sandseb123

sandseb123 / Leo_Health

Public

Parse Apple Health & Whoop exports into a local SQLite database. Zero dependencies. Zero network requests. MIT licensed.

45
6
100% credibility
Found Feb 19, 2026 at 18 stars 2x -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Leo Health automatically processes exported data files from Apple Health, Whoop, Oura, and Fitbit wearables into a local terminal dashboard showing heart rate, HRV, sleep, workouts, and recovery metrics.

How It Works

1
🔍 Discover Leo Health

You hear about Leo Health, a simple way to bring together all your fitness tracker data into one easy-to-see summary on your computer.

2
📥 Quick setup

Download the folder and run the installer script, which adds two handy shortcuts to your terminal: one to view your dashboard and one to watch for new data.

3
👀 Start the watcher

Launch the watcher command, and it quietly keeps an eye on your Downloads folder, ready to grab any health reports you drop there.

4
📱 Export from your app

From your phone or app like Apple Health, Whoop, Oura, or Fitbit, create an export file and send it to your Downloads folder.

5
⚡ Magic happens automatically

The watcher spots the file, pulls out your heart rates, sleep stages, workouts, and more, and organizes everything neatly for you.

6
📊 Check your dashboard

Type the simple view command anytime to see colorful charts of your average heart rate, sleep breakdown, workouts, and recovery scores.

🎉 Your health insights unlocked

Now you have a private, always-ready summary of your health journey from multiple trackers, all local on your computer with no internet needed.

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Star Growth

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AI-Generated Review

What is Leo_Health?

Leo_Health is a Python tool that parses exports from Apple Health, Whoop, Fitbit, and Oura—turning ZIPs and CSVs into a local SQLite database for querying your fitness data privately. Drop files into Downloads, and the watcher auto-ingests them with zero dependencies or network calls; run `leo` for a terminal dashboard showing heart rate averages, HRV breakdowns, sleep stages, and workouts. It solves the hassle of siloed wearable data by unifying parse Apple Health data alongside Whoop recovery scores into SQL you control.

Why is it gaining traction?

No cloud sync means full privacy for leo health and wellness tracking—no APIs or subscriptions. The CLI hooks like `leo-watch` scanning Downloads and instant `leo` summaries with progress bars beat manual github csv parse scripts or bloated ETL tools. Devs dig the MIT license and stdlib-only purity, perfect for quick local biomed parse github workflows without vendor lock-in.

Who should use this?

Quantified self hackers with Apple Watch or Whoop bands who export data regularly and want SQL over JSON/XML dumps. Python scripters building leo health issues dashboards or custom queries on parse apple health data. Biohackers tired of app silos, needing unified views of HRV, sleep, and recovery across devices.

Verdict

Grab it if you value local parse apple health data—15 stars and 1.0% credibility score signal early days with thin docs, but zero deps and solid CLI make it viable for personal use now. Scale up with your own queries once data flows.

(178 words)

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