"-Porg.gradle.java.installations.auto-download=false",
    os.javaInstallationLocations()
) + listOf(
    "-Porg.gradle.performance.branchName" to "%teamcity.build.branch%",
    "-Porg.gradle.performance.db.url" to "%performance.db.url%",
    "-Porg.gradle.performance.db.username" to "%performance.db.username%"
).map { (key, value) -> os.escapeKeyValuePair(key, value) }

const val individualPerformanceTestArtifactRules = """

[ {
  "scenario" : "org.gradle.performance.regression.android.AndroidIncrementalExecutionPerformanceTest.abi change",
  "durations" : [ {
    "testProject" : "nowInAndroidBuild",
    "linux" : 266,
    "windows" : 392,
    "macOs" : 209
  }, {
    "testProject" : "santaTrackerAndroidBuild",
    "linux" : 630,
    "windows" : 988,
    "macOs" : 462
  } ]
}, {

    "testId" : "org.gradle.performance.experiment.declarativedsl.DeclarativeDslFirstUsePerformanceTest.clean checkout",
    "groups" : [ {
      "testProject" : "largeEmptyMultiProjectDeclarativeDsl",
      "coverage" : {
        "per_day" : [ "linux", "macOs", "windows" ]
      }
    } ]
  }, {
    "testId" : "org.gradle.performance.experiment.declarativedsl.DeclarativeDslFirstUsePerformanceTest.cold daemon",
    "groups" : [ {

      "targets": [
        {
          "datasource": {
            "type": "prometheus",
            "uid": "${datasource}"
          },
          "refId": "A"
        }
      ],
      "title": "Performance Dashboard Notes",
      "type": "row"
    },
    {
      "gridPos": {
        "h": 6,
        "w": 24,
        "x": 0,
        "y": 1
      },
      "id": 19,
      "links": [],

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

            "\"-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%",

    val id = "Util_Performance_AdHocPerformanceScenario${os.asName()}${arch.asName()}"
    name = "AdHoc Performance Scenario - ${os.asName()} ${arch.asName()}"
    id(id)

    applyPerformanceTestSettings(os = os, arch = arch, timeout = 420)
    artifactRules = individualPerformanceTestArtifactRules

    params {
        text(
            "performance.baselines",
            "",

    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");

        params {
            text(
                "performance.baselines",
                type.defaultBaselines,
                display = ParameterDisplay.PROMPT,
                allowEmpty = true,
                description = "The baselines you want to run performance tests against. Empty means default baseline."
            )
            param("performance.channel", performanceTestBuildSpec.channel())

Specifically, to see Uvicorn, Starlette and FastAPI compared together (among many other tools).

The simpler the problem solved by the tool, the better performance it will get. And most of the benchmarks don't test the additional features provided by the tool.

The hierarchy is like:

* **Uvicorn**: an ASGI server
    * **Starlette**: (uses Uvicorn) a web microframework