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'), previous_run_id=graphql_execution_params.get('retryRunId'), ) 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'), previous_run_id=graphql_execution_params.get('retryRunId'), )
def create_execution_params(graphql_execution_params): return ExecutionParams( selector=graphql_execution_params['selector'].to_selector(), environment_dict=graphql_execution_params.get('environmentConfigData'), mode=graphql_execution_params['mode'], execution_metadata=create_execution_metadata( graphql_execution_params.get('executionMetadata')), step_keys=graphql_execution_params.get('stepKeys'), )
def execution_params_from_graphql(context, graphql_execution_params): return ExecutionParams( selector=pipeline_selector_from_graphql( context, graphql_execution_params.get('selector')), run_config=graphql_execution_params.get('runConfigData') or {}, mode=graphql_execution_params.get('mode'), execution_metadata=create_execution_metadata( graphql_execution_params.get('executionMetadata')), step_keys=graphql_execution_params.get('stepKeys'), )
def execution_params_from_graphql(context, graphql_execution_params): return ExecutionParams( selector=pipeline_selector_from_graphql( context, graphql_execution_params.get("selector")), run_config=graphql_execution_params.get("runConfigData") or {}, mode=graphql_execution_params.get("mode"), execution_metadata=create_execution_metadata( graphql_execution_params.get("executionMetadata")), step_keys=graphql_execution_params.get("stepKeys"), )
def execution_params_from_graphql(context, graphql_execution_params): return ExecutionParams( selector=PipelineSelector.from_graphql_input( context, graphql_execution_params.get('selector')), environment_dict=graphql_execution_params.get('runConfigData') or {}, mode=graphql_execution_params.get('mode'), execution_metadata=create_execution_metadata( graphql_execution_params.get('executionMetadata')), step_keys=graphql_execution_params.get('stepKeys'), )
def execution_params_from_graphql(graphql_execution_params): return ExecutionParams( selector=ExecutionSelector.from_dict( graphql_execution_params.get('selector')), environment_dict=graphql_execution_params.get('environmentConfigData') or {}, mode=graphql_execution_params.get('mode'), execution_metadata=create_execution_metadata( graphql_execution_params.get('executionMetadata')), step_keys=graphql_execution_params.get('stepKeys'), )
def create_execution_params(graphene_info, graphql_execution_params): preset_name = graphql_execution_params.get('preset') selector = pipeline_selector_from_graphql( graphene_info.context, graphql_execution_params['selector'] ) if preset_name: if graphql_execution_params.get('runConfigData'): raise UserFacingGraphQLError( graphene_info.schema.type_named('ConflictingExecutionParamsError')( conflicting_param='runConfigData' ) ) if graphql_execution_params.get('mode'): raise UserFacingGraphQLError( graphene_info.schema.type_named('ConflictingExecutionParamsError')( conflicting_param='mode' ) ) if selector.solid_selection: raise UserFacingGraphQLError( graphene_info.schema.type_named('ConflictingExecutionParamsError')( conflicting_param='selector.solid_selection' ) ) external_pipeline = get_full_external_pipeline_or_raise(graphene_info, selector) if not external_pipeline.has_preset(preset_name): raise UserFacingGraphQLError( graphene_info.schema.type_named('PresetNotFoundError')( preset=preset_name, selector=selector ) ) preset = external_pipeline.get_preset(preset_name) return ExecutionParams( selector=selector.with_solid_selection(preset.solid_selection), run_config=preset.run_config, mode=preset.mode, execution_metadata=create_execution_metadata( graphql_execution_params.get('executionMetadata') ), step_keys=graphql_execution_params.get('stepKeys'), ) return execution_params_from_graphql(graphene_info.context, graphql_execution_params)
def create_execution_params(graphene_info, graphql_execution_params): preset_name = graphql_execution_params.get('preset') selector = pipeline_selector_from_graphql( graphene_info.context, graphql_execution_params['selector']) if preset_name: # This should return proper GraphQL errors # https://github.com/dagster-io/dagster/issues/2507 check.invariant( not graphql_execution_params.get('runConfigData'), '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', ) check.invariant( not selector.solid_selection, 'Invalid ExecutionParams. Cannot define selector.solid_selection when using preset', ) external_pipeline = get_full_external_pipeline_or_raise( graphene_info, selector) if not external_pipeline.has_preset(preset_name): raise UserFacingGraphQLError( graphene_info.schema.type_named('PresetNotFoundError')( preset=preset_name, selector=selector)) preset = external_pipeline.get_preset(preset_name) return ExecutionParams( selector=selector.with_solid_selection(preset.solid_selection), environment_dict=preset.environment_dict, mode=preset.mode, execution_metadata=create_execution_metadata( graphql_execution_params.get('executionMetadata')), step_keys=graphql_execution_params.get('stepKeys'), ) return execution_params_from_graphql(graphene_info.context, graphql_execution_params)
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', ) external_pipeline = get_external_pipeline_or_raise( graphene_info, selector.name) if not external_pipeline.has_preset(preset_name): raise UserFacingGraphQLError( graphene_info.schema.type_named('PresetNotFoundError')( preset=preset_name, selector=selector)) preset = external_pipeline.get_preset(preset_name) return ExecutionParams( selector=ExecutionSelector(selector.name, preset.solid_subset), environment_dict=preset.environment_dict, mode=preset.mode, execution_metadata=create_execution_metadata( graphql_execution_params.get('executionMetadata')), step_keys=graphql_execution_params.get('stepKeys'), ) return execution_params_from_graphql(graphql_execution_params)