Polygon ETL allows you to setup an ETL pipeline in Google Cloud Platform for ingesting Polygon blockchain data into BigQuery and Pub/Sub. It comes with CLI tools for exporting Polygon data into convenient formats like CSVs and relational databases.

1. The nodes are run in a Kubernetes cluster.

2. Airflow DAGs export and load Polygon data to BigQuery daily. Refer to Polygon ETL Airflow for deployment instructions.

3. Polygon data is polled periodically from the nodes and pushed to Google Pub/Sub. Refer to Polygon ETL Streaming for deployment instructions.

4. Polygon data is pulled from Pub/Sub, transformed and streamed to BigQuery. Refer to Polygon ETL Dataflow for deployment instructions.

1. Follow the instructions in Polygon ETL Airflow to deploy a Cloud Composer cluster for exporting and loading historical Polygon data. It may take several days for the export DAG to catch up. During this time "load" and "verify_streaming" DAGs will fail.

2. Follow the instructions in Polygon ETL Streaming to deploy the Streamer component. For the value in last_synced_block.txt specify the last block number of the previous day. You can query it in BigQuery: SELECT number FROM crypto_polygon.blocks ORDER BY number DESC LIMIT 1.

3. Follow the instructions in Polygon ETL Dataflow to deploy the Dataflow component. Monitor "verify_streaming" DAG in Airflow console, once the Dataflow job catches up the latest block, the DAG will succeed.

Over time, we intend to format python files in this repo using isort and black. At the moment, we are only formatting any changed or added files

We have not implemented any sort of automation (e.g. pre-commit), but a requirements_dev.txt is provided for contributors to use.

Various tests are implemented (airflow/tests, cli/tests and ./tests). As part of an effort towards consistency, they all source the same requirements_test.txt.