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limo39/mpesa-transaction-cost-calculator

Domaine:

digital infrastructure

Type de record:

software
Créateur:
lim
Hôte:
# M-Pesa Statement Analyzer A web application that processes M-Pesa PDF statements and calculates the total amount spent on transaction costs/fees. ## Features - 📄 **PDF Upload**: Drag & drop or browse to upload M-Pesa statement PDFs - 🔐 **Password Protection**: Handles password-protected M-Pesa statements (6-digit passwords) - 💰 **Cost Analysis**: Automatically extracts and calculates total transaction costs - 📊 **Detailed Breakdown**: Shows individual transaction costs and summary statistics - 📱 **Responsive Design**: Works on desktop and mobile devices - 🎨 **Modern UI**: Clean, professional interface ## How to Use 1. **Start the Application** ```bash # Using Python (recommended) python -m http.server 8000 # Or using Node.js (if you have it installed) npx http-server -p 8000 ``` 2. **Open in Browser** Navigate to `localhost` in your web browser 3. **Upload M-Pesa Statement** - Click the upload area or drag and drop your M-Pesa PDF statement - If the PDF is password-protected, enter the 6-digit password when prompted - The application will process the PDF and extract transaction data 4. **View Results** - See total transaction costs - View number of transactions processed - Check average cost per transaction - Review detailed transaction breakdown ## Supported Transaction Types The analyzer can detect and process costs from various M-Pesa transaction types: - Send Money - Withdraw Cash - Buy Goods - Pay Bill - Airtime Purchase - Data Bundle Purchase - General transaction fees and charges ## Technical Details ### Built With - **HTML5**: Structure and semantics - **CSS3**: Styling and responsive design - **JavaScript**: PDF processing and data analysis - **PDF.js**: Mozilla's PDF parsing library ### How It Works 1. Detects if the uploaded PDF is password-protected 2. Prompts for 6-digit password if needed (typical M-Pesa statement protection) 3. Uses PDF.js to extract text content from uploaded PDF files 4. Applies regex patterns to identify …

Visit

github.com

Tasks

information extraction

Languages

Lusengo

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