Microsoft Feature Management

2.1.0 verified Mon Apr 27 auth: no python

A Python library for enabling/disabling features at runtime, commonly used in .NET-style feature flag systems. Current version: 2.1.0. Released as needed, follows semantic versioning.

pip install featuremanagement

Common errors

error ModuleNotFoundError: No module named 'featuremanagement' ↓

cause The library is not installed or the Python environment is incorrect.

fix

Run 'pip install featuremanagement' in the correct environment.

error AttributeError: 'FeatureManager' object has no attribute 'is_enabled' ↓

cause Typo or older version without 'is_enabled' method.

fix

Use FeatureManager from featuremanagement 2.0+, which includes 'is_enabled'. Check your installed version with 'pip show featuremanagement'.

error ValueError: The feature flag configuration is invalid. ↓

cause The flags dictionary passed to FeatureManager does not conform to the required schema.

fix

Ensure each flag has an 'enabled' key with a boolean value. Optionally add 'conditions' with appropriate filters.

Warnings

gotcha Feature flags dictionary must follow the correct schema: each flag must have an 'enabled' key (boolean) and optionally 'conditions'. ↓

fix Ensure your flag dictionary structure matches: {"FeatureName": {"enabled": True}}.

gotcha The library expects feature flags in a specific format when using Azure App Configuration; mismatched structure can cause silent failures. ↓

fix Use the Azure App Configuration provider to load flags automatically, or manually parse flags to match the expected schema.

deprecated The method 'is_enabled' is stable but some older documentation refers to 'is_enabled' with a different signature (without the user context). ↓

fix Ensure you pass the correct arguments: is_enabled(feature_name, user_context=None).

Imports

FeatureManager
```
from featuremanagement import FeatureManager
```
Import from featuremanagement directly, not from submodules.

FeatureFilterEvaluationContext

from featuremanagement import FeatureFilterEvaluationContext

Correct import path.

Quickstart

Basic usage: create a FeatureManager with a dictionary of flags and check if a feature is enabled.

from featuremanagement import FeatureManager

# Initialize with in-memory feature flags
feature_manager = FeatureManager(feature_flags={
    "Beta": {
        "enabled": True
    }
})

# Check if a feature is enabled
if feature_manager.is_enabled("Beta"):
    print("Beta feature is enabled")
else:
    print("Beta feature is disabled")