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Split OpenFeature Provider for Python

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Overview

This Provider is designed to allow the use of OpenFeature with Split, the platform for controlled rollouts, serving features to your users via the Split feature flag to manage your complete customer experience.

Compatibility

This SDK is compatible with Python 3.9 and higher.

Getting started

This package replaces the previous split-openfeature-provider Python provider in Pypi.

Pip Installation

pip install split-openfeature-provider==1.0.0

Configure it

Below is a simple example that describes using the Split Provider. Please see the OpenFeature Documentation for details on how to use the OpenFeature SDK.

from openfeature import api
from split_openfeature_provider import SplitProvider
config = {
      'impressionsMode': 'OPTIMIZED',
      'impressionsRefreshRate': 30,
    }
provider = SplitProvider({"SdkKey": "YOUR_API_KEY", "ConfigOptions": config, "ReadyBlockTime": 5})
api.set_provider(provider)

If you are more familiar with Split or want access to other initialization options, you can provide a Split client to the constructor. See the Harness Split Python SDK Documentation for more information.

from openfeature import api
from split_openfeature_provider import SplitProvider
from splitio import get_factory

config = {
      'impressionsMode': 'OPTIMIZED',
      'impressionsRefreshRate': 30,
    }
factory = get_factory("YOUR_API_KEY", config=config)
factory.block_until_ready(5)
api.set_provider(SplitProvider({"SplitClient": factory.client()}))

Use of OpenFeature with Split

After the initial setup you can use OpenFeature according to their documentation.

One important note is that the Split Provider requires a targeting key to be set. Often times this should be set when evaluating the value of a flag by setting an EvaluationContext which contains the targeting key. An example flag evaluation is

from openfeature import api
from openfeature.evaluation_context import EvaluationContext

client = api.get_client("CLIENT_NAME")

context = EvaluationContext(targeting_key="TARGETING_KEY")
value = client.get_boolean_value("FLAG_NAME", False, context)

If the same targeting key is used repeatedly, the evaluation context may be set at the client level

context = EvaluationContext(targeting_key="TARGETING_KEY")
client.context = context

or at the OpenFeatureAPI level

context = EvaluationContext(targeting_key="TARGETING_KEY")
api.set_evaluation_context(context)

If the context was set at the client or api level, it is not required to provide it during flag evaluation.

Asyncio mode

The provider supports asyncio mode as well, using the asyncio mode in Split SDK. Example below shows using the provider in asyncio

from openfeature import api
from split_openfeature_provider import SplitProviderAsync
config = {
      'impressionsMode': 'OPTIMIZED',
      'impressionsRefreshRate': 30,
    }
provider = SplitProvider({"SdkKey": "YOUR_API_KEY", "ConfigOptions": config, "ReadyBlockTime": 5})
await provider.create()
api.set_provider(provider)

Example below show how to create the Split Client externally and pass it to Provider

from openfeature import api
from split_openfeature_provider import SplitProviderAsync
from splitio import get_factory_async

config = {
      'impressionsMode': 'OPTIMIZED',
      'impressionsRefreshRate': 30,
    }
factory = get_factory_async("YOUR_API_KEY", config=config)
await factory.block_until_ready(5)
provider = SplitProviderAsync({"SplitClient": factory.client()})
await provider.create()
api.set_provider(provider)

Example below fetching the treatment in asyncio mode

from openfeature import api
from openfeature.evaluation_context import EvaluationContext

client = api.get_client("CLIENT_NAME")

context = EvaluationContext(targeting_key="TARGETING_KEY")
value = await client.get_boolean_value_async("FLAG_NAME", False, context)

Logging

Split Provider use logging library, Each module has it's own logger, the root being split_provider. Below is an example of simple usage which will set all libraries using logging including the provider, to use DEBUG mode.

import logging

logging.basicConfig(level=logging.DEBUG)

Shutting down Split SDK factory

Currently OpenFeature SDK does not provide override for provider shutdown, when using internal split client object, the Split SDK will not shutdown properly. We recommend using the example below before terminating the OpenFeature object

from threading import Event

destroy_event = Event()
provider._split_client_wrapper._factory.destroy(destroy_event)
destroy_event.wait()

Below the example for asyncio mode

await provider._split_client_wrapper._factory.destroy()

Submitting issues

The Split team monitors all issues submitted to this issue tracker. We encourage you to use this issue tracker to submit any bug reports, feedback, and feature enhancements. We'll do our best to respond in a timely manner.

Contributing

Please see Contributors Guide to find all you need to submit a Pull Request (PR).

License

Licensed under the Apache License, Version 2.0. See: Apache License.

About Split

Split is the leading Feature Delivery Platform for engineering teams that want to confidently deploy features as fast as they can develop them. Split’s fine-grained management, real-time monitoring, and data-driven experimentation ensure that new features will improve the customer experience without breaking or degrading performance. Companies like Twilio, Salesforce, GoDaddy and WePay trust Split to power their feature delivery.

To learn more about Split, contact [email protected], or get started with feature flags for free at https://www.split.io/signup.

Split has built and maintains SDKs for:

For a comprehensive list of open source projects visit our Github page.

Learn more about Split:

Visit split.io/product for an overview of Split, or visit our documentation at help.split.io for more detailed information.

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