# Header

{* ../../docs_src/dependencies/tutorial013_an_py310.py ln[19:21] *}

Some text

{* ../../docs_src/bigger_applications/app_an_py310/internal/admin.py hl[3] title["app/internal/admin.py"] *}

Some more text

{* ../../docs_src/dependencies/tutorial013_an_py310.py ln[30:38] hl[31:33] *}

And even more text

	handleListener := func(idx int, ln net.Listener) {
		for {
			conn, err := ln.Accept()
			select {
			case listener.acceptCh <- acceptResult{conn, err, idx}:
			case <-listener.ctxDoneCh:
				return
			}
		}
	}

	// Start separate goroutine for each listener to handle connection.
	for idx, ln := range listener.listeners {
		go handleListener(idx, ln)
	}
}

{* ../../docs_src/dependencies/tutorial013_an_py310.py ln[19:21] *}

{* ../../docs_src/dependencies/tutorial013_an_py310.py ln[30:38] *}


## Code includes with line ranges and highlighting { #code-includes-with-line-ranges-and-highlighting }

{* ../../docs_src/dependencies/tutorial013_an_py310.py ln[30:38] hl[31:33] *}

{* ../../docs_src/dependencies/tutorial015_an_py310.py ln[10:15] hl[12:14] *}

FastAPI에서 JSON Lines를 스트리밍하려면, *경로 처리 함수*에서 `return`을 사용하는 대신 `yield`로 각 항목을 차례로 생성하면 됩니다.

{* ../../docs_src/stream_json_lines/tutorial001_py310.py ln[1:24] hl[24] *}

보내려는 각 JSON 항목의 타입이 `Item`(Pydantic 모델)이고 함수가 async라면, 반환 타입을 `AsyncIterable[Item]`로 선언할 수 있습니다:

{* ../../docs_src/stream_json_lines/tutorial001_py310.py ln[1:24] hl[9:11,22] *}

반환 타입을 선언하면 FastAPI가 이를 사용해 데이터를 **검증**하고, OpenAPI에 **문서화**하고, **필터링**하고, Pydantic으로 **직렬화**합니다.

/// tip

{* ../../docs_src/json_base64_bytes/tutorial001_py310.py ln[1:9,29:35] hl[9] *}

If you check the `/docs`, they will show that the field `data` expects base64 encoded bytes:

<div class="screenshot">
<img src="/img/tutorial/json-base64-bytes/image01.png">
</div>

`EventSourceResponse`는 `fastapi.sse`에서 임포트합니다:

{* ../../docs_src/server_sent_events/tutorial001_py310.py ln[1:25] hl[4,22] *}

각 `yield`된 항목은 JSON으로 인코딩되어 SSE 이벤트의 `data:` 필드로 전송됩니다.

반환 타입을 `AsyncIterable[Item]`으로 선언하면 FastAPI가 이를 사용해 데이터를 Pydantic으로 **검증**, **문서화**, **직렬화**합니다.

{* ../../docs_src/server_sent_events/tutorial001_py310.py ln[1:25] hl[10:12,23] *}

/// tip | 팁

{* ../../docs_src/server_sent_events/tutorial001_py310.py ln[1:25] hl[4,22] *}

Each yielded item is encoded as JSON and sent in the `data:` field of an SSE event.

If you declare the return type as `AsyncIterable[Item]`, FastAPI will use it to **validate**, **document**, and **serialize** the data using Pydantic.

{* ../../docs_src/server_sent_events/tutorial001_py310.py ln[1:25] hl[10:12,23] *}

/// tip

{* ../../docs_src/stream_json_lines/tutorial001_py310.py ln[1:24] hl[24] *}

If each JSON item you want to send back is of type `Item` (a Pydantic model) and it's an async function, you can declare the return type as `AsyncIterable[Item]`:

{* ../../docs_src/stream_json_lines/tutorial001_py310.py ln[1:24] hl[9:11,22] *}

{* ../../docs_src/json_base64_bytes/tutorial001_py310.py ln[1:2,12:16,29,38:41] hl[16] *}

## 用于输入和输出数据的 Pydantic `bytes` { #pydantic-bytes-for-input-and-output-data }

当然，你也可以使用同一个配置了 base64 的模型，在接收和发送 JSON 数据时，同时处理输入（使用 `val_json_bytes` 进行验证）和输出（使用 `ser_json_bytes` 进行序列化）。

要在 FastAPI 中流式传输 JSON Lines，可以在路径操作函数中不用 `return`，而是用 `yield` 逐个产生每个数据项。

{* ../../docs_src/stream_json_lines/tutorial001_py310.py ln[1:24] hl[24] *}

如果你要返回的每个 JSON 项是类型 `Item`（一个 Pydantic 模型），并且这是一个异步函数，你可以将返回类型声明为 `AsyncIterable[Item]`：

{* ../../docs_src/stream_json_lines/tutorial001_py310.py ln[1:24] hl[9:11,22] *}

如果你声明了返回类型，FastAPI 会用它来验证数据、在 OpenAPI 中生成文档、进行过滤，并使用 Pydantic 进行序列化。

/// tip | 提示