OptimizelyConfig
This topic describes how to get access to project configuration data within the datafile using OptimizelyConfig.
Overview
Full Stack SDKs open a well-defined set of public APIs, hiding all implementation details. However, some clients may need access to project configuration data within the Manage config (datafile).
In this document, we extend our public APIs to define data models and access methods, which clients can use to access project configuration data.
OptimizelyConfig API
A public configuration data model (OptimizelyConfig) is defined below as a structured format of static Optimizely Project data.
Get OptimizelyConfig
OptimizelyConfig can be accessed from OptimizelyClient (top-level) with this public API call:
client, e := optimizelyFactory.Client()
var config = client.GetOptimizelyConfig()
getOptimizelyConfig
returns an OptimizelyConfig
instance which includes
- environment key
- SDK key
- the datafile revision number
- all experiments mapped by their key values
- all attributes
- all audiences
- all events
- feature flags mapped by their key values
- function to retrieve the project configuration (the datafile)
Note
When the SDK datafile is updated (the client can add a notification listener for
ProjectConfigUpdateNotification
to get notified), the client is expected to call the method to get the updated OptimizelyConfig data. See examples below.
Get datafile
To share the same datafile between multiple SDK instances (for example, in a client/server scenario), you can pass a JSON string representation of the config (the datafile) between the instances. To get the datafile, use the OptimizelyConfig
object's GetDatafile
method. For more information, see Multiple SDK implementations, sharing the datafile with client SDKs.
Object model
The following shows the object model for OptimizelyConfig.
type OptimizelyConfig struct {
EnvironmentKey string
SdkKey string
Revision string
// This experimentsMap is for experiments of legacy projects only.
// For flag projects, experiment keys are not guaranteed to be unique
// across multiple flags, so this map may not include all experiments
// when keys conflict.
ExperimentsMap map[string]OptimizelyExperiment
FeaturesMap map[string]OptimizelyFeature
Attributes []OptimizelyAttribute
Audiences []OptimizelyAudience
Events []OptimizelyEvent
}
type OptimizelyExperiment struct {
ID string
Key string
Audiences string
VariationsMap map[string]OptimizelyVariation
}
type OptimizelyFeature struct {
ID string
Key string
ExperimentRules []OptimizelyExperiment
DeliveryRules []OptimizelyExperiment
VariablesMap map[string]OptimizelyVariable
// Deprecated: Use experimentRules and deliveryRules
ExperimentsMap map[string]OptimizelyExperiment
}
type OptimizelyVariation struct {
ID string
Key string
FeatureEnabled bool
VariablesMap map[string]OptimizelyVariable
}
type OptimizelyVariable struct {
ID string
Key string
Type string
Value string
}
type OptimizelyAttribute struct {
ID string
Key string
}
type OptimizelyAudience struct {
ID string
Name string
Conditions string
}
type OptimizelyEvent struct {
ID string
Key string
ExperimentIds []string
}
Examples
OptimizelyConfig can be accessed from OptimizelyClient (top-level) like this:
optimizelyConfig := optimizelyClient.GetOptimizelyConfig()
fmt.Println("[OptimizelyConfig] revision = " + optimizelyConfig.Revision)
fmt.Println("[OptimizelyConfig] sdkKey = " + optimizelyConfig.SdkKey)
fmt.Println("[OptimizelyConfig] environmentKey = " + optimizelyConfig.EnvironmentKey)
fmt.Println("[OptimizelyConfig] attributes:")
for _, attribute := range optimizelyConfig.Attributes {
fmt.Println("[OptimizelyAttribute] -- (id, key) = " + attribute.ID + ", " + attribute.Key)
}
fmt.Println("[OptimizelyConfig] audiences:")
for _, audience := range optimizelyConfig.Audiences {
fmt.Println("[OptimizelyAudience] -- (id, name, conditions) = " + audience.ID + ", " + audience.Name + ", " + audience.Conditions)
}
fmt.Println("[OptimizelyConfig] events:")
for _, event := range optimizelyConfig.Events {
fmt.Println(fmt.Sprintf("[OptimizelyEvent] -- (id, key, experimentIds) = %s, %s, %v", event.ID, event.Key, event.ExperimentIds))
}
// all flags
flagKeys := []string{}
for flagKey := range optimizelyConfig.FeaturesMap {
flagKeys = append(flagKeys, flagKey)
}
for _, flagKey := range flagKeys {
flag := optimizelyConfig.FeaturesMap[flagKey]
experimentRules := flag.ExperimentRules
deliveryRules := flag.DeliveryRules
// use experiment rules and delivery rules and other flag data here...
for _, experiment := range experimentRules {
fmt.Println("[OptimizelyExperiment] - experiment rule-key = " + experiment.Key)
fmt.Println("[OptimizelyExperiment] - experiment audiences = " + experiment.Audiences)
variationKeys := []string{}
variationsMap := experiment.VariationsMap
for variationKey, _ := range variationsMap {
variationKeys = append(variationKeys, variationKey)
}
for _, varKey := range variationKeys {
variation := variationsMap[varKey]
fmt.Println(fmt.Sprintf("OptimizelyVariation] -- variation = { key: %s, id: %s, featureEnabled: %v }", varKey, variation.ID, variation.FeatureEnabled))
variablesMap := variationsMap[varKey].VariablesMap
variableKeys := []string{}
for variableKey := range variablesMap {
variableKeys = append(variableKeys, variableKey)
}
for _, variableKey := range variableKeys {
variable := variablesMap[variableKey]
fmt.Println(fmt.Sprintf("[OptimizelyVariable] --- variable: %s, %v", variableKey, variable))
}
}
}
for _, delivery := range deliveryRules {
fmt.Println("[OptimizelyExperiment] - delivery rule-key = " + delivery.Key)
fmt.Println("[OptimizelyExperiment] - delivery audiences = " + delivery.Audiences)
// use delivery rule data here...
}
}
// listen to NotificationType.datafileChange to get updated data
callback := func(notification notification.ProjectConfigUpdateNotification) {
var newOptConfig = optimizelyClient.GetOptimizelyConfig()
fmt.Println("[OptimizelyConfig] revision = " + newOptConfig.Revision)
}
optimizelyClient.ConfigManager.OnProjectConfigUpdate(callback)
Updated over 2 years ago