def _anonymize_checkpoint_config(self, name: str, config: dict) -> dict:
"""Anonymize Checkpoint objs from the 'great_expectations.checkpoint' module.
Args:
name (str): The name of the checkpoint.
config (dict): The dictionary configuration corresponding to the checkpoint.
Returns:
An anonymized dictionary payload that obfuscates user-specific details.
"""
anonymized_info_dict: dict = {
"anonymized_name": self._anonymize_string(name),
}
# Roundtrip through schema validation to remove any illegal fields add/or restore any missing fields.
from great_expectations.data_context.types.base import checkpointConfigSchema
checkpoint_config: dict = checkpointConfigSchema.load(
CommentedMap(**config))
checkpoint_config_dict: dict = checkpointConfigSchema.dump(
checkpoint_config)
self._anonymize_object_info(
anonymized_info_dict=anonymized_info_dict,
object_config=checkpoint_config_dict,
)
return anonymized_info_dict
def anonymize_checkpoint_info(self, name: str, config: dict) -> dict:
anonymized_info_dict: dict = {
"anonymized_name": self.anonymize(name),
}
# Roundtrip through schema validation to remove any illegal fields add/or restore any missing fields.
checkpoint_config: dict = checkpointConfigSchema.load(CommentedMap(**config))
checkpoint_config_dict: dict = checkpointConfigSchema.dump(checkpoint_config)
self.anonymize_object_info(
anonymized_info_dict=anonymized_info_dict,
ge_classes=self._ge_classes,
object_config=checkpoint_config_dict,
)
return anonymized_info_dict
def _build_checkpoint_config(self) -> CheckpointConfig:
action_list = self._default_action_list()
if self.site_names:
action_list = self._add_update_data_docs_action(action_list)
if self.slack_webhook:
action_list = self._add_slack_action(action_list)
config_kwargs: dict = self.other_kwargs or {}
# DataFrames shouldn't be saved to CheckpointStore
batch_request = config_kwargs.get("batch_request")
if batch_request_contains_batch_data(batch_request=batch_request):
config_kwargs.pop("batch_request", None)
else:
config_kwargs["batch_request"] = get_batch_request_as_dict(
batch_request=batch_request
)
# DataFrames shouldn't be saved to CheckpointStore
validations = config_kwargs.get("validations")
if batch_request_in_validations_contains_batch_data(validations=validations):
config_kwargs.pop("validations", [])
else:
config_kwargs["validations"] = get_validations_with_batch_request_as_dict(
validations=validations
)
specific_config_kwargs_overrides: dict = {
"config_version": 1.0,
"name": self.name,
"class_name": "Checkpoint",
"action_list": action_list,
"ge_cloud_id": self.other_kwargs.pop("ge_cloud_id", None),
}
config_kwargs.update(specific_config_kwargs_overrides)
# Roundtrip through schema validation to remove any illegal fields add/or restore any missing fields.
checkpoint_config: dict = checkpointConfigSchema.load(
CommentedMap(**config_kwargs)
)
config_kwargs = checkpointConfigSchema.dump(checkpoint_config)
logger.debug(
f"SimpleCheckpointConfigurator built this CheckpointConfig:"
f"{checkpoint_config}"
)
return CheckpointConfig(**config_kwargs)