Base Validations
Utilize default validation options to build your desired data import experience.
Last updated
Utilize default validation options to build your desired data import experience.
Last updated
String Validator: This validator ensures that the column value is a string. String and Number are both valid values.
Number Validator: The Number validator verifies that the column value is a valid numeric entry. It only permits numerical values like 12 but will not allow 12.33 and john.
Double Validator: The Double validator verifies that the column value is either a Number or a Number with decimals. Valid values are 12 and 12.5 but john is not valid.
Email Validator: With the Email validator, you can ensure that the column value conforms to a valid email format. Valid values look like [email protected] while values like john and john.com are not valid.
Regex Validator: The Regex validator enables you to define a custom regular expression pattern that the column value must match.
Select Validator: Use the Select validator to restrict column values to a predefined set of options. For instance, you can use it to ensure that a "Gender" column contains only values like "Male" or "Female."
Any Validator: Any validator offers maximum flexibility by allowing any value in the column.
isRequired: Ensures that a value must exist in each cell for the column.
isUnique: Ensures that the value is unique throughout the column.
allowMultiSelect: Accepts multiple values separated by , for the cell.
It's possible to extend validation functionality to adjust according to your needs. Read more in Custom Validation.
If you have any questions, suggestions, or comments. Feel free to reach out to us over Discord. We’re constantly improving to deliver the best Data Importer for your product, and we value your input.