Portfolio Tracker Web Application

A Flask-based web application for tracking stock portfolios, dividends, and portfolio analysis.

Features

• User Authentication: Create an account and securely login to manage your portfolio
• Portfolio Management: Add, edit, and remove stocks from your portfolio
• Real-time Data: Fetches current stock prices and information using Yahoo Finance API
• Dividend Tracking: Monitor dividend income and analyze dividend performance
• Risk Analysis: Advanced portfolio risk metrics
• Historical Returns: Individual stock and portfolio returns
• Responsive Design: Works on desktop and mobile devices

Project Structure

portfolio-tracker/
├── app.py                  # Main application file
├── requirements.txt        # Python dependencies
├── portfolio.db            # SQLite database
├── static/                 # Static files
│   ├── css/
│   │   └── style.css       # Custom CSS
│   └── images/
│       ├── risk_formulas.png
│       ├── sharp.png
│       └── wallstreet.jpeg
└── templates/              # HTML templates
    ├── base.html           # Base template with common elements
    ├── index.html          # Landing page
    ├── login.html          # Login page
    ├── signup.html         # Signup page
    ├── portfolio.html      # Portfolio management page
    ├── dividends.html      # Dividend tracking page
    └── analysis.html       # Portfolio analysis page

Installation and Setup

1. Clone the repository or download the source code

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install the required dependencies:

   pip install -r requirements.txt

4. Create the database directory:

   mkdir -p instance

5. Create the images directory in static folder and add required images:

   mkdir -p static/images

   Copy the following images to the static/images folder:

   • risk_formulas.png
   • sharp.png
   • wallstreet.jpg

6. Run the application:

   python app.py

7. Open your web browser and navigate to http://127.0.0.1:5000

Deployment to Web Hosting

Option 1: Deploy to PythonAnywhere

1. Create an account on PythonAnywhere

2. Upload your project files to PythonAnywhere using their file uploader or by cloning from a Git repository

3. Create a virtual environment and install dependencies:

   mkvirtualenv --python=/usr/bin/python3.9 myenv
   pip install -r requirements.txt

4. Configure a new web app:

   • Go to the Web tab
   • Create a new web app
   • Select "Flask" as the framework
   • Set the Python version to match your local development environment
   • Set the path to your Flask application (app.py)
   • Set the working directory to your project directory

5. Configure WSGI file to point to your app:

   import sys
   path = '/home/yourusername/portfolio-tracker'
   if path not in sys.path:
       sys.path.insert(0, path)
   from app import app as application

6. Restart your web app

Option 2: Deploy to Heroku

1. Create a Procfile in your project root:

   web: gunicorn app:app
   

2. Create a runtime.txt file to specify Python version:

   python-3.9.16
   

3. Ensure your app uses environment variables for sensitive data:

   import os
   app.config['SECRET_KEY'] = os.environ.get('SECRET_KEY', 'your-default-key')
   app.config['SQLALCHEMY_DATABASE_URI'] = os.environ.get('DATABASE_URL', 'sqlite:///portfolio.db')

4. Install the Heroku CLI and login:

   heroku login

5. Create a new Heroku app:

   heroku create portfolio-tracker

6. Set environment variables:

   heroku config:set SECRET_KEY=your-secret-key

7. Push your code to Heroku:

   git add .
   git commit -m "Initial commit"
   git push heroku main

8. Set up a PostgreSQL database on Heroku:

   heroku addons:create heroku-postgresql:hobby-dev

9. Open your deployed application:

   heroku open

Customization

• Account Types: Modify the account options in the app.py file to match your personal accounts
• UI Theme: Customize the colors and styles in the static/css/style.css file
• Add Features: Extend the application with additional features like tax optimization or asset allocation

License

This project is licensed under the MIT License - see the LICENSE file for details.