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)
