number_of_outliers_less_or_equal(

max_outliers=3,results = suite.run(train_dataset=train_dataset)

# validation post-processing (e.g. interpret results, take actions) can happen here

return results

Visualizing Deepchecks Suite Results

You can view visualizations of the suites and results generated by your pipeline steps directly in the ZenML dashboard by clicking on the respective artifact in the pipeline run DAG.

Alternatively, if you are running inside a Jupyter notebook, you can load and render the suites and results using the artifact.visualize() method, e.g.:

from zenml.client import Client

def visualize_results(pipeline_name: str, step_name: str) -> None:

pipeline = Client().get_pipeline(pipeline=pipeline_name)

last_run = pipeline.last_run

step = last_run.steps[step_name]

step.visualize()

if __name__ == "__main__":

visualize_results("data_validation_pipeline", "data_integrity_check")

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Last updated 19 days ago