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Intent Bus – SQLite job bus for coordinating scripts across devices

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Intent Bus – SQLite job bus for coordinating scripts across devices

I wanted my PythonAnywhere scrapers to ping my Termux phone when something interesting happened. Every solution I found was overkill — Firebase, Redis, MQTT. So I built a minimal alternative in ~100 lines of Flask. How it works: - Any script POSTs a job ("intent") to a Flask server - Workers anywhere poll for jobs matching their goal - Atomic SQLite lock prevents race conditions - 60s visibility timeout auto-requeues crashed workers - API key auth The interesting part is the architecture — workers poll outbound, so they work behind firewalls with no open ports. A Raspberry Pi in your home lab can execute jobs posted from a cloud server with zero Ngrok. After posting publicly, people stress-tested the open endpoint. Added API key auth and hardened it based on real feedback. GitHub: https://github.com/dsecurity49/Intent-Bus Dev.to writeup: https://dev.to/d_security/how-i-control-my-android-phone-fro...

Visit productView on Hacker NewsApr 27, 2026
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
68%68% predicted probability of success on Indie Hackers, 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 · Missing: https docs, excited, just released
60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: grok, open · Missing: mac, agents, macos
52%52% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
44%44% 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
34%34% 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
23%23% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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