nfiguration)

...

context.save_expectation_suite(expectation_suite=suite,

expectation_suite_name=expectation_suite_name,

context.build_data_docs()

return suite

The same approach must be used if you are using a Great Expectations configuration managed by ZenML and are using the Jupyter notebooks generated by the Great Expectations CLI.

Visualizing Great Expectations Suites and 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_name)

last_run = pipeline.last_run

validation_step = last_run.steps[step_name]

validation_step.visualize()

if __name__ == "__main__":

visualize_results("validation_pipeline", "profiler")

visualize_results("validation_pipeline", "train_validator")

visualize_results("validation_pipeline", "test_validator")

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Last updated 18 days ago