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I would like to run a check that fails if a column "col1" in my dataset has duplicate values. In the metrics tab I am running the "Distinct value count" on col1 and "Records Counts" on the table. How do I write a custom Python check to determine if the "Distinct value count" on col1 equals "Records Counts" to determine if col1 is unique?

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Here is an example of such a Python check:

# Define here a function that returns the outcome of the check.
def process(last_values, dataset, partition_id):
    # last_values is a dict of the last values of the metrics,
    # with the values as a dataiku.metrics.MetricDataPoint.
    # dataset is a dataiku.Dataset object
    #count_record = last_values["records:COUNT_RECORDS"]["raw"]["value"]
    #count_distinct =
    if last_values["records:COUNT_RECORDS"].get_value()== last_values["col_stats:COUNT_DISTINCT:<PUT_YOUR_COLUMN_NAME_HERE>"].get_value():
        return('OK', "no duplicate")
    	return("ERROR", "duplicates")

[EDIT] I had forgotten to call the get_value() method on last_values["..."]

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