Unlock Powerful A/B Testing with the Mida Python Client: A Developer's Guide

Harness the power of Mida directly within your Python projects using the Mida Python Client. This guide provides a comprehensive overview, enabling you to seamlessly integrate A/B testing and feature flagging into your applications. Boost user engagement and optimize your product with data-driven decisions.

Installation: Get Started in Minutes

Setting up the Mida Python client is quick and easy. Follow these simple steps:

1. Clone the Repository: Use Git to clone the Mida Python client repository to your local machine.

   git clone https://github.com/mida-so/mida-python.git
   

   Copy
2. Install Dependencies: Navigate to the cloned directory and install the necessary dependencies. This ensures your project has everything it needs to communicate with the Mida API.

Usage: Integrate A/B Testing & Feature Flags

The Mida Python Client simplifies the process of running experiments and managing feature flags. Use the provided methods to tailor user experiences and track key metrics.

Example Implementation:

from mida import Mida

# Replace 'your-project-key' with your actual key
mida_instance = Mida('your-project-key')

# Replace 'your-experiment-key' and 'your-distinct-id' with actual values
experiment = mida_instance.get_experiment('your-experiment-key', 'your-distinct-id')

if experiment == 'Control':
    print('Control variant execute')
elif experiment == 'Variant 1':
    print('Variant 1 variant execute')
elif experiment == 'Variant 2':
    print('Variant 2 variant execute')

# Set an event
mida_instance.set_event('event_name', 'your-distinct-id')

# Reload feature flags for a user
mida_instance.on_feature_flags('your-distinct-id')

# Check if a feature flag is enabled
is_enabled = mida_instance.is_feature_enabled('feature_flag_key')
if is_enabled:
    print('Feature flag is enabled')
else:
    print('Feature flag is disabled')

# Set user attributes
attributes = {
    'name': 'John Doe',
    'email': '[email protected]'
}
mida_instance.set_attribute('your-distinct-id', attributes)

Unleash the Power: Available Methods

The Mida Python Client offers a suite of powerful methods for managing experiments and feature flags:

• get_experiment(experiment_key, distinct_id): Retrieves the assigned variant for a specific user in an A/B test. This is core to running experiments with the Mida Python Client.
• set_event(event_name, distinct_id): Records user actions. It's critical for tracking goal conversions, like clicks or sign-ups, in your A/B test variants. Understanding event triggers lets you make data-driven decisions.
• is_feature_enabled(key): Determines if a feature flag is active for the user. Use this to roll out features to specific user segments.
• on_feature_flags(distinct_id): Refreshes a user's feature flag configurations. Useful when flag configurations change and need to be applied immediately.
• set_attribute(distinct_id, properties): Allows you to attach user attributes (e.g., age, location) that you can use for targeted experiments. This provides flexible rollout options.

Contribute and Help Improve

We welcome contributions from the community! If you encounter issues or have suggestions, feel free to submit a pull request to improve the stability and efficacy of the Mida Python Client.

Need Support? We're Here to Help

For any questions or assistance, please reach out to our support team at [email protected]. We're happy to help you integrate Mida in your Python projects!