class_docstr: Amazon AppFlow Base Operator class (not supposed to be used directly in DAGs).
  
  :param source: The source name (Supported: salesforce, zendesk)
  :param flow_name: The flow name
  :param flow_update: A boolean to enable/disable a flow update before the run
  :param source_field: The field name to apply filters
  :param filter_date: The date value (or template) to be used in filters.
  :param poll_interval: how often in seconds to check the query status
  :param max_attempts: how many times to check for status before timing out
  :param wait_for_completion: whether to wait for the run to end to return
  :param aws_conn_id: The Airflow connection used for AWS credentials.
      If this is ``None`` or empty then the default boto3 behaviour is used. If
      running Airflow in a distributed manner and aws_conn_id is None or
      empty, then default boto3 configuration would be used (and must be
      maintained on each worker node).
  :param region_name: AWS region_name. If not specified then the default boto3 behaviour is used.
  :param verify: Whether or not to verify SSL certificates. See:
      https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html
  :param botocore_config: Configuration dictionary (key-values) for botocore client. See:
      https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
code: def execute(self, context: Context) -> None:
      self.filter_date_parsed: datetime | None = (
          datetime.fromisoformat(self.filter_date)
          if self.filter_date
          else None
      )
      if self.source is not None:
          self.connector_type = self._get_connector_type()
      if self.flow_update:
          self._update_flow()
          # while schedule flows will pick up the update right away, on-demand flows might use out of date
          # info if triggered right after an update, so we need to wait a bit for the DB to be consistent.
          time.sleep(AppflowBaseOperator.UPDATE_PROPAGATION_TIME)
  
      self._run_flow(context)
  
imports: from __future__ import annotations
  import time
  import warnings
  from datetime import datetime, timedelta
  from typing import TYPE_CHECKING, cast
  from airflow.exceptions import AirflowException, AirflowProviderDeprecationWarning
  from airflow.operators.python import ShortCircuitOperator
  from airflow.providers.amazon.aws.hooks.appflow import AppflowHook
  from airflow.providers.amazon.aws.operators.base_aws import AwsBaseOperator
  from airflow.providers.amazon.aws.utils import datetime_to_epoch_ms
  from airflow.providers.amazon.aws.utils.mixins import AwsBaseHookMixin, AwsHookParams, aws_template_fields
label_desc: Use image node_id 2 for calling the AppflowBaseOperator obj's underlying member method code with example usage: obj.execute(context) without return types