--hash=sha256:a6df30f272c08bf8be66e0775fad862005d950a6b8449b94f7c788731d70ecd7
    # via -r ci/official/requirements_updater/requirements.in
tensorboard-data-server==0.7.2 \
    --hash=sha256:7e0610d205889588983836ec05dc098e80f97b7e7bbff7e994ebb78f578d0ddb \
    --hash=sha256:9fe5d24221b29625dbc7328b0436ca7fc1c23de4acf4d272f1180856e32f9f60 \

pkg crypto/tls, type RenegotiationSupport int
pkg crypto/x509, func SystemCertPool() (*CertPool, error)
pkg crypto/x509, type SystemRootsError struct, Err error
pkg debug/dwarf, method (*Data) Ranges(*Entry) ([][2]uint64, error)
pkg debug/dwarf, method (*Reader) SeekPC(uint64) (*Entry, error)
pkg debug/elf, const R_390_12 = 2
pkg debug/elf, const R_390_12 R_390
pkg debug/elf, const R_390_16 = 3

    --hash=sha256:a6df30f272c08bf8be66e0775fad862005d950a6b8449b94f7c788731d70ecd7
    # via -r ci/official/requirements_updater/requirements.in
tensorboard-data-server==0.7.2 \
    --hash=sha256:7e0610d205889588983836ec05dc098e80f97b7e7bbff7e994ebb78f578d0ddb \
    --hash=sha256:9fe5d24221b29625dbc7328b0436ca7fc1c23de4acf4d272f1180856e32f9f60 \

            }

            byte verify[] = new byte[read];
            randBytes(r, verify);
            byte actual[] = Arrays.copyOfRange(buffer, 0, read);

            assertArrayEquals("Data matches at offset " + p, actual, verify);

            p += read;
        }
        if ( expectEof ) {
            assertEquals("Expecting EOF", -1, is.read(buffer, 0, 1));
        }

@GwtIncompatible
public abstract class FeatureSpecificTestSuiteBuilder<
    B extends FeatureSpecificTestSuiteBuilder<B, G>, G> {
  @SuppressWarnings("unchecked")
  protected B self() {
    return (B) this;
  }

  // Test Data

  private @Nullable G subjectGenerator;
  // Gets run before every test.
  private Runnable setUp;
  // Gets run at the conclusion of every test.
  private Runnable tearDown;

  @CanIgnoreReturnValue

    throw new UnsupportedOperationException();
  }

  /**
   * {@inheritDoc}
   *
   * <p>This implementation of {@code getAllPresent} lacks any insight into the internal cache data
   * structure, and is thus forced to return the query keys instead of the cached keys. This is only
   * possible with an unsafe cast which requires {@code keys} to actually be of type {@code K}.
   *
   * @since 11.0
   */

    stream.writeObject(valueComparator());
    Serialization.writeMultimap(this, stream);
  }

  @GwtIncompatible // java.io.ObjectInputStream
  @J2ktIncompatible
  @SuppressWarnings("unchecked") // reading data stored by writeObject
  private void readObject(ObjectInputStream stream) throws IOException, ClassNotFoundException {
    stream.defaultReadObject();
    keyComparator = requireNonNull((Comparator<? super K>) stream.readObject());

import com.google.j2objc.annotations.WeakOuter;
import java.util.Map;
import javax.annotation.CheckForNull;
import org.checkerframework.checker.nullness.qual.Nullable;

/** A {@code RegularImmutableTable} optimized for dense data. */
@GwtCompatible
@Immutable(containerOf = {"R", "C", "V"})
@ElementTypesAreNonnullByDefault
final class DenseImmutableTable<R, C, V> extends RegularImmutableTable<R, C, V> {

// WithSharedResponse indicates it is unsafe to reuse the response
// when it has been returned on a handler.
// This will disable automatic response recycling/pooling.
// Typically this is used when the response sharing part of its data structure.
func (h *SingleHandler[Req, Resp]) WithSharedResponse() *SingleHandler[Req, Resp] {
	h.sharedResp = true
	return h
}

// NewResponse creates a new response.

Dies und die einfache Tatsache, dass Python die Hauptsprache für **Data Science**, maschinelles Lernen und insbesondere Deep Learning ist, machen FastAPI zu einem sehr passenden Werkzeug für Web-APIs und Anwendungen für Data Science / maschinelles Lernen (neben vielen anderen).