This provider allows for using LaunchDarkly with the OpenFeature SDK for Python.

This provider is designed primarily for use in multi-user systems such as web servers and applications. It follows the server-side LaunchDarkly model for multi-user contexts. It is not intended for use in desktop and embedded systems applications.

LaunchDarkly is a feature management platform that serves trillions of feature flags daily to help teams build better software, faster. Get started using LaunchDarkly today!

This version of the LaunchDarkly provider works with Python 3.9 and above.

Install the library via pip

$ pip install launchdarkly-openfeature-server

from ld_openfeature import LaunchDarklyProvider, Config
from openfeature import api

openfeature_provider = LaunchDarklyProvider(Config("sdk-key"))

api.set_provider(openfeature_provider)

# Refer to OpenFeature documentation for getting a client and performing evaluations.

The optional start_wait parameter is the number of seconds to wait for a successful connection to LaunchDarkly, matching the same parameter of the LaunchDarkly SDK's LDClient, and defaulting to the same five seconds. A positive value bounds the whole of initialization: the provider constructor blocks for up to that long, and OpenFeature initialization then completes immediately, reporting a failed initialization if the client did not become ready in time. Zero does not block the constructor at all, and initialization then waits without a deadline for the data source to become valid or to fail permanently.

Refer to the SDK reference guide for instructions on getting started with using the SDK.

For information on using the OpenFeature client please refer to the OpenFeature Documentation.

LaunchDarkly evaluates contexts, and it can either evaluate a single-context, or a multi-context. When using OpenFeature both single and multi-contexts must be encoded into a single EvaluationContext. This is accomplished by looking for an attribute named kind in the EvaluationContext.

There are 4 different scenarios related to the kind:

1. There is no kind attribute. In this case the provider will treat the context as a single context containing a "user" kind.
2. There is a kind attribute, and the value of that attribute is "multi". This will indicate to the provider that the context is a multi-context.
3. There is a kind attribute, and the value of that attribute is a string other than "multi". This will indicate to the provider a single context of the kind specified.
4. There is a kind attribute, and the attribute is not a string. In this case the value of the attribute will be discarded, and the context will be treated as a "user". An error message will be logged.

The kind attribute should be a string containing only contain ASCII letters, numbers, ., _ or -.

The OpenFeature specification allows for an optional targeting key, but LaunchDarkly requires a key for evaluation. A targeting key must be specified for each context being evaluated. It may be specified using either targetingKey, as it is in the OpenFeature specification, or key, which is the typical LaunchDarkly identifier for the targeting key. If a targetingKey and a key are specified, then the targetingKey will take precedence.

There are several other attributes which have special functionality within a single or multi-context.

• A key of privateAttributes. Must be an array of string values. Equivalent to the 'private' builder method in the SDK.
• A key of anonymous. Must be a boolean value. Equivalent to the 'anonymous' builder method in the SDK.
• A key of name. Must be a string. Equivalent to the 'name' builder method in the SDK.

context = EvaluationContext("the-key")

context = EvaluationContext("org-key", {"kind": "organization"});

attributes = {
    "kind": "multi",
    "organization": {
        "name": "the-org-name",
        "targetingKey", "my-org-key",
        "myCustomAttribute", "myAttributeValue"
    },
    "user": {
        "key": "my-user-key",
        "anonymous", true
    }
}
context = EvaluationContext(null, attributes)

attributes = {
    "kind": "organization",
    "myCustomAttribute": "myAttributeValue",
    "privateAttributes": ["myCustomAttribute"]
}

context = EvaluationContext("org-key", attributes)

attributes = {
    "kind": "organization",
    "organization": {
        "name": "the-org-name",
        "targetingKey": "my-org-key",
        # This will ONLY apply to the "organization" attributes.
        "privateAttributes": ["myCustomAttribute"],
        # This attribute will be private.
        "myCustomAttribute": "myAttributeValue",
    },
    "user": [
        "key": "my-user-key",
        "anonymous" = > true,
        # This attribute will not be private.
        "myCustomAttribute": "myAttributeValue",
    ]
}

context = EvaluationContext(null, attributes)

Evaluations include flag metadata for the LaunchDarkly specific parts of the evaluation result which have no OpenFeature equivalent. Each entry is absent when it does not apply to the evaluation.

details = client.get_boolean_details("my-flag", False, context)
in_experiment = details.flag_metadata.get("inExperiment", False)

Check out our documentation for in-depth instructions on configuring and using LaunchDarkly. You can also head straight to the complete reference guide for this SDK.

The authoritative description of all properties and methods is in the python documentation.

We encourage pull requests and other contributions from the community. Check out our contributing guidelines for instructions on how to contribute to this SDK.

• LaunchDarkly is a continuous delivery platform that provides feature flags as a service and allows developers to iterate quickly and safely. We allow you to easily flag your features and manage them from the LaunchDarkly dashboard. With LaunchDarkly, you can:
  • Roll out a new feature to a subset of your users (like a group of users who opt-in to a beta tester group), gathering feedback and bug reports from real-world use cases.
  • Gradually roll out a feature to an increasing percentage of users, and track the effect that the feature has on key metrics (for instance, how likely is a user to complete a purchase if they have feature A versus feature B?).
  • Turn off a feature that you realize is causing performance problems in production, without needing to re-deploy, or even restart the application with a changed configuration file.
  • Grant access to certain features based on user attributes, like payment plan (eg: users on the ‘gold’ plan get access to more features than users in the ‘silver’ plan). Disable parts of your application to facilitate maintenance, without taking everything offline.
• LaunchDarkly provides feature flag SDKs for a wide variety of languages and technologies. Check out our documentation for a complete list.
• Explore LaunchDarkly
  • launchdarkly.com for more information
  • docs.launchdarkly.com for our documentation and SDK reference guides
  • apidocs.launchdarkly.com for our API documentation
  • blog.launchdarkly.com for the latest product updates