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  # to you under the Apache License, Version 2.0 (the
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  """This module contains Google Cloud Bigtable sensor."""
  from typing import Optional, Sequence, Union
  
  import google.api_core.exceptions
  from google.cloud.bigtable.table import ClusterState
  from google.cloud.bigtable_admin_v2 import enums
  
  from airflow.providers.google.cloud.hooks.bigtable import BigtableHook
  from airflow.providers.google.cloud.operators.bigtable import BigtableValidationMixin
  from airflow.sensors.base import BaseSensorOperator
  
  
  class BigtableTableReplicationCompletedSensor(BaseSensorOperator, BigtableValidationMixin):
      """
      Sensor that waits for Cloud Bigtable table to be fully replicated to its clusters.
      No exception will be raised if the instance or the table does not exist.
  
      For more details about cluster states for a table, have a look at the reference:
      https://googleapis.github.io/google-cloud-python/latest/bigtable/table.html#google.cloud.bigtable.table.Table.get_cluster_states
  
      .. seealso::
          For more information on how to use this operator, take a look at the guide:
          :ref:`howto/operator:BigtableTableReplicationCompletedSensor`
  
      :type instance_id: str
      :param instance_id: The ID of the Cloud Bigtable instance.
      :type table_id: str
      :param table_id: The ID of the table to check replication status.
      :type project_id: str
      :param project_id: Optional, the ID of the Google Cloud project.
      :param impersonation_chain: Optional service account to impersonate using short-term
          credentials, or chained list of accounts required to get the access_token
          of the last account in the list, which will be impersonated in the request.
          If set as a string, the account must grant the originating account
          the Service Account Token Creator IAM role.
          If set as a sequence, the identities from the list must grant
          Service Account Token Creator IAM role to the directly preceding identity, with first
          account from the list granting this role to the originating account (templated).
      :type impersonation_chain: Union[str, Sequence[str]]
      """
  
      REQUIRED_ATTRIBUTES = ('instance_id', 'table_id')
      template_fields = [
          'project_id',
          'instance_id',
          'table_id',
          'impersonation_chain',
      ]
  
      def __init__(
          self,
          *,
          instance_id: str,
          table_id: str,
          project_id: Optional[str] = None,
          gcp_conn_id: str = 'google_cloud_default',
          impersonation_chain: Optional[Union[str, Sequence[str]]] = None,
          **kwargs,
      ) -> None:
          self.project_id = project_id
          self.instance_id = instance_id
          self.table_id = table_id
          self.gcp_conn_id = gcp_conn_id
          self._validate_inputs()
          self.impersonation_chain = impersonation_chain
          super().__init__(**kwargs)
  
      def poke(self, context: dict) -> bool:
          hook = BigtableHook(
              gcp_conn_id=self.gcp_conn_id,
              impersonation_chain=self.impersonation_chain,
          )
          instance = hook.get_instance(project_id=self.project_id, instance_id=self.instance_id)
          if not instance:
              self.log.info("Dependency: instance '%s' does not exist.", self.instance_id)
              return False
  
          try:
              cluster_states = hook.get_cluster_states_for_table(instance=instance, table_id=self.table_id)
          except google.api_core.exceptions.NotFound:
              self.log.info(
                  "Dependency: table '%s' does not exist in instance '%s'.", self.table_id, self.instance_id
              )
              return False
  
          ready_state = ClusterState(enums.Table.ClusterState.ReplicationState.READY)
  
          is_table_replicated = True
          for cluster_id in cluster_states.keys():
              if cluster_states[cluster_id] != ready_state:
                  self.log.info("Table '%s' is not yet replicated on cluster '%s'.", self.table_id, cluster_id)
                  is_table_replicated = False
  
          if not is_table_replicated:
              return False
  
          self.log.info("Table '%s' is replicated.", self.table_id)
          return True
  