## Managing hermetic Python

To make sure that TensorFlow's build is reproducible, behaves uniformly across
supported platforms (Linux, Windows, MacOS) and is properly isolated from
specifics of a local system, we rely on hermetic Python (see
[rules_python](https://github.com/bazelbuild/rules_python)) for all build
and test commands executed via Bazel. This means that your system Python
installation will be ignored during the build and Python interpreter itself

    }

    @Override
    public boolean equals(@CheckForNull Object object) {
      if (object instanceof StringConverter) {
        StringConverter that = (StringConverter) object;
        return sourceFormat.equals(that.sourceFormat) && targetFormat.equals(that.targetFormat);
      }
      return false;
    }

    @Override
    public int hashCode() {

     * @return
     */
    public Lifecycle get(String phase) {
        return getPhaseToLifecycleMap().get(phase);
    }

    /**
     * We use this to map all phases to the lifecycle that contains it. This is used so that a user can specify the
     * phase they want to execute and we can easily determine what lifecycle we need to run.
     *
     * @return A map of lifecycles, indexed on id
     */

	// since the `objectLayer==nil`  check is performed before any other checks inside the handlers.
	// The only aim is to generate an HTTP request in a way that the relevant/registered end point is evoked/called.
	// Indicating that all parts are uploaded and initiating completeMultipartUpload.
	nilBucket := "dummy-bucket"
	nilObject := ""

       Best practice is to use the JIRA issue title in both the pull request title and in the first line of the commit message.
 - [ ] Write a pull request description that is detailed enough to understand what the pull request does, how, and why.
 - [ ] Run `mvn clean verify` to make sure basic checks pass. A more thorough check will
       be performed on your pull request automatically.

import com.google.common.annotations.GwtCompatible;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.Future;
import java.util.concurrent.TimeoutException;

/** Methods factored out so that they can be emulated differently in GWT. */
@GwtCompatible(emulated = true)
final class TestPlatform {
  static void verifyGetOnPendingFuture(Future<?> future) {
    checkNotNull(future);
    try {

     *
     * @return The decrypted proxy, can be empty but never {@code null}.
     */
    List<Proxy> getProxies();

    /**
     * Gets the problems that were encountered during the settings decryption.
     *
     * @return The problems that were encountered during the decryption, can be empty but never {@code null}.
     */
    List<SettingsProblem> getProblems();

        a_uuid: MyUuid

        @field_serializer("a_uuid")
        def serialize_a_uuid(self, v):
            return str(v)

    @app.get("/get_custom_class")
    def return_some_user():
        # Test that the fix also works for custom pydantic classes
        return SomeCustomClass(a_uuid=MyUuid("b8799909-f914-42de-91bc-95c819218d01"))

    client = TestClient(app)

    with client:

#       ...
#       ./any.sh
#     or
#       export TF_ANY_EXTRA_ENV=ci/official/envs/local_rbe
#       ./any.sh
#       ...
set -euxo pipefail
cd "$(dirname "$0")/../../"  # tensorflow/
# Any request that includes "nightly_upload" should just use the
# local multi-cache (public read-only cache + disk cache) instead.
export TFCI="$(echo $TFCI | sed 's/,nightly_upload/,public_cache,disk_cache/')"
if [[ -n "${TF_ANY_EXTRA_ENV:-}" ]]; then

        change.changes == ["Interface has been removed"]
        acceptedChange.value == "@Incubating interface has been removed"
    }

    def "parses more than one change"() {
        when:
        def changes = AcceptedApiChanges.parse(["""
            {
                "acceptedApiChanges": [
                    {