import java.util.Properties;

import org.apache.maven.model.Activation;
import org.apache.maven.model.ActivationProperty;
import org.apache.maven.model.Profile;
import org.codehaus.plexus.context.Context;
import org.codehaus.plexus.context.ContextException;
import org.codehaus.plexus.personality.plexus.lifecycle.phase.Contextualizable;

/**
 * SystemPropertyProfileActivator
 */
@Deprecated

    public int size() {
        // Context header (16) + name length (4) + padding to 8-byte alignment (4) + data (32)
        return 16 + 4 + 4 + STRUCTURE_SIZE;
    }

    @Override
    public int encode(byte[] dst, int dstIndex) {
        int start = dstIndex;

        // Write context header
        SMBUtil.writeInt4(0, dst, dstIndex); // Next (offset to next context, 0 for last)
        dstIndex += 4;

	return types.TargetStats{}
}

func (t *testLogger) Init(ctx context.Context) error {
	return nil
}

func (t *testLogger) IsOnline(ctx context.Context) bool {
	return t.current.Load() != nil
}

func (t *testLogger) Cancel() {
	t.current.Store(nil)
}

func (t *testLogger) Send(ctx context.Context, entry any) error {
	tb := t.current.Load()
	var logf func(format string, args ...any)

                FessWebResourceRoot.class.getName());

        // Verify constructor exists with Context parameter
        try {
            FessWebResourceRoot.class.getConstructor(Context.class);
            assertTrue("Constructor with Context parameter exists", true);
        } catch (final NoSuchMethodException e) {
            fail("Constructor with Context parameter should exist");
        }
    }

    @Test

    password = user_dict["password"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```

#### Pydantic-модель из содержимого другой { #a-pydantic-model-from-the-contents-of-another }

Как в примере выше мы получили `user_dict` из `user_in.model_dump()`, этот код:

```Python
user_dict = user_in.model_dump()
UserInDB(**user_dict)
```

будет равнозначен такому:

    password = user_dict["password"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```

#### Um modelo Pydantic a partir do conteúdo de outro { #a-pydantic-model-from-the-contents-of-another }

Como no exemplo acima, obtivemos o `user_dict` a partir do `user_in.model_dump()`, este código:

```Python
user_dict = user_in.model_dump()
UserInDB(**user_dict)
```

seria equivalente a:

     * Executes query processing through the filter chain.
     *
     * @param context the query context containing search parameters and state
     * @param query the Lucene query to be processed
     * @param boost the boost factor to apply to the query
     * @return the processed OpenSearch QueryBuilder
     */
    public QueryBuilder execute(final QueryContext context, final Query query, final float boost) {

            @Override
            public boolean isActive(Profile profile, ProfileActivationContext context, ModelProblemCollector problems) {
                throw new RuntimeException("BOOM");
            }

            @Override
            public boolean presentInConfig(
                    Profile profile, ProfileActivationContext context, ModelProblemCollector problems) {
                return true;
            }
        });

                // Update context to use the temp directory
                when(context.invokerRequest.cwd()).thenReturn(tempDir);

                // Mock successful strategy execution
                when(mockOrchestrator.executeStrategies(Mockito.any(), Mockito.any()))
                        .thenReturn(UpgradeResult.empty());

                checkGoal.execute(context);

```jinja hl_lines="7"
{!../../docs_src/templates/templates/item.html!}
```

### Template Context Values { #template-context-values }

In the HTML that contains:

{% raw %}

```jinja
Item ID: {{ id }}
```

{% endraw %}

...it will show the `id` taken from the "context" `dict` you passed:

```Python
{"id": id}
```

For example, with an ID of `42`, this would render: