def titanic_profiled_name_column_evrs(): #This is a janky way to fetch expectations matching a specific name from an EVR suite. #TODO: It will no longer be necessary once we implement ValidationResultSuite._group_evrs_by_column from great_expectations.render.renderer.renderer import ( Renderer, ) titanic_profiled_evrs_1 = json.load( open("./tests/render/fixtures/BasicDatasetProfiler_evrs.json")) evrs_by_column = Renderer()._group_evrs_by_column(titanic_profiled_evrs_1) print(evrs_by_column.keys()) name_column_evrs = evrs_by_column["Name"] print(json.dumps(name_column_evrs, indent=2)) return name_column_evrs
def test_ProfilingResultsColumnSectionRenderer_render( titanic_profiled_evrs_1, titanic_profiled_name_column_evrs): #Smoke test for titanic names document = ProfilingResultsColumnSectionRenderer().render( titanic_profiled_name_column_evrs) print(document) assert document != {} #Smoke test for titanic Ages #This is a janky way to fetch expectations matching a specific name from an EVR suite. #TODO: It will no longer be necessary once we implement ValidationResultSuite._group_evrs_by_column from great_expectations.render.renderer.renderer import ( Renderer, ) evrs_by_column = Renderer()._group_evrs_by_column(titanic_profiled_evrs_1) print(evrs_by_column.keys()) age_column_evrs = evrs_by_column["Age"] print(json.dumps(age_column_evrs, indent=2)) document = ProfilingResultsColumnSectionRenderer().render(age_column_evrs) print(document)