Vim for Google Docs

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Vim for Google Docs

Hey HN, I’ve been working on a chrome extension the past few months that lets you use Vim keybindings in Google Docs. I’m in college and use Docs for note taking, so I initially started working on this as a toy project. When I realized other people were interested I started putting in more work to polish the extension. After a lot of development (and a lot more to come as well), I think the extension is genuinely a huge productivity boost. I’ve made it customizable, so you can remap keys, including even the regular Google Docs shortcuts. I think I may make a write-up about the technical details, because this project was surprisingly hard to build. Thanks to Google’s proprietary rendering and editing engine, there is only one <canvas> element that stores the whole Google Doc. Unfortunately, the <canvas> doesn’t even store the actual text in your document [1]. This effectively means that there’s no easy way to parse HTML, which led me down a painful path of implementing Vim keybindings via simulating user key presses. If you end up trying it out, let me know what you think, thanks -Viktor [1] https://news.ycombinator.com/item?id=27129858

Visit product View on Hacker NewsJun 22, 2024

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

84%84% 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.

Hacker NewsStrong engagement from HN community · Strong signals: io, including · Missing: https docs, excited, just released

76%76% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Strong signals: started, including · Missing: supports, reddit linkedin, podcasting

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: month, google, way · Missing: mobile apps, ios, personal

59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

31%31% 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

21%21% 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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