JudoChinX

JudoChinX / rangarr

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Rangarr automates and staggers media searches across your Radarr, Sonarr, and Lidarr instances.

51
1
100% credibility
Found Mar 28, 2026 at 51 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Rangarr automates staggered searches for missing media and upgrades across Radarr, Sonarr, and Lidarr instances to keep libraries complete without overwhelming indexers or APIs.

How It Works

1
👂 Discover Rangarr

You hear about Rangarr, a helpful companion for your movie, TV show, and music organizer apps that keeps your collection complete by smartly searching for missing pieces.

2
📥 Grab setup files

Download simple ready-made files to get started quickly from the project's page.

3
🔗 Connect your apps

Add the web addresses of your movie, TV, and music organizers so Rangarr knows where to look.

4
⚙️ Pick your preferences

Choose how often it runs, how many items to check at a time, and how to prioritize searches to fit your needs.

5
🧪 Test it out first

Run a pretend mode to see what it plans to do and make sure everything looks right in the logs.

6
🚀 Launch for real

Switch to live mode and watch as it gently searches, staggering requests to avoid overload, filling gaps in your library.

✅ Enjoy complete library

Your media collection stays fresh and full automatically, without you lifting a finger, all safely and privately.

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Star Growth

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AI-Generated Review

What is rangarr?

Rangarr is a Python service that automates and staggers media searches across Radarr, Sonarr, and Lidarr instances, keeping your movie, TV, and music libraries complete without slamming indexers or hitting API limits. It runs periodic cycles to hunt missing items and upgrades, interleaving them proportionally with configurable batch sizes, weights per instance, and retry windows. Docker Compose setup is dead simple—just drop in your API keys and hosts.

Why is it gaining traction?

Unlike bloated alternatives, Rangarr stays lean with no database, no telemetry, and zero external connections beyond your own *arr apps, addressing privacy gripes head-on. Developers dig the smart staggering (e.g., 30s delays), search ordering (like last-searched first), and dry-run mode for safe testing. Docker images for amd64/arm64 and solid config validation make it plug-and-play for homelabs.

Who should use this?

Homelab operators juggling multiple Radarr 4K/movie instances, Sonarr libraries, or Lidarr collections who manually trigger searches too often. Power users tweaking weights to prioritize movies over music, or anyone dodging thundering herds during bulk upgrades. Python/Docker fans wanting scheduled automation without Overseerr-style complexity.

Verdict

Grab it if you run *arr stacks and need hands-off searching—docs, SECURITY.md, and CI badges show polish despite 34 stars and 1.0% credibility score signaling early maturity. Test in dry-run first; it's MIT-licensed and verifiable in minutes.

(187 words)

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