Simplicity Builder:drag and drop builder web component, all frameworks

Hacker News

I have been working on this drag and drop builder web component to satisfy my own requirements of having a general purpose drag and drop builder that I could use in various projects that I am working on. The component lets you turn any HTML into a drag and drop builder via configuration files. There is a version that can be used with vanilla JavaScript as well as wrapped versions for Vue, React and Angular. The base version that works with Vanilla JavaScript can in theory work with any framework. It is a version one project. I am working on putting some better demos together and some basic changes to where menus and setting dialogs can show up, etc. The website requires an email address (but no credit card information) to get a free trial dev key. However, in the spirit of Show HN posts here is a trial dev key you can use: DFB7GDG8852 I will update the trial dev code a few times in this thread. Also, if you want to contact me you can email me at mike@simplicitywebtools.com I would love any feedback. Thank you.

Visit product View on Hacker NewsMay 14, 2024

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

85%85% 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

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

48%48% 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 · Strong signals: builder · Missing: plus, platform, intuitive

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

37%37% 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

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

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

Correct prediction on native model

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