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Merged
mredolatti merged 6 commits into from
Oct 31, 2019
Merged

Stack inspection performance issue #161

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43a95e5
remove stack inspection code, forward names manually
mredolatti Oct 30, 2019
26e3695
fix error messages
mredolatti Oct 30, 2019
babbdb2
remove print statement
mredolatti Oct 30, 2019
4fee7a0
fix tests
mredolatti Oct 30, 2019
3c2b13c
update changes & version
mredolatti Oct 31, 2019
fa304f5
fix version
mredolatti Oct 31, 2019
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3 changes: 3 additions & 0 deletions CHANGES.txt
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Original file line number Diff line number Diff line change
@@ -1,3 +1,6 @@
8.1.6 (Oct 31, 2019)
- Fixed input validation performance issue.

8.1.4 (Oct 14, 2019)
- Added logic to fetch multiple splits at once on get_treatments/get_treatments_with_config.
- Added flag `ipAddressesEnabled` into config to enable/disable sending machineName and machineIp when data is posted in headers.
Expand Down
189 changes: 100 additions & 89 deletions splitio/client/client.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,8 @@ class Client(object): # pylint: disable=too-many-instance-attributes

_METRIC_GET_TREATMENT = 'sdk.getTreatment'
_METRIC_GET_TREATMENTS = 'sdk.getTreatments'
_METRIC_GET_TREATMENT_WITH_CONFIG = 'sdk.getTreatmentWithConfig'
_METRIC_GET_TREATMENTS_WITH_CONFIG = 'sdk.getTreatmentsWithConfig'

def __init__(self, factory, labels_enabled=True, impression_listener=None):
"""
Expand Down Expand Up @@ -103,39 +105,25 @@ def _evaluate_if_ready(self, matching_key, bucketing_key, feature, attributes=No
attributes
)

def get_treatment_with_config(self, key, feature, attributes=None):
"""
Get the treatment and config for a feature and key, with optional dictionary of attributes.

This method never raises an exception. If there's a problem, the appropriate log message
will be generated and the method will return the CONTROL treatment.

:param key: The key for which to get the treatment
:type key: str
:param feature: The name of the feature for which to get the treatment
:type feature: str
:param attributes: An optional dictionary of attributes
:type attributes: dict
:return: The treatment for the key and feature
:rtype: tuple(str, str)
"""
def _make_evaluation(self, key, feature, attributes, method_name, metric_name):
try:
if self.destroyed:
self._logger.error("Client has already been destroyed - no calls possible")
return CONTROL, None

start = int(round(time.time() * 1000))

matching_key, bucketing_key = input_validator.validate_key(key)
matching_key, bucketing_key = input_validator.validate_key(key, method_name)
feature = input_validator.validate_feature_name(
feature,
self.ready,
self._factory._get_storage('splits') # pylint: disable=protected-access
self._factory._get_storage('splits'), # pylint: disable=protected-access
method_name
)

if (matching_key is None and bucketing_key is None) \
or feature is None \
or not input_validator.validate_attributes(attributes):
or not input_validator.validate_attributes(attributes, method_name):
return CONTROL, None

result = self._evaluate_if_ready(matching_key, bucketing_key, feature, attributes)
Expand All @@ -150,7 +138,7 @@ def get_treatment_with_config(self, key, feature, attributes=None):
start
)

self._record_stats(impression, start, self._METRIC_GET_TREATMENT)
self._record_stats([impression], start, metric_name)
self._send_impression_to_listener(impression, attributes)
return result['treatment'], result['configurations']
except Exception: # pylint: disable=broad-except
Expand All @@ -166,80 +154,29 @@ def get_treatment_with_config(self, key, feature, attributes=None):
bucketing_key,
start
)
self._record_stats(impression, start, self._METRIC_GET_TREATMENT)
self._record_stats([impression], start, metric_name)
self._send_impression_to_listener(impression, attributes)
except Exception: # pylint: disable=broad-except
self._logger.error('Error reporting impression into get_treatment exception block')
self._logger.debug('Error: ', exc_info=True)
return CONTROL, None

def get_treatment(self, key, feature, attributes=None):
"""
Get the treatment for a feature and key, with an optional dictionary of attributes.

This method never raises an exception. If there's a problem, the appropriate log message
will be generated and the method will return the CONTROL treatment.

:param key: The key for which to get the treatment
:type key: str
:param feature: The name of the feature for which to get the treatment
:type feature: str
:param attributes: An optional dictionary of attributes
:type attributes: dict
:return: The treatment for the key and feature
:rtype: str
"""
treatment, _ = self.get_treatment_with_config(key, feature, attributes)
return treatment

def _evaluate_features_if_ready(self, matching_key, bucketing_key, features, attributes=None):
if not self.ready:
return {
feature: {
'treatment': CONTROL,
'configurations': None,
'impression': {'label': Label.NOT_READY, 'change_number': None}
}
for feature in features
}

return self._evaluator.evaluate_features(
features,
matching_key,
bucketing_key,
attributes
)

def get_treatments_with_config(self, key, features, attributes=None):
"""
Evaluate multiple features and return a dict with feature -> (treatment, config).

Get the treatments for a list of features considering a key, with an optional dictionary of
attributes. This method never raises an exception. If there's a problem, the appropriate
log message will be generated and the method will return the CONTROL treatment.
:param key: The key for which to get the treatment
:type key: str
:param features: Array of the names of the features for which to get the treatment
:type feature: list
:param attributes: An optional dictionary of attributes
:type attributes: dict
:return: Dictionary with the result of all the features provided
:rtype: dict
"""
def _make_evaluations(self, key, features, attributes, method_name, metric_name):
if self.destroyed:
self._logger.error("Client has already been destroyed - no calls possible")
return input_validator.generate_control_treatments(features)
return input_validator.generate_control_treatments(features, method_name)

start = int(round(time.time() * 1000))

matching_key, bucketing_key = input_validator.validate_key(key)
matching_key, bucketing_key = input_validator.validate_key(key, method_name)
if matching_key is None and bucketing_key is None:
return input_validator.generate_control_treatments(features)
return input_validator.generate_control_treatments(features, method_name)

if input_validator.validate_attributes(attributes) is False:
return input_validator.generate_control_treatments(features)
if input_validator.validate_attributes(attributes, method_name) is False:
return input_validator.generate_control_treatments(features, method_name)

features, missing = input_validator.validate_features_get_treatments(
method_name,
features,
self.ready,
self._factory._get_storage('splits') # pylint: disable=protected-access
Expand Down Expand Up @@ -269,8 +206,8 @@ def get_treatments_with_config(self, key, features, attributes=None):
treatments[feature] = (result['treatment'], result['configurations'])

except Exception: # pylint: disable=broad-except
self._logger.error('get_treatments: An exception occured when evaluating '
'feature ' + feature + ' returning CONTROL.')
self._logger.error('%s: An exception occured when evaluating '
'feature %s returning CONTROL.' % (method_name, feature))
treatments[feature] = CONTROL, None
self._logger.debug('Error: ', exc_info=True)
continue
Expand All @@ -282,15 +219,91 @@ def get_treatments_with_config(self, key, features, attributes=None):
for impression in bulk_impressions:
self._send_impression_to_listener(impression, attributes)
except Exception: # pylint: disable=broad-except
self._logger.error('get_treatments: An exception when trying to store '
'impressions.')
self._logger.error('%s: An exception when trying to store '
'impressions.' % method_name)
self._logger.debug('Error: ', exc_info=True)

return treatments
except Exception: # pylint: disable=broad-except
self._logger.error('Error getting treatment for features')
self._logger.debug('Error: ', exc_info=True)
return input_validator.generate_control_treatments(list(features))
return input_validator.generate_control_treatments(list(features), method_name)

def _evaluate_features_if_ready(self, matching_key, bucketing_key, features, attributes=None):
if not self.ready:
return {
feature: {
'treatment': CONTROL,
'configurations': None,
'impression': {'label': Label.NOT_READY, 'change_number': None}
}
for feature in features
}

return self._evaluator.evaluate_features(
features,
matching_key,
bucketing_key,
attributes
)

def get_treatment_with_config(self, key, feature, attributes=None):
"""
Get the treatment and config for a feature and key, with optional dictionary of attributes.

This method never raises an exception. If there's a problem, the appropriate log message
will be generated and the method will return the CONTROL treatment.

:param key: The key for which to get the treatment
:type key: str
:param feature: The name of the feature for which to get the treatment
:type feature: str
:param attributes: An optional dictionary of attributes
:type attributes: dict
:return: The treatment for the key and feature
:rtype: tuple(str, str)
"""
return self._make_evaluation(key, feature, attributes, 'get_treatment_with_config',
self._METRIC_GET_TREATMENT_WITH_CONFIG)

def get_treatment(self, key, feature, attributes=None):
"""
Get the treatment for a feature and key, with an optional dictionary of attributes.

This method never raises an exception. If there's a problem, the appropriate log message
will be generated and the method will return the CONTROL treatment.

:param key: The key for which to get the treatment
:type key: str
:param feature: The name of the feature for which to get the treatment
:type feature: str
:param attributes: An optional dictionary of attributes
:type attributes: dict
:return: The treatment for the key and feature
:rtype: str
"""
treatment, _ = self._make_evaluation(key, feature, attributes, 'get_treatment',
self._METRIC_GET_TREATMENT)
return treatment

def get_treatments_with_config(self, key, features, attributes=None):
"""
Evaluate multiple features and return a dict with feature -> (treatment, config).

Get the treatments for a list of features considering a key, with an optional dictionary of
attributes. This method never raises an exception. If there's a problem, the appropriate
log message will be generated and the method will return the CONTROL treatment.
:param key: The key for which to get the treatment
:type key: str
:param features: Array of the names of the features for which to get the treatment
:type feature: list
:param attributes: An optional dictionary of attributes
:type attributes: dict
:return: Dictionary with the result of all the features provided
:rtype: dict
"""
return self._make_evaluations(key, features, attributes, 'get_treatments_with_config',
self._METRIC_GET_TREATMENTS_WITH_CONFIG)

def get_treatments(self, key, features, attributes=None):
"""
Expand All @@ -308,7 +321,8 @@ def get_treatments(self, key, features, attributes=None):
:return: Dictionary with the result of all the features provided
:rtype: dict
"""
with_config = self.get_treatments_with_config(key, features, attributes)
with_config = self._make_evaluations(key, features, attributes, 'get_treatments',
self._METRIC_GET_TREATMENTS)
return {feature: result[0] for (feature, result) in six.iteritems(with_config)}

def _build_impression( # pylint: disable=too-many-arguments
Expand Down Expand Up @@ -346,10 +360,7 @@ def _record_stats(self, impressions, start, operation):
"""
try:
end = int(round(time.time() * 1000))
if operation == self._METRIC_GET_TREATMENT:
self._impressions_storage.put([impressions])
else:
self._impressions_storage.put(impressions)
self._impressions_storage.put(impressions)
self._telemetry_storage.inc_latency(operation, get_latency_bucket_index(end - start))
except Exception: # pylint: disable=broad-except
self._logger.error('Error recording impressions and metrics')
Expand Down
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