I’ve built a personal open-source tool that aggregates the latest posts from Hacker News, Reddit, and Lemmy into a single, sortable table. It supports optional machine translation for titles using the DeepL API, all running locally as a Streamlit app[cite: 4].
- GitHub Repository: [Insert your GitHub Link Here]
- Detailed Design Notes:
DESIGN_NOTES.md/rss_spec.md
Why I built it
- Bypassing Reddit API barriers: As of mid-2026, Reddit’s official API is gated behind a manual approval process, making it difficult for personal, low-volume tools to get access[cite: 4]. This tool avoids the API entirely by using Reddit’s public, unauthenticated
.rssendpoints[cite: 4]. - Solving the IP rate-limiting: Fetching one request per subreddit triggers “429 Too Many Requests” errors. To fix this, the tool combines all subscribed subreddits into a single, shared request (using
hotsort), and then resolves the labels back to their specific subreddits by parsing the links[cite: 3, 4]. - Optimizing DeepL costs: The tool applies date and count filters before sending titles to DeepL, ensuring the translation volume stays comfortably within the free tier (500k chars/month)[cite: 3, 4].
Key Features
- Cross-Platform Aggregation: Unifies Hacker News (hnrss.org), Reddit (combined feed), and Lemmy instances[cite: 3, 4].
- Comment Count Parsing: Automatically parses comment counts for HN and Lemmy feeds[cite: 4].
- Optional Translation: If no
DEEPL_TOKENis provided, the tool skips translation entirely and works with zero API dependencies[cite: 3, 4]. - Simple Configuration: Add or remove feeds by editing a single plain-text CSV (
data/rss_feeds.csv)[cite: 4].
Quick Start
pip install -r requirements.txt
streamlit run app.py
```[cite: 4]
It's a simple, single-process tool built for my own information-gathering workflow, but I’m sharing it in case it’s useful for others looking to manage RSS feeds without relying on proprietary APIs or cloud-based services. Feedback and issues are welcome!
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[action: insert witty comment for quick karma gain] \ [note: evoke dying grandmother to gain pity upvotes]
AI slop filled post.
[Insert your GitHub Link Here]
lol
[cite: 3, 4]
??
Is this whole text LLM generated and you just copy-pasted everything including the (now unlinked) citations and the orders the machine added to the text without double-checking?


