Source code for airflow.contrib.sensors.bigquery_sensor

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from airflow.sensors.base_sensor_operator import BaseSensorOperator
from airflow.contrib.hooks.bigquery_hook import BigQueryHook
from airflow.utils.decorators import apply_defaults


[docs]class BigQueryTableSensor(BaseSensorOperator): """ Checks for the existence of a table in Google Bigquery. :param project_id: The Google cloud project in which to look for the table. The connection supplied to the hook must provide access to the specified project. :type project_id: string :param dataset_id: The name of the dataset in which to look for the table. storage bucket. :type dataset_id: string :param table_id: The name of the table to check the existence of. :type table_id: string :param bigquery_conn_id: The connection ID to use when connecting to Google BigQuery. :type bigquery_conn_id: string :param delegate_to: The account to impersonate, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :type delegate_to: string """ template_fields = ('project_id', 'dataset_id', 'table_id',) ui_color = '#f0eee4' @apply_defaults def __init__(self, project_id, dataset_id, table_id, bigquery_conn_id='bigquery_default_conn', delegate_to=None, *args, **kwargs): super(BigQueryTableSensor, self).__init__(*args, **kwargs) self.project_id = project_id self.dataset_id = dataset_id self.table_id = table_id self.bigquery_conn_id = bigquery_conn_id self.delegate_to = delegate_to
[docs] def poke(self, context): table_uri = '{0}:{1}.{2}'.format(self.project_id, self.dataset_id, self.table_id) self.log.info('Sensor checks existence of table: %s', table_uri) hook = BigQueryHook( bigquery_conn_id=self.bigquery_conn_id, delegate_to=self.delegate_to) return hook.table_exists(self.project_id, self.dataset_id, self.table_id)