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Utilize default validation options to build your desired data import experience.
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Base Validations

List of available validators:

  1. String Validator: This validator ensures that the column value is a string. String and Number are both valid values.
  2. 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.
  3. 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.
  4. Email Validator: With the Email validator, you can ensure that the column value conforms to a valid email format. Valid values look like john@gmail.com while values like john and john.com are not valid.
  5. Regex Validator: The Regex validator enables you to define a custom regular expression pattern that the column value must match.
  6. 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."
  7. Any Validator: Any validator offers maximum flexibility by allowing any value in the column.

Validator Enhancements

  • 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.md.

{% include "../.gitbook/includes/your-feedback-is-crucial-in....md" %}