#Expense Tracker App

A full-stack expense tracking application built with MongoDB, Express.js, React, and Node.js. Track your income and expenses, visualize data with charts, generate monthly reports, and export data to CSV.

Features

• 🔐 User Authentication: Secure login/signup with JWT
• 💰 Transaction Management: Add, edit, delete income/expenses with categories
• 📊 Data Visualization: Interactive charts (Pie charts for categories, Line charts for trends) using Chart.js
• 🔍 Advanced Filtering: Filter by date range, category, type (income/expense), and amount
• 💾 Local Storage Fallback: Store transactions locally for offline access and quick loading
• 📈 Monthly Reports: Generate detailed monthly summaries with category breakdowns
• 📥 CSV Export: Download transactions or reports as CSV files
• 📱 Responsive Design: Mobile-friendly UI built with Tailwind CSS
• 🤖 AI-Powered Features:
  • Smart Categorization: Automatically categorize transactions based on description
  • Spending Insights: AI-generated insights and recommendations
  • Anomaly Detection: Detect unusual spending patterns automatically
  • Budget Recommendations: AI-suggested budgets based on your spending patterns
  • Natural Language Entry: Add transactions using plain English (e.g., "spent $50 on groceries yesterday")

Tech Stack

Frontend

• React.js 18
• Redux Toolkit (State Management)
• React Router (Routing)
• Chart.js & react-chartjs-2 (Data Visualization)
• Axios (API Calls)
• Tailwind CSS (Styling)
• json2csv (CSV Export)

Backend

• Node.js
• Express.js
• MongoDB with Mongoose
• JWT (Authentication)
• bcryptjs (Password Hashing)
• express-validator (Input Validation)

Prerequisites

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

Installation

1. Clone the repository

cd "Expense Tracker App"

2. Backend Setup

cd backend
npm install

Create a .env file in the backend directory:

PORT=5000
MONGODB_URI=mongodb://localhost:27017/expense-tracker
JWT_SECRET=your-super-secret-jwt-key-change-this-in-production

Start the backend server:

npm run dev

The backend server will run on http://localhost:5000

3. Frontend Setup

Open a new terminal and navigate to the frontend directory:

cd frontend
npm install

Start the frontend development server:

npm start

The frontend will run on http://localhost:3000

Usage

1. Register/Login: Create a new account or login with existing credentials
2. Add Transactions: Click "Add Transaction" to record income or expenses
3. View Transactions: Browse all your transactions in the list view
4. Filter Data: Use the filter panel to find specific transactions
5. View Charts: Switch to the Charts tab to see visualizations
6. Generate Reports: Go to Reports tab to view monthly summaries
7. Export Data: Export transactions or reports as CSV files

Project Structure

Expense Tracker App/
├── backend/
│   ├── models/
│   │   ├── User.js
│   │   └── Transaction.js
│   ├── routes/
│   │   ├── auth.js
│   │   ├── transactions.js
│   │   └── reports.js
│   ├── middleware/
│   │   └── auth.js
│   ├── server.js
│   └── package.json
├── frontend/
│   ├── public/
│   │   └── index.html
│   ├── src/
│   │   ├── components/
│   │   │   ├── auth/
│   │   │   │   ├── Login.js
│   │   │   │   └── Register.js
│   │   │   ├── charts/
│   │   │   │   └── Charts.js
│   │   │   ├── dashboard/
│   │   │   │   └── SummaryCards.js
│   │   │   ├── filters/
│   │   │   │   └── FilterPanel.js
│   │   │   ├── layout/
│   │   │   │   └── Navbar.js
│   │   │   ├── reports/
│   │   │   │   └── MonthlyReport.js
│   │   │   ├── transactions/
│   │   │   │   ├── TransactionForm.js
│   │   │   │   └── TransactionList.js
│   │   │   ├── Dashboard.js
│   │   │   └── PrivateRoute.js
│   │   ├── store/
│   │   │   ├── slices/
│   │   │   │   ├── authSlice.js
│   │   │   │   └── transactionSlice.js
│   │   │   └── store.js
│   │   ├── utils/
│   │   │   ├── api.js
│   │   │   ├── exportCSV.js
│   │   │   └── localStorage.js
│   │   ├── App.js
│   │   ├── index.js
│   │   └── index.css
│   ├── package.json
│   ├── tailwind.config.js
│   └── postcss.config.js
└── README.md

API Endpoints

Authentication

• POST /api/auth/register - Register a new user
• POST /api/auth/login - Login user
• GET /api/auth/me - Get current user (Protected)

Transactions

• GET /api/transactions - Get all transactions (Protected, supports filters)
• GET /api/transactions/:id - Get a single transaction (Protected)
• POST /api/transactions - Create a new transaction (Protected)
• PUT /api/transactions/:id - Update a transaction (Protected)
• DELETE /api/transactions/:id - Delete a transaction (Protected)
• GET /api/transactions/stats/summary - Get summary statistics (Protected)

Reports

• GET /api/reports/monthly - Get monthly report (Protected)
• GET /api/reports/category-breakdown - Get category breakdown (Protected)
• GET /api/reports/trends - Get trends over time (Protected)

Local Storage

The app uses browser localStorage as a fallback mechanism:

• Transactions are automatically saved to localStorage when created/updated/deleted
• If the API is unavailable, the app can load data from localStorage
• Data syncs with the backend when online

Environment Variables

Backend (.env)

• PORT - Server port (default: 5000)
• MONGODB_URI - MongoDB connection string
• JWT_SECRET - Secret key for JWT tokens

Development

Backend Development

cd backend
npm run dev  # Uses nodemon for auto-reload

Frontend Development

cd frontend
npm start  # Runs on http://localhost:3000

Production Build

Frontend

cd frontend
npm run build

This creates an optimized production build in the build folder.

AI Features

The application includes several AI-powered features to enhance your expense tracking experience:

1. Smart Categorization: Automatically suggests categories based on transaction descriptions using pattern matching and keyword analysis.

2. Spending Insights: Provides intelligent insights such as:

   • Top spending categories
   • Budget health indicators
   • Daily spending averages
   • Spending diversity metrics

3. Anomaly Detection: Identifies unusual spending patterns:

   • Unusually large transactions
   • Spending spikes compared to historical data
   • Patterns that deviate from your normal behavior

4. Budget Recommendations: Suggests appropriate budgets for each category based on your historical spending patterns.

5. Natural Language Entry: Add transactions using conversational language. Examples:

   • "spent $50 on groceries yesterday"
   • "paid $25 for lunch today"
   • "earned $1000 from freelance work"

Note: The current implementation uses rule-based AI and pattern matching. For production use, consider integrating with OpenAI API or similar services for more advanced natural language processing.

Future Enhancements

• Recurring transactions
• Advanced budget management with AI suggestions
• Multi-currency support
• Dark mode
• Email notifications
• Data backup/restore
• Receipt OCR (Optical Character Recognition)
• Integration with OpenAI API for advanced NLP
• Predictive spending forecasts
• Smart alerts and reminders

License

This project is open source and available under the MIT License.

Contributing

Contributions, issues, and feature requests are welcome!

Support

For support, email sasanthasanju1111@gmail.com or create an issue in the repository.