Hi

Hiptex, text editor with recursive block highlighting

Hacker News

Hiptex, text editor with recursive block highlighting

Missing from the header: it's for the iPhone only. So, a 1 minute video of how it looks: http://www.youtube.com/watch?v=hdEPjjQWsxI Whenever you start a block (e.g "(", "[" ) it will update the highlighting of the background to reflect how deep you are. For many language settings though (e.g java/c), the "{" is highlighted as indent lines instead. But basically it's a C++/OpenGL text editor that runs fast enough on an iPhone 3GS (apparently some still use it on that thing). Here's a video of it running on an iPhone: http://www.youtube.com/watch?v=5w8M3F2RdOU (sorry for the video quality) The problem with text editors on a mobile phone is that it's just hard to type on, and nobody would bother typing code on the phone as it's rather hard to do. However, this could probably run nicely on the google glasses. This text editor is lightweight in terms of CPU usage, and is sort of usable on lower resolution (it was running on non-retina 480x320 mode for a while). With some kind of input device I think it'll be possible to use it nicely enough while outside, etc. Probably not something like the keyboard pants though. Thoughts? I thought it might be worth a try showing this around, the project's been out there for more than a year, and it only gets the occasional pickup from people randomly searching for text editors on the app store.

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, code, open · Missing: mac, agents, macos
83%83% 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
74%74% predicted probability of success on Indie Hackers, 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
52%52% 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: video, google · Missing: mobile apps, ios, personal
49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: occasional · Missing: plus, platform, intuitive
41%41% 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
28%28% 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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