def copy_for_configured(
self,
name: str,
description: Optional[str],
config_schema: Any,
config_or_config_fn: Any,
):
if not self.has_config_mapping:
raise DagsterInvalidDefinitionError(
"Only graphs utilizing config mapping can be pre-configured. The graph "
'"{graph_name}" does not have a config mapping, and thus has nothing to be '
"configured.".format(graph_name=self.name))
config_mapping = cast(ConfigMapping, self.config_mapping)
return GraphDefinition(
name=name,
description=check.opt_str_param(description,
"description",
default=self.description),
node_defs=self._node_defs,
dependencies=self._dependencies,
input_mappings=self._input_mappings,
output_mappings=self._output_mappings,
config=ConfigMapping(
config_mapping.config_fn,
config_schema=config_schema,
receive_processed_config_values=config_mapping.
receive_processed_config_values,
),
)
def _config_mapping_with_default_value(
inner_schema: ConfigType,
default_config: Dict[str, Any],
job_name: str,
graph_name: str,
) -> ConfigMapping:
if not isinstance(inner_schema, Shape):
check.failed(
"Only Shape (dictionary) config_schema allowed on Job ConfigMapping"
)
def config_fn(x):
return x
updated_fields = {}
field_aliases = inner_schema.field_aliases
for name, field in inner_schema.fields.items():
if name in default_config:
updated_fields[name] = Field(
config=field.config_type,
default_value=default_config[name],
description=field.description,
)
elif name in field_aliases and field_aliases[name] in default_config:
updated_fields[name] = Field(
config=field.config_type,
default_value=default_config[field_aliases[name]],
description=field.description,
)
else:
updated_fields[name] = field
config_schema = Shape(
fields=updated_fields,
description="run config schema with default values from default_config",
field_aliases=inner_schema.field_aliases,
)
config_evr = validate_config(config_schema, default_config)
if not config_evr.success:
raise DagsterInvalidConfigError(
f"Error in config when building job '{job_name}' from graph '{graph_name}' ",
config_evr.errors,
default_config,
)
return ConfigMapping(config_fn=config_fn,
config_schema=config_schema,
receive_processed_config_values=False)
def _config_mapping_with_default_value(
inner_schema: ConfigType,
default_config: Dict[str, Any],
) -> ConfigMapping:
if not isinstance(inner_schema, Shape):
check.failed(
"Only Shape (dictionary) config_schema allowed on Job ConfigMapping"
)
def config_fn(x):
return x
updated_fields = {}
field_aliases = inner_schema.field_aliases
for name, field in inner_schema.fields.items():
if name in default_config:
updated_fields[name] = Field(
config=field.config_type,
default_value=default_config[name],
description=field.description,
)
elif name in field_aliases and field_aliases[name] in default_config:
updated_fields[name] = Field(
config=field.config_type,
default_value=default_config[field_aliases[name]],
description=field.description,
)
return ConfigMapping(
config_fn=config_fn,
config_schema=Shape(
fields=updated_fields,
description=
"run config schema with default values from default_config",
),
)