* </p>
 * <ul>
 *   <li>{@code PRE_PROCESSING} - Represents the pre-processing state.</li>
 *   <li>{@code POST_PROCESSING} - Represents the post-processing state.</li>
 *   <li>{@code NO_URL_IN_QUEUE} - Indicates that there are no URLs in the queue.</li>
 *   <li>{@code WAIT_NEW_URL} - Indicates that the crawler is waiting for new URLs.</li>
 * </ul>
 */
public interface IntervalController {

 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.suggest.exception;

/**
 * Exception thrown when there is an issue with the suggest settings.
 * This exception extends {@link RuntimeException}, so it is an unchecked exception.
 *
 * <p>There are three constructors available for this exception:</p>
 * <ul>

     * The source indicates the timing of property evaluation in the Maven build lifecycle and the location
     * where the property value is defined.
     */
    enum Source {
        /**
         * Maven system properties. These properties are evaluated very early during the boot process,
         * typically set by Maven itself and flagged as readOnly=true or by users via maven-system.properties files.

 * implementing {@code Map}, the additional type-safe operations {@link #putInstance} and {@link
 * #getInstance} are available.
 *
 * <p>Generally, implementations don't support {@link #put} and {@link #putAll} because there is no
 * way to check an object at runtime to be an instance of a {@link TypeToken}. Instead, caller
 * should use the type safe {@link #putInstance}.
 *

 * implementing {@code Map}, the additional type-safe operations {@link #putInstance} and {@link
 * #getInstance} are available.
 *
 * <p>Generally, implementations don't support {@link #put} and {@link #putAll} because there is no
 * way to check an object at runtime to be an instance of a {@link TypeToken}. Instead, caller
 * should use the type safe {@link #putInstance}.
 *

from tensorflow.python.platform import app  # pylint: disable=g-import-not-at-top
app.flags = flags

# These symbols appear because we import the python package which
# in turn imports from tensorflow.core and tensorflow.python. They
# must come from this module. So python adds these symbols for the
# resolution to succeed.
# pylint: disable=undefined-variable
del python
del core

   * A scheduler defines the policy for how the {@link AbstractScheduledService} should run its
   * task.
   *
   * <p>Consider using the {@link #newFixedDelaySchedule} and {@link #newFixedRateSchedule} factory
   * methods, these provide {@link Scheduler} instances for the common use case of running the
   * service with a fixed schedule. If more flexibility is needed then consider subclassing {@link
   * CustomScheduler}.
   *

    add(element, 1);
    return true;
  }

  /**
   * A sensible definition of {@link #addAll(Collection)} in terms of {@link #add(Object)} and
   * {@link #add(Object, int)}. If you override either of these methods, you may wish to override
   * {@link #addAll(Collection)} to forward to this implementation.
   *
   * @since 7.0
   */
  @Override
  protected boolean standardAddAll(Collection<? extends E> elementsToAdd) {

            "API changes in file '${it.key.name}' should be in alphabetical order (by type and member), yet these changes were not:\n" +
                "$formattedMismatches\n"
        }.joinToString(separator = "\n")

        return "$messages\nTo automatically alphabetize these changes run: './gradlew :architecture-test:sortAcceptedApiChanges'"
    }

But you can also declare multiple body parameters, e.g. `item` and `user`:

{* ../../docs_src/body_multiple_params/tutorial002_py310.py hl[20] *}


In this case, **FastAPI** will notice that there is more than one body parameter in the function (there are two parameters that are Pydantic models).

So, it will then use the parameter names as keys (field names) in the body, and expect a body like:

```JSON
{
    "item": {