def create_execution_metadata(graphql_execution_metadata):
return (ExecutionMetadata(
graphql_execution_metadata.get('runId'),
{
t['key']: t['value']
for t in graphql_execution_metadata.get('tags', [])
},
) if graphql_execution_metadata else ExecutionMetadata(run_id=None,
tags={}))
def create_execution_params(graphene_info, graphql_execution_params):
preset_name = graphql_execution_params.get('preset')
if preset_name:
check.invariant(
not graphql_execution_params.get('environmentConfigData'),
'Invalid ExecutionParams. Cannot define environment_dict when using preset',
)
check.invariant(
not graphql_execution_params.get('mode'),
'Invalid ExecutionParams. Cannot define mode when using preset',
)
selector = graphql_execution_params['selector'].to_selector()
check.invariant(
not selector.solid_subset,
'Invalid ExecutionParams. Cannot define selector.solid_subset when using preset',
)
dauphin_pipeline = get_dauphin_pipeline_reference_from_selector(graphene_info, selector)
pipeline = dauphin_pipeline.get_dagster_pipeline()
if not pipeline.has_preset(preset_name):
raise UserFacingGraphQLError(
graphene_info.schema.type_named('PresetNotFoundError')(
preset=preset_name, selector=selector
)
)
preset = pipeline.get_preset(preset_name)
return ExecutionParams(
selector=ExecutionSelector(selector.name, preset.solid_subset),
environment_dict=preset.environment_dict,
mode=preset.mode,
execution_metadata=ExecutionMetadata(run_id=None, tags={}),
step_keys=graphql_execution_params.get('stepKeys'),
)
return ExecutionParams(
selector=graphql_execution_params['selector'].to_selector(),
environment_dict=graphql_execution_params.get('environmentConfigData'),
mode=graphql_execution_params.get('mode'),
execution_metadata=create_execution_metadata(
graphql_execution_params.get('executionMetadata')
),
step_keys=graphql_execution_params.get('stepKeys'),
)