Table<Integer, String, Character> original = HashBasedTable.create();
    Table<String, Integer, Character> table = Tables.transpose(original);
    table.clear();
    populate(table, data);
    return table;
  }

  public void testTransposeTransposed() {
    Table<Integer, String, Character> original = HashBasedTable.create();

elif _tf_api_dir not in __path__:
  __path__.append(_tf_api_dir)

# Hook external TensorFlow modules.

# Load tensorflow-io-gcs-filesystem if enabled
if (_os.getenv("TF_USE_MODULAR_FILESYSTEM", "0") == "true" or
    _os.getenv("TF_USE_MODULAR_FILESYSTEM", "0") == "1"):
  import tensorflow_io_gcs_filesystem as _tensorflow_io_gcs_filesystem

# Lazy-load Keras v2/3.
_tf_uses_legacy_keras = (

          }
        };
    Map<String, Map<Integer, Character>> backingMap = Maps.newLinkedHashMap();
    Table<String, Integer, Character> table = Tables.newCustomTable(backingMap, factory);
    populate(table, data);
    return table;
  }

  public void testRowKeySetOrdering() {
    table = create("foo", 3, 'a', "bar", 1, 'b', "foo", 2, 'c');
    assertThat(table.rowKeySet()).containsExactly("foo", "bar").inOrder();

      boolean modifiable, boolean allowsNulls, boolean supportsIteratorRemove) {
    super(allowsNulls, allowsNulls, false, modifiable, modifiable, supportsIteratorRemove);
  }

  protected void populate(Multimap<String, Integer> multimap) {
    multimap.put("one", 1);
    multimap.put("two", 2);
    multimap.put("two", 22);
    multimap.put("three", 3);
    multimap.put("three", 33);
    multimap.put("three", 333);

## Tasarım

Sonrasında, (**FastAPI** kullanan bir geliştirici olarak) sahip olmak istediğim "API"ı tasarlamak için biraz zaman harcadım.

Çeşitli fikirleri en popüler Python editörlerinde test ettim: PyCharm, VS Code, Jedi tabanlı editörler.

# lazy loading.
_current_module.compat.v2  # pylint: disable=pointless-statement

# Load tensorflow-io-gcs-filesystem if enabled
if (_os.getenv("TF_USE_MODULAR_FILESYSTEM", "0") == "true" or
    _os.getenv("TF_USE_MODULAR_FILESYSTEM", "0") == "1"):
  import tensorflow_io_gcs_filesystem as _tensorflow_io_gcs_filesystem

# Lazy-load Keras v1.
_tf_uses_legacy_keras = (

    Table<Integer, String, Character> original = HashBasedTable.create();
    Table<String, Integer, Character> table = Tables.transpose(original);
    table.clear();
    populate(table, data);
    return table;
  }

  public void testTransposeTransposed() {
    Table<Integer, String, Character> original = HashBasedTable.create();

    TestTable<String, Integer, Character> table = new TestTable<>();
    Table<String, Integer, Character> synced = Synchronized.table(table, table.mutex);
    populate(synced, data);
    return synced;
  }

import java.util.concurrent.BlockingQueue
import java.util.concurrent.LinkedBlockingQueue
import java.util.logging.Logger
import okhttp3.ExperimentalOkHttpApi

/**
 * Default dispatcher that processes a script of responses. Populate the script by calling [enqueueResponse].
 */
@ExperimentalOkHttpApi
open class QueueDispatcher : Dispatcher() {
  protected val responseQueue: BlockingQueue<MockResponse> = LinkedBlockingQueue()

    List<@Nullable Present<V>> values =
        futures.isEmpty()
            ? Collections.<@Nullable Present<V>>emptyList()
            : Lists.<@Nullable Present<V>>newArrayListWithCapacity(futures.size());

    // Populate the results list with null initially.
    for (int i = 0; i < futures.size(); ++i) {
      values.add(null);
    }

    this.values = values;
  }

  @Override