Automated Stock Tracking System

An intelligent, Python-based Stock Tracking System that automates the process of monitoring product availability on e-commerce websites. The system sends real-time notifications via Telegram when the stock status of a tracked product changes.

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Features

• Automatic Stock Status Detection: Dynamically identifies stock status elements on e-commerce websites using keyword matching and machine learning.
• Real-Time Notifications: Sends instant alerts via Telegram when stock status changes.
• Multi-Site Support: Works across multiple e-commerce platforms by adapting to different website structures.
• Machine Learning Integration: Uses a Random Forest Classifier to improve stock status prediction accuracy.
• User-Friendly Interface: A clean and responsive web interface built with Flask.
• QR Code Integration: Easily connect to the Telegram bot using a QR code.
• Database Support: Stores user data, product URLs, and tracking history in an SQLite database.
• Scalable and Customizable: Well-documented code for easy customization and deployment on cloud platforms like Heroku, AWS, and Google Cloud.

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How It Works

1. User Input: The user enters the product URL in the web interface.
2. HTML Scraping: Selenium opens the product page and retrieves the HTML content.
3. Stock Status Detection: BeautifulSoup parses the HTML, and the machine learning model predicts the stock status.
4. Notification Sending: If the stock status changes, a notification is sent to the user via Telegram.
5. Database Update: The stock status is updated in the SQLite database.

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Technologies Used

• Python: Primary programming language
• Flask: Web framework for the user interface
• Selenium: Browser automation for web scraping
• BeautifulSoup: HTML parsing library
• Scikit-learn: Machine learning library for stock status prediction
• SQLite: Lightweight database for storing user data and product information
• Telegram API: Sends real-time notifications to users
• QR Code Generation: Simplifies Telegram bot setup

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Installation

1. Clone the repository:

   git clone https://github.com/your-username/stock-tracking-system.git
   cd stock-tracking-system

2. Install the required dependencies:

   pip install -r requirements.txt

3. Set up your Telegram bot:

   • Create a bot using BotFather and get the bot token
   • Replace the TELEGRAM_BOT_TOKEN and TELEGRAM_CHAT_ID in app.py with your bot token and chat ID

4. Run the application:

   python app.py

5. Open your browser and navigate to http://127.0.0.1:5000 to access the web interface.

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Usage

1. Add Product URL: Enter the product URL in the web interface and click "Start Tracking."
2. Track Stock Status: The system will periodically check the stock status and send notifications via Telegram.
3. QR Code Setup: Scan the QR code to connect to the Telegram bot and receive notifications.

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Future Work

• Support for More E-commerce Platforms: Add site-specific rules for additional websites.
• Advanced Machine Learning Models: Improve accuracy with more complex models and larger datasets.
• Multi-User Support: Allow multiple users to track products with individual accounts.
• Integration with Other Messaging Platforms: Add support for WhatsApp, Slack, or email notifications.
• Mobile App Development: Create a mobile app for easier access and tracking.

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License

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

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Contact

For questions or feedback, feel free to reach out:

• Email: nisacayir@icloud.com
• GitHub: https://github.com/nisacayir
• LinkedIn: https://linkedin.com/in/nisacayir