initialized = true;
    }

    /**
     * Returns the logger adapter factory.
     * <p>
     * Detects available logging frameworks in the following order:
     * 1. SLF4J (if available)
     * 2. Commons Logging (if available)
     * 3. java.util.logging (fallback)
     * </p>
     *
     * @return the logger adapter factory
     */
    protected static LoggerAdapterFactory getLoggerAdapterFactory() {

   * ```
   */
  private val attributeTypeAndValue: BasicDerAdapter<AttributeTypeAndValue> =
    Adapters.sequence(
      "AttributeTypeAndValue",
      Adapters.OBJECT_IDENTIFIER,
      Adapters.any(
        String::class to Adapters.UTF8_STRING,
        Nothing::class to Adapters.PRINTABLE_STRING,
        AnyValue::class to Adapters.ANY_VALUE,
      ),
      decompose = {
        listOf(
          it.type,

            # Pydantic >= 2.12.0 warns about field specific metadata that is unused
            # (e.g. `TypeAdapter(Annotated[int, Field(alias='b')])`). In some cases, we
            # end up building the type adapter from a model field annotation so we
            # need to ignore the warning:
            if shared.PYDANTIC_VERSION_MINOR_TUPLE >= (2, 12):
                from pydantic.warnings import UnsupportedFieldAttributeWarning

Les modèles, bien qu'ils soient généralement livrés avec une configuration spécifique, sont conçus pour être flexibles et personnalisables. Cela vous permet de les modifier et de les adapter aux exigences de votre projet, ce qui en fait un excellent point de départ. 🏁

 * code changes, you can use <a
 * href="https://www.javadoc.io/doc/com.github.ben-manes.caffeine/guava/latest/com.github.benmanes.caffeine.guava/com/github/benmanes/caffeine/guava/CaffeinatedGuava.html">its
 * {@code CaffeinatedGuava} adapter class</a>, which lets you build a Guava {@code Cache} or a Guava
 * {@code LoadingCache} backed by a Guava {@code CacheLoader}.
 *
 * <p>Caffeine's API for asynchronous operations uses {@code CompletableFuture}: <a

Vous pouvez utiliser [`bump-pydantic`](https://github.com/pydantic/bump-pydantic) de la même équipe Pydantic.

Cet outil vous aidera à modifier automatiquement la majeure partie du code à adapter.

Après cela, vous pouvez exécuter les tests et vérifier que tout fonctionne. Si c'est le cas, vous avez terminé. 😎

## Pydantic v1 dans v2 { #pydantic-v1-in-v2 }

 * code changes, you can use <a
 * href="https://www.javadoc.io/doc/com.github.ben-manes.caffeine/guava/latest/com.github.benmanes.caffeine.guava/com/github/benmanes/caffeine/guava/CaffeinatedGuava.html">its
 * {@code CaffeinatedGuava} adapter class</a>, which lets you build a Guava {@code Cache} or a Guava
 * {@code LoadingCache} backed by a Guava {@code CacheLoader}.
 *
 * <p>Caffeine's API for asynchronous operations uses {@code CompletableFuture}: <a

=== ":material-language-kotlin: Kotlin"
    ```kotlin
      private val client = OkHttpClient()
      private val moshi = Moshi.Builder().build()
      private val gistJsonAdapter = moshi.adapter(Gist::class.java)

      fun run() {
        val request = Request.Builder()
            .url("https://api.github.com/gists/c2a7c39532239ff261be")
            .build()

    val request = Request.Builder().url("https://www.howsmyssl.com/a/check").build()

    val response = client.newCall(request).execute()

    val results =
      response.use {
        moshi.adapter(HowsMySslResults::class.java).fromJson(response.body.string())!!
      }

    Platform.get().log("results $results", Platform.WARN)

    assertTrue(results.session_ticket_supported)

/// tip

If you want to **learn FastAPI** in a structured way (recommended), go and read the [Tutorial - User Guide](../tutorial/index.md) chapter by chapter instead.