Collection<Entry<K, V>> entries = getSampleEntries(getNumEntries() - 1);
    entries.add(entry(null, v3()));
    Map<K, V> other = newHashMap(entries);

    assertFalse(
        "Two Maps should not be equal if exactly one of them contains a null key.",
        getMap().equals(other));
  }

  @CollectionSize.Require(absent = CollectionSize.ZERO)
  @MapFeature.Require(ALLOWS_NULL_VALUES)
  public void testEquals_containingNullValue() {

    int initialSize = collection.size();
    assertTrue("remove(present) should return true", collection.remove(e0()));
    assertEquals(
        "remove(present) should decrease a collection's size by one.",
        initialSize - 1,
        collection.size());
    expectMissing(e0());
  }

  @CollectionFeature.Require({SUPPORTS_REMOVE, FAILS_FAST_ON_CONCURRENT_MODIFICATION})
  @CollectionSize.Require(SEVERAL)

   * non-nullable {@code cause}, as many users expect to find one.
   */
  public UncheckedExecutionException(@Nullable String message, @Nullable Throwable cause) {
    super(message, cause);
  }

  /**
   * Creates a new instance with {@code null} as its detail message and the given cause. Prefer to
   * provide a non-nullable {@code cause}, as many users expect to find one.
   */

 * {@snippet :
 * public <N> someGraphAlgorithm(N startNode, SuccessorsFunction<N> successorsFunction);
 * }
 *
 * you will invoke it depending on the graph representation you're using.
 *
 * <p>If you have an instance of one of the primary {@code common.graph} types ({@link Graph},
 * {@link ValueGraph}, and {@link Network}):
 *
 * {@snippet :
 * someGraphAlgorithm(startNode, graph);
 * }
 *

## Use the dependency { #use-the-dependency }

Then we can use the dependency with:

{* ../../docs_src/dependencies/tutorial005_an_py310.py hl[23] *}

/// info

Notice that we are only declaring one dependency in the *path operation function*, the `query_or_cookie_extractor`.

But **FastAPI** will know that it has to solve `query_extractor` first, to pass the results of that to `query_or_cookie_extractor` while calling it.

//   like shadowing a numpy array.
// * We do not provide TF_OK since it is not strictly necessary and we
//   are not optimizing for convenience.
// * We make assumption that one session has one graph.  This should be
//   fine since we have the ability to run sub-graphs.
// * We could allow NULL for some arguments (e.g., NULL options arg).
//   However since convenience is not a primary goal, we don't do this.

Let's imagine that you have some **machine learning models** that you want to use to handle requests. 🤖

The same models are shared among requests, so, it's not one model per request, or one per user or something similar.

Let's imagine that loading the model can **take quite some time**, because it has to read a lot of **data from disk**. So you don't want to do it for every request.

                  }
                }
                return MinimalCollection.of(elements);
              }
            })
        .named("MinimalCollection")
        .withFeatures(CollectionFeature.NONE, CollectionSize.ANY)
        .createTestSuite();
  }

import java.io.IOException;
import java.io.InputStream;
import java.util.Iterator;
import org.jspecify.annotations.Nullable;

/**
 * An {@link InputStream} that concatenates multiple substreams. At most one stream will be open at
 * a time.
 *
 * @author Chris Nokleberg
 * @since 1.0
 */
@J2ktIncompatible
@GwtIncompatible
final class MultiInputStream extends InputStream {

    return new SampleElements<>(
        mapEntry("one", "January"),
        mapEntry("two", "February"),
        mapEntry("three", "March"),
        mapEntry("four", "April"),
        mapEntry("five", "May"));
  }

  @Override
  public SampleElements<String> sampleKeys() {
    return new SampleElements<>("one", "two", "three", "four", "five");
  }

  @Override