docs-archive/apache-airflow-providers-amazon/1.3.0/_sources/_api/airflow/providers/amazon/aws/operators/s3_bucket_tagging/index.rst.txt

:mod:`airflow.providers.amazon.aws.operators.s3_bucket_tagging`
===============================================================

.. py:module:: airflow.providers.amazon.aws.operators.s3_bucket_tagging

.. autoapi-nested-parse::

   This module contains AWS S3 operators.



Module Contents
---------------

.. data:: BUCKET_DOES_NOT_EXIST_MSG
   :annotation: = Bucket with name: %s doesn't exist

   

.. py:class:: S3GetBucketTaggingOperator(bucket_name: str, aws_conn_id: Optional[str] = 'aws_default', **kwargs)

   Bases: :class:`airflow.models.BaseOperator`

   This operator gets tagging from an S3 bucket

   .. seealso::
       For more information on how to use this operator, take a look at the guide:
       :ref:`howto/operator:S3GetBucketTaggingOperator`

   :param bucket_name: This is bucket name you want to reference
   :type bucket_name: str
   :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).
   :type aws_conn_id: Optional[str]

   .. attribute:: template_fields
      :annotation: = ['bucket_name']

      

   
   .. method:: execute(self, context)




.. py:class:: S3PutBucketTaggingOperator(bucket_name: str, key: Optional[str] = None, value: Optional[str] = None, tag_set: Optional[List[Dict[str, str]]] = None, aws_conn_id: Optional[str] = 'aws_default', **kwargs)

   Bases: :class:`airflow.models.BaseOperator`

   This operator puts tagging for an S3 bucket.

   .. seealso::
       For more information on how to use this operator, take a look at the guide:
       :ref:`howto/operator:S3PutBucketTaggingOperator`

   :param bucket_name: The name of the bucket to add tags to.
   :type bucket_name: str
   :param key: The key portion of the key/value pair for a tag to be added.
       If a key is provided, a value must be provided as well.
   :type key: str
   :param value: The value portion of the key/value pair for a tag to be added.
       If a value is provided, a key must be provided as well.
   :param tag_set: A List of key/value pairs.
   :type tag_set: List[Dict[str, str]]
   :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 the default boto3 configuration would be used (and must be
       maintained on each worker node).
   :type aws_conn_id: Optional[str]

   .. attribute:: template_fields
      :annotation: = ['bucket_name']

      

   
   .. method:: execute(self, context)




.. py:class:: S3DeleteBucketTaggingOperator(bucket_name: str, aws_conn_id: Optional[str] = 'aws_default', **kwargs)

   Bases: :class:`airflow.models.BaseOperator`

   This operator deletes tagging from an S3 bucket.

   .. seealso::
       For more information on how to use this operator, take a look at the guide:
       :ref:`howto/operator:S3DeleteBucketTaggingOperator`

   :param bucket_name: This is the name of the bucket to delete tags from.
   :type bucket_name: str
   :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).
   :type aws_conn_id: Optional[str]

   .. attribute:: template_fields
      :annotation: = ['bucket_name']

      

   
   .. method:: execute(self, context)