🚀 ToyPredictor

Welcome to ToyPredictor! This project aims to predict the resale value of toys using machine learning. Currently, I'm in the data engineering phase, collecting and processing data from platforms like eBay and StockX.

🎯 Features

• Data Collection: Automated scripts to scrape product data from eBay and StockX.
• Database Setup: SQL setup scripts to structure and store the collected data.
• Notification Handling: A Flask application to handle post requests and acknowledge notifications from eBay.

📂 Repository Structure

• ScrapingDriver.py: Sets up the web scraping driver with randomized user-agent headers.
• StockXDataCollection.py: Scrapes product data from StockX and stores in the database.
• StockXSQLSetup.py: Defines the SQL database structure for StockX data.
• eBayDataCollection.py: Fetches product data from eBay using the eBay SDK.
• ebaySQLSetup.py: Sets up the SQL database structure for eBay data.
• helpers.py: Utility functions for data extraction and processing.
• postRequests.py: Flask app to handle post requests from eBay.

🚧 Under Development

• Optimize Code: Plans to make the data collection and processing faster.
• Machine Learning Model: The next phase involves building and training a machine learning model to predict toy resale values.

⭐ Future Goals

• Optimize the code to make it faster.
• Implement scheduled API fetches to retrieve data on specific products at designated times.
• Begin the development of the machine learning model.

🤝 Contributing

Contributions, issues, and feature requests are welcome! Feel free to check issues page if you want to contribute.

🐞 Known Bugs

• Data Parsing Issues: While collecting data from eBay and StockX, there are instances where the release date of a product isn't parsed correctly. This is due to the limited cases considered during the parsing process.

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Thank you for checking out ToyPredictor. Happy coding! 🎉