def get_metric(self, metric_name, **kwargs):
metric_name_parts = metric_name.split(".")
metric_kwargs_id = get_metric_kwargs_id(metric_name, kwargs)
metric_value = None
# Expose overall statistics
if metric_name_parts[0] == "statistics":
if len(metric_name_parts) == 2:
return self.statistics.get(metric_name_parts[1])
else:
raise ge_exceptions.UnavailableMetricError(
"Unrecognized metric {}".format(metric_name)
)
# Expose expectation-defined metrics
elif metric_name_parts[0].lower().startswith("expect_"):
# Check our cache first
if (metric_name, metric_kwargs_id) in self._metrics:
return self._metrics[(metric_name, metric_kwargs_id)]
else:
for result in self.results:
try:
if (
metric_name_parts[0]
== result.expectation_config.expectation_type
):
metric_value = result.get_metric(metric_name, **kwargs)
break
except ge_exceptions.UnavailableMetricError:
pass
if metric_value is not None:
self._metrics[(metric_name, metric_kwargs_id)] = metric_value
return metric_value
raise ge_exceptions.UnavailableMetricError(
"Metric {} with metric_kwargs_id {} is not available.".format(
metric_name, metric_kwargs_id
)
)
def get_metric(self, metric_name, **kwargs):
if not self.expectation_config:
raise ge_exceptions.UnavailableMetricError(
"No ExpectationConfig found in this ExpectationValidationResult. Unable to "
"return a metric."
)
metric_name_parts = metric_name.split(".")
metric_kwargs_id = get_metric_kwargs_id(metric_name, kwargs)
if metric_name_parts[0] == self.expectation_config.expectation_type:
curr_metric_kwargs = get_metric_kwargs_id(
metric_name, self.expectation_config.kwargs
)
if metric_kwargs_id != curr_metric_kwargs:
raise ge_exceptions.UnavailableMetricError(
"Requested metric_kwargs_id (%s) does not match the configuration of this "
"ExpectationValidationResult (%s)."
% (metric_kwargs_id or "None", curr_metric_kwargs or "None")
)
if len(metric_name_parts) < 2:
raise ge_exceptions.UnavailableMetricError(
"Expectation-defined metrics must include a requested metric."
)
elif len(metric_name_parts) == 2:
if metric_name_parts[1] == "success":
return self.success
else:
raise ge_exceptions.UnavailableMetricError(
"Metric name must have more than two parts for keys other than "
"success."
)
elif metric_name_parts[1] == "result":
try:
if len(metric_name_parts) == 3:
return self.result.get(metric_name_parts[2])
elif metric_name_parts[2] == "details":
return self.result["details"].get(metric_name_parts[3])
except KeyError:
raise ge_exceptions.UnavailableMetricError(
"Unable to get metric {} -- KeyError in "
"ExpectationValidationResult.".format(metric_name)
)
raise ge_exceptions.UnavailableMetricError(
"Unrecognized metric name {}".format(metric_name)
)