**Typer** a FastAPI kistestvére. A **CLI-k FastAPI-ja**. ⌨️ 🚀

## Követelmények

A FastAPI óriások vállán áll:

* <a href="https://www.starlette.io/" class="external-link" target="_blank">Starlette</a> a webes részekhez.
* <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> az adat részekhez.

	"github.com/pkg/sftp"
	"golang.org/x/crypto/ssh"
)

const (
	kexAlgoDH1SHA1                = "diffie-hellman-group1-sha1"
	kexAlgoDH14SHA1               = "diffie-hellman-group14-sha1"
	kexAlgoDH14SHA256             = "diffie-hellman-group14-sha256"
	kexAlgoDH16SHA512             = "diffie-hellman-group16-sha512"
	kexAlgoECDH256                = "ecdh-sha2-nistp256"
	kexAlgoECDH384                = "ecdh-sha2-nistp384"

/**
 * Provides a fluent API for calculating <a
 * href="http://en.wikipedia.org/wiki/Quantile">quantiles</a>.
 *
 * <h3>Examples</h3>
 *
 * <p>To compute the median:
 *
 * <pre>{@code
 * double myMedian = median().compute(myDataset);
 * }</pre>
 *
 * where {@link #median()} has been statically imported.
 *
 * <p>To compute the 99th percentile:
 *
 * <pre>{@code

* Successivamente, premi sul pulsante "Execute". L'interfaccia utente comunicherà con la tua API, invierà i parametri, riceverà i risultati della richiesta, e li mostrerà sullo schermo:

![Swagger UI interaction](https://fastapi.tiangolo.com/img/index/index-05-swagger-04.png)

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  public void testMedian_compute_doubleCollection() {
    assertThat(median().compute(SIXTEEN_SQUARES_DOUBLES))
        .isWithin(ALLOWED_ERROR)
        .of(SIXTEEN_SQUARES_MEDIAN);
  }

  public void testMedian_computeInPlace() {
    double[] dataset = Doubles.toArray(SIXTEEN_SQUARES_DOUBLES);
    assertThat(median().computeInPlace(dataset)).isWithin(ALLOWED_ERROR).of(SIXTEEN_SQUARES_MEDIAN);

        mean += (value - mean) / (index + 1);
      } else {
        mean = calculateNewMeanNonFinite(mean, value);
      }
    }
    return mean;
  }

  /**
   * Returns the <a href="http://en.wikipedia.org/wiki/Arithmetic_mean">arithmetic mean</a> of the
   * values. The count must be non-zero.
   *
   * <p>The definition of the mean is the same as {@link Stats#mean}.
   *

      }
    } else {
      count++;
      if (isFinite(value) && isFinite(mean)) {
        // Art of Computer Programming vol. 2, Knuth, 4.2.2, (15) and (16)
        double delta = value - mean;
        mean += delta / count;
        sumOfSquaresOfDeltas += delta * (value - mean);
      } else {
        mean = calculateNewMeanNonFinite(mean, value);
        sumOfSquaresOfDeltas = NaN;
      }
      min = Math.min(min, value);

        accumulatorByAddAllStats.addAll(Stats.of(value));
      }
      double mean = accumulator.mean();
      double meanByAddAllStats = accumulatorByAddAllStats.mean();
      if (values.hasAnyNaN()) {
        assertWithMessage("mean of " + values).that(mean).isNaN();
        assertWithMessage("mean by addAll(Stats) of " + values).that(meanByAddAllStats).isNaN();

  }

  @GwtIncompatible // DoubleMath.mean
  @SuppressWarnings("deprecation") // test of deprecated method
  public void testMean_intVarargs() {
    assertThat(DoubleMath.mean(11, -22, 44, -88)).isWithin(1.0e-10).of(-13.75);
    assertThat(DoubleMath.mean(11)).isWithin(1.0e-10).of(11.0);
  }

  @GwtIncompatible // DoubleMath.mean
  @SuppressWarnings("deprecation") // test of deprecated method

  }

  @GwtIncompatible // DoubleMath.mean
  @SuppressWarnings("deprecation") // test of deprecated method
  public void testMean_intVarargs() {
    assertThat(DoubleMath.mean(11, -22, 44, -88)).isWithin(1.0e-10).of(-13.75);
    assertThat(DoubleMath.mean(11)).isWithin(1.0e-10).of(11.0);
  }

  @GwtIncompatible // DoubleMath.mean
  @SuppressWarnings("deprecation") // test of deprecated method