/**
     * Enable or disable thumbnail generation for documents.
     * When enabled, thumbnails are generated for supported file types.
     */
    @Size(max = 10)
    public String thumbnail;

    /**
     * Types of crawling failures to ignore during crawling operations.
     * Specified failure types will not be logged or counted as errors.
     */
    @Size(max = 1000)
    public String ignoreFailureType;

    /**

The same would happen if you had something like a <abbr title='A union between multiple types means "any of these types".'>union</abbr> between different types where one or more of them are not valid Pydantic types, for example this would fail 💥:

{* ../../docs_src/response_model/tutorial003_04_py310.py hl[8] *}

    protected final BeanDesc beanDesc;

    /** Constructor */
    protected final Constructor<?> constructor;

    /** Array of constructor parameter types */
    protected final Class<?>[] parameterTypes;

    /** Information about parameterized argument types */
    protected final ParameterizedClassDesc[] parameterizedClassDescs;

    /**
     * Constructs an instance.
     *
     * @param beanDesc

![ReDoc](https://fastapi.tiangolo.com/img/index/index-06-redoc-02.png)

### En résumé

En résumé, vous déclarez **une fois** les types de paramètres, <abbr title="en anglais : body">le corps</abbr>  de la requête, etc. en tant que paramètres de fonction.

Vous faites cela avec les types Python standard modernes.

Vous n'avez pas à apprendre une nouvelle syntaxe, les méthodes ou les classes d'une bibliothèque spécifique, etc.

name: Add to Project

on:
  pull_request_target:
  issues:
    types:
      - opened
      - reopened

jobs:
  add-to-project:
    name: Add to project
    runs-on: ubuntu-latest
    steps:
      - uses: actions/add-to-project@v1.0.2
        with:
          project-url: https://github.com/orgs/fastapi/projects/2

        }
    }

    private static int invokeProtectedInt(Object target, String name, Object... params) {
        try {
            var cls = target.getClass();
            // Build proper parameter types array, handling primitive types
            Class<?>[] paramTypes = new Class<?>[params.length];
            for (int i = 0; i < params.length; i++) {
                if (params[i] instanceof byte[]) {

  @Param Result result;
  @Param ExceptionType exceptionType;

  /**
   * The number of other exception types in the cache of known-good exceptions and the number of
   * other {@code ClassValue} entries for the exception type to be tested. This lets us evaluate
   * whether our solution scales to use with multiple exception types and to whether it is affected

 * limitations under the License.
 */
package okhttp3.recipes;

import com.squareup.moshi.JsonAdapter;
import com.squareup.moshi.Moshi;
import com.squareup.moshi.Types;
import java.io.IOException;
import java.util.LinkedHashMap;
import java.util.Map;
import okhttp3.Interceptor;
import okhttp3.MediaType;
import okhttp3.OkHttpClient;
import okhttp3.Request;

#include <memory>
#include <string>

#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/util/tensor_bundle/tensor_bundle.h"
#include "tensorflow/core/util/tensor_slice_reader.h"

namespace tensorflow {
namespace checkpoint {

class TensorSliceReader;

For example, you cannot put a Pydantic model in a `JSONResponse` without first converting it to a `dict` with all the data types (like `datetime`, `UUID`, etc) converted to JSON-compatible types.

For those cases, you can use the `jsonable_encoder` to convert your data before passing it to a response:

{* ../../docs_src/response_directly/tutorial001_py310.py hl[5:6,20:21] *}