<link href="${fe:url('/css/admin/bootstrap.min.css')}" rel="stylesheet" type="text/css" />
<link href="${fe:url('/css/admin/font-awesome.min.css')}" rel="stylesheet" type="text/css" />
<link href="${fe:url('/css/admin/adminlte.min.css')}" rel="stylesheet" type="text/css" />
<link href="${fe:url('/css/admin/plugins/daterangepicker/daterangepicker.css')}" rel="stylesheet" type="text/css" />

     * @param <T> the type of the object associated to this key
     */
    final class Key<T> {

        private final Class<T> type;
        private final Object id;

        private Key(Class<T> type, Object id) {
            this.type = type;
            this.id = id;
        }

        public Class<T> type() {
            return type;
        }

        @Override

	if response != nil {
		w.Write(response)
	}
}

// mimeType represents various MIME type used API responses.
type mimeType string

const (
	// Means no response type.
	mimeNone mimeType = ""
	// Means response type is JSON.
	mimeJSON mimeType = "application/json"
	// Means response type is XML.
	mimeXML mimeType = "application/xml"
)

* Convert the copied model to something that can be stored in your DB (for example, using the `jsonable_encoder`).
    * This is comparable to using the model's `.model_dump()` method again, but it makes sure (and converts) the values to data types that can be converted to JSON, for example, `datetime` to `str`.
* Save the data to your DB.
* Return the updated model.

{* ../../docs_src/body_updates/tutorial002_py310.py hl[28:35] *}

/// tip

        "price": 42.0,
        "tax": 3.2
    },
    "user": {
        "username": "dave",
        "full_name": "Dave Grohl"
    },
    "importance": 5
}
```

Encore une fois, cela convertira les types de données, les validera, permettra de générer la documentation, etc...

## Paramètres multiples body et query

	}
}

// metricDisplay - contains info on a metric for display purposes.
type metricDisplay struct {
	Name   string   `json:"name"`
	Help   string   `json:"help"`
	Type   string   `json:"type"`
	Labels []string `json:"labels"`
}

func (md metricDisplay) String() string {
	return fmt.Sprintf("Name: %s\nType: %s\nHelp: %s\nLabels: {%s}\n", md.Name, md.Type, md.Help, strings.Join(md.Labels, ","))
}

* Making the `tf.function` type system fully available:

    * `tf.types.experimental.TraceType` now allows custom tf.function inputs to declare Tensor decomposition and type casting support.

 *
 */
public interface SmbTree extends AutoCloseable {

    /**
     * Unwraps the tree instance to the specified type
     * @param <T> the target tree type
     * @param type the class of the tree type to unwrap to
     * @return tree instance with the given type
     */
    <T extends SmbTree> T unwrap(Class<T> type);

    /**
     * {@inheritDoc}
     *
     * @see java.lang.AutoCloseable#close()
     */
    @Override

        verify(logger).error("Missing toolchain factory for type: unknown. Possibly caused by misconfigured project.");
    }

    @Test
    void testModelAndFactory() {
        MavenSession session = mock(MavenSession.class);
        List<ToolchainModel> toolchainModels = List.of(
                ToolchainModel.newBuilder().type("basic").build(),
                ToolchainModel.newBuilder().type("basic").build(),

		return
	}
	switch {
	case target.Type == obj.TYPE_BRANCH:
		// JMP 4(PC)
		*targetAddr = obj.Addr{
			Type:   obj.TYPE_BRANCH,
			Offset: p.pc + 1 + target.Offset, // +1 because p.pc is incremented in append, below.
		}
	case target.Type == obj.TYPE_REG:
		// JMP R1
		*targetAddr = *target
	case target.Type == obj.TYPE_MEM && (target.Name == obj.NAME_EXTERN || target.Name == obj.NAME_STATIC):