Amundsen Databuilder is a [ETL](https://en.wikipedia.org/wiki/Extract,_transform,_load"ETL") framework designed to build data from Amundsen. You could use the library either with an adhoc python script([example](https://github.com/lyft/amundsendatabuilder/blob/master/example/scripts/sample_data_loader.py)) or inside an Apache Airflow DAG([example](https://github.com/lyft/amundsendatabuilder/blob/master/example/dags/sample_dag.py)).
Amundsen Databuilder is a [ETL](https://en.wikipedia.org/wiki/Extract,_transform,_load"ETL") framework designed to build data from Amundsen. You could use the library either with an adhoc python script([example](https://github.com/lyft/amundsendatabuilder/blob/master/example/scripts/sample_data_loader.py)) or inside an Apache Airflow DAG([example](https://github.com/lyft/amundsendatabuilder/blob/master/example/dags/sample_dag.py)).
## Requirements
## Requirements
- Python = 2.7.x
- Python = 2.7.x (And Python >= 3.x if you don't use column usage transformer as it depends on antlr python 2 runtime)
## Concept
## Concept
ETL job consists of extraction of records from the source, transform records, if necessary, and load records into the sink. Amundsen Databuilder is a ETL framework for Amundsen and there are corresponding components for ETL called Extractor, Transformer, and Loader that deals with record level operation. A component called task controls all these three components.
ETL job consists of extraction of records from the source, transform records, if necessary, and load records into the sink. Amundsen Databuilder is a ETL framework for Amundsen and there are corresponding components for ETL called Extractor, Transformer, and Loader that deals with record level operation. A component called task controls all these three components.
