* are broken arbitrarily.
   *
   * <p>For example:
   *
   * <pre>{@code
   * Stream.of("foo", "quux", "banana", "elephant")
   *     .collect(greatest(2, comparingInt(String::length)))
   * // returns {"elephant", "banana"}
   * }</pre>
   *
   * <p>This {@code Collector} uses O(k) memory and takes expected time O(n) (worst-case O(n log

    val stream = connection.newStream(headerEntries("b", "banana"), true)
    val out = stream.getSink().buffer()
    out.writeUtf8("c3po")
    out.close()
    stream.writeHeaders(headerEntries("e", "elephant"), false, false)
    connection.writePingAndAwaitPong()
    assertThat(connection.openStreamCount()).isEqualTo(0)

    // Verify the peer received what was expected.
    val synStream = peer.takeFrame()

## Zusammenfassung

Mit **FastAPI** haben Sie die maximale Flexibilität von Pydantic-Modellen, während Ihr Code einfach, kurz und elegant bleibt.

Aber mit all den Vorzügen:

* Editor-Unterstützung (Codevervollständigung überall)
* Datenkonvertierung (auch bekannt als Parsen, Serialisierung)
* Datenvalidierung
* Schema-Dokumentation

    And the `dict` you receive as `weights` will actually have `int` keys and `float` values.

## Recap

With **FastAPI** you have the maximum flexibility provided by Pydantic models, while keeping your code simple, short and elegant.

But with all the benefits:

* Editor support (completion everywhere!)
* Data conversion (a.k.a. parsing / serialization)
* Data validation
* Schema documentation