import org.apache.maven.artifact.repository.ArtifactRepository;

/**
 * A simple recording of the Artifacts that could not be resolved for a given resolution request, along with
 * the remote repositories where attempts were made to resolve the artifacts.
 *
 */
@Deprecated
public class UnresolvedArtifacts {
    private Artifact originatingArtifact;

    private List<Artifact> artifacts;

                + replacement.getVersionRange() + " to: " + newRange + " )");
    }

    /**
     * The logic used here used to be a copy of the logic used in the DefaultArtifactCollector, and this method was
     * called right before the actual version/artifactScope changes were done. However, a different set of conditionals

| `minio_notify_events_sent_total`               | Total number of events sent to the targets (deprecated, please use `minio_notify_target_total_events` instead)                              |

In the previous example, because the classes were different, we had to use the `response_model` parameter. But that also means that we don't get the support from the editor and tools checking the function return type.

But in most of the cases where we need to do something like this, we want the model just to **filter/remove** some of the data as in this example.

			if err != nil {
				continue
			}
			files = append(files, file{header: &f.FileHeader, content: content})
			if _, err := r.Open(f.Name); err != nil {
				continue
			}
		}

		// If we were unable to read anything out of the archive don't
		// bother trying to roundtrip it.
		if len(files) == 0 {
			return
		}

		w := NewWriter(io.Discard)
		for _, f := range files {

import java.util.ArrayList;
import java.util.List;

/**
 * The NormalizerChain class implements the Normalizer interface and allows chaining multiple normalizers together.
 * It applies each normalizer in the order they were added to the chain.
 *
 * <p>Usage example:</p>
 * <pre>
 * NormalizerChain chain = new NormalizerChain();
 * chain.add(new SomeNormalizer());
 * chain.add(new AnotherNormalizer());

     * track the problem back to its origin. A concrete example for such a source hint can be the file path or URL from
     * which the settings were read.
     *
     * @return the hint about the source of the problem or an empty string if unknown, never {@code null}
     */
    @Nonnull
    String getSource();

    /**

* Then it returns the **response**.

/// note | Technical Details

If you have dependencies with `yield`, the exit code will run *after* the middleware.

If there were any background tasks (covered in the [Background Tasks](background-tasks.md){.internal-link target=_blank} section, you will see it later), they will run *after* all the middleware.

///

Let's create a dependency `get_current_user`.

Remember that dependencies can have sub-dependencies?

`get_current_user` will have a dependency with the same `oauth2_scheme` we created before.

The same as we were doing before in the *path operation* directly, our new dependency `get_current_user` will receive a `token` as a `str` from the sub-dependency `oauth2_scheme`:

{* ../../docs_src/security/tutorial002_an_py310.py hl[25] *}

## Reporting vulnerabilities

### Vulnerabilities in TensorFlow

This document covers different use cases for TensorFlow together with comments
whether these uses were recommended or considered safe, or where we recommend
some form of isolation when dealing with untrusted data. As a result, this
document also outlines what issues we consider as TensorFlow security
vulnerabilities.