Skip to main content

Split OpenFeature Provider for Python

Twitter Follow

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

  • Python 3.9 and higher.
  • Split SDK: Split Python SDK 10.5.1 or later. Provider lifecycle events (PROVIDER_READY, PROVIDER_CONFIGURATION_CHANGED, PROVIDER_ERROR) require 10.6.0 or later; on 10.5.1 the provider works without emitting those events.

Getting started

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

Pip Installation

pip install split-openfeature-provider==1.1.0

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()}))

Example

A minimal end-to-end example (sync): initialize the provider, set a targeting context, and evaluate a flag.

from openfeature import api
from openfeature.evaluation_context import EvaluationContext
from split_openfeature_provider import SplitProvider

# Initialize with your SDK key (or use "localhost" + splitFile for local YAML)
provider = SplitProvider({
    "SdkKey": "YOUR_API_KEY",
    "ConfigOptions": {"impressionsMode": "optimized"},
    "ReadyBlockTime": 5,
})
api.set_provider(provider)

# Get a client and set targeting context
client = api.get_client()
client.context = EvaluationContext(targeting_key="user-123")

# Evaluate flags
show_new_ui = client.get_boolean_value("my_feature_flag", False)
print("show_new_ui:", show_new_ui)

With asyncio, use SplitProviderAsync, await provider.create(), and await client.get_boolean_value_async(...) as shown in the Asyncio mode section below.

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 = SplitProviderAsync({"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 hello@split.io, 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.

Metadata

Release files for split-openfeature-provider 1.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for split-openfeature-provider 1.1.0
File Size Uploaded Provenance
split_openfeature_provider-1.1.0.tar.gz 11.3 kB Without provenance Details

Release files / split_openfeature_provider-1.1.0.tar.gz

Download URL split_openfeature_provider-1.1.0.tar.gz
Size 11.3 kB
Tags Source
SHA-256 checksum
How to use checksums
a273f3dfae9954fabe0923e935459362c52290b501046e3948221a8150c2ced9
BLAKE2b-256 checksum
How to use checksums
7afd29f706a03265cb9b3351db1ef4f2441d40ab1bf77df00a03db43d98cb94e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.10.16

Security for split-openfeature-provider 1.1.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

Release history Release notifications | RSS feed

This release

1.1.0 This release

1 release file No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page