Par exemple, vous ne pouvez pas mettre un modèle Pydantic dans une `JSONResponse` sans d'abord le convertir en un `dict` avec tous les types de données (comme `datetime`, `UUID`, etc.) convertis en types compatibles avec JSON.

Pour ces cas, vous pouvez spécifier un appel à `jsonable_encoder` pour convertir vos données avant de les passer à une réponse :

import org.apache.maven.api.annotations.Nonnull;
import org.apache.maven.api.annotations.Nullable;

/**
 * Base interface for service requests in Maven. This interface defines the common contract
 * for all request types within the Maven service layer, providing access to session context
 * and request tracing capabilities.
 *
 * <p>Each request is associated with a {@link ProtoSession} that contains the configuration

     *
     * @param paramTypes
     *            array of parameter types
     * @param args
     *            array of arguments
     * @param adjustNumber
     *            if {@literal true}, converts arguments to match number types if necessary
     * @return {@literal true} if the arguments are suitable for the parameter types
     */

/**
 * Utility class for calculating and verifying PAC (Privilege Attribute Certificate) message authentication codes.
 * This class provides methods for computing MACs using various Kerberos encryption types including
 * ARCFOUR-HMAC-MD5 and AES-based HMAC algorithms.
 */
public class PacMac {

    /**
     * Private constructor to prevent instantiation of utility class.
     */
    private PacMac() {

     */
    private static final ObjectInputFilter DEFAULT_FILTER = filterInfo -> {
        final Class<?> serialClass = filterInfo.serialClass();
        if (serialClass == null) {
            return ObjectInputFilter.Status.UNDECIDED;
        }

        final String className = serialClass.getName();

        // Allow primitive types and their wrappers

And these models are all sharing a lot of the data and duplicating attribute names and types.

We could do better.

We can declare a `UserBase` model that serves as a base for our other models. And then we can make subclasses of that model that inherit its attributes (type declarations, validation, etc).

     *
     * @param labelTypeList The list of label types.
     */
    public void refresh(final List<LabelType> labelTypeList) {
        buildLabelTypeItems(labelTypeList);
        buildLabelTypePatternList(labelTypeList);
    }

    /**
     * Builds a list of label type items.
     *
     * @param labelTypeList The list of label types.
     */

    * JSON.
    * Path parameters.
    * Query parameters.
    * Cookies.
    * Headers.
    * Forms.
    * Files.
* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of output data: converting from Python data and types to network data (as JSON):
    * Convert Python types (`str`, `int`, `float`, `bool`, `list`, etc).

import java.util.Map;

import org.codelibs.core.lang.StringUtil;
import org.codelibs.fess.crawler.exception.CrawlerSystemException;

/**
 * Helper class for managing content length limits based on MIME types.
 * It allows setting default and MIME type-specific maximum content lengths.
 * The class provides methods to add, retrieve, and manage these limits.
 */
public class ContentLengthHelper {
    /**

 */
package okhttp3.survey

import java.security.Security
import okhttp3.Cache
import okhttp3.OkHttpClient
import okhttp3.survey.ssllabs.SslLabsClient
import okhttp3.survey.types.Client
import okhttp3.survey.types.SuiteId
import okio.FileSystem
import okio.Path.Companion.toPath
import org.conscrypt.Conscrypt

@Suppress("ktlint:standard:property-naming")
suspend fun main() {
  val includeConscrypt = false