import unittest
import json

import great_expectations as ge
from great_expectations import render

class TestPageRenderers(unittest.TestCase):

    def test_import(self):
        from great_expectations import render

    def test_prescriptive_expectation_renderer(self):
        results = render.render(
            renderer_class=render.PrescriptiveExpectationPageRenderer,
            expectations=json.load(open('tests/test_fixtures/rendering_fixtures/expectation_suite_3.json'))["expectations"],
        )
        assert results != None

        # with open('./test.html', 'w') as f:
        #     f.write(results)

    def test_descriptive_evr_renderer(self):
        R = render.DescriptiveEvrPageRenderer(
          json.load(open('tests/test_fixtures/rendering_fixtures/evr_suite_3.json'))["results"],
        )
        rendered_page = R.render()
        assert rendered_page != None

        # with open('./test.html', 'w') as f:
        #     f.write(rendered_page)


    def test_full_oobe_flow(sefl):
        df = ge.read_csv("/Users/abe/Documents/superconductive/data/Sacramentorealestatetransactions.csv")
        df.autoinspect(ge.dataset.autoinspect.pseudo_pandas_profiling)
        evrs = df.validate()["results"]

        R = render.DescriptiveEvrPageRenderer(evrs)
        rendered_page = R.render()
        assert rendered_page != None

        # with open('./test.html', 'w') as f:
        #     f.write(rendered_page)
@@ -1037,82 +1037,29 @@
 sv(%22
-/Users/abe/Documents/superconductive/data/Sacramentorealestatetransactions
+examples/data/Titanic
 .csv

Use the Titanic example data set