PySAD

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About

PySAD is ranked #9 of 19 in anomaly detection software on Inferse. It runs on Linux, macOS, Windows. There is a free plan.

Compared on anomaly detection software

Free plan: Yesgithub.com
Detection method: hybridgithub.com
Real-time detection: Yesgithub.com
Supported data: univariate data; multivariate data; streaming datagithub.com
Deployment options: self-hostedgithub.com

Facts

Purpose: PySAD is an open-source Python framework for anomaly detection on streaming multivariate data.pysad.readthedocs.io · 2 Oct 2026
Online detection: Its models update as each new data instance arrives for online or sequential anomaly detection.pysad.readthedocs.io · 2 Oct 2026
Detectors: The repository describes 16 online detectors, including xStream, LODA, RS-Hash, Half-Space Trees, and Robust Random Cut Forest.github.com · 2 Oct 2026
Resource use: The documentation says streaming methods may store only an instance or a small window of recent instances to meet memory and processing constraints.pysad.readthedocs.io · 2 Oct 2026
Evaluation tools: PySAD includes stream simulators, evaluators, preprocessors, statistic trackers, postprocessors, and probability calibrators.pysad.readthedocs.io · 2 Oct 2026
PyOD integration: PySAD provides integrations that let batch anomaly detectors from PyOD run in a streaming setting.pysad.readthedocs.io · 2 Oct 2026
Data and learning settings: The framework supports models for univariate and multivariate data and experiments in supervised, semi-supervised, and unsupervised settings.pysad.readthedocs.io · 2 Oct 2026
Installation: The project can be installed with pip or from its GitHub source, and its current README lists Python 3.10 or newer on Linux, macOS, and Windows.github.com · 2 Oct 2026
License: The project is distributed under a BSD 3-Clause license.github.com · 2 Oct 2026
Support: The maintainer says issues and pull requests are welcome and aims to reply within a few days; questions and show-and-tell go in GitHub Discussions.github.com · 2 Oct 2026
Benchmarks: The README says 17 labelled benchmark datasets are downloaded on first use.github.com · 2 Oct 2026
Security: The repository links to a security policy, but the policy page could not be opened during this research.github.com · 2 Oct 2026
Maintainer: The GitHub profile identifies Selim Firat Yilmaz as an AI researcher based in London, UK.github.com · 2 Oct 2026