--- title: OptimizelyUserContext for the Python SDK slug: feature-experimentation/docs/optimizelyusercontext-python docTags: createdAt: 2026-08-05T20:39:56.000Z --- The OptimizelyUserContext object lets you make flag decisions and track events for a user context you have already created using the [Create User Context](docId\:IQktksuBns7WFb6Xv_OVE) method. Also, if you have configured [Real-Time Audiences for Feature Experimentation](docId:6UBBxxRv331nBIVZ2lun8), you can evaluate if your user would qualify for a [real-time audience from Optimizely Data Platform (ODP)](docId:7-qDl01uxXDPl5_jFVF1E). ## OptimizelyUserContext minimum SDK version `OptimizelyUserContext` is supported on SDK v3.8.0 and higher. ### Forced decision methods minimum SDK version The `set_forced_decision()`, `get_forced_decision()`, `remove_forced_decision()` and `remove_all_forced_decision()` methods are supported on 4.0.0 and higher. ### Real-Time Audiences for Feature Experimentation minimum SDK version The `fetch_qualified_segments()` and `is_qualified_for()` methods are supported on version 5.0.0 and higher. ## `OptimizelyUserContext` definition The following code sample demonstrates the object definition for `OptimizelyUserContext`: ```python class OptimizelyUserContext(object): # set an attribute for the user def set_attribute(self, attribute_key, attribute_value): # get attributes for the user def get_user_attributes(self): # make a decision about which flag variation the user buckets into for the flag key def decide(self, key, options=None): # make decisions about which flag variations the user buckets into for flag keys def decide_for_keys(self, keys, options=None): # make decisions about which flag variations the user buckets into for all flags def decide_all(self, options=None): # track user event def track_event(self, event_key, event_tags=None): # OptimizelyDecisionContext class OptimizelyDecisionContext(object): def __init__(self, flag_key, rule_key): # OptimizelyForcedDecision class OptimizelyForcedDecision(object): def __init__(self, variation_key): # Sets the forced decision (variation_key) for a given decision context def set_forced_decision(self, OptimizelyDecisionContext, OptimizelyForcedDecision): # Returns the forced decision for a given decision context def get_forced_decision(self, OptimizelyDecisionContext): # Removes the forced decision for a given decision context def remove_forced_decision(self, OptimizelyDecisionContext): # Removes all forced decisions bound to this user context def remove_all_forced_decisions(self): # The following methods require Real-Time Audiences for Feature Experimentation. # See note following this code sample. # Returns the saved results of **fetch_qualified_segments()**. # Can be None if not properly updated with fetch_qualified_segments(). def get_qualified_segments(self): # Overwrite the qualified segments array. # This lets you bypass the remote fetching process from ODP # or for utilizing your own fetching service. def set_qualified_segments(self, segments): # Fetch all qualified audience segments for the user context. # If no callback is provided, this method fetches the qualified segments # and return a boolean signifying success. # # If a callback is provided, the method fetches segments in a separate thread, # invoke the provided callback when results are available, and return the thread handle. def fetch_qualified_segments(callback=None, options=None): # Check if the user is qualified for the given segment. def is_qualified_for(self, segment): ``` :::hint{type="info"} **Note** You must first configure [Real-Time Audiences for Feature Experimentation](docId:6UBBxxRv331nBIVZ2lun8) to be able to call the `get_qualified_segments()`, `set_qualified_segments()`, `fetch_qualified_segments()`, and `is_qualified_for()` methods. ::: ## Properties The following table shows attributes for the `OptimizelyUserContext` object: | Attribute | Type | Comment | | ------------------------- | ------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | \`user\_id\` | String | The ID of the user | | \`attributes\` (Optional) | Dict | A dictionary of custom key-value pairs specifying attributes for the user that are used for \[audience targeting]\(https\://support.optimizely.com/hc/en-us/articles/38683417490957). You can pass the dictionary with the user ID when you create the user. | ## Methods The following table shows the methods for the `OptimizelyUserContext` object: | Method | Comment | | ----------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | \`set\_attribute\` | Pass a custom user attribute as a key-value pair to the user context. | | \`decide\` | Returns a decision result for a flag key for a user. The method returns the decision result in an OptimizelyDecision object, which contains all data required to deliver the flag rule. See \[Decide methods]\(https\://docs.developers.optimizely.com/feature-experimentation/docs/decide-methods-python#decide) | | \`decide\_for\_keys\` | Returns a dictionary of flag decisions for specified flag keys. See \[Decide methods]\(https\://docs.developers.optimizely.com/feature-experimentation/docs/decide-methods-python#decide-for-keys) | | \`decide\_all\` | Returns decisions for all active (unarchived) flags for a user. See \[Decide methods]\(https\://docs.developers.optimizely.com/feature-experimentation/docs/decide-methods-python#decide-all) | | \`track\_event\` | Tracks a conversion event for a user (an action a user takes) and logs an error message if the specified event key does not match any existing events. See \[Track Event]\(https\://docs.developers.optimizely.com/feature-experimentation/docs/track-event-python) | | \`set\_forced\_decision\` | Forces a user into a specific variation. See \[Set Forced Decision]\(https\://docs.developers.optimizely.com/feature-experimentation/docs/forced-decision-methods-python#set-forced-decision-method---set\_forced\_decision) | | \`get\_forced\_decision\` | Returns what variation the user was forced into. See \[Get Forced Decision]\(https\://docs.developers.optimizely.com/feature-experimentation/docs/forced-decision-methods-python#get-forced-decision-method---get\_forced\_decision) | | \`remove\_forced\_decision\` | Removes a user from a specific forced variation. See \[Remove Forced Decision]\(https\://docs.developers.optimizely.com/feature-experimentation/docs/forced-decision-methods-python#remove-forced-decision-method---remove\_forced\_decision) | | \`remove\_all\_forced\_decisions\` | Removes a user from all forced variations. See \[Remove All Forced Decisions]\(https\://docs.developers.optimizely.com/feature-experimentation/docs/forced-decision-methods-python#remove-all-forced-decisions-method---remove\_all\_forced\_decisions) | | \`fetch\_qualified\_segments\` \*\* | Fetch all ODP real-time audiences that the user context qualified for. Has a synchronous and asynchronous implementation. See \[Real-Time Audiences for Feature Experimentation segment qualification methods]\(https\://docs.developers.optimizely.com/feature-experimentation/docs/real-time-audiences-for-feature-experimentation-segment-qualification-methods-python). | | \`is\_qualified\_for\` \*\* | Checks if the user context qualifies for a given ODP real-time audience. See \[Real-Time Audiences for Feature Experimentation segment qualification methods]\(https\://docs.developers.optimizely.com/feature-experimentation/docs/real-time-audiences-for-feature-experimentation-segment-qualification-methods-python). | \*\* Requires [Real-Time Audiences for Feature Experimentation](docId:6UBBxxRv331nBIVZ2lun8). ## See also [Create User Context](docId\:IQktksuBns7WFb6Xv_OVE) ## Source files The language and platform source files containing the implementation for Python are available on [GitHub](https://github.com/optimizely/python-sdk/blob/master/optimizely/optimizely.py).