Scan a finance or commission spreadsheet for broken references and circular formulas before it ships.
Add a CI check that fails a pull request when an xlsx file contains risky formula patterns.
Generate a business-readable HTML audit report for non-technical reviewers of a spreadsheet.
| madara88645/sheetci | 0xallam/my-recipe | 0xhassaan/nn-from-scratch | |
|---|---|---|---|
| Stars | 0 | — | 0 |
| Language | Python | Python | Python |
| Last pushed | — | 2022-11-22 | — |
| Maintenance | — | Dormant | — |
| Setup difficulty | easy | moderate | moderate |
| Complexity | 2/5 | 2/5 | 4/5 |
| Audience | ops devops | general | developer |
Figures from each repo's GitHub metadata at analysis time.
Installs via pip, runs fully locally with no cloud upload or API key needed.
SheetCI is a command line tool that checks Excel spreadsheet files for risky formulas and produces an audit report. The README describes it as a linter, tester, and continuous integration guardrail for Excel files, aimed at business spreadsheets that carry real financial weight, like commission models, pricing calculators, or budget plans, which normally do not get the same scrutiny that program code does. The idea is that a small formula change in a spreadsheet can quietly shift revenue, commission payouts, or a budget number without anyone noticing until it causes a problem. SheetCI scans a workbook for issues such as broken references, circular formulas, or hardcoded values sitting inside calculations, and produces a report before that spreadsheet gets shared, committed to a repository, or used to make a decision. It runs entirely on your own machine or inside a continuous integration pipeline, and the README is explicit that the current version does not upload workbooks anywhere, does not use a database, does not call any AI service, and does not send file contents to the cloud. To install it, you run a standard Python pip command in editable mode for local development. From there, the main command is a scan of an xlsx file, which can be pointed at a specific workbook. You can generate a plain Markdown report with the findings, an interactive HTML report meant to be readable by non-technical business reviewers, or a raw JSON summary meant for feeding into other CI or CD tooling. The project also ships its own GitHub Actions workflow, which runs its test suite, confirms that a known-clean example workbook passes, and generates reports against an example workbook that is intentionally broken to prove the checks catch real problems. That intentionally broken example is expected to fail with a nonzero exit code, since it contains findings on purpose, which is what makes it useful for verifying the tool works as a gate in an automated pipeline.
A local-first command line tool that scans Excel workbooks for risky formulas and produces audit reports, acting like a linter and CI guardrail for spreadsheets.
Mainly Python. The stack also includes Python, CLI.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly ops devops.
This repo across BitVibe Labs
double-check against the repo, no cap.