class_docstr: Class to Create and Update FeatureProcessor Lineage Entities.
  
  Attributes:
      pipeline_name (str): Pipeline Name.
      pipeline_arn (str): The ARN of the Pipeline.
      pipeline (str): The details of the Pipeline.
      inputs (Sequence[Union[FeatureGroupDataSource, CSVDataSource, ParquetDataSource,
          BaseDataSource]]): The inputs to the Feature processor.
      output (str): The output Feature Group.
      transformation_code (TransformationCode): The Transformation Code for Feature Processor.
      sagemaker_session (Session): Session object which manages interactions
          with Amazon SageMaker APIs and any other AWS services needed. If not specified, the
          function creates one using the default AWS configuration chain.
class_docstr_tok: ["Class","to","Create","and","Update","FeatureProcessor","Lineage","Entities",".","Attributes",":","pipeline_name","(","str",")",":","Pipeline","Name",".","pipeline_arn","(","str",")",":","The","ARN","of","the","Pipeline",".","pipeline","(","str",")",":","The","details","of","the","Pipeline",".","inputs","(","Sequence","[","Union","[","FeatureGroupDataSource",",","CSVDataSource",",","ParquetDataSource",",","BaseDataSource","]","]",")",":","The","inputs","to","the","Feature","processor",".","output","(","str",")",":","The","output","Feature","Group",".","transformation_code","(","TransformationCode",")",":","The","Transformation","Code","for","Feature","Processor",".","sagemaker_session","(","Session",")",":","Session","object","which","manages","interactions","with","Amazon","SageMaker","APIs","and","any","other","AWS","services","needed",".","If","not","specified",",","the","function","creates","one","using","the","default","AWS","configuration","chain","."]
docstr: Class to Create and Update FeatureProcessor Lineage Entities.
  
  Arguments:
      pipeline_name (str): Pipeline Name.
      schedule_arn (str): The ARN of the Schedule.
      schedule_expression (str): The expression that defines when the schedule runs.
          It supports at expression, rate expression and cron expression.
      state (str):Specifies whether the schedule is enabled or disabled. Valid values are
          ENABLED and DISABLED. See https://docs.aws.amazon.com/scheduler/latest/APIReference/
          API_CreateSchedule.html#scheduler-CreateSchedule-request-State for more details.
          If not specified, it will default to ENABLED.
      start_date (Optional[datetime]): The date, in UTC, after which the schedule can begin
          invoking its target. Depending on the schedule’s recurrence expression, invocations
          might occur on, or after, the StartDate you specify.
      tags (Optional[List[Dict[str, str]]]): Custom tags to be attached to schedule
          lineage resource.
code: def create_schedule_lineage(
      self,
      pipeline_name: str,
      schedule_arn,
      schedule_expression,
      state,
      start_date: datetime,
      tags: Optional[List[Dict[str, str]]] = None,
  ) -> None:
      """Class to Create and Update FeatureProcessor Lineage Entities.
  
      Arguments:
          pipeline_name (str): Pipeline Name.
          schedule_arn (str): The ARN of the Schedule.
          schedule_expression (str): The expression that defines when the schedule runs.
              It supports at expression, rate expression and cron expression.
          state (str):Specifies whether the schedule is enabled or disabled. Valid values are
              ENABLED and DISABLED. See https://docs.aws.amazon.com/scheduler/latest/APIReference/
              API_CreateSchedule.html#scheduler-CreateSchedule-request-State for more details.
              If not specified, it will default to ENABLED.
          start_date (Optional[datetime]): The date, in UTC, after which the schedule can begin
              invoking its target. Depending on the schedule’s recurrence expression, invocations
              might occur on, or after, the StartDate you specify.
          tags (Optional[List[Dict[str, str]]]): Custom tags to be attached to schedule
              lineage resource.
      """
      pipeline_context: Context = self._get_pipeline_context()
      pipeline_version_context: Context = (
          self._get_pipeline_version_context(
              last_update_time=pipeline_context.properties[
                  LAST_UPDATE_TIME
              ]
          )
      )
      pipeline_schedule: PipelineSchedule = PipelineSchedule(
          schedule_name=pipeline_name,
          schedule_arn=schedule_arn,
          schedule_expression=schedule_expression,
          pipeline_name=pipeline_name,
          state=state,
          start_date=start_date.strftime("%s"),
      )
      schedule_artifact: Artifact = (
          S3LineageEntityHandler.retrieve_pipeline_schedule_artifact(
              pipeline_schedule=pipeline_schedule,
              sagemaker_session=self.sagemaker_session,
          )
      )
      if tags:
          schedule_artifact.set_tags(tags)
  
      LineageAssociationHandler.add_upstream_schedule_associations(
          schedule_artifact=schedule_artifact,
          pipeline_version_context_arn=pipeline_version_context.context_arn,
          sagemaker_session=self.sagemaker_session,
      )
  
imports: from __future__ import absolute_import
  import logging
  from datetime import datetime
  from typing import Optional, Iterator, List, Dict, Set, Sequence, Union
  import attr
  from botocore.exceptions import ClientError
  from sagemaker.feature_store.feature_processor._event_bridge_rule_helper import EventBridgeRuleHelper
  from sagemaker.feature_store.feature_processor._event_bridge_scheduler_helper import EventBridgeSchedulerHelper
  from sagemaker.feature_store.feature_processor.lineage._lineage_association_handler import LineageAssociationHandler
  from sagemaker.feature_store.feature_processor.lineage._feature_group_lineage_entity_handler import FeatureGroupLineageEntityHandler
  from sagemaker.feature_store.feature_processor.lineage._feature_group_contexts import FeatureGroupContexts
  from sagemaker.feature_store.feature_processor.lineage._pipeline_lineage_entity_handler import PipelineLineageEntityHandler
  from sagemaker.feature_store.feature_processor.lineage._pipeline_schedule import PipelineSchedule
  from sagemaker.feature_store.feature_processor.lineage._pipeline_trigger import PipelineTrigger
  from sagemaker.feature_store.feature_processor.lineage._pipeline_version_lineage_entity_handler import PipelineVersionLineageEntityHandler
  from sagemaker.feature_store.feature_processor.lineage._s3_lineage_entity_handler import S3LineageEntityHandler
  from sagemaker.feature_store.feature_processor.lineage._transformation_code import TransformationCode
  from sagemaker.feature_store.feature_processor.lineage.constants import SAGEMAKER, LAST_UPDATE_TIME, PIPELINE_CONTEXT_NAME_KEY, PIPELINE_CONTEXT_VERSION_NAME_KEY, FEATURE_GROUP_PIPELINE_VERSION_CONTEXT_TYPE, DATA_SET, TRANSFORMATION_CODE, CREATION_TIME, RESOURCE_NOT_FOUND, ERROR, CODE, LAST_MODIFIED_TIME, TRANSFORMATION_CODE_STATUS_INACTIVE, TRANSFORMATION_CODE_STATUS_ACTIVE, CONTRIBUTED_TO
  from sagemaker.lineage.context import Context
  from sagemaker.lineage.artifact import Artifact
  from sagemaker.lineage.association import AssociationSummary
  from sagemaker import Session
  from sagemaker.feature_store.feature_processor._data_source import CSVDataSource, FeatureGroupDataSource, ParquetDataSource, BaseDataSource
label_desc: Use image node_id 3 for calling the FeatureProcessorLineageHandler obj's underlying member method code with example usage: obj.create_schedule_lineage(pipeline_name, schedule_arn, schedule_expression, state, start_date, tags) without return types