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I built a live preview web code editor

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I built a live preview web code editor

Hello everyone, Recently while using JSBin, I decided to attempt replicating the functionality applications in that same space have, like Codpen, JsFiddle etc as a learning exercise. Basically the core feature of these apps is seeing changes “live” as code is being edited. I built the frontend with Vue and made my best attempt at keeping dependencies as lean as the only other dependency is CodeMirror which does all the heavy lifting for code editing. The backend is written in Go. All in all it was a nice “and not so easy it becomes boring” project to tackle. I have plans if I can find the time to add some more features like more flexibility with layouts and have also been considering adding more complex features like collaborative editing after using and reading some articles from Repl.it. You can try out the editor here: https://live-editor.ikeoha.xyz Github here: https://github.com/ikeohachidi/live-editor

Visit productView on Hacker NewsMay 12, 2024
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, using, code · Missing: mac, agents, macos
93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
62%62% predicted probability of success on AppSumo, 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
60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: apps · Missing: mobile apps, ios, personal
52%52% 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
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
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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