Great Expectations

Great expectations (GX) is an open-source Python library that allows you to define and check expectations for your data.

Openlayer integrates with GX and you can use any GX expectation as an Openlayer test. Refer to the GX expectations gallery to check all the expectations supported.

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Creating GX tests

To create a GX test, click on “Create test” under the “Great expectations” test.

Then, after the modal is open, select the expectation you are interested in from the dropdown. For example, let’s select the expect_column_mean_to_be_between.

Now, you need to provide the arguments required by the expectation. You can click the link next to “Parameters” to see the documentation for the expectation selected.

In this case, the expectation requires a column, with the name of the column, a min_value, and a max_value. You can provide these arguments by clicking on “Add kwarg”.

The “Threshold” should be kept as “Success is True,” as the expectation will return True if the expectation is met (in this case, if the column mean is between the min_value and the max_value).

Once you have added all the arguments, you can click on “Create test” to create the test.

Refer to the GX expectations gallery to check all the expectations supported.