ScaleTrack

A mobile-optimized web application for tracking and visualizing weight data with secure user authentication.

Table of Contents

• About
  • Who Is This For?
• Features
• Screenshots
• Technologies
• Project Structure
• Deployment Instructions
  • Prerequisites
  • Docker Deployment
• Environment Variables
  • Environment Variable Descriptions
• Development Instructions
  • Local Development Setup
  • Database Management
• Data Import/Export
• API Reference
• Roadmap
• Contributing
• License

About

ScaleTrack is designed for individuals who want to monitor their weight changes over time. The application provides an intuitive interface for recording weight measurements, viewing historical data in a table, and visualizing trends through interactive charts.

Who is this for?

ScaleTrack is designed for:

• Health-conscious individuals tracking their weight as part of a fitness journey
• People with specific health goals who need to monitor weight fluctuations
• Fitness coaches who want a simple tool to track client progress
• Anyone interested in logging and analyzing their weight data over time

Currently, deployment requires basic knowledge of Docker and Docker Compose as the project is in an early development stage.

Features

• User Authentication: Secure multi-user system with registration and login
• Password Recovery: Self-service password reset via email
• Mobile-optimized UI: Responsive design works great on smartphones and tablets
• Data Input: Simple form for recording weight values with optional notes
• Data Visualization: Interactive chart showing weight trends over time with floor/ceiling guidelines
• Data Table: Comprehensive table view of all recorded entries
• Secure Data Storage: Each user can only access their own data
• Data Filtering: Filter chart data by date ranges
• Data Export: Export chart visualizations as images
• Data Import: Import weight data from Excel files (see Import/Export section)
• Dark Mode: Support for light and dark themes
• User Settings: Customize application behavior and display preferences

Screenshots

Home Screen - Weight Input	Chart Visualization
Data Table View	User Settings
Login Screen	Excel Data Import

Technologies

• Frontend: Next.js 14+ with TypeScript and Tailwind CSS
• Database: SQLite with Prisma ORM
• Authentication: NextAuth.js for secure user management
• Visualization: Chart.js with react-chartjs-2
• API: Next.js API Routes
• Containerization: Docker support for easy deployment

Deployment Instructions

Prerequisites

• Docker and Docker Compose
• Git
• SMTP server details (for password reset functionality)

Docker Deployment

1. Clone the repository:

   git clone https://github.com/BadWinniePooh/weight-tracking.git
   cd weight-tracking

2. Create and configure the .env file according to the environment variables section

3. Adjust the docker compose yaml to your needs (add labels for traefik, etc.)

4. Build and run the container:

   docker-compose up -d --build

5. Access the application at http://localhost:3000 (or your configured domain)

6. To stop the container:

   docker-compose down

Environment Variables

Create a .env file in the root directory with the following variables:

NODE_ENV=production

# Database configuration
## Default development path:
# DATABASE_URL="file:./prisma/dev.db?connection_limit=1"
## Default production path:
DATABASE_URL="file:/app/data/weight-tracking.db"

# NextAuth.js configuration
NEXTAUTH_SECRET=your-nextauth-secret-key-change-in-production
NEXTAUTH_URL=http://localhost:3000

# Email configuration (for password reset)
EMAIL_SERVER_HOST=smtp.example.com
EMAIL_SERVER_PORT=587
[email protected]
EMAIL_SERVER_PASSWORD=your-email-password
[email protected]
EMAIL_SERVER_SECURE=false

# Timezone configuration
# Use IANA timezone names: Europe/Berlin for Germany (MEZ/CET)
TIMEZONE="Europe/Berlin"

Environment Variable Descriptions

• NODE_ENV: Sets application environment (production/development)
• DATABASE_URL: Connection string for your database (Prisma by default)
• NEXTAUTH_SECRET: A random string used to encrypt cookies and tokens (use a secure random generator)
• NEXTAUTH_URL: The base URL of your deployed application
• EMAIL_SERVER_*: SMTP settings for sending password reset emails
• EMAIL_FROM: The "from" address for outgoing emails
• EMAIL_SERVER_SECURE: TLS setting for connection security (check with your provider whether TLS (true) is used)
• TIMEZONE: Default timezone for date calculations and display

Development Instructions

Local Development Setup

1. Clone the repository:

   git clone https://github.com/BadWinniePooh/weight-tracking.git
   cd weight-tracking

2. Install dependencies:

   npm install

3. Create a .env.local file based on the example above, using:

   DATABASE_URL="file:./prisma/dev.db?connection_limit=1"
   NEXTAUTH_SECRET=any-random-string-for-development
   NEXTAUTH_URL=http://localhost:3000
   

4. Set up the database:

   npx prisma migrate dev

5. Start the development server:

   npm run dev

6. Open http://localhost:3000 in your browser

Database Management

• View your database with Prisma Studio:

  npx prisma studio

• Create a migration after schema changes:

  npx prisma migrate dev --name your_migration_name

• Reset database (deletes all data):

  npx prisma migrate reset

Data Import/Export

Importing Data

ScaleTrack allows you to import weight data from Excel files:

1. Navigate to the Import page (/import)
2. Upload an Excel file (.xlsx) containing your weight data
3. The system expects columns for date and weight measurements (up to 3 per day) with one line for headers

Example Table for reference

date	measurement 1	measurement 2	measurement 3
11.08.2024	102.4		104.4
12.08.2024	...	...	...

Exporting Data

You can export your data in the following formats:

1. Chart Export: From the Chart page, use the export button to save the visualization as a PNG image

Roadmap

Future development plans include in no particular order:

• Add image upload of scale (7 segment display) as alternative input method
• Docker image published to docker hub
• Table export to CSV/Excel
• Multi-language support
• Design improvements

Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Commit your changes: git commit -m 'Add amazing feature'
4. Push to the branch: git push origin feature/amazing-feature
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.