Health Auto Export

Overview

This project provides a web interface for viewing Apple Health data via a web interface using Grafana and a Node.js server.

This project aims to be as beginner-friendly as possible, so if you're just getting started with programming, or consider yourself a "non-technical" person, this is a safe space! Of course, this also serves as a great base for the more seasoned developers to build on.

Requirements

In order to use this project, you will need:

1. The Health Auto Export app for iPhone
2. Docker Desktop installed on your computer

Setup Guide

Step 1: Computer Setup

1. Download and install Docker Desktop for your platform here
2. Clone or download this repository to your desired location on your computer
3. Open a terminal/command prompt in the project folder
4. Run sh ./create-env.sh to create the .env file, or create the file manually with the following variables:
   • NODE_ENV: production
   • MONGO_HOST: hae-mongo
   • MONGO_USERNAME: admin
   • MONGO_PASSWORD: mypassword (set a secure password)
   • MONGO_DB: health-auto-export
   • MONGO_PORT: 27017
5. You may need to uncomment the line user: "0:0" in docker-compose.yaml when running Ubuntu.
6. Run docker compose up -d in your terminal.
7. Open Grafana in your browser at http://localhost:3000
8. Login with the default credentials: admin / admin
9. Determine your computer's local IP address and note it down
10. Configure the Health Auto Export app to send data to http://your-computer-ip:3001/api/data as outlined in Step 3

Step 2: Grafana Setup

1. Configure the Grafana data source by selecting Administration in the left sidebar, then search for Infinity
2. Select and install Infinity plugin. After installation, select Add new data source
3. Give the data source a name, for example Health Auto Export
4. In the URL, Headers & Params section, set the Base URL to http://host.docker.internal:3001
5. Select Save & test to complete the data source setup
6. This data source can now be used to create dashboards using the synced data

Step 3: iPhone Setup

1. Install and open the Health Auto Export app on your iPhone
2. Navigate to the Automations tab
3. Create a new automation
4. Configure the automation with the following settings:
   • Automation Type: REST API
   • URL: http://your-computer-ip:3001/api/data
   • Headers: api-key sk-xxx (write token in .env)
   • Data Type: Health Metrics or Workouts (create separate automations for each if you want to sync different data types)
   • Export Format: JSON
   • Aggregate Data: Enabled 🟢
   • Aggregate Interval: Days (this can be adjusted according to the level granularity you want when viewing your data)
   • Batch Requests: Enabled 🟢
5. Tap Update in the top navigation bar to save the automation
6. Use Manual Export to select a date range and manually trigger a data export to your computer

Step 4: Viewing Data

1. Open Grafana in your browser at http://localhost:3000
2. Create a new dashboard or import a pre-configured dashboard as described in Step 5

Step 5: Import Dashboards (Optional)

If you are unfamiliar with Grafana, you can import pre-configured dashboards to get started quickly.

1. Navigate to the Dashboards tab
2. Select New and then Import
3. Upload the dashboard JSON file from the dashboard-examples folder, or copy the JSON into the Import via dashboard JSON model text area
4. You can find a full list of metrics available in MetricName.ts. These can be used in the datasource URL in order to fetch each metric from the database.

Troubleshooting

If you encounter issues:

1. You can use ChatGPT or Claude to help you troubleshoot or fix specific errors
2. Ensure Docker is running
3. If you're still stuck, feel free to reach out using the support options below.

Support

If you need assistance:

• Open an issue on GitHub
• Join the Discord server
• Contact support

Contributing

Your contributions are welcome! Whether it's a bug fix, a new feature, a documentation update, or sharing your dashboards, we appreciate your help.

If you'd like to contribute to this project, create a pull request with your changes.