Shopify Product CSV Preflight Checker

Find common product CSV problems before attempting an import. Paste your CSV and receive a report with the exact row, affected column, issue and suggested correction. Useful for merchants, catalog assistants and agencies preparing repeated imports.

This is an independent tool. It checks selected file rules and cannot guarantee Shopify will accept an import. It never connects to or changes your store.

What you get

• A summary: rows checked, product groups, variant rows, errors and warnings.
• Row-level findings for malformed rows, missing required headers, duplicate variants, inconsistent option names, duplicate SKUs, invalid prices and inventory risks.
• A full JSON report and a downloadable issues CSV.
• Support for both current product headers and common legacy headers, quoted commas, multi-line cells and UTF-8 BOMs.

Extra image rows are distinguished from variant rows. SKU strings keep their leading zeros. The tool reports issues without silently changing your data.

Run it

1. Export or prepare a Shopify product CSV, then paste its text into Product CSV text.
2. Choose Create new products or Update existing products.
3. Select whether the store has one or multiple inventory locations, if known.
4. Run the Actor and open the full report or issues CSV from the output.

Maximum input: 1 MiB, 5000 non-empty data rows, 300 columns. Findings are capped at 1000; summary counts include additional findings. A malformed quoted row stops parsing and marks the report incomplete. Oversized or empty input fails validation.

Example

The prefilled example is synthetic:

Handle,Title,Option1 Name,Option1 Value,Variant SKU,Variant Price
demo-shirt,Demo Shirt,Size,S,SHIRT-001,19.99
demo-shirt,,Size,S,SHIRT-002,$24.00

The report flags row 3 because the size duplicates row 2 and the price contains a currency symbol. It does not guess the intended size or currency.

{
  "summary": {
    "rowsChecked": 2,
    "errors": 2,
    "warnings": 0,
    "verdict": "FIX_ERRORS"
  }
}

The full output also contains issues, limitations and a reference to Shopify's rules. API users can read the single dataset report item or the REPORT key-value record. ISSUES.csv contains the flat findings.

Interpreting the result

• FIX_ERRORS: correct the reported errors and run the checker again.
• REVIEW_WARNINGS: review inventory, price or update risks with your actual store settings.
• NO_ISSUES_IN_CHECKED_RULES: the implemented checks found no issues. Other Shopify rules and store-specific conflicts can still cause an import to fail.

Update mode always reminds you that existing store state was not checked. Keep a backup and test a small import before changing a catalog.

Limits and data handling

This version does not check inventory CSVs, live store state, category taxonomies, metafield definitions, custom fulfillment integrations, remote image reachability or existing variant IDs. It does not generate or import a corrected file.

The Actor uses deterministic Python rules, without an LLM call, paid API or third-party enrichment service. CSV text is processed on Apify and stored as the run input under Apify's normal storage controls; results are stored in the run dataset and key-value store. The code does not log the input or transmit it to outside services. Only provide product data you are authorized to process. You can delete run/storage records through your Apify account.

One completed report is the intended billing unit. The pricing shown in Apify Console at run time is authoritative. Each run produces one report, even when many issues are found; individual errors are not separate billing units.

Report bugs through the Actor's Issues tab with a small redacted or synthetic example. Rules were checked against Shopify documentation on September 6, 2026.

Local verification

python -m unittest discover -s tests -v

The checker itself uses the Python standard library. The cloud runner uses the Apify SDK pinned in requirements.txt.