def test_render_asset_notes():
# import pypandoc
# print(pypandoc.convert_text("*hi*", to='html', format="md"))
result = PrescriptivePageRenderer._render_asset_notes({
"meta" : {
"notes" : "*hi*"
}
})
print(result)
assert result["content"] == ["*hi*"]
result = PrescriptivePageRenderer._render_asset_notes({
"meta" : {
"notes" : ["*alpha*", "_bravo_", "charlie"]
}
})
print(result)
assert result["content"] == ["*alpha*", "_bravo_", "charlie"]
result = PrescriptivePageRenderer._render_asset_notes({
"meta" : {
"notes" : {
"format": "string",
"content": ["*alpha*", "_bravo_", "charlie"]
}
}
})
print(result)
assert result["content"] == ["*alpha*", "_bravo_", "charlie"]
result = PrescriptivePageRenderer._render_asset_notes({
"meta" : {
"notes" : {
"format": "markdown",
"content": "*alpha*"
}
}
})
print(result)
assert result["content"] == ["<p><em>alpha</em></p>\n"]
result = PrescriptivePageRenderer._render_asset_notes({
"meta" : {
"notes" : {
"format": "markdown",
"content": ["*alpha*", "_bravo_", "charlie"]
}
}
})
print(result)
assert result["content"] == ["<p><em>alpha</em></p>\n", "<p><em>bravo</em></p>\n", "<p>charlie</p>\n"]
def test_expectation_summary_in_render_asset_notes():
result = PrescriptivePageRenderer._render_asset_notes({
"meta" : {},
"expectations" : {}
})
print(result)
assert result["content"] == ['This Expectation suite currently contains 0 total Expectations across 0 columns.']
result = PrescriptivePageRenderer._render_asset_notes({
"meta" : {
"notes" : {
"format": "markdown",
"content": ["hi"]
}
},
"expectations" : {}
})
print(result)
assert result["content"] == [
'This Expectation suite currently contains 0 total Expectations across 0 columns.',
'<p>hi</p>\n',
]
result = PrescriptivePageRenderer._render_asset_notes({
"meta" : {},
"expectations" : [
{
"expectation_type": "expect_table_row_count_to_be_between",
"kwargs": { "min_value": 0, "max_value": None, }
},
{
"expectation_type": "expect_column_to_exist",
"kwargs": { "column": "x", }
},
{
"expectation_type": "expect_column_to_exist",
"kwargs": { "column": "y", }
},
]
})
print(result)
assert result["content"][0] == 'This Expectation suite currently contains 3 total Expectations across 2 columns.'
def test_render_profiled_fixture_expectations(
tetanus_varicella_basic_dataset_profiler_expectations):
rendered_json = PrescriptivePageRenderer.render(
tetanus_varicella_basic_dataset_profiler_expectations)
rendered_page = DefaultJinjaPageView.render(rendered_json)
with open(
'./tests/render/output/test_render_profiled_fixture_expectations.html',
'w') as f:
f.write(rendered_page)
assert rendered_page[:15] == "<!DOCTYPE html>"
assert rendered_page[-7:] == "</html>"
def render(render_object):
"""Render a great expectations object to documentation.
RENDER_OBJECT: path to a GE object to render
"""
with open(render_object, "r") as infile:
raw = json.load(infile)
if "results" in raw:
model = DescriptivePageRenderer.render(raw)
else:
model = PrescriptivePageRenderer.render(raw)
print(DefaultJinjaPageView.render(model))
def test_render_profiled_fixture_expectations_with_distribution(
titanic_dataset_profiler_expectations_with_distribution):
# Tests sparkline
rendered_json = PrescriptivePageRenderer.render(
titanic_dataset_profiler_expectations_with_distribution)
rendered_page = DefaultJinjaPageView.render(rendered_json)
with open(
'./tests/render/output/titanic_dataset_profiler_expectations_with_distribution.html',
'wb') as f:
f.write(rendered_page.encode("utf-8"))
assert rendered_page[:15] == "<!DOCTYPE html>"
assert rendered_page[-7:] == "</html>"