Finwiz: AI-Powered Personal Finance Dashboard

Welcome to Finwiz, a comprehensive, full-stack personal finance application designed to empower users with intelligent tools for tracking expenses, managing goals, and planning for the future. This application provides a clean, intuitive interface for visualizing financial data and leverages a Python backend for data processing, user management, and AI-powered predictions.

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✨ Core Features

Finwiz is packed with features to provide a complete personal finance management experience:

• Secure User Authentication: Full signup and login functionality with password hashing to ensure user data is secure. Each user's financial data is completely private.
• Dynamic Dashboard: An at-a-glance overview of the user's financial health, including recent transactions, goal progress, and a dynamic expense chart.
• Full Transaction Management (CRUD):
  • Create: Add new income or expense transactions through a user-friendly modal.
  • Read: View a complete, paginated history of all transactions.
  • Delete: Easily remove incorrect or unwanted transactions.
• Goal Management (CRUD):
  • Create: Set new financial goals with a name and a target amount.
  • Read: View all goals and their current progress on the dashboard and a dedicated goals page.
  • Delete: Remove goals that are no longer relevant.
• AI-Powered Expense Prediction: The dashboard features a smart widget that analyzes a user's past spending habits to predict their expenses for the upcoming month, broken down by category.
• Interactive Investment Predictor: A powerful calculator that projects the growth of an investment over time based on initial amount, monthly contributions, and estimated annual interest rate, visualized with a dynamic line chart.
• UPI QR Code Scanner: Quickly add expenses by scanning real-world UPI QR codes. The scanner intelligently parses the recipient's name and the transaction amount to pre-fill the expense form, making data entry fast and seamless.

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🛠️ Tech Stack & Architecture

This project is a full-stack application leveraging modern technologies for a robust and scalable solution.

Area	Technology	Description
Frontend	React.js	A powerful JavaScript library for building dynamic and responsive user interfaces.
	Axios	For making clean, promise-based HTTP requests to the backend API.
	Recharts	A declarative charting library for creating beautiful and interactive data visualizations.
	HTML5-QRCode	A library for integrating camera-based QR code scanning functionality.
Backend	Python	A versatile and powerful language for server-side logic and data processing.
	Flask	A lightweight and flexible web framework for building the REST API.
	Pandas	Used in our AI engine for efficient data manipulation and analysis.
Database	SQLite	A self-contained, serverless SQL database engine perfect for rapid development.

📊 Application Flow Chart

The application follows a standard client-server architecture. The React frontend communicates with the Flask backend via a REST API, and the backend interacts with the SQLite database to store and retrieve user data.

graph TD
    A[User's Browser] -- Interacts with --> B(React Frontend);
    B -- Sends API Requests (Axios) --> C{Flask Backend API};
    C -- Reads/Writes Data --> D[(SQLite Database)];
    D -- Returns Data --> C;
    C -- Sends JSON Response --> B;
    B -- Renders UI --> A;

    subgraph "Client-Side (localhost:3000)"
        B
    end

    subgraph "Server-Side (localhost:5000)"
        C
        D
    end

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🚀 Getting Started

To get a local copy up and running, follow these simple steps.

Prerequisites

• Node.js and npm (for the React frontend)
• Python and pip (for the Flask backend)

Installation & Setup

1. Clone the repository:

   git clone https://github.com/TejasVijaya74/Fin.git
   cd Fin

2. Setup the Backend (Server):

   • Navigate to the server directory.

     cd server

   • Create and activate a Python virtual environment.

     # On Windows
     python -m venv venv
     .\venv\Scripts\activate
     
     # On macOS/Linux
     python3 -m venv venv
     source venv/bin/activate

   • Install the required Python packages.

     pip install -r requirements.txt

   • Initialize the database. (Run this command only once!)

     python init_db.py

   • Run the Flask server.

     flask run

   • Your backend will now be running at http://127.0.0.1:5000.

3. Setup the Frontend (Client):

   • Open a new terminal and navigate to the client directory.

     cd client

   • Install the required npm packages.

     npm install

   • Run the React development server.

     npm start

   • Your frontend will now be running. Open your browser and go to http://localhost:3000.

Default User Credentials

You can log in with the default user created during database initialization:

• Email: test@example.com
• Password: password123

You can also sign up with a new account to start with a blank slate.

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🌐 API Endpoints

The Flask server exposes the following REST API endpoints:

Endpoint	Method	Description
/api/signup	POST	Creates a new user account.
/api/login	POST	Logs in a user and returns their user ID.
/api/transactions	GET	Fetches all transactions for a given userId.
/api/transactions	POST	Adds a new transaction for a given userId.
/api/transactions/<id>	DELETE	Deletes a specific transaction by its ID.
/api/goals	GET	Fetches all goals for a given userId.
/api/goals	POST	Adds a new goal for a given userId.
/api/goals/<id>	DELETE	Deletes a specific goal by its ID.
/api/expense-chart-data	GET	Calculates and returns dynamic expense chart data for a user.
/api/predict-expenses	GET	Predicts a user's future expenses based on their history.
/api/predict-investment	POST	Calculates and returns an investment growth projection.