kameleoon-openfeature 0.0.1

OpenFeature Kameleoon Provider.

Kameleoon OpenFeature provider for Python

The Kameleoon OpenFeature provider for Python allows you to connect your OpenFeature Python implementation to Kameleoon without installing the Python Kameleoon SDK.

[!WARNING] This is a beta version. Breaking changes may be introduced before general release.

Supported Python versions

This version of the SDK is built for the following targets:

• Python 3.8 and above.

Get started

This section explains how to install, configure, and customize the Kameleoon OpenFeature provider.

Install dependencies

First, install the required dependencies in your application.

• Run pip install -r requirements.txt

Usage

The following example shows how to use the Kameleoon provider with the OpenFeature SDK.

from openfeature import api
from openfeature.evaluation_context import EvaluationContext
from kameleoon_openfeature.kameleoon_provider import KameleoonProvider, KameleoonClientConfig


client_config = KameleoonClientConfig(
    'clientId',
    'clientSecret',
    top_level_domain='topLevelDomain'
)

provider = KameleoonProvider('siteCode', config=client_config)

api.set_provider(provider)
client = api.get_client()

values = {
    'variableKey': 'variableKey'
}

eval_context = EvaluationContext(attributes=values, targeting_key='visitorCode')

number_of_recommended_products = client.get_integer_value(flag_key='featureKey', default_value=5,
                                               evaluation_context=eval_context)

print(f"Number of recommended products: {number_of_recommended_products}")

Customize the Kameleoon provider

You can customize the Kameleoon provider by changing the KameleoonClientConfig object that you passed to the constructor above. For example:

from kameleoon_openfeature.kameleoon_provider import KameleoonProvider, KameleoonClientConfig

client_config = KameleoonClientConfig(
    'clientId',
    'clientSecret',
    top_level_domain='topLevelDomain',
    refresh_interval_minute=1,    # Optional field
    session_duration_minute=5,    # Optional field
)

provider = KameleoonProvider('siteCode', config=client_config)

[!NOTE] For additional configuration options, see the Kameleoon documentation.

EvaluationContext and Kameleoon Data

Kameleoon uses the concept of associating Data to users, while the OpenFeature SDK uses the concept of an EvaluationContext, which is a dictionary of string keys and values. The Kameleoon provider maps the EvaluationContext to the Kameleoon Data.

[!NOTE] To get the evaluation for a specific visitor, set the targeting_key value for the EvaluationContext to the visitor code (user ID). If the value is not provided, then the defaultValue parameter will be returned.

from openfeature.evaluation_context import EvaluationContext

eval_context = EvaluationContext(targeting_key='userId')

The Kameleoon provider provides a few predefined parameters that you can use to target a visitor from a specific audience and track each conversion. These are:

Parameter	Description
Data.Type.CUSTOM_DATA	The parameter is used to set CustomData for a visitor.
Data.Type.CONVERSION	The parameter is used to track a Conversion for a visitor.

Data.Type.CUSTOM_DATA

Use Data.Type.CUSTOM_DATA to set CustomData for a visitor. The Data.Type.CUSTOM_DATA field has the following parameters:

Parameter	Type	Description
Data.CustomDataType.INDEX	int	Index or ID of the custom data to store. This field is mandatory.
Data.CustomDataType.VALUES	str	Value of the custom data to store. This field is mandatory.

Example

from openfeature.evaluation_context import EvaluationContext
from kameleoon_openfeature.types import Data

custom_data_dictionary = {
    Data.Type.CUSTOM_DATA: {
        Data.CustomDataType.INDEX: 1,
        Data.CustomDataType.VALUES: '10'
    }
}

eval_context = EvaluationContext(attributes=custom_data_dictionary , targeting_key='userId')

Data.Type.CONVERSION

Use Data.Type.CONVERSION to track a Conversion for a visitor. The Data.Type.CONVERSION field has the following parameters:

Parameter	Type	Description
Data.ConversionType.GOAL_ID	int	Identifier of the goal. This field is mandatory.
Data.ConversionType.REVENUE	float	Revenue associated with the conversion. This field is optional.

Example

from openfeature.evaluation_context import EvaluationContext
from kameleoon_openfeature.types import Data

conversion_dictionary = {
    Data.Type.CONVERSION: {
        Data.ConversionType.GOAL_ID: 1,
        Data.ConversionType.REVENUE: 200
    }
}

eval_context = EvaluationContext(attributes=conversion_dictionary, targeting_key='userId')

Use multiple Kameleoon Data types

You can provide many different kinds of Kameleoon data within a single EvaluationContext instance.

For example, the following code provides one Data.Type.CONVERSION instance and two Data.Type.CUSTOM_DATA instances.

from openfeature.evaluation_context import EvaluationContext
from kameleoon_openfeature.types import Data

data_dictionary = {
    Data.Type.CONVERSION: {
        Data.ConversionType.GOAL_ID: 1,
        Data.ConversionType.REVENUE: 200
    },
    Data.Type.CUSTOM_DATA: [
        {
            Data.CustomDataType.INDEX: 1,
            Data.CustomDataType.VALUES: ['10', '30']
        },
        {
            Data.CustomDataType.INDEX: 2,
            Data.CustomDataType.VALUES: '20'
        }
    ]
}

eval_context = EvaluationContext(attributes=data_dictionary, targeting_key='userId')