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ETL Frameworks
Database-to-Database CLI Tool
★ 4.1
Fast DataFrame library for Python and Rust
★ 4.8
pip install ingestrpip install polarspip install ingestrpip install polarsPython 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 Polars as a high-performance pandas replacement for processing large datasets on a single machine. Its lazy API lets you chain transformations like .filter(), .group_by(), and .join() that Polars optimizes before executing. Common in data pipelines where pandas runs out of memory or becomes too slow, but where spinning up a Spark cluster is overkill.
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