tuisheet, a terminal spreadsheet compatible with OpenXML (xlsx) files

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Presenting tuisheet: A love letter to VisiCalc and Lotus 1-2-3. The motive was to code a programme inspired by VisiCalc and Lotus 1-2-3 interface, running on terminal, but fully compatible with the current universal standard of OpenXML (xlsx files for spreadsheets). Coded in Go lang; apart from my being more familiar with this programming language, it helps making a single executable, low on resources. Also, I like Go's compiler ability to cross compile to many platforms and OSes (which I personally often meet through my daily job). By the way, tuisheet is much more thoroughly tested and used on Linux than on Windows (or Solaris, AIX, BSD).

Visit product View on Hacker NewsSep 18, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: single, code, open · Missing: mac, agents, macos

83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Indie HackersFits the IH revenue-focused audience · Strong signals: compatible · Missing: supports, reddit linkedin, podcasting

82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released

79%79% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: personal, way · Missing: mobile apps, ios, entrepreneurs

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, interface · Missing: plus, intuitive, reviews

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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