Unlock Powerful A/B Testing with the Mida Python Client: A Quickstart Guide

Ready to take your A/B testing and feature flagging to the next level? The Mida Python client offers a streamlined way to integrate these powerful tools into your Python projects. This guide provides a clear, concise overview so you can quickly get started and maximize your impact.

Installation: Get Up and Running in Minutes

Installing the mida-python client is incredibly simple. Follow these two quick steps:

1. Clone the Repository: Open your terminal and run:

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

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2. Install Dependencies: Navigate to the cloned directory and install the necessary packages. This ensures everything runs smoothly.

Unleash the Power: Basic Usage Examples

The Mida Python client is designed for ease of use. Here's how to use some key function to get you started.

Retrieve Experiment Variants: Dynamically serve different experiences to users.

from mida import Mida

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

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')

Track Key Events: Measure the impact of changes within your application.

mida_instance.set_event('event_name', 'your-distinct-id')

Manage Feature Flags: Enable or disable features for specific user segments.

is_enabled = mida_instance.is_feature_enabled('feature_flag_key')

if is_enabled:
    print('Feature flag is enabled')
else:
    print('Feature flag is disabled')

Core Methods: Your Toolkit for Optimization with Mida

The mida-python library exposes several crucial methods for fine-grained control over your experiments and feature flags:

• get_experiment(experiment_key, distinct_id): Determines which variant a user sees in a given experiment. Perfect for A/B testing different features or content.
• set_event(event_name, distinct_id): Records user actions, allowing you to track the effectiveness of your experiments and features.
• is_feature_enabled(key): Checks the status of a given feature flag, enabling dynamic control over your application's functionality.
• on_feature_flags(distinct_id): Refreshes the feature flags for a specific user which is important when user attributes change.
• set_attribute(distinct_id, properties): Assigns user attributes which allows to filter users based on certain properties.

These methods give you the flexibility to implement sophisticated A/B testing and feature flagging strategies.

Contribute to the Project

Found a bug? Have a great idea for improvement? Contributions are highly encouraged! Submit a pull request to help make mida-python even better.

Need Help?

Contact the Mida team at [email protected] for any questions or support needs.

License

This project is licensed under the MIT License. See the LICENSE.md file for more information. Unlock the potential of data-driven decisions with the mida-python client today, use sophisticated feature flag management, and improve your applications customer experience.