Concept Drift Python Packages

river

🌊 Online machine learning in Python

alibi-detect

Algorithms for outlier, adversarial and drift detection

capymoa

CapyMOA does efficient machine learning for data streams in Python. CapyMOA is a toolbox of methods and evaluators for: classification, regression, clustering, anomaly detection, semi-supervised learning, online continual learning, and drift detection for data streams.

frouros

Frouros: an open-source Python library for drift detection in machine learning systems.

creme

🌊 Online machine learning in Python

stabilization-uplift

Stabilization of classification ML-models using synthetic data with outliers on Open Data. Metrics on PyPI: pip install stabilization-uplift. NeurIPS 2025 GenAI in Finance Workshop.

calm-data-generator

CALM-Data-Generator is a comprehensive Python library for synthetic data generation with advanced features

vigil-drift

Unsupervised concept-drift detection and feature attribution for tabular data streams.

streamcal

Streaming isotonic probability calibration with compact per-bin state and forgetting

drift-or-shift

Label-shift vs concept-drift experiments and a lightweight logit-offset adapter for prevalence shift in binary classification.

octopus-ml

A collection of handy ML and data visualization and validation tools. Go ahead and train, evaluate and validate your ML models and data with minimal effort.

menelaus

Online and batch-based concept and data drift detection algorithms to monitor and maintain ML performance.

safety-compass

Detect safety degradation during LLM fine-tuning before it becomes behavioral

driftlens

Drift-Lens: an Unsupervised Drift Detection Framework for Deep Learning Classifiers on Unstructured Data

cinnamon

CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system