openfeature-provider-flagsmith 0.2.0

Openfeature provider for Flagsmith

flagsmith-openfeature-provider-python

The Flagsmith provider allows you to connect to your Flagsmith instance through the OpenFeature SDK

Python SDK usage

Install dependencies

First, you'll need to install the OpenFeature SDK and the Flagsmith Provider.

pip install openfeature-sdk openfeature-provider-flagsmith

Using the Flagsmith Provider with the OpenFeature SDK

To create a Flagsmith provider you will need to provide a number of arguments. These are shown and described below. See the Flagsmith docs for further information on the configuration options available for the Flagsmith python client.

from flagsmith import Flagsmith
from openfeature_flagsmith.provider import FlagsmithProvider

provider = FlagsmithProvider(
    # Provide an instance of the Flagsmith python client.
    # Required: True
    client=Flagsmith(...),
    
    # By enabling the use_flagsmith_defaults setting, you can instruct the OpenFeature SDK to use
    # the default logic included in the Flagsmith client as per the docs here: 
    # https://docs.flagsmith.com/clients/server-side#managing-default-flags. This will override the 
    # default provided at evaluation time in the OpenFeature SDK in most cases (excluding those where 
    # an unexpected exception happens in the Flagsmith client itself).
    # Required: False
    # Default: False
    use_flagsmith_defaults=False,
    
    # By default, when evaluating the boolean value of a feature in the OpenFeature SDK, the Flagsmith 
    # OpenFeature Provider will use the 'Enabled' state of the feature as defined in Flagsmith. This 
    # behaviour can be changed to use the 'value' field defined in the Flagsmith feature instead by 
    # enabling the use_boolean_config_value setting. 
    # Note: this relies on the value being defined as a Boolean in Flagsmith. If the value is not a 
    # Boolean, an error will occur and the default value provided as part of the evaluation will be 
    # returned instead.  
    # Required: False
    # Default: False
    use_boolean_config_value=False,
    
    # By default, the Flagsmith OpenFeature Provider will raise an exception (triggering the 
    # OpenFeature SDK to return the provided default value) if the flag is disabled. This behaviour
    # can be configured by enabling this flag so that the Flagsmith OpenFeature provider ignores
    # the enabled state of a flag when returning a value.
    # Required: False
    # Default: False
    return_value_for_disabled_flags=False,
)

The provider can then be used with the OpenFeature client as per the documentation.

Tracking

The provider supports the OpenFeature tracking API, which lets you associate user actions with feature flag evaluations for experimentation.

Tracking requires pipeline analytics to be enabled on the Flagsmith client (available from flagsmith version 5.2.0). The provider acts as a thin delegate — all buffering and flushing is managed by the client.

from flagsmith import Flagsmith, PipelineAnalyticsConfig
from openfeature import api
from openfeature.evaluation_context import EvaluationContext
from openfeature.track import TrackingEventDetails
from openfeature_flagsmith.provider import FlagsmithProvider

# Enable pipeline analytics on the Flagsmith client
client = Flagsmith(
    environment_key="your-environment-key",
    pipeline_analytics_config=PipelineAnalyticsConfig(
        analytics_server_url="https://analytics-collector.flagsmith.com/",
        max_buffer_items=1000,      # optional, default 1000
        flush_interval_seconds=10,  # optional, default 10s
    ),
)

api.set_provider(FlagsmithProvider(client=client))
of_client = api.get_client()

# Flag evaluations are tracked automatically — no extra code needed
variant = of_client.get_string_value(
    "checkout-variant",
    "control",
    evaluation_context=EvaluationContext(targeting_key="user-123"),
)

# Track a custom event explicitly
of_client.track(
    "purchase",
    evaluation_context=EvaluationContext(
        targeting_key="user-123",
        attributes={"plan": "premium"},
    ),
    tracking_event_details=TrackingEventDetails(
        value=99.77,
        attributes={"currency": "USD"},
    ),
)

If pipeline_analytics_config is not set on the Flagsmith client, calls to track() are silently ignored.

Evaluation Context

The evaluation context supports traits in two ways:

1. Flat top-level attributes
2. A nested traits object

The two forms are merged and sent to Flagsmith, with the traits object taking precedence if keys conflict.

context = EvaluationContext( # Traits are: {"abc":"def", "foo": "bar2"}
    targeting_key="user",
    attributes={
        "foo": "bar", 
        "abc": "def", 
        "traits": {"foo": "bar2"}
    },
)