GS

GS-Calc – a spreadsheet with 12M rows

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GS-Calc – a spreadsheet with 12M rows

Loading a 4GB+ workbook with over 500 million cells with random floating-point numbers and text strings - 8 worksheets, ~12 million rows each should take less than 30s on a computer with 16GB RAM. Updating 12 million vlookups searching 12 million rows takes seconds. Effective use of up to 64 processor cores for calculations applying any functions, including any number of user-created functions that can both extend and replace the default built-in set of ~390 functions. Filtering, regular expressions, Monte Carlo simulations, pivot tables with up to 12 million rows, scripting. GS-Calc can be installed on any portable storage device and used without performing any registry modifications. The installation folder requires ~8.5MB. https://citadel5.com/gs-calc.htm (incl. YT videos with examples) Any suggestions, especially regarding the ETL-related functions, are welcome. Thanks

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, including · Missing: supports, reddit linkedin, podcasting
72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, computer · Missing: mac, agents, macos
54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · Missing: https docs, excited, just released
54%54% 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: video · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
37%37% 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
18%18% 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
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

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