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OptimizelyUserContext for the Java SDK

Explains the OptimizelyUserContext object for the Java SDK, which allows you to make flag decisions and track events for a user context in Optimizely Feature Experimentation.

The OptimizelyUserContext object lets you make flag decisions and track events for a user context you have already created using the Create User Context method.

Also, if you have Real-Time Segments for Feature Experimentation configured, you can evaluate if the user would qualify for an Real-Time segment.

OptimizelyUserContext minimum SDK version

SDK v3.7 and higher.

Forced decision methods minimum SDK version

setForcedDecision(), getForcedDecision(), removeForcedDecision() and removeAllForcedDecisions() methods are supported on version 3.10.0 and higher.

Real-Time Segments for Feature Experimentation minimum SDK version

fetchQualifiedSegments() and isQualifiedFor() methods are supported on version 4.0.0 and higher.

OptimizelyUserContext definition

The following code shows the object definition for OptimizelyUserContext:

public class OptimizelyUserContext {
    public String getUserId()
    public Map<String, Object> getAttributes()

    public OptimizelyUserContext(Optimizely optimizely, 
                                 String userId, 
                                 Map<String, Object> attributes)
      
    // set an attribute for the user
    public void setAttribute(String key, Object value)
    
    // make a decision about which flag variation the user buckets into for the flag key
    public OptimizelyDecision decide(String key, 
                                     List<OptimizelyDecideOption> options)
    
    // make decisions about which flag variations the user buckets into for flag keys  
    public Map<String, OptimizelyDecision> decideForKeys(List<String> keys, 
                                      List<OptimizelyDecideOption> options)
    
    // make decisions about which flag variations the user buckets into for all flags  
    public Map<String, OptimizelyDecision> decideAll(List<OptimizelyDecideOption> options)
    
    // track user event  
    public void trackEvent(String eventName, Map<String, ?> eventTags)
  
    // sets a forced decision (variationKey) for a given decision context
    public Boolean setForcedDecision(OptimizelyDecisionContext context, OptimizelyForcedDecision decision)

    // returns the forced decision (variationKey) for a given decision context
    public OptimizelyForcedDecision getForcedDecision(OptimizelyDecisionContext context)

    // removes the forced decision (variationKey) for a given decision context
    public Boolean removeForcedDecision(OptimizelyDecisionContext context)

    // removes all the forced decisions (variationKeys) for the user context
    public Boolean removeAllForcedDecisions()
      
    //
    // The following methods require Real-Time Segments for Feature Experimentation. 
    // See note following the code sample. 
    //

    // An array of segment names that the user is qualified for. 
    // The result of **fetchQualifiedSegments()** is saved here. 
    // Can be nil if not properly updated with fetchQualifiedSegments(). 
    // 
    //  You can read and write directly to the qualified segments array. 
    //  This lets you bypass the remote fetching process from ODP 
    //  or utilize your own fetching service.   
    private List<String> qualifiedSegments() 
      
    // Fetch all qualified segments for the user context. 
    // The segments fetched will be saved in the **qualifiedSegments** array
    // and can be accessed any time. 
    public Boolean fetchQualifiedSegments(List<ODPSegmentOption> segmentOptions) 

    // Fetch all qualified segments for the user context in a non-blocking manner. 
    // This method will fetch segments in a separate thread and invoke the provided 
    //  callback when results are available.
    public void fetchQualifiedSegments(ODPSegmentCallback callback, List<ODPSegmentOption> segmentOptions)
 
    //  Check is the user qualified for the given segment. 
    public Boolean isQualifiedFor(String segment)
}

πŸ“˜

Note

You must first configure Real-Time Segments for Feature Experimentation to use the qualifiedSegments(), fetchQualifiedSegments(), and isQualifiedFor() methods.

Properties

The following table shows the attributes for the OptimizelyUserContext object:

AttributeTypeComment
userIdStringThe ID of the user
(optional) attributesMapA map of custom key-value pairs specifying attributes for the user that are used for audience targeting. You can pass the map with the user ID when you create the user.

Methods

The following table shows methods for the OptimizelyUserContext object:

MethodComment
setAttributePass a custom user attribute as a key-value pair to the user context.
decideReturns a decision result for a flag key for a user in an OptimizelyDecision object containing all data required to deliver the flag rule.
See Decide methods
decideAllReturns decisions for all active (unarchived) flags for a user.
See Decide methods
decideForKeysReturns a map of flag decisions for specified flag keys.
See Decide methods
trackEventTracks 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
setForcedDecisionForces a user into a specific variation.
See Set Forced Decision
getForcedDecisionReturns what variation the user was forced into.
See Get Forced Decision
removeForcedDecisionRemoves a user from a specific forced variation.
See Remove Forced Decision
removeAllForcedDecisionsRemoves a user from all forced variations.
See Remove All Forced Decisions
fetchQualifiedSegments **Fetch all Optimizely Data Platform (ODP) real-time segments that the user context qualified for. See Real-Time Segments for Feature Experimentation segment qualification methods for the Java SDK.
isQualifiedFor **Check if the user context qualifies for a given ODP real-time segment. See Real-Time Segments for Feature Experimentation segment qualification methods for the Java SDK.

** Requires [Real-Time Segments for Feature Experimentation](doc:real-time-segments-for-feature-experimentation.

See also

Create User Context

Source files

The language and platform source files containing the implementation for Java are available on GitHub.