Leo-Health-Core: Import Health Exports into Local SQLite
Summary
Leo-Health-Core parses Apple Health and Whoop exports into a normalized SQLite database for local querying and dashboards. It suits people who want to explore wearable data privately with standard SQL, without sending it to a network service.
At a glance
- Language
- Python
- License
- MIT
- Stars
- 94
- Forks
- 9
- Added to OSRepos
- May 17, 2026
- Last analyzed
- October 3, 2026
Topics
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Overview
Leo-Health-Core is a Python tool for combining Apple Health XML exports and Whoop CSV exports in a local SQLite database. It addresses the difficulty of working with large, differently structured health exports by parsing and normalizing common metrics for SQL queries and a local dashboard.
It is designed for privacy-conscious users comfortable with a command line. Data remains on the user's machine according to the project description; the dashboard is intended for localhost and single-user use.
Key Features
- Parses Apple Health exports from
export.zip, including heart rate, HRV, sleep, workouts, and blood oxygen. - Imports Whoop CSV data for recovery, strain, and sleep.
- Stores normalized records in SQLite for queries across sources.
- Includes terminal and browser-based dashboard commands.
- Watches a folder for new exports and can ingest them automatically.
- Provides Docker support for running the dashboard across operating systems.
- Uses Python's standard library, with the project describing the tool as having zero dependencies.
Use Cases
- Apple Health users who want to query exported measurements with SQLite instead of browsing a large XML export.
- Whoop users who want recovery, strain, and sleep records in a local database.
- Users of both services who want to compare selected metrics across data sources.
- Developers who want a local foundation for analyzing wearable data or building additional integrations.
- Privacy-conscious users who prefer local files and tools over uploading personal health data to a hosted service.
Project Facts
- Language: Python
- License: MIT
- Stars: 94
- Forks: 9
- Archived: No
Getting Started
git clone https://github.com/sandseb123/Leo-Health-Core.git
cd Leo-Health-Core
pip3 install -e .
See the README for platform-specific setup, Docker instructions, supported exports, and usage details.
Alternatives
- fasten-onprem: Fasten OnPrem organizes medical records from FHIR uploads and manual entry, while Leo-Health-Core imports wearable exports into a normalized SQLite database.
Considerations
- The README lists Python 3.9 or newer for direct installation; Docker is offered as an alternative.
- The dashboard has no authentication and is intended for single-user desktop use. Anyone with access to the machine can read the database.
- Ingestion depends on the formats supported by the current parsers. Oura, Fitbit, and Garmin support are listed as roadmap items, not current features.
- The README describes the AI health coach as coming soon; it is not part of the currently described core workflow.
- The repository reports 10 open issues, so check its issue tracker for known gaps before relying on it for a particular export.
Source repository
Open the original repository on GitHub.
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