* Used for audit trail purposes to track who made changes.
     */
    @Size(max = 1000)
    public String updatedBy;

    /**
     * The timestamp when this elevate word configuration was last updated.
     * Stored as a long value representing milliseconds since epoch.
     * Used for audit trail and concurrency control.
     */
    @ValidateTypeFailure

     * Used for audit trail purposes to track who made changes.
     */
    @Size(max = 1000)
    public String updatedBy;

    /**
     * The timestamp when this request header configuration was last updated.
     * Stored as a long value representing milliseconds since epoch.
     * Used for audit trail and concurrency control.
     */
    @ValidateTypeFailure

fi

if [[ $(uname -s) != MSYS_NT* ]]; then
  tfrun bazel $TFCI_BAZEL_BAZELRC_ARGS test $TFCI_BAZEL_COMMON_ARGS --config=linux_libtensorflow_test
  tfrun bazel $TFCI_BAZEL_BAZELRC_ARGS build $TFCI_BAZEL_COMMON_ARGS --config=linux_libtensorflow_build
else
  tfrun bazel $TFCI_BAZEL_BAZELRC_ARGS build $TFCI_BAZEL_COMMON_ARGS --config=windows_libtensorflow_build
fi

#                                           ^^^^
# This env is only valid when RBE is available on the selected platform, since
# it enables a derived --config setting.  If RBE is not available (i.e. there
# is no --config setting), bazel would fail and quit. This script does a quick
# check This script checks for such errors early
if ! grep "rbe_$TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX" .bazelrc; then
  cat <<EOF

# ==============================================================================

set -exo pipefail

function resultstore_extract_fallback {
  # In case the main script fails somehow.
  cat <<EOF
IMPORTANT: For bazel invocations that uploaded to ResultStore (e.g. RBE), you
can view more detailed results that are probably easier to read than this log.
Try the links below:
EOF
  # Find any "Streaming build results to" lines,

#   destroys some temporary bazel data and causes longer builds.
#
#   You will need the NVIDIA Container Toolkit for GPU testing:
#   https://github.com/NVIDIA/nvidia-container-toolkit
#
#   Note: if you interrupt a bazel command on docker (ctrl-c), you
#   will need to run `docker exec tf pkill bazel` to quit bazel.
#
#   Note: new files created from the container are owned by "root".

     * Used for audit trail purposes to track who made changes.
     */
    @Size(max = 1000)
    public String updatedBy;

    /**
     * The timestamp when this duplicate host configuration was last updated.
     * Stored as a long value representing milliseconds since epoch.
     * Used for audit trail and concurrency control.
     */
    @ValidateTypeFailure

# limitations under the License.
# ==============================================================================
# any.sh has two run modes.
#
# 1. RUN, TEST, OR BUILD BAZEL TARGET(S) WITHIN A TFCI ENVIRONMENT
#    To use:
#       export TFCI=ci/official/envs/env_goes_here
#       export TF_ANY_TARGETS="quoted list of targets, like on the command line"

if [[ "$TFCI_INDEX_HTML_ENABLE" == 1 ]]; then
  ./ci/official/utilities/generate_index_html.sh "$TFCI_OUTPUT_DIR/index.html"
fi

# Re-try `bazel --version` multiple times to get around
# Bazel download issues.
set +e
MAX_RETRIES=2
for ((i=1; i <= $MAX_RETRIES; i++)); do
  tfrun bazel --version
done
set -e

# Single handler for all cleanup actions, triggered on an EXIT trap.

* Tecniche più avanzate (ma ugualmente semplici) per dichiarare **modelli JSON altamente nidificati** (grazie a Pydantic).
* E altre funzionalità (grazie a Starlette) come:
    * **WebSockets**
    * **GraphQL**
    * test molto facili basati su `requests` e `pytest`
    * **CORS**
    * **Cookie Sessions**
    * ...e altro ancora.