LiteShoper Product CSV
Safe, deterministic CSV import and export for products and variations
Free
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Overview
LiteShoper Product CSV gives merchants a controlled way to move catalog data in and out of LiteShoper. Export the full catalog or pick products from a searchable list. Import with a dry-run preview that never writes until you confirm.
Rows update products by product_slug and variations by unique sku. Categories and brands are resolved from slug fields (missing ones can be created on apply). Built for shops that maintain stock and pricing in spreadsheets or migrate large catalogs without risky one-click overwrites.
Features
- Export all products, or search/select products and export only those
- One CSV row per variation (canonical UTF-8 columns)
- Import products + variations with strict header validation
- Dry-run preview: create/update actions and per-row errors before writing
- Explicit confirmation checkbox required to apply an import
- Download error CSV when validation fails
- Stale-preview detection if catalog changed after preview
- Map products by slug; map variations by unique SKU
- Supports categories (JSON slugs), brands, GTIN/MPN, package dims, images
- Variation fields: price, cost, stock, backorder, weight, attributes JSON, image path
- Limits: 10 MB file size / 5,000 rows; preview TTL ~30 minutes
- Uses Products admin permission (read to export, write to import)
- Fires stock/product save hooks after a successful apply
- Settings/pending previews retained on deactivate
How to use
- Install LiteShoper Product CSV and activate it with your license key.
- Open Shop → Product CSV.
- Export: click Export all products, or search, tick products, then Export selected.
- Edit the CSV in a spreadsheet that preserves UTF-8 (keep the header row exactly).
- Import: upload the CSV → Preview import.
- Review the dry-run table (line, slug, SKU, action, result). Fix any errors and re-upload if needed.
- When validation is clean, check the confirmation box and click Apply confirmed import.
Tip: Export first to learn the required column names. Variation rows need a unique sku; every row needs product_name and product_slug. Categories use a JSON array of slugs; attributes use a JSON object.