ss', cat_features=['country', 'state']),
    ...
)check_kwargs: Additional keyword arguments to be passed to the Deepchecks check object constructors. Arguments are grouped for each check and indexed using the full check class name or check enum value as dictionary keys, e.g.:Copydeepchecks_data_integrity_check_step(
    check_list=[
        DeepchecksDataIntegrityCheck.TABULAR_OUTLIER_SAMPLE_DETECTION,
        DeepchecksDataIntegrityCheck.TABULAR_STRING_LENGTH_OUT_OF_BOUNDS,
        DeepchecksDataIntegrityCheck.TABULAR_STRING_MISMATCH,
    ],
    check_kwargs={
        DeepchecksDataIntegrityCheck.TABULAR_OUTLIER_SAMPLE_DETECTION: dict(
            nearest_neighbors_percent=0.01,
            extent_parameter=3,
        ),
        DeepchecksDataIntegrityCheck.TABULAR_STRING_LENGTH_OUT_OF_BOUNDS: dict(
            num_percentiles=1000,
            min_unique_values=3,
        ),
    },
    ...
)

run_kwargs: Additional keyword arguments to be passed to the Deepchecks Suite run method.

The check_kwargs attribute can also be used to customize the conditions configured for each Deepchecks test. ZenML attaches a special meaning to all check arguments that start with condition_ and have a dictionary as value. This is required because there is no declarative way to specify conditions for Deepchecks checks. For example, the following step configuration:

deepchecks_data_integrity_check_step(

check_list=[

DeepchecksDataIntegrityCheck.TABULAR_OUTLIER_SAMPLE_DETECTION,

DeepchecksDataIntegrityCheck.TABULAR_STRING_LENGTH_OUT_OF_BOUNDS,

],

dataset_kwargs=dict(label='class', cat_features=['country', 'state']),

check_kwargs={

DeepchecksDataIntegrityCheck.TABULAR_OUTLIER_SAMPLE_DETECTION: dict(

nearest_neighbors_percent=0.01,

extent_parameter=3,

condition_outlier_ratio_less_or_equal=dict(

max_outliers_ratio=0.007,

outlier_score_threshold=0.5,

),

condition_no_outliers=dict(

outlier_score_threshold=0.6,

),

DeepchecksDataIntegrityCheck.TABULAR_STRING_LENGTH_OUT_OF_BOUNDS: dict(

num_percentiles=1000,