Stream large Excel files with constant memory. 46x faster than openpyxl, handles multi-sheet workbooks. Python API. - pip install pystreamxl

PyStreamXL treats spreadsheet data as enterprise asset — query with SQL-like language, validate quality, track transformations, and govern with audit trails. Streams row by row on both read and write, so you never load the entire workbook into memory. Runs ~46× faster than openpyxl on read and ~10× faster on write. Architectural Role: Owns spreadsheet data as enterprise asset. Applies same quality validation and governance as databases. Bridge between spreadsheets and data platforms. Process 1M-row spreadsheets in milliseconds — Never load a workbook into memory; stream rows on demand 46× faster than openpyxl — Rust-powered performance without sacrificing Python simplicity Quality validation built-in — Catch data errors at the source, not downstream in your pipeline Governance + audit trails — Track every transformation; prove data lineage for compliance

PyStreamXL

Streaming huge Excel files without blowing up memory solves a surprisingly common pain point. What was the biggest technical challenge you had to overcome to make that work reliably?

Love that it keeps memory usage flat no matter the file size, that constant-memory streaming approach is genuinely clever engineering rather than just throwing more RAM at the problem.

PyStreamXL

Streaming huge Excel files without blowing up memory solves a surprisingly common pain point. What was the biggest technical challenge you had to overcome to make that work reliably?

Love that it keeps memory usage flat no matter the file size, that constant-memory streaming approach is genuinely clever engineering rather than just throwing more RAM at the problem.