💰 FinanceApp CLI A secure, role-aware command-line banking system built in Python. Supports user authentication, account management, deposits, withdrawals, audit logging — and now spending forecasts with charting and Excel export.

🚀 Features 🔐 Secure login with bcrypt password hashing

👤 Role-based access: admin vs user

🏦 Account types: Checking, Savings, Retirement

💸 Deposit and withdrawal with overdraft protection

📜 Audit logs for admin and user actions

📊 Spending forecast with chart visualization

📁 Excel export with timestamped reports

🧾 View account summaries and activity history

📈 New Forecasting Capabilities 🧠 Predict next month’s spending using Linear Regression

📅 Group transactions by month for trend analysis

📊 Visualize actual vs predicted spending with matplotlib

📁 Export forecast and historical data to Excel with timestamped filenames

🧪 Simulate multi-month transactions for testing

🛠️ Setup bash git clone https://github.com/jesse-aluiso/FinanceApp-CLI.git cd FinanceApp-CLI Create a .env file:

env DB_HOST=localhost
DB_USER=root
DB_PASSWORD=your_mysql_password
DB_NAME=finance_app_schema Install dependencies:

bash pip install -r requirements.txt Run the CLI:

bash python cli.py 🧪 Testing Use MySQL Workbench or CLI to create the schema and tables. Make sure the database name matches .env. You can simulate past transactions by specifying how many days ago they occurred.

📂 File Structure Code finance_app/ ├── .env ├── db.py ├── auth.py ├── finance_app.py ├── forecast_module.py ├── cli.py ├── user_log.py ├── README.md ├── requirements.txt 📦 requirements.txt text mysql-connector-python
python-dotenv
bcrypt
pandas
scikit-learn
matplotlib
openpyxl 🧠 Data Structures & Logic Relational Tables (SQL-backed) Table Name Purpose users Stores user credentials, roles, and metadata password_history Tracks last 3 password hashes per user audit_log Logs admin actions for accountability transactions Logs deposits/withdrawals with category/date categories User-defined spending categories Python Structures Dictionaries: Used to pass user session data

Lists: Used for password reuse checks

DataFrames: Used for forecasting and Excel export

⚙️ Algorithms and Security bcrypt for password hashing and verification

Password reuse prevention via history tracking

Password expiry enforcement

Audit logging for all admin actions

Forecasting using LinearRegression from scikit-learn

Excel export using pandas and openpyxl

🧩 Opportunities ✅ Security: Strong use of bcrypt, password history, and expiry logic ✅ Scalability: SQL-backed design supports growth and indexing ✅ Auditability: Admin actions are traceable ✅ Analytics: Forecasting and export features mirror enterprise-grade workflows 🧩 Future: Embed charts in Excel, auto-archive reports, add monthly summaries