:py:mod:`airflow.providers.google.firebase.example_dags.example_firestore`
==========================================================================

.. py:module:: airflow.providers.google.firebase.example_dags.example_firestore

.. autoapi-nested-parse::

   Example Airflow DAG that shows interactions with Google Cloud Firestore.

   Prerequisites
   =============

   This example uses two Google Cloud projects:

   * ``GCP_PROJECT_ID`` - It contains a bucket and a firestore database.
   * ``G_FIRESTORE_PROJECT_ID`` - it contains the Data Warehouse based on the BigQuery service.

   Saving in a bucket should be possible from the ``G_FIRESTORE_PROJECT_ID`` project.
   Reading from a bucket should be possible from the ``GCP_PROJECT_ID`` project.

   The bucket and dataset should be located in the same region.

   If you want to run this example, you must do the following:

   1. Create Google Cloud project and enable the BigQuery API
   2. Create the Firebase project
   3. Create a bucket in the same location as the Firebase project
   4. Grant Firebase admin account permissions to manage BigQuery. This is required to create a dataset.
   5. Create a bucket in Firebase project and
   6. Give read/write access for Firebase admin to bucket to step no. 5.
   7. Create collection in the Firestore database.


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

.. py:data:: GCP_PROJECT_ID
   

.. py:data:: FIRESTORE_PROJECT_ID
   

.. py:data:: EXPORT_DESTINATION_URL
   

.. py:data:: BUCKET_NAME
   

.. py:data:: EXPORT_PREFIX
   

.. py:data:: EXPORT_COLLECTION_ID
   

.. py:data:: DATASET_NAME
   

.. py:data:: DATASET_LOCATION
   

.. py:data:: export_database_to_gcs