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ETL Frameworks
Sheets to Data Warehouse Loader
★ 3.7
Database-to-Database CLI Tool
★ 4.1
pip install gspreadpip install ingestrpip install gspreadpip install ingestrPython data engineers use the `gspread` library to read business-owned datasets from Google Sheets into pandas DataFrames for pipeline processing. A common pattern is a weekly data feed maintained by a business team in Sheets — Python reads the latest values, validates them with Pydantic, transforms them, and loads them into the warehouse alongside operational data.
Python 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.
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