def resolve_runConfigSchemaOrError(self, graphene_info, **kwargs):
return resolve_run_config_schema_or_error(
graphene_info,
pipeline_selector_from_graphql(graphene_info.context,
kwargs['selector']),
kwargs.get('mode'),
)
def resolve_isPipelineConfigValid(self, graphene_info, pipeline, **kwargs):
return validate_pipeline_config(
graphene_info,
pipeline_selector_from_graphql(graphene_info.context, pipeline),
kwargs.get('runConfigData'),
kwargs.get('mode'),
)
def resolve_executionPlanOrError(self, graphene_info, pipeline, **kwargs):
return get_execution_plan(
graphene_info,
pipeline_selector_from_graphql(graphene_info.context, pipeline),
kwargs.get('runConfigData'),
kwargs.get('mode'),
)
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 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 resolve_pipelineSnapshotOrError(self, graphene_info, **kwargs):
snapshot_id_arg = kwargs.get('snapshotId')
pipeline_selector_arg = kwargs.get('activePipelineSelector')
check.invariant(
not (snapshot_id_arg and pipeline_selector_arg),
'Must only pass one of snapshotId or activePipelineSelector',
)
check.invariant(
snapshot_id_arg or pipeline_selector_arg,
'Must set one of snapshotId or activePipelineSelector',
)
if pipeline_selector_arg:
pipeline_selector = pipeline_selector_from_graphql(
graphene_info.context, kwargs['activePipelineSelector'])
return get_pipeline_snapshot_or_error_from_pipeline_selector(
graphene_info, pipeline_selector)
else:
return get_pipeline_snapshot_or_error_from_snapshot_id(
graphene_info, snapshot_id_arg)
def resolve_pipelineOrError(self, graphene_info, **kwargs):
return get_pipeline_or_error(
graphene_info,
pipeline_selector_from_graphql(graphene_info.context,
kwargs['params']),
)
