ETL Bot
ETL Bot automates the full Extract-Transform-Load (ETL) pipeline for Shopify data at scale. Using multi-threaded Python scripts, it crawls and caches thousands of product records and associated media efficiently. Extracted data is then processed, transformed, and stored in a MongoDB database for easy access and analysis. A companion Vue/NuxtJS Admin Dashboard enables users to edit product details, reorder images, download media archives, and export datasets to Excel — turning complex data management into a smooth, visual workflow.
Timeline
6 month
Team
2 Full-stack Developer
Key Features
Multi-threaded Shopify scraping
Automated data cleaning & transformation
MongoDB data storage
Image download & Excel export
Vue/NuxtJS admin dashboard
Technologies Used
PythonMongoDBNuxtJSREST API
Challenges
Crawling large Shopify stores (4K+ products, 10K+ images) efficiently
Handling rate limits and anti-bot restrictions during scraping
Ensuring accurate data synchronization between raw extracts and MongoDB
Providing non-technical users with an easy way to manage and export product data
Solutions
Built a multi-threaded Python scraper to parallelize crawling and reduce runtime
Implemented intelligent retry, caching, and throttling to avoid API rate limits
Automated data cleaning and recalculation before loading into MongoDB
Designed a Vue/NuxtJS admin dashboard for real-time editing, image management, and Excel exports
Results & Impact
Reduced crawl time from hours to minutes using parallel processing
Successfully processed 4K+ products and 10K+ images with 99% accuracy
Streamlined content management through the admin dashboard
Enabled faster product updates and exports for operational use
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