object := gcs.client.Bucket(gcs.Bucket).Object(gcs.getDest(key)).ReadCompressed(true)

	r, err = object.NewRangeReader(ctx, opts.startOffset, opts.length)
	if err != nil {
		return nil, gcsToObjectError(err, gcs.Bucket, key)
	}
	return r, nil
}

func (gcs *warmBackendGCS) Remove(ctx context.Context, key string, rv remoteVersionID) error {
	err := gcs.client.Bucket(gcs.Bucket).Object(gcs.getDest(key)).Delete(ctx)

import com.google.cloud.storage.StorageOptions;

/**
 * Handler for the "gcs" protocol, allowing access to objects stored in Google Cloud Storage.
 * This handler extends {@link URLStreamHandler} to provide a way to open connections to GCS objects
 * using URLs with the "gcs" protocol.
 *
 * <p>
 * The URL format is expected to be: {@code gcs://bucketName/objectName}.
 * The bucket name and object name are extracted from the URL.

            return StorageType.S3;
        }

        final String lowerEndpoint = endpoint.toLowerCase(Locale.ROOT);

        // GCS patterns
        if (lowerEndpoint.contains("storage.googleapis.com") || lowerEndpoint.contains(".storage.cloud.google.com")) {
            return StorageType.GCS;
        }

        // S3 patterns

	switch tier.Type {
	case madmin.S3:
		d, err = newWarmBackendS3(*tier.S3, tier.Name)
	case madmin.Azure:
		d, err = newWarmBackendAzure(*tier.Azure, tier.Name)
	case madmin.GCS:
		d, err = newWarmBackendGCS(*tier.GCS, tier.Name)
	case madmin.MinIO:
		d, err = newWarmBackendMinIO(*tier.MinIO, tier.Name)
	default:
		return nil, errTierTypeUnsupported
	}
	if err != nil {
		tierLogIf(ctx, err)

        applyRule<DependencyRemovalByNameRule>(libs.samplesCheck, setOf("slf4j-simple"))

        // GCS transitively depends on commons-logging.
        // Ensure jcl-over-slf4j is pulled in when we use GCS so it can conflict.
        applyRule<DependencyAdditionRule>(libs.gcs, libs.jclToSlf4j)

        // asciidoctorj depends on a lot of stuff, which causes `Can't create process, argument list too long` on Windows

		class="org.codelibs.fess.crawler.client.s3.S3Client" instance="prototype">
		<property name="charset">"UTF-8"</property>
	</component>

	<component name="gcsClient"
		class="org.codelibs.fess.crawler.client.gcs.GcsClient" instance="prototype">
		<property name="charset">"UTF-8"</property>
	</component>

	<component name="crawlerClientCreator"
		class="org.codelibs.fess.crawler.client.CrawlerClientCreator">
	</component>

scipy >= 1.13.0, < 1.15.0
requests >= 2.31.0
packaging==23.2
setuptools==78.1.1
jax==0.4.7
zstandard==0.23.0
# The dependencies below are needed for TF wheel testing.
tensorflow-io-gcs-filesystem==0.37.1 ; python_version <= "3.12"
libclang >= 13.0.0
google_pasta ~= 0.2

 */
package org.codelibs.fess.storage;

/**
 * Enum for supported storage types.
 */
public enum StorageType {

    /** Amazon S3 */
    S3,

    /** Google Cloud Storage */
    GCS,

    /** S3-compatible storage (MinIO, etc.) */
    S3_COMPAT

# ==============================================================================
# Release jobs are very basic. They don't use any caching or RBE,
# but they do upload logs to resultstore.
# IMPORTANT: trailing slash is required on GCS URIs, as it tells gcloud to
# pretend the path is a directory.
TFCI_ARTIFACT_FINAL_GCS_ENABLE=1
TFCI_ARTIFACT_FINAL_GCS_SA_PATH="${KOKORO_KEYSTORE_DIR}/73361_tensorflow_release_binary_uploader_service_account"

# limitations under the License.
# ==============================================================================
# This script uploads all staged artifacts from all previous builds in the same
# job chain to GCS and PyPI.
source "${BASH_SOURCE%/*}/utilities/setup.sh"

# Calculate the version number for choosing the final directory name. This adds
# "-devYYYYMMDD" to the end of the version string for nightly builds.