Example usage of the Python SDK

Once you have installed an SDK, import the Optimizely Feature Experimentation library into your code, get your Optimizely Feature Experimentation project's datafile, and instantiate a client. Then, you can use the client to evaluate flag rules, including A/B tests and flag deliveries.

This example demonstrates the basic usage of each of these concepts:

1. Evaluate a flag with the key product_sort using the Decide method. As a side effect, the Decide function also sends a decision event to Optimizely Feature Experimentation to record that the current user has been exposed to the experiment.

2. Conditionally execute your feature code. You have a couple of options:

• Fetch the flag enabled state, then check a configuration variable on the flag called sort_method. The SDK evaluates your flag rules and determines what flag variation the user is in, and therefore which sort method variable they should see.
• Fetch on the flag variation, then run 'control' or 'treatment' code.

3. Use event tracking to track an event called purchased. This conversion event measures the impact of an experiment. Using the Track Event method, the purchase is automatically attributed back to the running A/B test for which we made a decision. The SDK sends a network request to Optimizely Feature Experimentation using the customizable event dispatcher so Optimizely can count it in your results page.

from optimizely import optimizely

# Instantiate an Optimizely client
optimizely_client = optimizely.Optimizely(sdk_key = "<Your_SDK_Key>")

# create a user and decide a flag rule (such as an A/B test) for them
user = optimizely_client.create_user_context("user123", {"logged_in": True})
decision = user.decide("product_sort")

# did the decision fail with a critical error?
try:
  variation_key = decision.variation_key
except:
  print("decision error: {}".format(decision.reasons))

# execute code based on flag enabled state
enabled = decision.enabled
        
if enabled:
  # get flag variable values
  sort_method = decision.variables["sort_method"]

# or execute code based on flag variation
if variation_key == 'control':
    pass
    # Execute code for variation A
elif variation_key == 'treatment':
    pass
    # Execute code for variation B
else:
    pass
    # Execute code for users who don't qualify for the experiment

# Track a user event        
user.track_event("purchased")