Ra

Random Caplocks Prank

Hacker News

Random Caplocks Prank

I was building a program that needed to allow a user to set a hotkey but the program lives in the taskbar so there's no UI. I decided what I would do is enable the caplock key when they click "Set Hotkey" and then they can disable the caplock key (or set it to its initial state, rather) to indicate they have finished. That project is still going but I got sidetracked by the idea that I could just build a program to randomly enable the caplock key every once in a while. This isn't a program designed to calculate child malnutrition or do anything to stop genocide etc but I was able to do it in a few hours and learn some new tricks. I hope this isn't too stupid for HN.

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, new · Missing: mac, agents, macos
71%71% 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 · Missing: https docs, excited, just released
68%68% 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
48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
38%38% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% 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.

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