Expense Tracker Pro

Production-grade Python application demonstrating OOP, SOLID principles, and 4 design patterns. Enterprise-level code with logging, error handling, and type hints.

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Features

• ✅ Add/View/Delete Expenses with automatic validation
• ✅ Advanced Analytics (min, max, average, totals)
• ✅ Category-wise Breakdown with percentage charts
• ✅ Filtering by category and date range
• ✅ CSV Export for external analysis
• ✅ Comprehensive Logging (file + console)
• ✅ Production-Grade Error Handling
• ✅ Type Hints & Custom Exceptions

Installation

Requirements: Python3 No external dependencies needed! Just run: python expense_tracker.py

Usage Examples

Add an Expense

 Enter your choice (1-9): 1
Enter date (DDMMYyyyy): 07122025
Select category (1-8): 1
Enter description: Coffee at Cafe
Enter amount (₹): 150
Expense added: Coffee at Cafe (₹150)

View Total Spending

Enter your choice (1-9): 3
TOTAL SPENDING SUMMARY
Total Expenses: 5
Total Spending: ₹2,500.00
Average Expense: ₹500.00

Export to CSV

Enter your choice (1-9): 7
Exported 5 expenses to expenses_export.csv

Configuration

Data Storage

• Format: JSON (expenses.json)
• Location: Root directory
• Auto-created: Yes, on first run

Logging

• File: logs/expense_tracker.log
• Levels: DEBUG (file), INFO (console)
• Auto-created: Yes

Categories

ExpenseCategory:
  1. Food
  2. Travel
  3. Shopping
  4. Entertainment
  5. Utilities
  6. Health
  7. Education
  8. Other

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Example Output

View All Expenses:

ALL EXPENSES
────────────────────────────────────────────────────────────
#    Date       Category        Description         Amount
────────────────────────────────────────────────────────────
1    07122025   Food            Coffee               ₹150.00
2    07122025   Travel          Taxi                 ₹300.00
3    08122025   Shopping        Books                ₹1,200.00
────────────────────────────────────────────────────────────

Category Breakdown:

SPENDING BY CATEGORY
──────────────────────────────────────
Shopping        ████████████░░   ₹1,200.00 (48.0%)
Travel          ██████░░░░░░░░   ₹300.00  (12.0%)
Food            ████░░░░░░░░░░   ₹150.00  (6.0%)
──────────────────────────────────────
TOTAL                             ₹2,500.00 (100.0%)

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Architecture

Design Patterns Implemented:

• Singleton: LoggerSetup (centralized logging)
• Repository: DataRepository + JSONRepository
• Strategy: Multiple filtering approaches
• Enum: Type-safe categories

SOLID Principles:

• Single Responsibility: Each class has one purpose
• Open/Closed: Easy to extend (add SQLRepository)
• Liskov Substitution: Any repository implementation works
• Interface Segregation: Minimal, focused interfaces
• Dependency Injection: Manager receives repository as parameter

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Contributing

Ideas for Extensions

1. Database Integration - Add SQLRepository for PostgreSQL/MySQL
2. Budget Limits - Set spending caps per category
3. Monthly Reports - Generate comprehensive monthly analysis
4. Web Interface - Convert to Flask/Django web app
5. Data Visualization - Add matplotlib charts

Feedback

If you have any feedback, please reach out to me at samithnitta1@gmail.com

📄 License

MIT License file for details.