💰 Expense Tracker - MERN Stack Application

📝 Description

Expense Tracker is a full-stack MERN (MongoDB, Express, React, Node.js) application that helps you manage your personal finances. Track your spending habits, categorize expenses, visualize your financial data, and plan for the future with our built-in compound interest calculator.

✨ Key Features

• 🔐 Secure user authentication
• 💸 Track and categorize expenses
• 📊 Visual representation of spending with interactive charts
• 🧮 Compound interest calculator for financial planning
• 📱 Responsive design for desktop and mobile

📸 Screenshots

🚀 Getting Started

Prerequisites

• Node.js (v14 or higher)
• MongoDB (local or Atlas)
• npm or yarn

⚙️ Installation

1. Clone the repository

   git clone https://github.com/deekshith-b48/ExpenseTracker.git
   cd ExpenseTracker

2. Install dependencies

   npm install

3. Set up environment variables

   • Create a .env file in the root directory
   • Add your MongoDB connection string:

     MONGODB_URI=your_mongodb_connection_string
     

4. Seed the database

   npm run seed

5. Start the development server

   npm run develop

6. Access the application

   • Frontend: http://localhost:3000
   • GraphQL API: http://localhost:3001/graphql

🧩 How to Use

1. Sign Up/Login: Create an account or log in with existing credentials
2. Add Transactions: Enter your expenses with details like amount, date, and category
3. View Analytics: Explore the visual breakdown of your spending habits
4. Financial Planning: Use the compound interest calculator to see potential savings growth

🛠️ Technology Stack

Frontend

• React: UI library for building component-based interfaces
• Apollo Client: GraphQL client for state management and data fetching
• Chart.js & React-Chartjs-2: Data visualization libraries
• Bootstrap & React-Bootstrap: Responsive UI framework
• JWT-Decode: Token decoding for authentication
• React Router DOM: Client-side routing

Backend

• Node.js: JavaScript runtime environment
• Express: Web application framework
• Apollo Server: GraphQL server implementation
• MongoDB: NoSQL database
• Mongoose: MongoDB object modeling
• JWT (JSON Web Tokens): Secure authentication
• Bcrypt: Password hashing

Development Tools

• Concurrently: Run multiple commands concurrently
• Nodemon: Auto-restart server on changes
• dotenv: Environment variable management

🏗️ Application Architecture

┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ │ │ │ │ │
│ React Frontend │◄───────►│ Apollo Server │◄───────►│ MongoDB │
│ │ API │ │ Query │ │
│ (Client-side) │ Requests│ (Server-side) │ Data │ (Database) │
│ │ │ │ │ │
└─────────────────┘ └─────────────────┘ └─────────────────┘

Data Flow

1. User Authentication:

   • User credentials → JWT token generation → Client storage → Protected routes

2. Transaction Management:

   • Create/Read/Update/Delete operations via GraphQL mutations and queries
   • Real-time UI updates through Apollo Client cache

3. Data Visualization:

   • Database data → GraphQL queries → Chart.js rendering → Interactive visualizations

🧮 Core Algorithms

Expense Categorization

function categorizeExpenses(transactions) {
return transactions.reduce((categories, transaction) => {
const category = transaction.category;
if (!categories[category]) {
categories[category] = 0;
}
categories[category] += transaction.amount;
return categories;
}, {});
}

Compound Interest Calculator

function calculateCompoundInterest(principal, rate, time, frequency) {
// A = P(1 + r/n)^(nt)
const n = frequency;
const r = rate / 100;
const t = time;
const P = principal;
return P * Math.pow(1 + r/n, n*t);
}

Spending Analysis

function analyzeSpending(transactions, timeframe) {
// Group by date and calculate totals
const groupedByDate = transactions
.filter(t => isWithinTimeframe(t.date, timeframe))
.reduce((groups, transaction) => {
const date = formatDate(transaction.date);
if (!groups[date]) {
groups[date] = 0;
}
groups[date] += transaction.amount;
return groups;
}, {});
return {
dailyAverage: calculateAverage(Object.values(groupedByDate)),
total: calculateSum(Object.values(groupedByDate)),
trend: calculateTrend(groupedByDate)
};
}

📄 License

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

👥 Contributors

• Deekshith B

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

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

❓ Troubleshooting

• Port already in use: Kill the process using port 3001 with fuser -k 3001/tcp
• Database connection issues: Verify your MongoDB connection string in the .env file
• Login problems: Make sure you're using the correct credentials

📞 Support

If you encounter any issues or have questions, please open an issue on the GitHub repository or contact the development team.

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Happy budgeting! 💸✨