Le

Ledit – a read-only, client-side only Reddit and HN client

Hacker News

Ledit – a read-only, client-side only Reddit and HN client

I've been frustrated with Reddit's recent API turn, and am also not the biggest fan of HN on mobile. I used to take part in discussion years ago on both sites, but have slowly turned into a lurker. As such, I need a slick client that works on both desktop and mobile, that let's me merely consume content, both media and comments, on both sites. I build ledit over the past few nights for exactly that purpose. I gather others might also have a similar need that's not yet filled by other options out there. https://github.com/badlogic/ledit How does it work? * As a default, you see a multi-reddit called ledit mix. It's an set of subreddits my partner in crime combined to a multi-subreddit. Great for quick media fueled dopamine. * Click on the icon in the top left corner to view bookmarked subreddits as well as the entry for hackernews. You can remove bookmarks by clicking the minus icon, or set them as the default by clicking their checkmark. You can also change the theme there if you so wish. Beware my terrible design skills. * When you view a subreddit, indicated by `r/<subreddit>`, you can click the header bar and enter the name of a new subreddit you want to navigate to. No fuzzing with the browser's URL bar. * You can bookmark the currently viewed subreddit via the icon in the top right corner. The icon will not be visible if you've already bookmarked the subreddit. * You can also change the sorting of the currently viewed subreddit. For HN, the sorting lets you pick between news, newest, jobst, ask, show. * Media will be fitted to the screen in a best effort manner. * To view a post's comments, click the comment icon at the bottom of the post. They will be shown inline * To collapse the comments either click the comments icon again, swipe back on mobile, or press Escape on the desktop. * To collaps the children of a comment, click the comment itself. * If you must reply to a comment, click the tiny reply button in its header. You'll be navigated to the comment on either Reddit or HN, where you can reply if you're logged in. * Posts that have an image gallery are marked with an image icon. Click the image (not the icon) to expand and collapse the gallery. * Tap videos to start/pause/resume them. If they scroll out of view, they'll get paused automatically. The whole app is a single page app that directly talks to CORS enabled endpoints of Reddit and Hacker News. In case of Reddit, I use the old `.json` endpoints. No API keys required. In case of Hacker News, I use both the official Firebase API to fetch the stories, then use Algolia and the Firebase API to fetch comments and restore their order (that was fun to figure out...). I could add additional sources that follow the posts -> comments structure pretty easily. I'm open for suggestions.

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, single, tiny · 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
73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: hacker news, ide, io · Missing: https docs, excited, just released
62%62% 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 · Missing: plus, platform, intuitive
35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal
31%31% 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
17%17% 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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