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# coding: utf-8 # Copyright (c) 2016, 2026, Oracle and/or its affiliates. All rights reserved. # This software is dual-licensed to you under the Universal Permissive License (UPL) 1.0 as shown at https://oss.oracle.com/licenses/upl or Apache License 2.0 as shown at http://www.apache.org/licenses/LICENSE-2.0. You may choose either license. # NOTE: This class is auto generated by OracleSDKGenerator. DO NOT EDIT. API Version: 20190101 from oci.util import formatted_flat_dict, NONE_SENTINEL, value_allowed_none_or_none_sentinel # noqa: F401 from oci.decorators import init_model_state_from_kwargs @init_model_state_from_kwargs class PipelineStepUpdateDetails(object): """ The details of the step to update. """ #: A constant which can be used with the step_type property of a PipelineStepUpdateDetails. #: This constant has a value of "ML_JOB" STEP_TYPE_ML_JOB = "ML_JOB" #: A constant which can be used with the step_type property of a PipelineStepUpdateDetails. #: This constant has a value of "CUSTOM_SCRIPT" STEP_TYPE_CUSTOM_SCRIPT = "CUSTOM_SCRIPT" #: A constant which can be used with the step_type property of a PipelineStepUpdateDetails. #: This constant has a value of "CONTAINER" STEP_TYPE_CONTAINER = "CONTAINER" #: A constant which can be used with the step_type property of a PipelineStepUpdateDetails. #: This constant has a value of "DATAFLOW" STEP_TYPE_DATAFLOW = "DATAFLOW" def __init__(self, *kwargs): """ Initializes a new PipelineStepUpdateDetails object with values from keyword arguments. This class has the following subclasses and if you are using this class as input to a service operations then you should favor using a subclass over the base class: :class:`~oci.data_science.models.PipelineDataflowStepUpdateDetails` * :class:`~oci.data_science.models.PipelineMLJobStepUpdateDetails` * :class:`~oci.data_science.models.PipelineCustomScriptStepUpdateDetails` * :class:`~oci.data_science.models.PipelineContainerStepUpdateDetails` The following keyword arguments are supported (corresponding to the getters/setters of this class): :param step_type: The value to assign to the step_type property of this PipelineStepUpdateDetails. Allowed values for this property are: "ML_JOB", "CUSTOM_SCRIPT", "CONTAINER", "DATAFLOW" :type step_type: str :param step_name: The value to assign to the step_name property of this PipelineStepUpdateDetails. :type step_name: str :param description: The value to assign to the description property of this PipelineStepUpdateDetails. :type description: str :param step_configuration_details: The value to assign to the step_configuration_details property of this PipelineStepUpdateDetails. :type step_configuration_details: oci.data_science.models.PipelineStepConfigurationDetails """ self.swagger_types = { 'step_type': 'str', 'step_name': 'str', 'description': 'str', 'step_configuration_details': 'PipelineStepConfigurationDetails' } self.attribute_map = { 'step_type': 'stepType', 'step_name': 'stepName', 'description': 'description', 'step_configuration_details': 'stepConfigurationDetails' } self._step_type = None self._step_name = None self._description = None self._step_configuration_details = None @staticmethod def get_subtype(object_dictionary): """ Given the hash representation of a subtype of this class, use the info in the hash to return the class of the subtype. """ type = object_dictionary['stepType'] if type == 'DATAFLOW': return 'PipelineDataflowStepUpdateDetails' if type == 'ML_JOB': return 'PipelineMLJobStepUpdateDetails' if type == 'CUSTOM_SCRIPT': return 'PipelineCustomScriptStepUpdateDetails' if type == 'CONTAINER': return 'PipelineContainerStepUpdateDetails' else: return 'PipelineStepUpdateDetails' @property def step_type(self): """ [Required] Gets the step_type of this PipelineStepUpdateDetails. The type of step. Allowed values for this property are: "ML_JOB", "CUSTOM_SCRIPT", "CONTAINER", "DATAFLOW" :return: The step_type of this PipelineStepUpdateDetails. :rtype: str """ return self._step_type @step_type.setter def step_type(self, step_type): """ Sets the step_type of this PipelineStepUpdateDetails. The type of step. :param step_type: The step_type of this PipelineStepUpdateDetails. :type: str """ allowed_values = ["ML_JOB", "CUSTOM_SCRIPT", "CONTAINER", "DATAFLOW"] if not value_allowed_none_or_none_sentinel(step_type, allowed_values): raise ValueError( f"Invalid value for `step_type`, must be None or one of {allowed_values}" ) self._step_type = step_type @property def step_name(self): """ [Required] Gets the step_name of this PipelineStepUpdateDetails. The name of the step. :return: The step_name of this PipelineStepUpdateDetails. :rtype: str """ return self._step_name @step_name.setter def step_name(self, step_name): """ Sets the step_name of this PipelineStepUpdateDetails. The name of the step. :param step_name: The step_name of this PipelineStepUpdateDetails. :type: str """ self._step_name = step_name @property def description(self): """ Gets the description of this PipelineStepUpdateDetails. A short description of the step. :return: The description of this PipelineStepUpdateDetails. :rtype: str """ return self._description @description.setter def description(self, description): """ Sets the description of this PipelineStepUpdateDetails. A short description of the step. :param description: The description of this PipelineStepUpdateDetails. :type: str """ self._description = description @property def step_configuration_details(self): """ Gets the step_configuration_details of this PipelineStepUpdateDetails. :return: The step_configuration_details of this PipelineStepUpdateDetails. :rtype: oci.data_science.models.PipelineStepConfigurationDetails """ return self._step_configuration_details @step_configuration_details.setter def step_configuration_details(self, step_configuration_details): """ Sets the step_configuration_details of this PipelineStepUpdateDetails. :param step_configuration_details: The step_configuration_details of this PipelineStepUpdateDetails. :type: oci.data_science.models.PipelineStepConfigurationDetails """ self._step_configuration_details = step_configuration_details def __repr__(self): return formatted_flat_dict(self) def __eq__(self, other): if other is None: return False return self.__dict__ == other.__dict__ def __ne__(self, other): return not self == other

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