from fastapi import FastAPI, Path

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(*, item_id: int = Path(title="The ID of the item to get"), q: str):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})

    UNIFORM_0_TO_2(0, 2),
    UNIFORM_0_TO_9(0, 9),
    ALWAYS_0(0, 0),
    ALWAYS_10(10, 10);

    final int min;
    final int max;

    ListSizeDistribution(int min, int max) {
      this.min = min;
      this.max = max;
    }

    public int chooseSize(Random random) {
      return random.nextInt(max - min + 1) + min;
    }
  }

  private BenchmarkHelpers() {}

    /**
     * Event severity levels
     */
    public enum Severity {
        INFO(0), WARNING(1), ERROR(2), CRITICAL(3);

        private final int level;

        Severity(int level) {
            this.level = level;
        }

        public int getLevel() {
            return level;
        }
    }

    private static class SingletonHolder {

   * SetView#maxSize()} of {@code max}.
   */
  private static SetView<Integer> setSizeRange(int min, int max) {
    checkArgument(min >= 0 && max >= min);
    SetView<Integer> set = difference(setSize(max), setSize(max - min));
    checkState(set.minSize() == min && set.maxSize() == max);
    return set;
  }

  /**

You would do the same to declare `tuple`s and `set`s:

{* ../../docs_src/python_types/tutorial007_py39.py hl[1] *}

This means:

* The variable `items_t` is a `tuple` with 3 items, an `int`, another `int`, and a `str`.
* The variable `items_s` is a `set`, and each of its items is of type `bytes`.

#### Dict { #dict }

To define a `dict`, you pass 2 type parameters, separated by commas.

    assertTrue(delegateFuture.isCancelled());
  }

  private static final class ThrowingRunnable implements Runnable {
    final int throwAfterCount;
    final RuntimeException thrown;
    int count;

    ThrowingRunnable(int throwAfterCount, RuntimeException thrown) {
      this.throwAfterCount = throwAfterCount;
      this.thrown = thrown;
    }

    @Override

      if (AnnotatedElement.class.isAssignableFrom(TypeVariable.class)) {
        if (new TypeCapture<Entry<String, int[][]>>() {}.capture()
            .toString()
            .contains("java.util.Map.java.util.Map")) {
          CURRENT = JAVA8;
        } else {
          CURRENT = JAVA9;
        }
      } else if (new TypeCapture<int[]>() {}.capture() instanceof Class) {
        CURRENT = JAVA7;
      } else {
        CURRENT = JAVA6;

Mit demselben Trick könnten Sie ein Pydantic-Modell verwenden, um das JSON-Schema zu definieren, das dann im benutzerdefinierten Abschnitt des OpenAPI-Schemas für die *Pfadoperation* enthalten ist.

Und Sie könnten dies auch tun, wenn der Datentyp im Request nicht JSON ist.

Esto sería útil si deseas recibir claves que aún no conoces.

---

Otro caso útil es cuando deseas tener claves de otro tipo (por ejemplo, `int`).

Eso es lo que vamos a ver aquí.

En este caso, aceptarías cualquier `dict` siempre que tenga claves `int` con valores `float`:

{* ../../docs_src/body_nested_models/tutorial009_py39.py hl[7] *}

/// tip | Consejo

        request.setModelSource(modelSource);

        return this;
    }

    @Override
    public int getValidationLevel() {
        return request.getValidationLevel();
    }

    @Override
    public FilterModelBuildingRequest setValidationLevel(int validationLevel) {
        request.setValidationLevel(validationLevel);

        return this;
    }

    @Override