Python SDK for Featureflip - a feature flag SaaS platform
Project description
Featureflip Python SDK
Python SDK for Featureflip - evaluate feature flags locally with near-zero latency.
Installation
pip install featureflip
Quick Start
from featureflip import FeatureflipClient
# Initialize the client (blocks until flags are loaded)
client = FeatureflipClient(sdk_key="your-sdk-key")
# Evaluate a feature flag
enabled = client.variation("my-feature", {"user_id": "user-123"}, default=False)
if enabled:
print("Feature is enabled!")
else:
print("Feature is disabled")
# Clean shutdown
client.close()
Configuration
from featureflip import FeatureflipClient, Config
client = FeatureflipClient(
sdk_key="your-sdk-key",
config=Config(
base_url="https://eval.featureflip.io", # Evaluation API URL
streaming=True, # Use SSE for real-time updates (default)
poll_interval=30.0, # Polling interval if streaming=False
send_events=True, # Enable analytics event tracking
flush_interval=30.0, # Event flush interval in seconds
init_timeout=10.0, # Max seconds to wait for initialization
)
)
The SDK key can also be set via the FEATUREFLIP_SDK_KEY environment variable.
Context Manager
with FeatureflipClient(sdk_key="your-sdk-key") as client:
enabled = client.variation("my-feature", {"user_id": "123"}, default=False)
# Automatically closes and flushes events on exit
Evaluation
# Boolean flag
enabled = client.variation("feature-key", {"user_id": "123"}, default=False)
# String flag
tier = client.variation("pricing-tier", {"user_id": "123"}, default="free")
# Number flag
limit = client.variation("rate-limit", {"user_id": "123"}, default=100)
# JSON flag
config = client.variation("ui-config", {"user_id": "123"}, default={"theme": "light"})
Detailed Evaluation
detail = client.variation_detail("feature-key", {"user_id": "123"}, default=False)
print(detail.value) # The evaluated value
print(detail.reason) # "RULE_MATCH", "FALLTHROUGH", "FLAG_DISABLED", etc.
print(detail.rule_id) # Rule ID if reason is RULE_MATCH
Event Tracking
# Track custom events
client.track("checkout-completed", {"user_id": "123"}, metadata={"total": 99.99})
# Identify users for segment building
client.identify({"user_id": "123", "email": "user@example.com", "plan": "pro"})
# Force flush pending events
client.flush()
Testing
Use the test client for deterministic unit tests:
from featureflip import FeatureflipClient
# Create a test client with fixed values (no network calls)
client = FeatureflipClient.for_testing({
"my-feature": True,
"pricing-tier": "pro",
})
# Evaluations return the configured values
assert client.variation("my-feature", {}, default=False) is True
assert client.variation("pricing-tier", {}, default="free") == "pro"
# Unknown flags return the default
assert client.variation("unknown", {}, default="fallback") == "fallback"
# Update values at runtime
client.set_test_value("my-feature", False)
Features
- Client-side evaluation - Near-zero latency after initialization
- Real-time updates - SSE streaming with polling fallback
- Event tracking - Automatic batching and flushing of analytics events
- Test support -
for_testing()factory for deterministic unit tests - Type-safe - Full type hints with mypy strict mode compliance
Requirements
- Python 3.10+
Development
# Install development dependencies
pip install -e ".[dev]"
# Run tests
pytest
# Run linting
ruff check src/featureflip tests
# Run type checking
mypy src/featureflip --strict
License
MIT
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