DATASET VERIFY

Verifies structural properties of a dataset against a chosen condition — row count, column count, or column existence. Use this worker in workflow branching to gate downstream steps on a dataset meeting expected shape requirements.

When to use

Classification: process.

Tagged: column_check, data_quality, dataset_check, null_check, row_count, validation, verify.

Inputs

Label ID Type Default Required Description
Dataset dataset dataset   The input dataset to be verified; must be a tabular dataset object connected from an upstream worker.
Columns To Check columnstocheck scalar   One or more column names within the dataset to target for verification; required when using column-scoped checks such as ‘has_col_by_name’.
Verification Type verification_type select num_rows_gt_0   The type of structural check to perform: ‘num_rows_gt_0’ (default) asserts the dataset is non-empty, ‘num_rows_eq_0’ asserts it is empty, ‘num_cols_gt_0’ asserts at least one column exists, and ‘has_col_by_name’ checks for a named column.
Verification value based on Type verification_value text   Auxiliary value required by certain verification types — for example, when verification_type is ‘has_col_by_name’, provide the exact column name string to search for; leave blank for count-based checks.

Outputs

Label ID Type Description
Verification Status dataset_verify_output_1 dataset A single-row dataset reporting the boolean result of the verification check, indicating whether the specified condition was satisfied.

Disciplines

  • data.dataset.transform
  • platform.workflow

Runnable example

A runnable example is registered for this worker. Open the example workflow on the d3VIEW canvas: /api/workflow/example?id=dataset_verify


Auto-generated from transformation schema. Worker id: dataset_verify. Schema hash: cb9323e24f95. Hand-curated docs in workerexamples/ override this page when present.