internal communication only. It is not built for use in untrusted environments
or networks.

For performance reasons, the default TensorFlow server does not include any
authorization protocol and sends messages unencrypted. It accepts connections
from anywhere, and executes the graphs it is sent without performing any checks.
Therefore, if you run a `tf.train.Server` in your network, anybody with access

* Gerçekten etkileyici bir performansa sahip.Python'un ise en hızlı frameworklerinden bir tanesi, <a href="https://github.com/encode/starlette#performance" class="external-link" target="_blank">**NodeJS** ve **Go** ile ise eşdeğer performansa sahip.</a>.
* **WebSocket** desteği.
* **GraphQL** desteği.
* Kullanım halinde arka plan işlevleri.

   * to consider using {@link #forEachPair} instead of this method.
   *
   * <p><b>Performance note:</b> The resulting stream is not <a
   * href="http://gee.cs.oswego.edu/dl/html/StreamParallelGuidance.html">efficiently splittable</a>.
   * This may harm parallel performance.
   */
  @Beta
  public static <A extends @Nullable Object, B extends @Nullable Object, R extends @Nullable Object>

                param("performance.db.username", "tcagent")
                param("env.PERFORMANCE_CHANNEL", performanceTestSpec.channel())
            }

            features {
                publishBuildStatusToGithub(model)
            }

            val performanceResultsDir = "perf-results"
            val performanceProjectName = "performance"

            val taskName =

 * POSITIVE_INFINITY}, {@link Double#NaN NaN} is returned (note that this will only happen if the
 * dataset contains no finite values).
 *
 * <h3>Performance</h3>
 *
 * <p>The average time complexity of the computation is O(N) in the size of the dataset. There is a
 * worst case time complexity of O(N^2). You are extremely unlikely to hit this quadratic case on

Insbesondere dass Uvicorn, Starlette und FastAPI zusammen verglichen werden (neben vielen anderen Tools).

Je einfacher das Problem, das durch das Tool gelöst wird, desto besser wird die Performanz sein. Und die meisten Benchmarks testen nicht die zusätzlichen Funktionen, die das Tool bietet.

Die Hierarchie ist wie folgt:

* **Uvicorn**: ein ASGI-Server
    * **Starlette**: (verwendet Uvicorn) ein Web-Mikroframework

---

FastAPI est un framework web moderne et rapide (haute performance) pour la création d'API avec Python, basé sur les annotations de type standard de Python.

Les principales fonctionnalités sont :

* **Rapidité** : De très hautes performances, au niveau de **NodeJS** et **Go** (grâce à Starlette et Pydantic). [L'un des frameworks Python les plus rapides](#performance).

And that's the same level of performance you get with **FastAPI**.

 * application-specific ordering in addition to performing general cycle detection.
 *
 * <p><strong>Garbage Collection</strong>
 *
 * <p>In order to allow proper garbage collection of unused locks, the edges of the lock graph are
 * weak references.
 *
 * <p><strong>Performance</strong>
 *
 * <p>The extra bookkeeping done by cycle detecting locks comes at some cost to performance.
 * Benchmarks (as of December 2011) show that:

- **Switch Expressions** - Optimized implementations using switch expressions for better performance
- **Sequenced Collections** - Full support for Java 21 sequenced collections API with dedicated utility methods
- **Performance Focused** - Optimized implementations for better runtime performance with reduced memory allocation
- **Type Safe** - Comprehensive use of generics and modern Java type system features