But if you need to access variables and objects from the same **FastAPI** app, or you need to perform small background tasks (like sending an email notification), you can simply just use `BackgroundTasks`.

## Recap

    val jansi = "org.fusesource.jansi:jansi"
    val jatl = "com.googlecode.jatl:jatl"
    val javaPoet = "com.squareup:javapoet"
    val jaxbCore = "com.sun.xml.bind:jaxb-core"
    val jaxbImpl = "com.sun.xml.bind:jaxb-impl"
    val jcifs = "jcifs:jcifs"
    val jclToSlf4j = "org.slf4j:jcl-over-slf4j"
    val jcommander = "com.beust:jcommander"
    val jetbrainsAnnotations = "org.jetbrains:annotations"

    super(new DataOutputStream(Preconditions.checkNotNull(out)));
  }

  @Override
  public void write(byte[] b, int off, int len) throws IOException {
    // Override slow FilterOutputStream impl
    out.write(b, off, len);
  }

  @Override
  public void writeBoolean(boolean v) throws IOException {
    ((DataOutputStream) out).writeBoolean(v);
  }

  @Override

 * <p>
 * <strong>Note:</strong> This class is part of work in progress and can be changed or removed without notice.
 * @since 3.2.4
 * @deprecated since 4.0.0, use {@code maven-api-impl} jar instead
 */
@Deprecated(since = "4.0.0")
public class ArtifactDescriptorReaderDelegate {
    public void populateResult(RepositorySystemSession session, ArtifactDescriptorResult result, Model model) {

 * KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
 * under the License.
 */
package org.apache.maven.internal.impl;

import javax.inject.Inject;
import javax.inject.Named;
import javax.inject.Singleton;

import java.io.File;
import java.io.IOException;
import java.io.InputStream;
import java.net.URI;

Normally, this just means running the queue.
All informers created by `kube.Client` are kept track in the client, and started in one go with `RunAndWait` in one centralized call.
As a result, each individual controllers should simply wait until informers have synced, then run the queue to start processing things.

A queue is used to give a few properties:

 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,
 * either express or implied. See the License for the specific language
 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.thumbnail.impl;

import java.awt.Image;
import java.awt.Rectangle;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;
import java.util.Iterator;
import java.util.Map;

        : new ImmutableGraph<N>(
            new StandardValueGraph<N, Presence>(
                GraphBuilder.from(graph), getNodeConnections(graph), graph.edges().size()));
  }

  /**
   * Simply returns its argument.
   *
   * @deprecated no need to use this
   */
  @Deprecated
  public static <N> ImmutableGraph<N> copyOf(ImmutableGraph<N> graph) {
    return checkNotNull(graph);
  }

  @Override

// a map (`tensorflow::eager::TensorTape`) from the wrapped tensor to the id of
// the op that produced it (or -1 if this tensor was watched using
// `GradientTape::Watch`.) The op_id is simply a unique index assigned to each
// op executed under the tape. A separate map (`tensorflow::eager::OpTape`)
// maintains the map from `op_id` to a `OpTapeEntry` which stores the `op_type`,

    end
```

At a high level, each client job will find the correct generator for the request, generate the required configuration, and send it.

#### Optimizations

A naive implementation would simply regenerate all resources, of all subscribed types, for each client, on any configuration change. However, this scales poorly. As a result, we have many levels of optimizations to avoid doing this work.