*
 * ... or as a single "flattened" collection of key-value pairs:
 *
 * <ul>
 *   <li>a → 1
 *   <li>a → 2
 *   <li>b → 3
 * </ul>
 *
 * <p><b>Important:</b> although the first interpretation resembles how most multimaps are
 * <i>implemented</i>, the design of the {@code Multimap} API is based on the <i>second</i> form.
 * So, using the multimap shown above as an example, the {@link #size} is {@code 3}, not {@code 2},

{* ../../docs_src/path_operation_advanced_configuration/tutorial004_py310.py hl[17:27] *}

## Additional Responses { #additional-responses }

You probably have seen how to declare the `response_model` and `status_code` for a *path operation*.

That defines the metadata about the main response of a *path operation*.

You can also declare additional responses with their models, status codes, etc.

    </dependency>
    <dependency>
      <groupId>org.apache.maven</groupId>
      <artifactId>maven-plugin-api</artifactId>
    </dependency>
    <!-- Remove the following dep to see how to remove Settings from the core -->
    <dependency>
      <groupId>org.apache.maven</groupId>
      <artifactId>maven-settings</artifactId>
    </dependency>
    <dependency>

    query_item: string for feature related to the variable, e.g. "CUDA for
      Nvidia GPUs".
    enabled_by_default: boolean for default behavior.
    question: optional string for how to ask for user input.
    yes_reply: optional string for reply when feature is enabled.
    no_reply: optional string for reply when feature is disabled.

  Returns:
    boolean value of the variable.

  Raises:

      "FINE: Q10000 scheduled after 100 µs: task",
      "FINE: Q10000 starting              : task",
      "FINE: Q10000 finished run in   0 µs: task",
    )
  }

  /** Inspect how many runnables have been enqueued. If none then we're truly sequential. */
  @Test fun singleQueueIsSerial() {
    redQueue.execute("task one", 100.µs) {
      log += "one:run@${taskFaker.nanoTime} parallel=${taskFaker.isParallel}"

// error information in *status.
TF_CAPI_EXPORT extern void TFE_ContextOptionsSetConfig(
    TFE_ContextOptions* options, const void* proto, size_t proto_len,
    TF_Status* status);

// Controls how to act when we try to run an operation on a given device but
// some input tensors are not on that device.
// LINT.IfChange
// Note: Keep in sync with internal copy of enum in eager/context.h.

* Security - HTTPS
* Running on startup
* Restarts
* Replication (the number of processes running)
* Memory
* Previous steps before starting

 * make sense for different situations.
 *
 * <p><b>Note:</b> The dispatcher is orthogonal to the subscriber's {@code Executor}. The dispatcher
 * controls the order in which events are dispatched, while the executor controls how (i.e. on which
 * thread) the subscriber is actually called when an event is dispatched to it.
 *
 * @author Colin Decker
 */
abstract class Dispatcher {

  /**

      runnables = null; // allow GC to free listeners even if this stays around for a while.
    }
    // If we succeeded then list holds all the runnables we to execute. The pairs in the stack are
    // in the opposite order from how they were added so we need to reverse the list to fulfill our
    // contract.
    // This is somewhat annoying, but turns out to be very fast in practice. Alternatively, we could

# Stream Data { #stream-data }

If you want to stream data that can be structured as JSON, you should [Stream JSON Lines](../tutorial/stream-json-lines.md).

But if you want to **stream pure binary data** or strings, here's how you can do it.

/// info

Added in FastAPI 0.134.0.

///

## Use Cases { #use-cases }

You could use this if you want to stream pure strings, for example directly from the output of an **AI LLM** service.