Weekle – a web app to learn how to calculate the day of the week

Hacker News

Mentally calculating the day-of-the-week for any date in history sounds like an impossible task for a normal person, but the algorithm is actually pretty simple to learn. Although there are tutorials for this elsewhere online, and little quizzes available, there didn't seem to be anything well optimised with multiple practice modes etc. I originally created a basic version of this just for myself, but a small group of friends and family found it interesting and gave suggestions such as the daily game. Multi-lingual support is a bit rudimentary at the moment, it will only translate the month names and weekday names, not other text. If any translation mistakes are identified please let me know. Other feedback is welcome too.

Visit product View on Hacker NewsMay 19, 2023

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

86%86% 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.

TrustMRRFits verified-revenue profile · Strong signals: month · Missing: mobile apps, ios, personal

64%64% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

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

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

24%24% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

23%23% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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