PER_DAY(
        displayName = "Slow Performance Regression Test",
        timeout = 420,
        channel = "commits",
    ),
    PER_WEEK(
        displayName = "Performance Experiment",
        timeout = 420,
        channel = "experiments",
    ),
    FLAKINESS_DETECTION(
        displayName = "Performance Test Flakiness Detection",
        timeout = 600,
        defaultBaselines = "flakiness-detection-commit",

     * determined experimentally to match our desired probability of false positives.
     */
    // NB: yes, this is surprisingly high, but that's what the experiments said was necessary
    // Raising this number slows the worst-case contains behavior, speeds up hashFloodingDetected,
    // and reduces the false-positive probability.
    static final int MAX_RUN_MULTIPLIER = 13;

			return i
		}
		i++
		fails++
		if fails >= 4+i>>4 && i < t {
			// Give up on IndexByte, it isn't skipping ahead
			// far enough to be better than Rabin-Karp.
			// Experiments (using IndexPeriodic) suggest
			// the cutover is about 16 byte skips.
			// TODO: if large prefixes of sep are matching
			// we should cutover at even larger average skips,

## Quick Start

{
  "performanceTests" : [ {
    "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",

[ {
  "scenario" : "org.gradle.performance.experiment.declarativedsl.DeclarativeDslFirstUsePerformanceTest.clean checkout",
  "durations" : [ {
    "testProject" : "largeEmptyMultiProjectDeclarativeDsl",
    "linux" : 468
  } ]
}, {
  "scenario" : "org.gradle.performance.experiment.declarativedsl.DeclarativeDslFirstUsePerformanceTest.cold daemon",
  "durations" : [ {
    "testProject" : "largeEmptyMultiProjectDeclarativeDsl",
    "linux" : 467
  } ]

```

</div>

Esse comando gerará o código em `./src/client` e usará o `axios` (a biblioteca HTTP frontend) internamente.

### Experimente o Código do Cliente

Agora você pode importar e usar o código do cliente, ele poderia ser assim, observe que você obtém preenchimento automático para os métodos:

<img src="/img/tutorial/generate-clients/image02.png">

## Testing locally with Traefik { #testing-locally-with-traefik }

You can easily run the experiment locally with a stripped path prefix using <a href="https://docs.traefik.io/" class="external-link" target="_blank">Traefik</a>.

* Fornecer diretamente 2 interfaces _web_ de documentação interativa.

---

Nós apenas arranhamos a superfície, mas você já tem idéia de como tudo funciona.

Experimente mudar a seguinte linha:

```Python
    return {"item_name": item.name, "item_id": item_id}
```

...de:

```Python
        ... "item_name": item.name ...
```

...para:

*   Add `execute_fn_for_device function` to dynamically choose the
    implementation based on underlying device placement.
*   Eager:
    *   Add `reduce_logsumexp` benchmark with experiment compile.
    *   Give `EagerTensor`s a meaningful `__array__` implementation.
    *   Add another version of defun matmul for performance analysis.
*   `tf.function`/AutoGraph: