added("Method", "SourceKt.getBazool()"),
                added("Method", "SourceKt.getBool()"),
                added("Method", "SourceKt.invoke(java.lang.String,java.lang.String,kotlin.jvm.functions.Function1)"),
                added("Method", "SourceKt.isBool()"),
                added("Method", "SourceKt.isFool()"),
                added("Method", "SourceKt.setBazar(java.lang.String)"),

   * the data points and the best fit line). For this fit, this error is a fraction {@code sqrt(1 -
   * R*R)} of the population standard deviation of {@code y}, where {@code R} is the Pearson's
   * correlation coefficient (as given by {@link #pearsonsCorrelationCoefficient()}).
   *
   * <p>The corresponding root-mean-square error in {@code x} as a function of {@code y} is a

{* ../../docs_src/background_tasks/tutorial001_py39.py hl[1,13] *}

**FastAPI** erstellt für Sie das Objekt vom Typ `BackgroundTasks` und übergibt es als diesen Parameter.

## Eine Taskfunktion erstellen { #create-a-task-function }

Erstellen Sie eine Funktion, die als Hintergrundtask ausgeführt werden soll.

*   `tf.function`:

    *   `tf.function` now uses the Python inspect library directly for parsing the signature of the Python function it is decorated on. This change may break code where the function signature is malformed, but was ignored previously, such as:
        *   Using `functools.wraps` on a function with different signature

 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package gradlebuild.binarycompatibility.metadata

import java.util.function.Supplier
import kotlin.metadata.KmClass
import kotlin.metadata.KmConstructor
import kotlin.metadata.KmFunction
import kotlin.metadata.KmPackage
import kotlin.metadata.KmProperty

  opts->opts.validate_colocation_constraints = enable;
}

// Load a Pluggable Device library.
// On success, returns the handle to library in result and return OK from the
// function. Otherwise return nullptr in result and error Status from the
// function.
//
// If `library_filename` has already been loaded, we return a cached handle.
// Device and Kernels/Ops are registered as globals when a library is loaded
// for the first time.

   * the data points and the best fit line). For this fit, this error is a fraction {@code sqrt(1 -
   * R*R)} of the population standard deviation of {@code y}, where {@code R} is the Pearson's
   * correlation coefficient (as given by {@link #pearsonsCorrelationCoefficient()}).
   *
   * <p>The corresponding root-mean-square error in {@code x} as a function of {@code y} is a

   * {@code function} to the argument, then evaluating using {@code this}. That is, for any pair of
   * non-null objects {@code x} and {@code y}, {@code equivalence.onResultOf(function).equivalent(a,
   * b)} is true if and only if {@code equivalence.equivalent(function.apply(a), function.apply(b))}
   * is true.
   *
   * <p>For example:
   *
   * {@snippet :

            .put(5, "Pinky")
            .put(5, "Clyde")
            .build();

    List<String> badGuys = Arrays.asList("Inky", "Blinky", "Pinky", "Pinky", "Clyde");
    Function<String, Integer> stringLengthFunction =
        new Function<String, Integer>() {
          @Override
          public Integer apply(String input) {
            return input.length();
          }
        };

///

### Lifespan-Funktion { #lifespan-function }

Das Erste, was auffällt, ist, dass wir eine asynchrone Funktion mit `yield` definieren. Das ist sehr ähnlich zu Abhängigkeiten mit `yield`.

{* ../../docs_src/events/tutorial003_py39.py hl[14:19] *}

Der erste Teil der Funktion, vor dem `yield`, wird ausgeführt **bevor** die Anwendung startet.