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[FSSDK-10763] Implement UPS request batching for decideForKeys (#440)
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* update: UserProfile class created, changes in decision_service, decide_for_keys

* update: get_variation function changed

* update: new function in decision_service

* update: everything implemented from java. tests are failing

* update: minor changes

* update: user_profile_tracker added to tests

* update: some tests fixed

* optimizely/decision_service.py -> Added check for `ignore_user_profile` in decision logic.
optimizely/user_profile.py -> Improved user profile loading with missing key checks.
tests/test_decision_service.py -> Updated tests to include user profile tracker.

* tests/test_decision_service.py -> Added expected decision object.
tests/test_decision_service.py -> Updated experiment bucket map call.
tests/test_decision_service.py -> Introduced user_profile_tracker usage.
tests/test_decision_service.py -> Modified method calls with user_profile_tracker.

* optimizely/decision_service.py -> fixed get_variations_for_feature_list

* optimizely/decision_service.py -> Fixed how rollout reasons are added
tests/test_decision_service.py -> Added user profile tracker object

* tests/test_user_context.py -> fixed some tests

* optimizely/user_profile.py -> Updated type for `experiment_bucket_map`.
tests/test_decision_service.py -> Fixed tests

* all unit tests passing

* lint check

* fix: typechecks added

* more types updated

* all typechecks passing

* gha typechecks fixed

* all typecheck should pass

* lint check should pass

* removed unnecessary comments

* removed comments from test

* optimizely/decision_service.py -> Removed user profile save logic
optimizely/optimizely.py -> Added loading and saving profile logic

* optimizely/user_profile.py -> Updated experiment_bucket_map type
optimizely/user_profile.py -> Testing user profile update logic

* optimizely/decision_service.py -> Commented out profile loading
optimizely/user_profile.py -> Removed unused import statement

* optimizely/decision_service.py -> Removed unused profile loading
optimizely/user_profile.py -> Fixed handling of reasons list
optimizely/user_profile.py -> Improved profile retrieval error logging
tests/test_decision_service.py -> Updated mock checks to simplify tests
tests/test_user_profile.py -> Added tests for user profile handling
tests/test_optimizely.py -> New test for variation lookup and save

* optimizely/user_profile.py -> Reverted back to variation ID retrieval logic.

* optimizely/user_profile.py -> Added error handling logic
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@FarhanAnjum-opti
FarhanAnjum-opti authored Nov 27, 2024
1 parent 40880ff commit 22c74ee
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Showing 7 changed files with 601 additions and 477 deletions.
169 changes: 108 additions & 61 deletions optimizely/decision_service.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,7 @@
from .helpers import experiment as experiment_helper
from .helpers import validator
from .optimizely_user_context import OptimizelyUserContext, UserAttributes
from .user_profile import UserProfile, UserProfileService
from .user_profile import UserProfile, UserProfileService, UserProfileTracker

if TYPE_CHECKING:
# prevent circular dependenacy by skipping import at runtime
Expand All @@ -35,7 +35,7 @@ class Decision(NamedTuple):
None if no experiment/variation was selected."""
experiment: Optional[entities.Experiment]
variation: Optional[entities.Variation]
source: str
source: Optional[str]


class DecisionService:
Expand Down Expand Up @@ -247,6 +247,8 @@ def get_variation(
project_config: ProjectConfig,
experiment: entities.Experiment,
user_context: OptimizelyUserContext,
user_profile_tracker: Optional[UserProfileTracker],
reasons: list[str] = [],
options: Optional[Sequence[str]] = None
) -> tuple[Optional[entities.Variation], list[str]]:
""" Top-level function to help determine variation user should be put in.
Expand All @@ -260,7 +262,9 @@ def get_variation(
Args:
project_config: Instance of ProjectConfig.
experiment: Experiment for which user variation needs to be determined.
user_context: contains user id and attributes
user_context: contains user id and attributes.
user_profile_tracker: tracker for reading and updating user profile of the user.
reasons: Decision reasons.
options: Decide options.
Returns:
Expand All @@ -275,6 +279,8 @@ def get_variation(
ignore_user_profile = False

decide_reasons = []
if reasons is not None:
decide_reasons += reasons
# Check if experiment is running
if not experiment_helper.is_experiment_running(experiment):
message = f'Experiment "{experiment.key}" is not running.'
Expand All @@ -296,23 +302,14 @@ def get_variation(
return variation, decide_reasons

# Check to see if user has a decision available for the given experiment
user_profile = UserProfile(user_id)
if not ignore_user_profile and self.user_profile_service:
try:
retrieved_profile = self.user_profile_service.lookup(user_id)
except:
self.logger.exception(f'Unable to retrieve user profile for user "{user_id}" as lookup failed.')
retrieved_profile = None

if retrieved_profile and validator.is_user_profile_valid(retrieved_profile):
user_profile = UserProfile(**retrieved_profile)
variation = self.get_stored_variation(project_config, experiment, user_profile)
if variation:
message = f'Returning previously activated variation ID "{variation}" of experiment ' \
f'"{experiment}" for user "{user_id}" from user profile.'
self.logger.info(message)
decide_reasons.append(message)
return variation, decide_reasons
if user_profile_tracker is not None and not ignore_user_profile:
variation = self.get_stored_variation(project_config, experiment, user_profile_tracker.get_user_profile())
if variation:
message = f'Returning previously activated variation ID "{variation}" of experiment ' \
f'"{experiment}" for user "{user_id}" from user profile.'
self.logger.info(message)
decide_reasons.append(message)
return variation, decide_reasons
else:
self.logger.warning('User profile has invalid format.')

Expand Down Expand Up @@ -340,10 +337,9 @@ def get_variation(
self.logger.info(message)
decide_reasons.append(message)
# Store this new decision and return the variation for the user
if not ignore_user_profile and self.user_profile_service:
if user_profile_tracker is not None and not ignore_user_profile:
try:
user_profile.save_variation_for_experiment(experiment.id, variation.id)
self.user_profile_service.save(user_profile.__dict__)
user_profile_tracker.update_user_profile(experiment, variation)
except:
self.logger.exception(f'Unable to save user profile for user "{user_id}".')
return variation, decide_reasons
Expand Down Expand Up @@ -479,44 +475,7 @@ def get_variation_for_feature(
Returns:
Decision namedtuple consisting of experiment and variation for the user.
"""
decide_reasons = []

# Check if the feature flag is under an experiment and the the user is bucketed into one of these experiments
if feature.experimentIds:
# Evaluate each experiment ID and return the first bucketed experiment variation
for experiment_id in feature.experimentIds:
experiment = project_config.get_experiment_from_id(experiment_id)
decision_variation = None

if experiment:
optimizely_decision_context = OptimizelyUserContext.OptimizelyDecisionContext(feature.key,
experiment.key)

forced_decision_variation, reasons_received = self.validated_forced_decision(
project_config, optimizely_decision_context, user_context)
decide_reasons += reasons_received

if forced_decision_variation:
decision_variation = forced_decision_variation
else:
decision_variation, variation_reasons = self.get_variation(project_config,
experiment, user_context, options)
decide_reasons += variation_reasons

if decision_variation:
message = f'User "{user_context.user_id}" bucketed into a ' \
f'experiment "{experiment.key}" of feature "{feature.key}".'
self.logger.debug(message)
return Decision(experiment, decision_variation,
enums.DecisionSources.FEATURE_TEST), decide_reasons

message = f'User "{user_context.user_id}" is not bucketed into any of the ' \
f'experiments on the feature "{feature.key}".'
self.logger.debug(message)
variation, rollout_variation_reasons = self.get_variation_for_rollout(project_config, feature, user_context)
if rollout_variation_reasons:
decide_reasons += rollout_variation_reasons
return variation, decide_reasons
return self.get_variations_for_feature_list(project_config, [feature], user_context, options)[0]

def validated_forced_decision(
self,
Expand Down Expand Up @@ -580,3 +539,91 @@ def validated_forced_decision(
user_context.logger.info(user_has_forced_decision_but_invalid)

return None, reasons

def get_variations_for_feature_list(
self,
project_config: ProjectConfig,
features: list[entities.FeatureFlag],
user_context: OptimizelyUserContext,
options: Optional[Sequence[str]] = None
) -> list[tuple[Decision, list[str]]]:
"""
Returns the list of experiment/variation the user is bucketed in for the given list of features.
Args:
project_config: Instance of ProjectConfig.
features: List of features for which we are determining if it is enabled or not for the given user.
user_context: user context for user.
options: Decide options.
Returns:
List of Decision namedtuple consisting of experiment and variation for the user.
"""
decide_reasons: list[str] = []

if options:
ignore_ups = OptimizelyDecideOption.IGNORE_USER_PROFILE_SERVICE in options
else:
ignore_ups = False

user_profile_tracker: Optional[UserProfileTracker] = None
if self.user_profile_service is not None and not ignore_ups:
user_profile_tracker = UserProfileTracker(user_context.user_id, self.user_profile_service, self.logger)
user_profile_tracker.load_user_profile(decide_reasons, None)

decisions = []

for feature in features:
feature_reasons = decide_reasons.copy()
experiment_decision_found = False # Track if an experiment decision was made for the feature

# Check if the feature flag is under an experiment
if feature.experimentIds:
for experiment_id in feature.experimentIds:
experiment = project_config.get_experiment_from_id(experiment_id)
decision_variation = None

if experiment:
optimizely_decision_context = OptimizelyUserContext.OptimizelyDecisionContext(
feature.key, experiment.key)
forced_decision_variation, reasons_received = self.validated_forced_decision(
project_config, optimizely_decision_context, user_context)
feature_reasons.extend(reasons_received)

if forced_decision_variation:
decision_variation = forced_decision_variation
else:
decision_variation, variation_reasons = self.get_variation(
project_config, experiment, user_context, user_profile_tracker, feature_reasons, options
)
feature_reasons.extend(variation_reasons)

if decision_variation:
self.logger.debug(
f'User "{user_context.user_id}" '
f'bucketed into experiment "{experiment.key}" of feature "{feature.key}".'
)
decision = Decision(experiment, decision_variation, enums.DecisionSources.FEATURE_TEST)
decisions.append((decision, feature_reasons))
experiment_decision_found = True # Mark that a decision was found
break # Stop after the first successful experiment decision

# Only process rollout if no experiment decision was found
if not experiment_decision_found:
rollout_decision, rollout_reasons = self.get_variation_for_rollout(project_config,
feature,
user_context)
if rollout_reasons:
feature_reasons.extend(rollout_reasons)
if rollout_decision:
self.logger.debug(f'User "{user_context.user_id}" '
f'bucketed into rollout for feature "{feature.key}".')
else:
self.logger.debug(f'User "{user_context.user_id}" '
f'not bucketed into any rollout for feature "{feature.key}".')

decisions.append((rollout_decision, feature_reasons))

if self.user_profile_service is not None and user_profile_tracker is not None and ignore_ups is False:
user_profile_tracker.save_user_profile()

return decisions
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