Compose your start page using codepen like widgets

Hacker News

There are lots of existing start page services. To name a few, start.me and www.netvibes.com are both great at what they are doing. The problem is that in the process of using these product I always find myself wanting some more flexibility. Then I was wondering what could happen if I can use my CodePen/JSFiddle/JS Bin pens/fiddles/bins as widgets instead of choosing existing ones from service providers. My initial idea was to build something just like that, where people can select their CodePen/JSFiddle/JS Bin snippets and put them to a “home screen”. I still think this is the best idea because they all provide great editors and fork/share functionalities. But in the process, I found they are not very friendly to work with when you try to integrate them in a third-party web application. I was like, okay, let me grab some simple open source web based code editor and and a home screen to where I can throw my widgets in. And that’s exact what I did. I build this thing which allows people to write widgets with css/javascript/html and place them in a home screen. Also, there’s some basic functionality which enables people to share and fork widgets. This thing is still in a very early stage, and is buggy AF. For example, the editor might be too basic, and it only allows authentication through Google OAuth. It was built with Phoenix 1.3 and React. Quite a (re-)learning curve for me. I Haven’t touched Elixir for a while, but find it still charming in the end. If you are interested, please check it out here: https://unidash.io/ All comments and criticizes will be appreciated.

Visit product View on Hacker NewsAug 29, 2017

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

86%86% 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

82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: exist, open source, existing · Missing: https docs, excited, just released

80%80% 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: google, widgets, way · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

47%47% 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

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.

Incorrect prediction on native model

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