def test_passing_run_id_as_a_parameter_to_warning_and_failure_vo(
warning_failure_validation_operator_data_context, assets_to_validate
):
# this tests whether the run_id, run_name and run_time passed to WarningAndFailureExpectationSuitesValidationOperator
# is saved in the validation result.
data_context = warning_failure_validation_operator_data_context
vo = WarningAndFailureExpectationSuitesValidationOperator(
data_context=data_context,
action_list=[],
name="test",
)
# pass run id
user_run_name = "test_run_name"
run_dt = dateutil.parser.parse("2021-09-11 1:47:03+00:00")
return_obj = vo.run(
assets_to_validate=[assets_to_validate[3]],
run_id={"run_name": user_run_name, "run_time": run_dt},
base_expectation_suite_name="f1",
)
run_results = list(return_obj.run_results.values())
assert (
run_results[0]["validation_result"]["meta"]["run_id"].run_name == user_run_name
)
assert run_results[0]["validation_result"]["meta"]["run_id"].run_time == run_dt
assert (
run_results[1]["validation_result"]["meta"]["run_id"].run_name == user_run_name
)
assert run_results[1]["validation_result"]["meta"]["run_id"].run_time == run_dt
# pass run name
return_obj = vo.run(
assets_to_validate=[assets_to_validate[3]],
run_name=user_run_name,
base_expectation_suite_name="f1",
)
run_results = list(return_obj.run_results.values())
assert (
run_results[0]["validation_result"]["meta"]["run_id"].run_name == user_run_name
)
assert (
run_results[1]["validation_result"]["meta"]["run_id"].run_name == user_run_name
)
# pass run time
return_obj = vo.run(
assets_to_validate=[assets_to_validate[3]],
run_time=run_dt,
base_expectation_suite_name="f1",
)
run_results = list(return_obj.run_results.values())
assert run_results[0]["validation_result"]["meta"]["run_id"].run_time == run_dt
assert run_results[1]["validation_result"]["meta"]["run_id"].run_time == run_dt
def test_errors_warnings_validation_operator_succeeded_vo_result_with_only_failed_warning_suite(
warning_failure_validation_operator_data_context, assets_to_validate):
# this tests whether the WarningAndFailureExpectationSuitesValidationOperator properly returns
# a failed ValidationOperatorResult if there is a failed validation with a suite severity level of "failure"
data_context = warning_failure_validation_operator_data_context
vo = WarningAndFailureExpectationSuitesValidationOperator(
data_context=data_context,
action_list=[],
name="test",
)
# only pass asset that yields succeeded "failure-level" suite and failed "warning-level" suite
return_obj = vo.run(
assets_to_validate=[assets_to_validate[0]],
run_id="test_100",
base_expectation_suite_name="f1",
)
run_results = list(return_obj.run_results.values())
# make sure there are no failed validations with suite severity of failure
assert not any([
run_result for run_result in run_results
if run_result["expectation_suite_severity_level"] == "failure"
and not run_result["validation_result"].success
])
# make sure there is at least one failed validation with suite severity of warning
assert any([
run_result for run_result in run_results
if run_result["expectation_suite_severity_level"] == "warning"
and not run_result["validation_result"].success
])
assert return_obj.success
# only pass asset that yields succeeded "failure-level" suite and succeeded "warning-level" suite
return_obj_2 = vo.run(
assets_to_validate=[assets_to_validate[2]],
run_id="test_100",
base_expectation_suite_name="f1",
)
run_results_2 = list(return_obj_2.run_results.values())
# make sure there are no failed validations with suite severity of failure
assert not any([
run_result for run_result in run_results_2
if run_result["expectation_suite_severity_level"] == "failure"
and not run_result["validation_result"].success
])
# make sure there are no failed validation with suite severity of warning
assert not any([
run_result for run_result in run_results_2
if run_result["expectation_suite_severity_level"] == "warning"
and not run_result["validation_result"].success
])
assert return_obj_2.success
def test_errors_warnings_validation_operator_run_slack_query(
warning_failure_validation_operator_data_context, assets_to_validate
):
data_context = warning_failure_validation_operator_data_context
vo = WarningAndFailureExpectationSuitesValidationOperator(
data_context=data_context,
action_list=[],
name="test",
slack_webhook="https://hooks.slack.com/services/test/slack/webhook",
)
return_obj = vo.run(
assets_to_validate=assets_to_validate,
run_id=RunIdentifier(run_name="test_100"),
base_expectation_suite_name="f1",
)
slack_query = vo._build_slack_query(return_obj)
expected_slack_query = {
"blocks": [
{"type": "divider"},
{
"type": "section",
"text": {
"type": "mrkdwn",
"text": "*FailureVsWarning Validation Operator Completed.*",
},
},
{"type": "divider"},
{
"type": "section",
"text": {"type": "mrkdwn", "text": "*Status*: Failed :x:"},
},
{
"type": "section",
"text": {
"type": "mrkdwn",
"text": "*Batch Id List:* ['ge_batch_id=82a8de83-e063-11e9-8133-acde48001122', "
"'ge_batch_id=82a8de83-e063-11e9-8226-acde48001122', "
"'ge_batch_id=82a8de83-e063-11e9-a53d-acde48001122']",
},
},
{
"type": "section",
"text": {
"type": "mrkdwn",
"text": "*Failed Batches:* ['f1.failure-ge_batch_id=82a8de83-e063-11e9-8133-acde48001122']",
},
},
{
"type": "section",
"text": {"type": "mrkdwn", "text": "*Run Name:* test_100"},
},
{
"type": "section",
"text": {"type": "mrkdwn", "text": "*Run Time:* LOCALEDATE"},
},
{"type": "divider"},
{
"type": "context",
"elements": [
{
"type": "mrkdwn",
"text": "Learn about FailureVsWarning Validation Operators at https://docs.greatexpectations.i"
"o/en/latest/reference/validation_operators/warning_and_failure_expectation_suites_val"
"idation_operator.html",
}
],
},
]
}
# We're okay with system variation in locales (OS X likes 24 hour, but not Travis)
slack_query["blocks"][7]["text"]["text"] = slack_query["blocks"][7]["text"][
"text"
].replace("09/26/2019 13:42:41", "LOCALEDATE")
slack_query["blocks"][7]["text"]["text"] = slack_query["blocks"][7]["text"][
"text"
].replace("09/26/2019 01:42:41 PM", "LOCALEDATE")
expected_slack_query["blocks"][7]["text"]["text"] = expected_slack_query["blocks"][
7
]["text"]["text"].replace("09/26/2019 13:42:41", "LOCALEDATE")
expected_slack_query["blocks"][7]["text"]["text"] = expected_slack_query["blocks"][
7
]["text"]["text"].replace("09/26/2019 01:42:41 PM", "LOCALEDATE")
import json
print(json.dumps(slack_query, indent=2))
print(json.dumps(expected_slack_query, indent=2))
assert slack_query == expected_slack_query
def test_errors_warnings_validation_operator_run_slack_query(basic_data_context_config_for_validation_operator, tmp_path_factory, filesystem_csv_4):
project_path = str(tmp_path_factory.mktemp('great_expectations'))
# NOTE: This setup is almost identical to test_DefaultDataContextAwareValidationOperator.
# Consider converting to a single fixture.
data_context = BaseDataContext(
basic_data_context_config_for_validation_operator,
project_path,
)
data_context.add_datasource("my_datasource",
class_name="PandasDatasource",
batch_kwargs_generators={
"subdir_reader": {
"class_name": "SubdirReaderBatchKwargsGenerator",
"base_directory": str(filesystem_csv_4)
}
}
)
data_context.create_expectation_suite(expectation_suite_name="f1.failure")
df = data_context.get_batch(expectation_suite_name="f1.failure",
batch_kwargs=data_context.build_batch_kwargs("my_datasource", "subdir_reader", "f1"))
df.expect_column_values_to_be_between(column="x", min_value=1, max_value=9)
failure_expectations = df.get_expectation_suite(discard_failed_expectations=False)
data_context.save_expectation_suite(failure_expectations, expectation_suite_name="f1.failure")
data_context.create_expectation_suite(expectation_suite_name="f1.warning")
df = data_context.get_batch(expectation_suite_name="f1.warning",
batch_kwargs=data_context.build_batch_kwargs("my_datasource", "subdir_reader", "f1"))
df.expect_column_values_to_be_between(column="x", min_value=1, max_value=9)
df.expect_column_values_to_not_be_null(column="y")
warning_expectations = df.get_expectation_suite(discard_failed_expectations=False)
data_context.save_expectation_suite(warning_expectations, expectation_suite_name="f1.warning")
data_context.save_expectation_suite(failure_expectations, expectation_suite_name="f2.failure")
data_context.save_expectation_suite(failure_expectations, expectation_suite_name="f3.failure")
data_context.save_expectation_suite(warning_expectations, expectation_suite_name="f2.warning")
data_context.save_expectation_suite(warning_expectations, expectation_suite_name="f3.warning")
vo = WarningAndFailureExpectationSuitesValidationOperator(
data_context=data_context,
action_list=[],
slack_webhook="https://hooks.slack.com/services/test/slack/webhook"
)
my_df_1 = pd.DataFrame({"x": [1, 2, 3, 4, 5], "y": [1, 2, 3, 4, None]})
my_ge_df_1 = ge.dataset.PandasDataset(my_df_1, batch_kwargs={"ge_batch_id":
"82a8de83-e063-11e9-8226-acde48001122"})
my_df_2 = pd.DataFrame({"x": [1, 2, 3, 4, 99], "y": [1, 2, 3, 4, 5]})
my_ge_df_2 = ge.dataset.PandasDataset(my_df_2, batch_kwargs={"ge_batch_id":
"82a8de83-e063-11e9-8133-acde48001122"})
my_df_3 = pd.DataFrame({"x": [1, 2, 3, 4, 5], "y": [1, 2, 3, 4, 5]})
my_ge_df_3 = ge.dataset.PandasDataset(my_df_3, batch_kwargs={"ge_batch_id":
"82a8de83-e063-11e9-a53d-acde48001122"})
return_obj = vo.run(
assets_to_validate=[
my_ge_df_1,
my_ge_df_2,
my_ge_df_3
],
run_id="test_100",
base_expectation_suite_name="f1"
)
slack_query = vo._build_slack_query(return_obj)
expected_slack_query = {
'blocks': [
{'type': 'divider'},
{'type': 'section',
'text': {
'type': 'mrkdwn',
'text': '*FailureVsWarning Validation Operator Completed.*'}},
{'type': 'divider'},
{'type': 'section',
'text': {
'type': 'mrkdwn',
'text': '*Status*: Failed :x:'
}
},
{'type': 'section',
'text': {
'type': 'mrkdwn',
'text': "*Batch Id List:* ['ge_batch_id=82a8de83-e063-11e9-8226-acde48001122', "
"'ge_batch_id=82a8de83-e063-11e9-8133-acde48001122', "
"'ge_batch_id=82a8de83-e063-11e9-a53d-acde48001122']"
}
},
{'type': 'section',
'text': {''
'type': 'mrkdwn',
'text': "*Failed Batches:* ['f1.failure-ge_batch_id=82a8de83-e063-11e9-8133-acde48001122']"
}
},
{'type': 'section',
'text': {
'type': 'mrkdwn', 'text': '*Run ID:* test_100'
}
},
{'type': 'section',
'text': {
'type': 'mrkdwn',
'text': '*Timestamp:* 09/26/2019 13:42:41'
}
},
{'type': 'divider'},
{'type': 'context', 'elements': [
{'type': 'mrkdwn',
'text': 'Learn about FailureVsWarning Validation Operators at https://docs.greatexpectations.io/en/latest/reference/validation_operators/warning_and_failure_expectation_suites_validation_operator.html'
}
]
}
]}
# We're okay with system variation in locales (OS X likes 24 hour, but not Travis)
slack_query['blocks'][7]['text']['text'] = \
slack_query['blocks'][7]['text']['text'].replace('09/26/2019 13:42:41', 'LOCALEDATE')
slack_query['blocks'][7]['text']['text'] = \
slack_query['blocks'][7]['text']['text'].replace('09/26/2019 01:42:41 PM', 'LOCALEDATE')
expected_slack_query['blocks'][7]['text']['text'] = \
expected_slack_query['blocks'][7]['text']['text'].replace('09/26/2019 13:42:41', 'LOCALEDATE')
expected_slack_query['blocks'][7]['text']['text'] = \
expected_slack_query['blocks'][7]['text']['text'].replace('09/26/2019 01:42:41 PM', 'LOCALEDATE')
import json
print(json.dumps(slack_query, indent=2))
print(json.dumps(expected_slack_query, indent=2))
assert slack_query == expected_slack_query
def test_errors_warnings_validation_operator_run_slack_query(
basic_data_context_config_for_validation_operator, tmp_path_factory,
filesystem_csv_4):
#####
#####
#
# WARNING: PY2 SUPPORT IS UNTESTED BECAUSE OF DICTIONARY ORDER ISSUES NOT YET RESOLVED
#
#####
#####
if PY2:
pytest.skip(
"skipping test_errors_warnings_validation_operator_run_slack_query in py2"
)
project_path = str(tmp_path_factory.mktemp('great_expectations'))
# NOTE: This setup is almost identical to test_DefaultDataContextAwareValidationOperator.
# Consider converting to a single fixture.
data_context = ConfigOnlyDataContext(
basic_data_context_config_for_validation_operator,
project_path,
)
data_context.add_datasource("my_datasource",
class_name="PandasDatasource",
base_directory=str(filesystem_csv_4))
data_context.create_expectation_suite(
data_asset_name="my_datasource/default/f1",
expectation_suite_name="failure")
df = data_context.get_batch("my_datasource/default/f1",
"failure",
batch_kwargs=data_context.yield_batch_kwargs(
"my_datasource/default/f1"))
df.expect_column_values_to_be_between(column="x", min_value=1, max_value=9)
failure_expectations = df.get_expectation_suite(
discard_failed_expectations=False)
data_context.save_expectation_suite(
failure_expectations,
data_asset_name="my_datasource/default/f1",
expectation_suite_name="failure")
data_context.create_expectation_suite(
data_asset_name="my_datasource/default/f1",
expectation_suite_name="warning")
df = data_context.get_batch("my_datasource/default/f1",
"warning",
batch_kwargs=data_context.yield_batch_kwargs(
"my_datasource/default/f1"))
df.expect_column_values_to_be_between(column="x", min_value=1, max_value=9)
df.expect_column_values_to_not_be_null(column="y")
warning_expectations = df.get_expectation_suite(
discard_failed_expectations=False)
data_context.save_expectation_suite(
warning_expectations,
data_asset_name="my_datasource/default/f1",
expectation_suite_name="warning")
data_context.save_expectation_suite(
failure_expectations,
data_asset_name="my_datasource/default/f2",
expectation_suite_name="failure")
data_context.save_expectation_suite(
failure_expectations,
data_asset_name="my_datasource/default/f3",
expectation_suite_name="failure")
data_context.save_expectation_suite(
warning_expectations,
data_asset_name="my_datasource/default/f2",
expectation_suite_name="warning")
data_context.save_expectation_suite(
warning_expectations,
data_asset_name="my_datasource/default/f3",
expectation_suite_name="warning")
vo = WarningAndFailureExpectationSuitesValidationOperator(
data_context=data_context,
action_list=[],
slack_webhook="https://hooks.slack.com/services/test/slack/webhook")
my_df_1 = pd.DataFrame({"x": [1, 2, 3, 4, 5], "y": [1, 2, 3, 4, None]})
my_ge_df_1 = ge.from_pandas(my_df_1)
my_ge_df_1._expectation_suite["data_asset_name"] = DataAssetIdentifier(
"my_datasource", "default", "f1")
my_df_2 = pd.DataFrame({"x": [1, 2, 3, 4, 99], "y": [1, 2, 3, 4, 5]})
my_ge_df_2 = ge.from_pandas(my_df_2)
my_ge_df_2._expectation_suite["data_asset_name"] = DataAssetIdentifier(
"my_datasource", "default", "f2")
my_df_3 = pd.DataFrame({"x": [1, 2, 3, 4, 5], "y": [1, 2, 3, 4, 5]})
my_ge_df_3 = ge.from_pandas(my_df_3)
my_ge_df_3._expectation_suite["data_asset_name"] = DataAssetIdentifier(
"my_datasource", "default", "f3")
return_obj = vo.run(
assets_to_validate=[my_ge_df_1, my_ge_df_2, my_ge_df_3],
run_id="test_100")
slack_query = vo._build_slack_query(return_obj)
expected_slack_query = {
'blocks': [{
'type': 'divider'
}, {
'type': 'section',
'text': {
'type': 'mrkdwn',
'text': '*FailureVsWarning Validation Operator Completed.*'
}
}, {
'type': 'divider'
}, {
'type': 'section',
'text': {
'type': 'mrkdwn',
'text': '*Status*: Failed :x:'
}
}, {
'type': 'section',
'text': {
'type':
'mrkdwn',
'text':
'*Data Asset List:* [my_datasource/default/f1, my_datasource/default/f2, my_datasource/default/f3]'
}
}, {
'type': 'section',
'text': {
''
'type': 'mrkdwn',
'text': '*Failed Data Assets:* [my_datasource/default/f2]'
}
}, {
'type': 'section',
'text': {
'type': 'mrkdwn',
'text': '*Run ID:* test_100'
}
}, {
'type': 'section',
'text': {
'type': 'mrkdwn',
'text': '*Timestamp:* 09/26/2019 13:42:41'
}
}, {
'type': 'divider'
}, {
'type':
'context',
'elements': [{
'type':
'mrkdwn',
'text':
'Learn about FailureVsWarning Validation Operators at https://docs.greatexpectations.io/en/latest/reference/validation_operators/warning_and_failure_expectation_suites_validation_operator.html'
}]
}]
}
# We're okay with system variation in locales (OS X likes 24 hour, but not Travis)
slack_query['blocks'][7]['text']['text'] = \
slack_query['blocks'][7]['text']['text'].replace('09/26/2019 13:42:41', 'LOCALEDATE')
slack_query['blocks'][7]['text']['text'] = \
slack_query['blocks'][7]['text']['text'].replace('09/26/2019 01:42:41 PM', 'LOCALEDATE')
expected_slack_query['blocks'][7]['text']['text'] = \
expected_slack_query['blocks'][7]['text']['text'].replace('09/26/2019 13:42:41', 'LOCALEDATE')
expected_slack_query['blocks'][7]['text']['text'] = \
expected_slack_query['blocks'][7]['text']['text'].replace('09/26/2019 01:42:41 PM', 'LOCALEDATE')
import json
print(json.dumps(slack_query, indent=2))
print(json.dumps(expected_slack_query, indent=2))
assert slack_query == expected_slack_query