@featurevisor/roku
v1.1.0
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Roku FeatureVisor SDK
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@featurevisor/roku
BrightScript SDK for Roku is meant to be used with kopytko-framework.
However, if you don't use it, you can simply copy all SDK files and their dependencies to your project (a version will be prepared in the future if anyone is interested).
Visit https://featurevisor.com/docs/sdks/roku for more information.
Installation
npm i -P @featurevisor/roku
Usage
Initialize the SDK (creates FeaturevisorInstance
node).
For example, in the new MyFeaturevisorNode
created:
' @import /components/libs/featurevisor/FeaturevisorSDK.brs from @featurevisor/roku
sub init()
f = FeaturevisorSDK()
f.createInstance({
datafileUrl: "<featurevisor-datafile-url>",
})
end sub
You can also pass an existing instance to SDK, to not create a new instance, but to use an existing one to use FeaturevisorSDK methods that are invoked on it.
' @import /components/libs/featurevisor/FeaturevisorSDK.brs from @featurevisor/roku
sub init()
f = FeaturevisorSDK()
f.createInstance({
' options from an existing instance are kept but could be overridden
}, existingInstance)
end sub
Options
Options you can pass when creating Featurevisor SDK instance:
bucketKeySeparator
- Type:
string
- Required: no
- Defaults to:
.
configureAndInterceptStaticContext
- Type:
associativeArray
- Required: no
The context for configureBucketKey
, configureBucketValue
, and interceptContext
functions,
this object will be accessible via m
in those functions.
configureBucketKey
- Type:
function
- Required: no
Use it to take over bucketing key generation process.
' @import /components/libs/featurevisor/FeaturevisorSDK.brs from @featurevisor/roku
sub init()
f = FeaturevisorSDK()
f.createInstance({
configureBucketKey: function (feature as Dynamic, context as Object, bucketKey as String) as String
return bucketKey
end function,
})
end sub
configureBucketValue
- Type:
function
- Required: no
Use it to take over bucketing process.
' @import /components/libs/featurevisor/FeaturevisorSDK.brs from @featurevisor/roku
sub init()
f = FeaturevisorSDK()
f.createInstance({
configureBucketValue: function (feature as Dynamic, context as Object, bucketValue as String) as Integer
return bucketValue ' 0 to 100000
end function,
})
end sub
datafile
- Type:
associativeArray
- Required: either
datafile
ordatafileUrl
is required
Use it to pass the datafile object directly.
datafileUrl
- Type:
string
- Required: either
datafile
ordatafileUrl
is required
Use it to pass the URL to fetch the datafile from.
initialFeatures
- Type:
associativeArray
- Required: no
Pass set of initial features with their variation and (optional) variables that you want the SDK to return until the datafile is fetched and parsed:
' @import /components/libs/featurevisor/FeaturevisorSDK.brs from @featurevisor/roku
sub init()
f = FeaturevisorSDK()
f.createInstance({
initialFeatures: {
myFeatureKey: {
enabled: true,
' optional
variation: "treatment",
variables: {
myVariableKey: "my-variable-value",
},
},
},
})
end sub
interceptContext
- Type:
function
- Required: no
Intercept given context before they are used to bucket the user:
' @import /components/libs/featurevisor/FeaturevisorSDK.brs from @featurevisor/roku
sub init()
defaultContext = {
platform: "roku",
locale: "en_US",
country: "US",
timezone: "America/New_York",
}
f = FeaturevisorSDK()
f.createInstance({
configureAndInterceptStaticContext: defaultContext,
interceptContext: function (context as Object) as Object
joinedContext = {}
joinedContext.append(m)
joinedContext.append(context)
return joinedContext
end function,
})
end sub
onActivation
- Type:
associativeArray
- Required: no
- Structure:
{ callback: function, context?: associativeArray }
Capture activated features along with their evaluated variation:
' @import /components/libs/featurevisor/FeaturevisorSDK.brs from @featurevisor/roku
sub init()
f = FeaturevisorSDK()
f.createInstance({
onActivation: {
callback: sub (data as Object)
' feature has been activated
end sub,
context: {}, ' optional context for the callback
},
})
end sub
data
Object fields:
captureContext
feature
context
variationValue
captureContext
will only contain attributes that are marked as capture: true
in the Attributes' YAML files.
onReady
- Type:
associativeArray
- Required: no
- Structure:
{ callback: function, context?: associativeArray }
Triggered maximum once when the SDK is ready to be used.
' @import /components/libs/featurevisor/FeaturevisorSDK.brs from @featurevisor/roku
sub init()
f = FeaturevisorSDK()
f.createInstance({
onReady: {
callback: sub ()
' agent has been createInstanced and it is ready
end sub,
context: {}, ' optional context for the callback
},
})
end sub
onRefresh
- Type:
associativeArray
- Required: no
- Structure:
{ callback: function, context?: associativeArray }
Triggered every time the datafile is refreshed.
Works only when datafileUrl
and refreshInterval
are set.
' @import /components/libs/featurevisor/FeaturevisorSDK.brs from @featurevisor/roku
sub init()
f = FeaturevisorSDK()
f.createInstance({
onRefresh: {
callback: sub ()
' datafile has been refreshed
end sub,
context: {}, ' optional context for the callback
},
})
end sub
onUpdate
- Type:
associativeArray
- Required: no
- Structure:
{ callback: function, context?: associativeArray }
Triggered every time the datafile is refreshed, and the newly fetched datafile is detected to have different content than last fetched one.
Works only when datafileUrl
and refreshInterval
are set.
' @import /components/libs/featurevisor/FeaturevisorSDK.brs from @featurevisor/roku
sub init()
f = FeaturevisorSDK()
f.createInstance({
onUpdate: {
callback: sub ()
' datafile has been updated (the revision has changed)
end sub,
context: {}, ' optional context for the callback
},
})
end sub
refreshInterval
- Type:
integer
(in seconds) - Required: no
Set the interval grater than zero to refresh the datafile.
' @import /components/libs/featurevisor/FeaturevisorSDK.brs from @featurevisor/roku
sub init()
f = FeaturevisorSDK()
f.createInstance({
datafileUrl: "<featurevisor-datafile-url>",
refreshInterval: 60 * 5, ' every 5 minutes
})
end sub
stickyFeatures
- Type:
associativeArray
- Required: no
If set, the SDK will skip evaluating the datafile and return variation and variable results from this object instead.
If a feature key is not present in this object, the SDK will continue to evaluate the datafile.
' @import /components/libs/featurevisor/FeaturevisorSDK.brs from @featurevisor/roku
sub init()
f = FeaturevisorSDK()
f.createInstance({
stickyFeatures: {
myFeatureKey: {
enabled: true,
' optional
variation: "treatment",
variables: {
myVariableKey: "my-variable-value",
},
},
},
})
end sub
API
f.isEnabled
Check if a feature is enabled or not.
f.isEnabled(featureKey as String, context = {} as Object) as Boolean
f.getVariation
Get feature variation.
f.getVariation(feature as Dynamic, context = {} as Object) as Dynamic
f.getVariable
Get feature variable.
f.getVariable(feature as Dynamic, variableKey as String, context = {} as Object) as Dynamic
Also supports additional type specific methods, returns the value of the desired type, or Invalid if the value does not exist or it does not have a desired type:
f.getVariableBoolean(feature as Dynamic, variableKey as String, context = {} as Object) as Dynamic
f.getVariableString(feature as Dynamic, variableKey as String, context = {} as Object) as Dynamic
f.getVariableInteger(feature as Dynamic, variableKey as String, context = {} as Object) as Dynamic
f.getVariableDouble(feature as Dynamic, variableKey as String, context = {} as Object) as Dynamic
f.getVariableArray(feature as Dynamic, variableKey as String, context = {} as Object) as Dynamic
f.getVariableObject(feature as Dynamic, variableKey as String, context = {} as Object) as Dynamic
f.getVariableJSON(feature as Dynamic, variableKey as String, context = {} as Object) as Dynamic
f.activate
Same as getVariation
, but also calls the onActivation
callback.
This is a convenience method meant to be called when you know the User has been exposed to your Feature, and you also want to track the activation.
f.activate(feature as Dynamic, context = {} as Object) as Object
f.onActivation
Adds on activation callback which will be called after an feature activation.
f.onActivation(func as Function, context = Invalid as Object)
f.onReady
Adds on ready callback which will be called after an instance is ready (datafile is saved).
It should be called before createInstance
f.onReady(func as Function, context = Invalid as Object)
f.onRefresh
Adds on refresh callback which will be called after a successful datafile refresh. But the file doesn't need to change.
f.onRefresh(func as Function, context = Invalid as Object)
f.onUpdate
Adds on update callback which will be called after a successful datafile refresh when it has been changed compared to the previous one.
f.onUpdate(func as Function, context = Invalid as Object)
f.clear
Stop refreshing and clear the whole instance. It needs to be initialized once again.
f.clear()
f.getRevision
Get the datafile revision.
f.getRevision() as String
f.isReady
Check if the instance is ready to be used (the datafile is set).
f.isReady() as Boolean
f.refresh
Manually refresh datafile.
f.refresh()
f.setDatafile
Set datafile manually.
f.setDatafile(datafile as Object)
f.setStickyFeatures
Set sticky features.
f.setStickyFeatures(stickyFeatures as Object)
f.startRefreshing
Resume or start refreshing if refreshInterval was provided.
f.startRefreshing()
f.stopRefreshing
Stop refreshing.
f.stopRefreshing()
License
MIT © Błażej Chełkowski