使用 `Query` 和 `Path`（以及你将在后面看到的其他类）可以声明字符串约束，但也可以声明数值约束。

像下面这样，添加 `ge=1` 后，`item_id` 将必须是一个大于（`g`reater than）或等于（`e`qual）`1` 的整数。

```Python hl_lines="8"
{!../../docs_src/path_params_numeric_validations/tutorial004.py!}
```

## 数值校验：大于和小于等于

同样的规则适用于：

* `gt`：大于（`g`reater `t`han）
* `le`：小于等于（`l`ess than or `e`qual）

```Python hl_lines="9"
{!../../docs_src/path_params_numeric_validations/tutorial005.py!}

    if (tag < 31) {
      val byte0 = tagClass or constructedBit or tag.toInt()
      sink.writeByte(byte0)
    } else {
      val byte0 = tagClass or constructedBit or 0b0001_1111
      sink.writeByte(byte0)
      writeVariableLengthLong(tag)
    }

    // Write the length. This takes 1 byte if length is less than 128.
    val length = content.size
    if (length < 128) {

   * does not normally minimize that error: to do that, you should swap the roles of {@code x} and
   * {@code y}.
   *
   * <h3>Non-finite values</h3>
   *
   * <p>If the dataset contains any non-finite values ({@link Double#POSITIVE_INFINITY}, {@link
   * Double#NEGATIVE_INFINITY}, or {@link Double#NaN}) then the result is {@link
   * LinearTransformation#forNaN()}.
   *

   * <p><b>Performance note:</b> When feasible, {@code initialCapacity} should be the exact number
   * of values that will be added, if that knowledge is readily available. It is better to guess a
   * value slightly too high than slightly too low. If the value is not exact, the {@link
   * ImmutableIntArray} that is built will very likely occupy more memory than strictly necessary;
   * to trim memory usage, build using {@code builder.build().trimmed()}.
   */

  }

  /**
   * Updates the index an iterator is pointing to after a call to remove: returns the index of the
   * entry that should be looked at after a removal on indexRemoved, with indexBeforeRemove as the
   * index that *was* the next entry that would be looked at.
   */
  int adjustAfterRemove(int indexBeforeRemove, @SuppressWarnings("unused") int indexRemoved) {
    return indexBeforeRemove - 1;
  }

    return result;
  }

  /**
   * Returns a new array that prepends {@code element} to {@code array}.
   *
   * @param element the element to prepend to the front of {@code array}
   * @param array the array of elements to append
   * @return an array whose size is one larger than {@code array}, with {@code element} occupying

class Item(BaseModel):
    name: str
    description: str | None = Field(
        default=None, title="The description of the item", max_length=300
    )
    price: float = Field(gt=0, description="The price must be greater than zero")
    tax: float | None = None


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item = Body(embed=True)):
    results = {"item_id": item_id, "item": item}

  @Override
  protected void setUp() throws Exception {
    super.setUp();

    handler = new TestLogHandler();

    // You could also apply it higher up the Logger hierarchy than this
    ExampleClassUnderTest.logger.addHandler(handler);

    ExampleClassUnderTest.logger.setUseParentHandlers(false); // optional

    stack.addTearDown(
        new TearDown() {
          @Override

     * objects from the parent.
     *
     * @param child The child model into which to merge the values inherited from the parent, must not be
     *            <code>null</code>.
     * @param parent The (read-only) parent model from which to inherit the values, may be <code>null</code>.
     * @param request The model building request that holds further settings, must not be {@code null}.

revolves around the idea of applications deployed as micro services, that scale well. It is not about just retrofitting monolithic applications onto modern container based compute environment. A cloud-native application is portable and resilient by design, and can scale horizontally by simply replicating. Modern orchestration platforms like Kubernetes, DC/OS make replicating and managing containers in huge clusters easier than ever.

While containers provide isolated application execution...