async def _compute_result(self) -> Dict[str, Any]:
# set filter for contextualized logging
execution_context_filter.bind_context(
currently_executed_instance_id=self.operator_hierarchical_id,
currently_executed_component_id=self.component_id,
currently_executed_component_node_name=self.operator_name,
)
logger.info(
"Starting computation for operator %s of type component with operator id %s",
self.operator_name,
self.operator_hierarchical_id,
)
self._in_computation = True
self._check_inputs()
# Gather data from input sources (detects cycles):
input_values = await self._gather_data_from_inputs()
# Actual execution of current node
function_result = await self._run_comp_func(input_values)
# cleanup
self._in_computation = False
execution_context_filter.clear_context()
return function_result
async def execute_transformation_revision(
exec_by_id_input: ExecByIdInput, ) -> ExecutionResponseFrontendDto:
"""Execute transformation revision
raises subtypes of TrafoExecutionError on errors.
"""
execution_context_filter.bind_context(job_id=exec_by_id_input.job_id)
execution_input = prepare_execution_input(exec_by_id_input)
return await run_execution_input(execution_input)
async def result(self) -> Dict[str, Any]:
self._wire_workflow_inputs()
execution_context_filter.bind_context(
currently_executed_instance_id=self.operator_hierarchical_id,
currently_executed_component_id=None,
currently_executed_component_node_name=self.
operator_hierarchical_name,
)
logger.info(
"Starting computation for operator %s of type workflow with operator id %s",
self.operator_hierarchical_name,
self.operator_hierarchical_id,
)
# gather result from workflow operators
results = {}
exe_context_config = execution_context.get()
for (
wf_output_name,
(
sub_node,
sub_node_output_name,
),
) in self.output_mappings.items():
try:
results[wf_output_name] = (
(await sub_node.result)[sub_node_output_name]
if not (sub_node.has_only_plot_outputs
and not exe_context_config.run_pure_plot_operators)
else {})
except KeyError as e:
# possibly an output_name missing in the result dict of one of the providing nodes!
logger.info(
"Execution failed due to missing output of a node",
exc_info=True,
)
raise MissingOutputException(
"Could not obtain output result from another node while preparing to "
"run operator").set_context(
operator_hierarchical_id=self.operator_hierarchical_id,
operator_hierarchical_name="workflow",
) from e
# cleanup
execution_context_filter.clear_context()
return results