drift-monitor 1.1.1

Drift monitoring client in Python.

Drift Monitoring Detector

Description

Drift Monitoring Detector is a Python client for monitoring concept and data drift in machine learning models. It provides an easy-to-use interface to interact with a drift monitoring server, allowing users to create experiments, log drift detections, and manage drift runs.

Features

• Create and manage experiments
• Log concept and data drift detections
• Automatically handle drift run statuses
• Integration with external monitoring servers

Badges

Visuals

Installation

To install the library (client), run:

pip install drift-monitor

Usage

Setting Up Environment Variables

Set the following environment variables to connect to your drift monitoring server:

• DRIFT_MONITOR_URL: Url pointing to the monitor server, e.g. https://drift-watch.dev.ai4eosc.eu
• DRIFT_MONITOR_MYTOKEN: Token to authenticate with the monitor server from mytoken.data.kit.edu

If you do not know how to set environment variables before starting your Python script, you can set them in your script as follows:

import os
os.environ["DRIFT_MONITOR_URL"] = "https://drift-watch.dev.ai4eosc.eu"
os.environ["DRIFT_MONITOR_MYTOKEN"] = "token_from_mytoken.data.kit.edu"
import drift_monitor

Note this is not PEP8 compliant, but it is a quick way to set environment variables in your script.

Example Usage

from drift_monitor import DriftMonitor, new_experiment, register

# Register the user
register(accept_terms=True)

# Create a new experiment
experiment_name = f"My Experiment Example"
description = "Test experiment example"
new_experiment(experiment_name, description, public=True)

# Define your detector methods
def concept_detector(*args, **kwds) -> tuple[bool, dict]:
    return True, {"feature1": 0.05, "feature2": 0.1}

def data_detector(*args, **kwds) -> tuple[bool, dict]:
    return True, {"feature3": 0.02, {"feature4": 0.08}

# Use DriftMonitor context
with DriftMonitor(experiment_name, "model_1") as monitor:
    detected, detection_parameters = concept_detector()
    monitor.concept(detected, detection_parameters)
    detected, detection_parameters = data_detector()
    monitor.data(detected, detection_parameters)

License

This project is licensed under the MIT License. See the LICENSE file for details.

Project Status

This project is actively maintained. Contributions are welcome!