def test_run_job(self): # Setup Expected Response name_2 = "name2-1052831874" description = "description-1724546052" schedule = "schedule-697920873" time_zone = "timeZone36848094" expected_response = { "name": name_2, "description": description, "schedule": schedule, "time_zone": time_zone, } expected_response = job_pb2.Job(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = scheduler_v1beta1.CloudSchedulerClient() # Setup Request name = client.job_path("[PROJECT]", "[LOCATION]", "[JOB]") response = client.run_job(name) assert expected_response == response assert len(channel.requests) == 1 expected_request = cloudscheduler_pb2.RunJobRequest(name=name) actual_request = channel.requests[0][1] assert expected_request == actual_request
def test_run_job(self): # Setup Expected Response name_2 = 'name2-1052831874' description = 'description-1724546052' schedule = 'schedule-697920873' time_zone = 'timeZone36848094' expected_response = { 'name': name_2, 'description': description, 'schedule': schedule, 'time_zone': time_zone } expected_response = job_pb2.Job(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) client = scheduler_v1beta1.CloudSchedulerClient(channel=channel) # Setup Request name = client.job_path('[PROJECT]', '[LOCATION]', '[JOB]') response = client.run_job(name) assert expected_response == response assert len(channel.requests) == 1 expected_request = cloudscheduler_pb2.RunJobRequest(name=name) actual_request = channel.requests[0][1] assert expected_request == actual_request
def run_job(self, name, retry=google.api_core.gapic_v1.method.DEFAULT, timeout=google.api_core.gapic_v1.method.DEFAULT, metadata=None): """ Forces a job to run now. When this method is called, Cloud Scheduler will dispatch the job, even if the job is already running. Example: >>> from google.cloud import scheduler_v1beta1 >>> >>> client = scheduler_v1beta1.CloudSchedulerClient() >>> >>> name = client.job_path('[PROJECT]', '[LOCATION]', '[JOB]') >>> >>> response = client.run_job(name) Args: name (str): Required. The job name. For example: ``projects/PROJECT_ID/locations/LOCATION_ID/jobs/JOB_ID``. retry (Optional[google.api_core.retry.Retry]): A retry object used to retry requests. If ``None`` is specified, requests will not be retried. timeout (Optional[float]): The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata that is provided to the method. Returns: A :class:`~google.cloud.scheduler_v1beta1.types.Job` instance. Raises: google.api_core.exceptions.GoogleAPICallError: If the request failed for any reason. google.api_core.exceptions.RetryError: If the request failed due to a retryable error and retry attempts failed. ValueError: If the parameters are invalid. """ # Wrap the transport method to add retry and timeout logic. if 'run_job' not in self._inner_api_calls: self._inner_api_calls[ 'run_job'] = google.api_core.gapic_v1.method.wrap_method( self.transport.run_job, default_retry=self._method_configs['RunJob'].retry, default_timeout=self._method_configs['RunJob'].timeout, client_info=self._client_info, ) request = cloudscheduler_pb2.RunJobRequest(name=name, ) return self._inner_api_calls['run_job'](request, retry=retry, timeout=timeout, metadata=metadata)