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To build an auditable Excel financial model with openpyxl, use formula-first conventions that separate inputs from formulas, apply blue/black/green cell formatting rules, and add named ranges with balance-check assertions to ensure reviewer transparency.

Formula-first Excel modeling reduces silent errors by writing derived cells as live Excel formulas rather than precomputed Python values, allowing reviewers to trace calculations directly within the generated workbook instead of relying on hidden backend scripts.

Yes, you can generate sensitivity tables with a base-case center-cell sanity check and optionally recalculate Excel formulas headlessly via LibreOffice to validate the formula-first outputs downstream before sharing the final workbook.

Auditable financial modeling conventions use blue fonts for human-entered inputs, black for formulas, and green for links to external or other-sheet values, ensuring clear input and output separation for reviewers.

Yes, this approach supports DCF and 3-statement financial models by using named ranges for cross-sheet references and adding a Checks tab with TRUE/FALSE balance and reconciliation assertions to verify model integrity.

The generated Excel workbook is written as a single .xlsx file to the ./out/<name>.xlsx directory, ensuring a reproducible output location for every financial modeling workflow.