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ETL Frameworks
Database-to-Database CLI Tool
★ 4.1
Python ETL Package
★ 4.3
pip install ingestrpip install petlpip install ingestrpip install petlPython data engineers use ingestr as a fast way to set up one-off or recurring data copies between systems — running `ingestr ingest --source-uri pg://... --dest-uri bq://... --table schema.table` from Python subprocess calls or shell scripts. For more complex transformations or pipeline logic, ingestr handles the raw ingestion while Python handles the business logic.
Python data engineers use petl for lightweight, script-based ETL tasks where Spark or Airflow would be overkill. A typical pipeline reads from a CSV or SQLite source, applies field renames and filters, then writes to a Postgres table — all in under 50 lines of readable Python.
Individual Tool Pages