# rob-med/awesome-TS-anomaly-detection

List of tools & datasets for anomaly detection on time-series data.

Repository: https://github.com/rob-med/awesome-TS-anomaly-detection
Canonical: https://ross.abutalabs.com/products/awesome-ts-anomaly-detection
License Family: other
Topics: anomaly-detection, awesome-list, outlier-detection, machine-learning, data-mining, data-analysis, time-series, temporal-data
Last push: 2024-10-21T16:22:32+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3179, "days_push": 681, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3161, forks 463 (observed 2026-08-28T04:07:46.581547+00:00)

## What it is
A curated awesome-list of software tools, libraries, and datasets for anomaly detection on time-series data. It catalogs maintained and unmaintained projects across languages like Python, Java, Julia, and C++ with license and maintenance status.

## Use cases
- find libraries for time series anomaly detection
- discover datasets for outlier detection research
- compare anomaly detection tools before choosing one
- find change point detection packages
- locate maintained time-series monitoring software
- research anomaly detection methods for streaming data

## When to choose
- you need an overview of the anomaly detection ecosystem
- you want datasets or benchmarks for time-series outlier research
- you are evaluating tools and want maintenance/license info upfront

## When to avoid
- you need a ready-to-run detection tool rather than a catalog
- you need guaranteed long-term upkeep, as it is a community-maintained list without a license

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, analytics, data-science
- domain: time-series, machine-learning, data-science, awesome-lists
- platform: cross-platform
- tags: anomaly-detection, outlier-detection, time-series, curated-list, datasets, data-mining

## Member repositories
- rob-med/awesome-TS-anomaly-detection (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:46.581547+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:25:14.309755+00:00, confidence not recorded.
  - readme: https://github.com/rob-med/awesome-TS-anomaly-detection (fetched 2026-08-28T04:07:46.581547+00:00, sha e5987425f137)
- Data as of 2026-08-30T08:39:29.467469+00:00.