def _resolve_bound_config(solid_config: Any,
solid_def: SolidDefinition) -> Any:
"""Validate config against config schema, and return validated config."""
from dagster.config.validate import process_config
# Config processing system expects the top level config schema to be a dictionary, but solid
# config schema can be scalar. Thus, we wrap it in another layer of indirection.
outer_config_shape = Shape({"config": solid_def.get_config_field()})
config_evr = process_config(
outer_config_shape, {"config": solid_config} if solid_config else {})
if not config_evr.success:
raise DagsterInvalidConfigError(
f"Error in config for {solid_def.node_type_str} ",
config_evr.errors,
solid_config,
)
validated_config = cast(Dict, config_evr.value).get("config")
mapped_config_evr = solid_def.apply_config_mapping(
{"config": validated_config})
if not mapped_config_evr.success:
raise DagsterInvalidConfigError(
f"Error in config for {solid_def.node_type_str} ",
mapped_config_evr.errors,
solid_config,
)
validated_config = cast(Dict, mapped_config_evr.value).get("config")
return validated_config
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",
),
)