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Documentation Index

Fetch the complete documentation index at: https://docs.qwoty.io/llms.txt

Use this file to discover all available pages before exploring further.

Pre-import validation

After uploading your file and mapping fields, Qwoty validates your data before importing. This lets you catch and fix errors without affecting your existing data.

How it works

The 4-step import wizard surfaces errors at two points:
1

Upload

Drop your CSV file. Qwoty parses it and detects basic issues (file format, encoding, separator).
2

Mapping

Match each header to a Qwoty field. If a required field isn’t mapped, you can’t proceed to the next step.
3

Confirm

Qwoty validates every row against the rules of the target object. The summary shows:
  • The number of records that will be imported
  • The number of variants the file contains (for products)
  • The number of rows with validation errors
Errors don’t block valid rows. You can go back to fix your CSV or proceed.
4

Result

Qwoty processes the file. You see a count of rows imported and rows that failed. If any failed, click Download unimported rows to get a CSV of the failures with the reason for each.

Error display

Errors are surfaced in two ways:
  • At the Confirm step — a summary count tells you how many rows have validation errors before you commit
  • At the Result step — after import, the Download unimported rows button gives you a CSV listing every failed row, the column at fault, and the validation message
The unimported-rows CSV is the same format as your original file, plus an error_reason column. Fix the rows in your spreadsheet and re-upload — only the failed rows are processed on the second import.

Common error types

Duplicate values

Cause: A unique field (like product_api_name) already exists in Qwoty or appears twice in your file. Fix:
  • Edit the duplicate value in your CSV and re-upload
  • Remove one of the duplicate rows
  • If you intended to update the existing record, populate the id column (the import detects updates automatically)
See Uniqueness constraints for the full list of unique fields.

Invalid format

Cause: A value doesn’t match the expected format — invalid UUID, wrong date format, lowercase enum where Qwoty expects capitalized values, percentage out of range. Fix: Edit the cell to match the expected format. See Field mapping for the format requirements of each field type. Common offenders:
  • pricing_model = flat instead of Flat (case-sensitive)
  • settings[recurrence_type] = monthly instead of recurring
  • default_vat = 20.0 instead of FR_200
  • amount = 99,00 instead of 99.00 (wrong decimal separator)
  • settings[is_active] = TRUE instead of true (booleans must be lowercase)

Missing required fields

Cause: A column marked with * in the Mapping step is empty for a given row. Fix: Enter a value in the required field, or remove the row from your file.

Relation not found

Cause: The referenced record doesn’t exist — for example, a parent_product_api_name that points to a master that wasn’t imported, or a pricebook_id referencing a pricebook that doesn’t exist. Fix:
  • Import the parent records first (see Import order)
  • Or correct the reference value to match an existing record

Inconsistent values within a master

Cause: Two variants of the same master declare different settings[recurrence_type], different option names, or different shipping defaults. Fix: Standardize the values across all variants of the same master. A master has a single recurrence type and a single set of option names — variants only differ on option values.

Wrong file separator

Cause: Your CSV uses semicolon ; instead of comma , (or vice versa). Qwoty expects comma. Fix: Re-export your file with comma as the separator. In Excel, save as CSV UTF-8 (Comma delimited).

Tips for fewer errors

  1. Download the example file from the import screen first — it shows the exact column headers and expected formats
  2. Clean your data in your spreadsheet first — remove blank rows, fix typos, normalize enum values
  3. Import files in the correct order — Master products → Products → Prices
  4. Test with small batches before importing thousands of rows — fix the systematic issues, then run the full import
  5. Check for duplicates before uploading — sort your file by the unique field
  6. Limit your file size — split very large datasets into batches of a few thousand rows each, or use the API

Field mapping

Format requirements for every field type.

Uniqueness constraints

Which fields are unique and how to use them.

Import relations

The right import order to avoid relation errors.

Prepare your CSV

Step-by-step preparation guide.