Python exceptions.GoogleCloudError方法代碼示例

# 需要導入模塊: from google.cloud import exceptions [as 別名]
# 或者: from google.cloud.exceptions import GoogleCloudError [as 別名]
def cost_usage_source_is_reachable(self, credential_name, data_source):
        """
        Verify that the GCP bucket exists and is reachable.

        Args:
            credential_name (object): not used; only present for interface compatibility
            data_source (dict): dict containing name of GCP storage bucket

        """
        storage_client = storage.Client()
        bucket = data_source["bucket"]
        try:
            bucket_info = storage_client.lookup_bucket(bucket)
            if not bucket_info:
                # if the lookup does not return anything, then this is an nonexistent bucket
                key = "billing_source.bucket"
                message = f"The provided GCP bucket {bucket} does not exist"
                raise serializers.ValidationError(error_obj(key, message))

        except GoogleCloudError as e:
            key = "billing_source.bucket"
            raise serializers.ValidationError(error_obj(key, e.message))

        return True 

# 需要導入模塊: from google.cloud import exceptions [as 別名]
# 或者: from google.cloud.exceptions import GoogleCloudError [as 別名]
def wait_for_operation(self, operation: Operation, project_id: Optional[str] = None) -> Operation:
        """
        Given an operation, continuously fetches the status from Google Cloud until either
        completion or an error occurring

        :param operation: The Operation to wait for
        :type operation: google.cloud.container_V1.gapic.enums.Operation
        :param project_id: Google Cloud Platform project ID
        :type project_id: str
        :return: A new, updated operation fetched from Google Cloud
        """
        self.log.info("Waiting for OPERATION_NAME %s", operation.name)
        time.sleep(OPERATIONAL_POLL_INTERVAL)
        while operation.status != Operation.Status.DONE:
            if operation.status == Operation.Status.RUNNING or operation.status == \
                    Operation.Status.PENDING:
                time.sleep(OPERATIONAL_POLL_INTERVAL)
            else:
                raise exceptions.GoogleCloudError(
                    "Operation has failed with status: %s" % operation.status)
            # To update status of operation
            operation = self.get_operation(operation.name, project_id=project_id or self.project_id)
        return operation 

# 需要導入模塊: from google.cloud import exceptions [as 別名]
# 或者: from google.cloud.exceptions import GoogleCloudError [as 別名]
def copy_to(self, source_path):
    if os.path.getsize(source_path) == 0:
      message = (
          'Local source file {0:s} is empty.  Not uploading to GCS'.format(
              source_path))
      log.error(message)
      raise TurbiniaException(message)

    bucket = self.client.get_bucket(self.bucket)
    destination_path = os.path.join(
        self.base_output_dir, self.unique_dir, os.path.basename(source_path))
    log.info(
        'Writing {0:s} to GCS path {1:s}'.format(source_path, destination_path))
    try:
      blob = storage.Blob(destination_path, bucket, chunk_size=self.CHUNK_SIZE)
      blob.upload_from_filename(source_path, client=self.client)
    except exceptions.GoogleCloudError as exception:
      message = 'File upload to GCS failed: {0!s}'.format(exception)
      log.error(message)
      raise TurbiniaException(message)
    return os.path.join('gs://', self.bucket, destination_path) 

# 需要導入模塊: from google.cloud import exceptions [as 別名]
# 或者: from google.cloud.exceptions import GoogleCloudError [as 別名]
def setup_stackdriver_handler(project_id):
  """Set up Google Cloud Stackdriver Logging

  The Google Cloud Logging library will attach itself as a
  handler to the default Python logging module.

  Attributes:
    project_id: The name of the Google Cloud project.
  Raises:
    TurbiniaException: When an error occurs enabling GCP Stackdriver Logging.
  """
  try:
    client = cloud_logging.Client(project=project_id)
    cloud_handler = cloud_logging.handlers.CloudLoggingHandler(client)
    logger = logging.getLogger('turbinia')
    logger.addHandler(cloud_handler)
  except exceptions.GoogleCloudError as exception:
    msg = 'Error enabling Stackdriver Logging: {0:s}'.format(str(exception))
    raise TurbiniaException(msg) 

# 需要導入模塊: from google.cloud import exceptions [as 別名]
# 或者: from google.cloud.exceptions import GoogleCloudError [as 別名]
def setup_stackdriver_traceback(project_id):
  """Set up Google Cloud Error Reporting

  This method will enable Google Cloud Error Reporting.
  All exceptions that occur within a Turbinia Task will be logged.

  Attributes:
    project_id: The name of the Google Cloud project.
  Raises:
    TurbiniaException: When an error occurs enabling GCP Error Reporting.
  """
  try:
    client = error_reporting.Client(project=project_id)
  except exceptions.GoogleCloudError as exception:
    msg = 'Error enabling GCP Error Reporting: {0:s}'.format(str(exception))
    raise TurbiniaException(msg)
  return client 

# 需要導入模塊: from google.cloud import exceptions [as 別名]
# 或者: from google.cloud.exceptions import GoogleCloudError [as 別名]
def _error_result_to_exception(error_result):
    """Maps BigQuery error reasons to an exception.

    The reasons and their matching HTTP status codes are documented on
    the `troubleshooting errors`_ page.

    .. _troubleshooting errors: https://cloud.google.com/bigquery\
        /troubleshooting-errors

    Args:
        error_result (Mapping[str, str]): The error result from BigQuery.

    Returns:
        google.cloud.exceptions.GoogleCloudError: The mapped exception.
    """
    reason = error_result.get("reason")
    status_code = _ERROR_REASON_TO_EXCEPTION.get(
        reason, http_client.INTERNAL_SERVER_ERROR
    )
    return exceptions.from_http_status(
        status_code, error_result.get("message", ""), errors=[error_result]
    ) 

# 需要導入模塊: from google.cloud import exceptions [as 別名]
# 或者: from google.cloud.exceptions import GoogleCloudError [as 別名]
def result(self, retry=DEFAULT_RETRY, timeout=None):
        """Start the job and wait for it to complete and get the result.

        Args:
            retry (Optional[google.api_core.retry.Retry]): How to retry the RPC.
            timeout (Optional[float]):
                The number of seconds to wait for the underlying HTTP transport
                before using ``retry``.
                If multiple requests are made under the hood, ``timeout``
                applies to each individual request.

        Returns:
            _AsyncJob: This instance.

        Raises:
            google.cloud.exceptions.GoogleCloudError:
                if the job failed.
            concurrent.futures.TimeoutError:
                if the job did not complete in the given timeout.
        """
        if self.state is None:
            self._begin(retry=retry, timeout=timeout)
        # TODO: modify PollingFuture so it can pass a retry argument to done().
        return super(_AsyncJob, self).result(timeout=timeout) 

# 需要導入模塊: from google.cloud import exceptions [as 別名]
# 或者: from google.cloud.exceptions import GoogleCloudError [as 別名]
def _create_temp_table(self, timestamp, total_lines):
        """Save in a temporary table the data in the source table shuffled."""
        _, temp_table_uri = self._build_destination_table(timestamp, TEMP_TABLE_SUFFIX)
        try:
            logging.info('Creating temporary table %s', temp_table_uri)
            query = queries.QUERY_TEMP_DATA_TEMPLATE.format(
                temp_table=temp_table_uri,
                feature_columns=self._columns,
                target_columns_shuffle=self._target_columns_shuffle,
                source_table=self._source_table_uri,
                total_lines=total_lines)
            self._bq_client.run_query(query)
            return temp_table_uri
        except GoogleCloudError as gcp_exception:
            raise exceptions.MLDataPrepException(
                'Could not create table {}'.format(temp_table_uri),
                ERR_CALCULATE_DATASET_SIZE,
                gcp_exception) 

# 需要導入模塊: from google.cloud import exceptions [as 別名]
# 或者: from google.cloud.exceptions import GoogleCloudError [as 別名]
def test_no_bucket_exists_exception(self, mock_storage):
        """Test that ValidationError is raised when GoogleCloudError is raised."""
        gcp_client = mock_storage.return_value
        gcp_client.lookup_bucket.return_value = None

        credentials = {"project_id": FAKE.word()}
        storage_resource_name = {"bucket": FAKE.word()}

        with self.assertRaises(ValidationError):
            GCPProvider().cost_usage_source_is_reachable(credentials, storage_resource_name) 

# 需要導入模塊: from google.cloud import exceptions [as 別名]
# 或者: from google.cloud.exceptions import GoogleCloudError [as 別名]
def test_bucket_access_exception(self, mock_storage):
        """Test that ValidationError is raised when GoogleCloudError is raised."""
        gcp_client = mock_storage.return_value
        gcp_client.lookup_bucket.side_effect = GoogleCloudError("GCP Error")
        credentials = {"project_id": FAKE.word()}
        storage_resource_name = {"bucket": FAKE.word()}
        with self.assertRaises(ValidationError):
            GCPProvider().cost_usage_source_is_reachable(credentials, storage_resource_name) 

# 需要導入模塊: from google.cloud import exceptions [as 別名]
# 或者: from google.cloud.exceptions import GoogleCloudError [as 別名]
def test_wait_for_response_exception(self, time_mock):
        from google.cloud.container_v1.gapic.enums import Operation
        from google.cloud.exceptions import GoogleCloudError

        mock_op = mock.Mock()
        mock_op.status = Operation.Status.ABORTING

        with self.assertRaises(GoogleCloudError):
            self.gke_hook.wait_for_operation(mock_op)
            self.assertEqual(time_mock.call_count, 1) 

# 需要導入模塊: from google.cloud import exceptions [as 別名]
# 或者: from google.cloud.exceptions import GoogleCloudError [as 別名]
def mark(*args, **kwargs):
    """Marks an entire test as eventually consistent and retries.

    Args:
        tries: The number of retries.
        exceptions: The exceptions on which it will retry. It can be
            single value or a tuple.
        wait_exponential_multiplier: The exponential multiplier in
            milliseconds.
        wait_exponential_max: The maximum wait before the next try in
            milliseconds.
    """
    __tracebackhide__ = True
    tries = kwargs.get('tries', STOP_MAX_ATTEMPT_NUMBER_DEFAULT)
    retry_exceptions = kwargs.get(
        'exceptions', (AssertionError, exceptions.GoogleCloudError))
    wait_exponential_multiplier = kwargs.get(
        'wait_exponential_multiplier', WAIT_EXPONENTIAL_MULTIPLIER_DEFAULT)
    wait_exponential_max = kwargs.get(
        'wait_exponential_max', WAIT_EXPONENTIAL_MAX_DEFAULT)
    # support both `@mark` and `@mark()` syntax
    if len(args) == 1 and callable(args[0]):
        return retry(
            wait_exponential_multiplier=wait_exponential_multiplier,
            wait_exponential_max=wait_exponential_max,
            stop_max_attempt_number=tries,
            retry_on_exception=_retry_on_exception(retry_exceptions))(args[0])

    # `mark()` syntax
    def inner(f):
        __tracebackhide__ = True
        return retry(
            wait_exponential_multiplier=wait_exponential_multiplier,
            wait_exponential_max=wait_exponential_max,
            stop_max_attempt_number=tries,
            retry_on_exception=_retry_on_exception(retry_exceptions))(f)
    return inner 

# 需要導入模塊: from google.cloud import exceptions [as 別名]
# 或者: from google.cloud.exceptions import GoogleCloudError [as 別名]
def client_library_errors(e, *args):
    """Used by mark_flaky to retry on remote service errors."""
    exception_class, exception_instance, traceback = e

    return isinstance(
        exception_instance,
        (GoogleCloudError,)) 

# 需要導入模塊: from google.cloud import exceptions [as 別名]
# 或者: from google.cloud.exceptions import GoogleCloudError [as 別名]
def update_task(self, task):
    task.touch()
    try:
      with self.client.transaction():
        entity = self.client.get(task.state_key)
        if not entity:
          self.write_new_task(task)
          return
        entity.update(self.get_task_dict(task))
        log.debug('Updating Task {0:s} in Datastore'.format(task.name))
        self.client.put(entity)
    except exceptions.GoogleCloudError as e:
      log.error(
          'Failed to update task {0:s} in datastore: {1!s}'.format(
              task.name, e)) 

# 需要導入模塊: from google.cloud import exceptions [as 別名]
# 或者: from google.cloud.exceptions import GoogleCloudError [as 別名]
def write_new_task(self, task):
    key = self.client.key('TurbiniaTask', task.id)
    try:
      entity = datastore.Entity(key)
      entity.update(self.get_task_dict(task))
      log.info('Writing new task {0:s} into Datastore'.format(task.name))
      self.client.put(entity)
      task.state_key = key
    except exceptions.GoogleCloudError as e:
      log.error(
          'Failed to update task {0:s} in datastore: {1!s}'.format(
              task.name, e))
    return key