// but work beyond that must take at least one second
      assertThat(afterBurst).isAtLeast(1000);
    }
  }

  /**
   * This neat test shows that no matter what weights we use in our requests, if we push X amount of
   * permits in a cool state, where X = rate * timeToCoolDown, and we have specified a
   * timeToWarmUp() period, it will cost as the prescribed amount of time. E.g., calling

      // but work beyond that must take at least one second
      assertThat(afterBurst).isAtLeast(1000);
    }
  }

  /**
   * This neat test shows that no matter what weights we use in our requests, if we push X amount of
   * permits in a cool state, where X = rate * timeToCoolDown, and we have specified a
   * timeToWarmUp() period, it will cost as the prescribed amount of time. E.g., calling

def test_post_body(client: TestClient):
    data = {"2": 2.2, "3": 3.3}
    response = client.post("/index-weights/", json=data)
    assert response.status_code == 200, response.text
    assert response.json() == data


def test_post_invalid_body(client: TestClient):
    data = {"foo": 2.2, "3": 3.3}
    response = client.post("/index-weights/", json=data)
    assert response.status_code == 422, response.text
    assert response.json() == {

        `tf.keras.mixed_precision.experimental.LossScaleOptimizer`, the weights
        of the `DynanmicLossScale` are copied into the `LossScaleOptimizer`
        instead of being reused. This means modifying the weights of the
        `DynamicLossScale` will no longer affect the weights of the
        LossScaleOptimizer, and vice versa.

      ValueReference<K, V> previous = entry.getValueReference();
      int weight = map.weigher.weigh(key, value);
      checkState(weight >= 0, "Weights must be non-negative");

      ValueReference<K, V> valueReference =
          map.valueStrength.referenceValue(this, entry, value, weight);
      entry.setValueReference(valueReference);
      recordWrite(entry, weight, now);
      previous.notifyNewValue(value);
    }

    checkArgument(maximumWeight >= 0, "maximum weight must not be negative");
    this.maximumWeight = maximumWeight;
    return this;
  }

  /**
   * Specifies the weigher to use in determining the weight of entries. Entry weight is taken into
   * consideration by {@link #maximumWeight(long)} when determining which entries to evict, and use

      ValueReference<K, V> previous = entry.getValueReference();
      int weight = map.weigher.weigh(key, value);
      checkState(weight >= 0, "Weights must be non-negative");

      ValueReference<K, V> valueReference =
          map.valueStrength.referenceValue(this, entry, value, weight);
      entry.setValueReference(valueReference);
      recordWrite(entry, weight, now);
      previous.notifyNewValue(value);
    }

Esto significa que, aunque tus clientes de API solo pueden enviar strings como claves, mientras esos strings contengan enteros puros, Pydantic los convertirá y validará.

Y el `dict` que recibas como `weights` tendrá realmente claves `int` y valores `float`.

///

## Resumen { #recap }

Con **FastAPI** tienes la máxima flexibilidad proporcionada por los modelos Pydantic, manteniendo tu código simple, corto y elegante.

Ancak Pydantic otomatik veri dönüştürme yapar.

Yani API client’larınız key’leri sadece string olarak gönderebilse bile, bu string’ler saf tamsayı içeriyorsa Pydantic bunları dönüştürür ve doğrular.

Ve `weights` olarak aldığınız `dict`, gerçekte `int` key’lere ve `float` value’lara sahip olur.

///

## Özet { #recap }

Isso significa que, embora os clientes da API só possam enviar strings como chaves, desde que essas strings contenham inteiros puros, o Pydantic irá convertê-los e validá-los.

E o `dict` que você recebe como `weights` terá, na verdade, chaves `int` e valores` float`.

///

## Recapitulação { #recap }