docs-archive/apache-airflow-providers-amazon/4.0.0/_sources/_api/airflow/providers/amazon/aws/transfers/mongo_to_s3/index.rst.txt

:py:mod:`airflow.providers.amazon.aws.transfers.mongo_to_s3`
============================================================

.. py:module:: airflow.providers.amazon.aws.transfers.mongo_to_s3


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

Classes
~~~~~~~

.. autoapisummary::

   airflow.providers.amazon.aws.transfers.mongo_to_s3.MongoToS3Operator




.. py:class:: MongoToS3Operator(*, s3_conn_id = None, mongo_conn_id = 'mongo_default', aws_conn_id = 'aws_default', mongo_collection, mongo_query, s3_bucket, s3_key, mongo_db = None, mongo_projection = None, replace = False, allow_disk_use = False, compression = None, **kwargs)

   Bases: :py:obj:`airflow.models.BaseOperator`

   Operator meant to move data from mongo via pymongo to s3 via boto.

   .. seealso::
       For more information on how to use this operator, take a look at the guide:
       :ref:`howto/operator:MongoToS3Operator`

   :param mongo_conn_id: reference to a specific mongo connection
   :param aws_conn_id: reference to a specific S3 connection
   :param mongo_collection: reference to a specific collection in your mongo db
   :param mongo_query: query to execute. A list including a dict of the query
   :param mongo_projection: optional parameter to filter the returned fields by
       the query. It can be a list of fields names to include or a dictionary
       for excluding fields (e.g ``projection={"_id": 0}`` )
   :param s3_bucket: reference to a specific S3 bucket to store the data
   :param s3_key: in which S3 key the file will be stored
   :param mongo_db: reference to a specific mongo database
   :param replace: whether or not to replace the file in S3 if it previously existed
   :param allow_disk_use: enables writing to temporary files in the case you are handling large dataset.
       This only takes effect when `mongo_query` is a list - running an aggregate pipeline
   :param compression: type of compression to use for output file in S3. Currently only gzip is supported.

   .. py:attribute:: template_fields
      :annotation: :Sequence[str] = ['s3_bucket', 's3_key', 'mongo_query', 'mongo_collection']

      

   .. py:attribute:: ui_color
      :annotation: = #589636

      

   .. py:attribute:: template_fields_renderers
      

      

   .. py:method:: execute(self, context)

      Is written to depend on transform method


   .. py:method:: transform(docs)
      :staticmethod:

      This method is meant to be extended by child classes
      to perform transformations unique to those operators needs.
      Processes pyMongo cursor and returns an iterable with each element being
      a JSON serializable dictionary

      Base transform() assumes no processing is needed
      ie. docs is a pyMongo cursor of documents and cursor just
      needs to be passed through

      Override this method for custom transformations