## Validación de datos { #data-validation }

Pero si vas al navegador en [http://127.0.0.1:8000/items/foo](http://127.0.0.1:8000/items/foo), verás un bonito error HTTP de:

```JSON
{
  "detail": [
    {
      "type": "int_parsing",
      "loc": [
        "path",
        "item_id"
      ],
      "msg": "Input should be a valid integer, unable to parse string as an integer",
      "input": "foo"
    }
  ]
}
```

  const DataType& dt = node->output_type(idx);
  return IsRefType(dt)
             ? InvalidArgument("Output ", idx, " of node '", node->name(),
                               "' has a reference type ", DataTypeString(dt))
             : absl::OkStatus();
}

// Converts `ninputs` and `inputs` into `inputs_tensors` and `input_nodes` and
// does various checks while doing so. `input_nodes` will contain the same

        Object result = scriptEngine.evaluate(template, paramMap);
        assertTrue(result.toString().contains("item1"));
    }

    // Test evaluate method returns different object type
    @Test
    public void test_evaluate_returnsObject() {
        scriptEngine = new ObjectReturningScriptEngine();
        String template = "return object";
        Map<String, Object> paramMap = new HashMap<>();

   * structure, and is thus forced to return the query keys instead of the cached keys. This is only
   * possible with an unsafe cast which requires {@code keys} to actually be of type {@code K}.
   *
   * @since 11.0
   */
  /*
   * <? extends Object> is mostly the same as <?> to plain Java. But to nullness checkers, they

              getLowerEndpoint(),
              getLowerBoundType());
      result.reverse = this;
      return this.reverse = result;
    }
    return result;
  }

  // This method helps J2KT's type inference.
  private static <T extends @Nullable Object> Comparator<T> reverseComparator(
      Comparator<T> comparator) {
    return Ordering.from(comparator).reverse();
  }

  @Override

        assertEquals(1, od.getChunksWritten());
        assertEquals(2, od.getChunkBytesWritten());
        assertEquals(3, od.getTotalBytesWritten());

        // Type mismatch should raise SmbException
        assertThrows(SmbException.class, () -> resp.getOutputData(SrvRequestResumeKeyResponse.class));
    }

    @Test

 * A {@code DependencyCoordinates} extends {@code ArtifactCoordinates} with additional information about how
 * the artifact will be used: type, scope and obligation (whether the dependency is optional or mandatory).
 * The version and the obligation may not be defined precisely.</p>
 *

在这个示例中，我们没有声明任何 Pydantic 模型。事实上，请求体甚至没有被 <dfn title="从某种纯文本格式（如字节）转换为 Python 对象">解析</dfn> 为 JSON，而是直接以 `bytes` 读取，并由函数 `magic_data_reader()` 以某种方式负责解析。

尽管如此，我们仍然可以声明请求体的预期方案。

### 自定义 OpenAPI 内容类型 { #custom-openapi-content-type }

使用同样的技巧，你可以用一个 Pydantic 模型来定义 JSON Schema，然后把它包含到该 *路径操作* 的自定义 OpenAPI 方案部分中。

即使请求中的数据类型不是 JSON，你也可以这样做。

Ancak tarayıcınızda [http://127.0.0.1:8000/items/foo](http://127.0.0.1:8000/items/foo) adresine giderseniz, şuna benzer güzel bir HTTP hatası görürsünüz:

```JSON
{
  "detail": [
    {
      "type": "int_parsing",
      "loc": [
        "path",
        "item_id"
      ],
      "msg": "Input should be a valid integer, unable to parse string as an integer",
      "input": "foo"
    }
  ]
}
```

// Code generated by "stringer -type=APIErrorCode -trimprefix=Err api-errors.go"; DO NOT EDIT.

package cmd

import "strconv"

func _() {
	// An "invalid array index" compiler error signifies that the constant values have changed.
	// Re-run the stringer command to generate them again.
	var x [1]struct{}
	_ = x[ErrNone-0]
	_ = x[ErrAccessDenied-1]
	_ = x[ErrBadDigest-2]
	_ = x[ErrEntityTooSmall-3]
	_ = x[ErrEntityTooLarge-4]