"-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 = """

    "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" : [ {

            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%",

        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

      env:
        # Exclude some projects and configurations that should not contribute to the dependency graph
        DEPENDENCY_GRAPH_EXCLUDE_PROJECTS: ':docs|:internal-performance-testing|:enterprise-plugin-performance|:performance|:internal-integ-testing'

  kubectl create configmap -n istio-system istio-grafana-dashboards \
    --dry-run=client -oyaml \
    --from-file=pilot-dashboard.json="${TMP}/pilot-dashboard.json" \
    --from-file=istio-performance-dashboard.json="${TMP}/istio-performance-dashboard.json"

  echo -e "\n---\n"
  kubectl create configmap -n istio-system istio-services-grafana-dashboards \
    --dry-run=client -oyaml \

      maintainer="MinIO Inc <******@****.***>" \
      version="${RELEASE}" \
      release="${RELEASE}" \
      summary="MinIO is a High Performance Object Storage, API compatible with Amazon S3 cloud storage service." \

!!! check "Inspired **FastAPI** to"
    Find a way to have a crazy performance.

    That's why **FastAPI** is based on Starlette, as it is the fastest framework available (tested by third-party benchmarks).

### <a href="https://falconframework.org/" class="external-link" target="_blank">Falcon</a>