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)