return Math.sqrt(populationVariance());
  }

  /**
   * Returns the <a href="http://en.wikipedia.org/wiki/Variance#Sample_variance">unbiased sample
   * variance</a> of the values. If this dataset is a sample drawn from a population, this is an
   * unbiased estimator of the population variance of the population. The count must be greater than
   * one.
   *

    ticker.advance(1, MILLISECONDS);
    assertThat(cache.getUnchecked(key)).isSameInstanceAs(one);
    stats = cache.stats();
    assertThat(stats.missCount()).isEqualTo(1);
    assertThat(stats.loadSuccessCount()).isEqualTo(1);
    assertThat(stats.loadExceptionCount()).isEqualTo(0);
    assertThat(stats.hitCount()).isEqualTo(1);

    ticker.advance(1, MILLISECONDS);

		</postConstruct>
		<postConstruct name="addDesignJspFileName">
			<arg>"searchOptions"</arg>
			<arg>"searchOptions.jsp"</arg>
		</postConstruct>
		<postConstruct name="addDesignJspFileName">
			<arg>"advance"</arg>
			<arg>"advance.jsp"</arg>
		</postConstruct>
		<postConstruct name="addDesignJspFileName">
			<arg>"help"</arg>
			<arg>"help.jsp"</arg>
		</postConstruct>
		<postConstruct name="addDesignJspFileName">

    ticker.advance(1, MILLISECONDS);
    assertThat(cache.getUnchecked(key)).isSameInstanceAs(one);
    stats = cache.stats();
    assertThat(stats.missCount()).isEqualTo(1);
    assertThat(stats.loadSuccessCount()).isEqualTo(1);
    assertThat(stats.loadExceptionCount()).isEqualTo(0);
    assertThat(stats.hitCount()).isEqualTo(1);

    ticker.advance(1, MILLISECONDS);

					<i class="fa fa-search" aria-hidden="true"></i>
					<la:message key="labels.search" />
				</button>
				<la:link href="/search/advance?q=${f:u(q)}${fe:pagingQuery(null)}" styleClass="btn btn-outline-secondary">
					<i class="fa fa-cog" aria-hidden="true"></i>
					<la:message key="labels.advance" />
				</la:link>
			</div>
		</div>
	</div>
	</c:if>

					<i class="fa fa-search" aria-hidden="true"></i>
					<la:message key="labels.search" />
				</button>
				<la:link href="/search/advance?q=${f:u(q)}${fe:pagingQuery(null)}" styleClass="btn btn-outline-secondary">
					<i class="fa fa-cog" aria-hidden="true"></i>
					<la:message key="labels.advance" />
				</la:link>
			</div>
		</div>
	</div>
	</c:if>

### Do

* Ensure that the system executing your microbenchmarks has as little load as possible. Shutdown every process that can cause unnecessary
  runtime jitter. Watch the `Error` column in the benchmark results to see the run-to-run variance.
* Ensure to run enough warmup iterations to get the benchmark into a stable state. If you are unsure, don't change the defaults.
* Avoid CPU migrations by pinning your benchmarks to specific CPU cores. On Linux you can use `taskset`.

Siga os tutoriais do seu provedor de nuvem para implantar aplicações FastAPI com esse provedor. 🤓

## Implantar no seu próprio servidor { #deploy-your-own-server }

import okio.buffer

internal class GzipRequestBody(
  val delegate: RequestBody,
) : RequestBody() {
  override fun contentType() = delegate.contentType()

  // We don't know the compressed length in advance!
  override fun contentLength() = -1L

  override fun writeTo(sink: BufferedSink) {
    GzipSink(sink).buffer().use(delegate::writeTo)
  }

  override fun isOneShot() = delegate.isOneShot()

      if (values.hasAnyNonFinite()) {
        assertWithMessage("population variance of %s", values).that(populationVariance).isNaN();
        assertWithMessage("population variance by addAll(Stats) of %s", values)
            .that(populationVarianceByAddAllStats)
            .isNaN();
      } else {
        assertWithMessage("population variance of %s", values)
            .that(populationVariance)