Anomaly Detection Python Packages

pyod

A Python library for anomaly detection across tabular, time series, graph, text, image, and audio data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.

sktime

A unified framework for machine learning with time series

drain3

A robust streaming log template miner based on the Drain algorithm

stumpy

STUMPY is a powerful and scalable Python library for modern time series analysis

pycaret

Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.

adtk

A Python toolkit for rule-based/unsupervised anomaly detection in time series

darts

A python library for user-friendly forecasting and anomaly detection on time series.

pypots

A Python toolkit/library for reality-centric machine/deep learning & data mining on partially-observed time series, with 50+ SOTA neural network models for scientific analysis tasks (imputation, classification, clustering, forecasting, anomaly detection, cleaning) on incomplete industrial irregularly-sampled multivariate TS with NaN missing values

nixtla

TimeGPT-2.1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.

u8darts

A python library for user-friendly forecasting and anomaly detection on time series.

cleanlab

Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

pynomaly

Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].

spectral

Python module for hyperspectral image processing

arbiter-engine

A detection engine that reports what it did not check. Eight axiom families over a domain model declared in YAML, with every declined evaluation recorded as a machine-readable reason.

deadwood

Deadwood: Outlier Detection via Pruning Mutual Reachability Minimum Spanning Trees

rbeast

Bayesian Change-Point Detection and Time Series Decomposition

suod

(MLSys' 21) An Acceleration System for Large-scare Unsupervised Heterogeneous Outlier Detection (Anomaly Detection)

salesforce-merlion

Merlion: A Machine Learning Framework for Time Series Intelligence

isotree

(Python, R, C/C++) Isolation Forest and variations such as SCiForest and EIF, with some additions (outlier detection + similarity + NA imputation)

lumbermark

Lumbermark: Resistant Clustering via Chopping Up Mutual Reachability Minimum Spanning Trees

wickra-genome

A vector database of the whole market: every asset as a live vector over the 497 O(1) streaming indicators the registry resolves. Similarity search, clustering, anomaly detection over microstructure DNA.

desbordante

Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.

finops-mcp

The headless FinOps intelligence layer: API-first, agent-first cost control for cloud + AI. Connect your cloud stack in Claude, Cursor, or the terminal, and gate what agents do to your infra before they act. Propose-only. Open source, local-first.

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.