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Ikas to Trendyol B2B Bulk Product Migration Bot

An automated ETL (Extract, Transform, Load) Python script engineered to migrate raw e-commerce product exports from the Ikas platform directly into structured Trendyol bulk-upload Excel templates.

Tech stack

Languages
Frameworks & libraries

Performance & metrics

  • Vectorized DataFrame filtering reduces thousands of rows to categorized subsets in milliseconds
  • In-memory Excel manipulation prevents disk I/O bottlenecks during the mapping phase
  • Eliminates hours of manual administrative work, reducing entire catalog migration times to a few seconds

Why I built it

Manually transferring thousands of product variations (frames, albums, magnets) from an Ikas storefront to Trendyol is highly prone to human error and massively time-consuming. Trendyol requires strict formatting, specific category codes, and commission-adjusted pricing. I built this automation bot to completely eliminate manual data entry. It parses the raw Ikas CSV, applies complex heuristic filters to categorize items, automatically recalculates prices based on commission rates, and injects the formatted data directly into Trendyol's proprietary .xlsx templates.

Architecture & decisions

The script utilizes pandas for high-speed, vectorized CSV ingestion and filtering. Products are routed into specific in-memory DataFrames (Frames, Albums, Magnets, Digital Prints) using RegEx masking to prevent overlap. Custom heuristic functions parse unstructured product names to extract metadata like dimensions, colors, and materials. The transformation pipeline computes pricing margins dynamically. Finally, openpyxl accesses the target .xlsx template sheets, maps the structured data to Trendyol's strict column headers, and saves the bulk-upload-ready files without disrupting the original Excel formatting.

Key features

  1. 01Automated parsing and routing of Ikas CSV exports into distinct product categories
  2. 02Heuristic string analysis via Regex to extract dimensions and localize color/material metadata
  3. 03Dynamic margin and commission recalculation pipeline
  4. 04Direct I/O writing to proprietary .xlsx bulk upload templates via openpyxl
  5. 05Strict SKU formatting and automated barcode standardization

Technical review

This project serves as a robust bridging utility between disjointed e-commerce architectures. By treating the migration process as a strict data pipeline, the script ensures absolute data integrity. The complex regex-based extraction logic successfully parses unstructured user-input strings into cleanly localized columns, proving that heavy administrative overhead can be reliably solved with targeted Python automation.