*
   * <p><b>{@code Stream} equivalent:</b> {@code stream.filter(predicate).findFirst()}.
   */
  public final Optional<@NonNull E> firstMatch(Predicate<? super E> predicate) {
    // Unsafe, but we can't do much about it now.
    return Iterables.<@NonNull E>tryFind((Iterable<@NonNull E>) getDelegate(), predicate);
  }

  /**
   * Returns a fluent iterable that applies {@code function} to each element of this fluent

   *
   * <p><b>{@code Stream} equivalent:</b> {@code stream.filter(predicate).findFirst()}.
   */
  public final Optional<@NonNull E> firstMatch(Predicate<? super E> predicate) {
    // Unsafe, but we can't do much about it now.
    return Iterables.<@NonNull E>tryFind((Iterable<@NonNull E>) getDelegate(), predicate);
  }

  /**
   * Returns a fluent iterable that applies {@code function} to each element of this fluent

### Summary { #summary }

I used to say I didn't like history that much... and look at me now giving "tech history" lessons. 😅

/// info

Keep in mind that dataclasses can't do everything Pydantic models can do.

So, you might still need to use Pydantic models.

But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

///

## Dataclasses in `response_model` { #dataclasses-in-response-model }

Many packages that simplify it a lot have to make many compromises with the data model, database, and available features. And some of these packages that simplify things too much actually have security flaws underneath.

---

**FastAPI** doesn't make any compromise with any database, data model or tool.

It gives you all the flexibility to choose the ones that fit your project the best.

This would be even more important with large or infinite streams.

///

/// tip

Instead of returning a `StreamingResponse` directly, you should probably follow the style in [Stream Data](./stream-data.md), it's much more convenient and handles cancellation behind the scenes for you.

If you are streaming JSON Lines, follow the [Stream JSON Lines](../tutorial/stream-json-lines.md) tutorial.

///

```

</div>

as Uvicorn by default will use the port `8000`, the documentation on port `8008` won't clash.

### Translations

Help with translations is VERY MUCH appreciated! And it can't be done without the help from the community. 🌎 🚀

        * **FastAPI**: (uses Starlette) an API microframework with several additional features for building APIs, with data validation, etc.

* **Uvicorn**:
    * Will have the best performance, as it doesn't have much extra code apart from the server itself.

Your server(s) is (are) a **resource**, you can consume or **utilize**, with your programs, the computation time on the CPUs, and the RAM memory available.

How much of the system resources do you want to be consuming/utilizing? It might be easy to think "not much", but in reality, you will probably want to consume **as much as possible without crashing**.

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

/// tip

As Pydantic will serialize it in the **Rust** side, you will get much higher **performance** than if you don't declare a return type.

///

### Non-async *path operation functions* { #non-async-path-operation-functions }