This project was built for merchants and SEO specialists who needed spreadsheet-speed editing without the limitations of the Shopify admin UI. The tool creates a safer path for large-scale metadata work across multiple resource types.
Problem
Updating titles, descriptions, and alt text across large catalogs in Shopify is slow and awkward when done through the native interface. Bulk edits are possible, but the process is usually fragmented and easy to get wrong.
Solution
I built a Python CLI that exports live SEO and media data to CSV, supports manual editing in spreadsheet tools, validates the modified data through a dry-run step, and then pushes the approved changes back through Shopify’s GraphQL Admin API.
Workflow shape
Export, edit, validate, upload
Resources
Products to files
Safety layer
Dry-run validation
API model
GraphQL Admin
Why it holds up operationally
- CSV made the workflow accessible to non-developers without sacrificing control.
- Rate-limit handling watched Shopify API cost budgets and paused work when necessary.
- JSON-in-CSV mapping supported richer image-alt updates for products with multiple media records.
- Environment-driven secrets and clear job modes kept the tool safer to operate across stores.
Note
Open detail
The source notes describe the architecture well, but do not include typical catalog size, average run duration, or whether the tool was used across multiple stores. Those would improve the case study later.
Outcome
The result is a practical bridge between SEO operations and platform APIs: large-scale metadata editing becomes faster, safer, and easier to validate before anything goes live.
