

 *   <li>Potential memory savings through string deduplication</li>
 *   <li>Most frequent string values and their occurrence counts</li>
 *   <li>Statistics grouped by POM element types</li>
 * </ul>
 *
 * <p>This tool is particularly useful for identifying memory optimization opportunities
 * in large Maven multi-module projects where POM files may contain significant
 * duplicate content.</p>
 */
public class PomMemoryAnalyzer {

Ви можете використовувати ті самі оголошення типів з `str`, `float`, `bool` та багатьма іншими складними типами даних.

Декілька з них розглядаються в наступних розділах посібника.

## Порядок має значення { #order-matters }

                "url": author.url,
            }
            users[user] = user_data
            users_list.append(user_data)
    return users_list


def update_content(*, content_path: Path, new_content: Any) -> bool:
    old_content = content_path.read_text(encoding="utf-8")

    new_content = yaml.dump(new_content, sort_keys=False, width=200, allow_unicode=True)
    if old_content == new_content: