* 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.

            gradleRunnerStep(
                model,
                ":$performanceProjectName:$taskName",
                extraParameters = listOf(
                    "-Porg.gradle.performance.branchName" to "%teamcity.build.branch%",
                    "-Porg.gradle.performance.db.url" to "%performance.db.url%",

Ele claramente inspirou Uvicorn e Starlette, que são atualmente mais rápidos que o Sanic em testes de performance abertos.

///

/// check | "**FastAPI** inspirado para"

Achar um jeito de ter uma performance insana.

É por isso que o **FastAPI** é baseado em Starlette, para que ele seja o framework mais rápido disponível (performance testada por terceiros).

///

 * 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

   * other. But Atomic objects residing in arrays will tend to be
   * placed adjacent to each other, and so will most often share
   * cache lines (with a huge negative performance impact) without
   * this precaution.
   *
   * In part because Cells are relatively large, we avoid creating
   * them until they are needed.  When there is no contention, all

Avec **FastAPI** vous aurez toutes les fonctionnalités de **Starlette** (FastAPI est juste Starlette sous stéroïdes):

* Des performances vraiment impressionnantes. C'est l'<a href="https://github.com/encode/starlette#performance" class="external-link" target="_blank">un des framework Python les plus rapide, à égalité avec **NodeJS** et **GO**</a>.
* Le support des **WebSockets**.
* Le support de **GraphQL**.

 * 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:

    HISTORICAL_PERFORMANCE("Historical Performance", "Once a week: Run performance tests for multiple Gradle versions", "HistoricalPerformance"),
    EXPERIMENTAL_VFS_RETENTION("Experimental FS Watching", "On demand checks to run tests with file system watching enabled", "ExperimentalVfsRetention"),
    EXPERIMENTAL_PERFORMANCE("Experimental Performance", "Try out new performance test running", "ExperimentalPerformance");

    val id: String

            "\"-Porg.gradle.performance.branchName=%teamcity.build.branch%\"",
            "\"-Porg.gradle.performance.db.url=%performance.db.url%\"",
            "\"-Porg.gradle.performance.db.username=%performance.db.username%\"",
            "-DenableTestDistribution=%enableTestDistribution%",
            "-Dorg.gradle.workers.max=%maxParallelForks%",

            description = "Which performance test to run. Should be the fully qualified class name dot (unrolled) method name. E.g. org.gradle.performance.regression.java.JavaUpToDatePerformanceTest.up-to-date assemble (parallel true)"
        )
        text("testJavaVersion", "17", display = ParameterDisplay.PROMPT, allowEmpty = false, description = "The java version to run the performance tests, e.g. 8/11/17")
        select(