TransportException exception = new TransportException("Test");

            assertTrue(exception instanceof IOException);

            // Should be able to assign to IOException variable
            IOException ioException = exception;
            assertNotNull(ioException);
        }

        @Test
        @DisplayName("Should work in catch blocks for IOException")

    private final String name;
    private final ImmutableList<Type> bounds;

    TypeVariableImpl(D genericDeclaration, String name, Type[] bounds) {
      disallowPrimitiveType(bounds, "bound for type variable");
      this.genericDeclaration = checkNotNull(genericDeclaration);
      this.name = checkNotNull(name);
      this.bounds = ImmutableList.copyOf(bounds);
    }

    @Keep
    public Type[] getBounds() {

        // Verify - invalid format should return empty due to exception in LocaleUtils.toLocale
        assertFalse(result.isPresent());
    }

    // Test findBusinessLocale with language and country and variant
    public void test_findBusinessLocale_withLanguageCountryVariant() {
        // Setup mock config
        FessConfig mockConfig = new FessConfig.SimpleImpl() {
            @Override

```Python
user_in = UserIn(username="john", password="secret", email="******@****.***")
```

und wir rufen seine `.dict()`-Methode auf:

```Python
user_dict = user_in.dict()
```

dann haben wir jetzt in der Variable `user_dict` ein `dict` mit den gleichen Daten (es ist ein `dict` statt eines Pydantic-Modellobjekts).

Wenn wir es ausgeben:

```Python
print(user_dict)
```

bekommen wir ein Python-`dict`:

```Python

```Python
user_in = UserIn(username="john", password="secret", email="******@****.***")
```

and then we call:

```Python
user_dict = user_in.dict()
```

we now have a `dict` with the data in the variable `user_dict` (it's a `dict` instead of a Pydantic model object).

And if we call:

```Python
print(user_dict)
```

we would get a Python `dict` with:

```Python
{
    'username': 'john',

Vous écrivez du python standard avec des annotations de types:

```Python
from datetime import date

from pydantic import BaseModel

# Déclare une variable comme étant une str
# et profitez de l'aide de votre IDE dans cette fonction
def main(user_id: str):
    return user_id


# Un modèle Pydantic
class User(BaseModel):
    id: int
    name: str

     */
    public void setQueryBuilder(final QueryBuilder queryBuilder) {
        this.queryBuilder = queryBuilder;
    }

    /**
     * Adds sort builders to the query context.
     * @param sortBuilders Variable number of sort builders to add.
     */
    public void addSorts(final SortBuilder<?>... sortBuilders) {
        stream(sortBuilders).of(stream -> stream.forEach(sortBuilder -> sortBuilderList.add(sortBuilder)));
    }

```Python
user_in = UserIn(username="john", password="secret", email="******@****.***")
```

y luego llamamos a:

```Python
user_dict = user_in.dict()
```

ahora tenemos un `dict` con los datos en la variable `user_dict` (es un `dict` en lugar de un objeto modelo Pydantic).

Y si llamamos a:

```Python
print(user_dict)
```

obtendremos un `dict` de Python con:

```Python
{
    'username': 'john',

    server.requireClientAuth()
    val call = client.newCall(Request.Builder().url(server.url("/")).build())
    assertFailsWith<IOException> {
      call.execute()
    }

    // Observed Events are variable
    // JDK 14
    // CallStart, ProxySelectStart, ProxySelectEnd, DnsStart, DnsEnd, ConnectStart, SecureConnectStart,
    // SecureConnectEnd, ConnectEnd, ConnectionAcquired, RequestHeadersStart, RequestHeadersEnd,

    public void addReplyTo(String replyTo, String personal) {
        doAddReplyTo(replyTo, personal);
    }

    // -----------------------------------------------------
    //                                  Application Variable
    //                                  --------------------
    /**
     * Set the value of hostname, used in parameter comment. <br>