Shopify Automation: How I Managed an 80,000-Product Catalog with Python & Pandas

Manually managing an e-commerce catalog with 80,000 products, 11 different suppliers, and 5 languages is not just inefficient — it's a direct risk to your business margins. Each supplier sends price lists in different formats (.csv, .xlsx) with inconsistently named columns, making it practically impossible to keep prices, wholesale costs, and stock availability updated by hand. To solve this, I built a Python and Pandas workflow based on three technical pillars: backup management, dynamic price optimization, and automatic product onboarding. 1. Data Architecture: Safety and Golden Backup Catalog integrity starts with two strategic exports from Matrixify: Safety Backup (Daily): Contains only the essential columns (barcode, ID, handle, SKU, price, and quantity). This is the file processed daily for fast syncs. Golden Backup (Weekly): The complete "source of truth" for the entire site, imported into a SQL database for deeper analysis and duplicate management. Each script cross-references