linkedin/luminol

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1230 stars · 217 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Luminol is a lightweight Python library for time series analysis that provides anomaly detection and correlation between time series. It assigns anomaly scores to data points without predefined thresholds and supports correlating shifted peaks to help identify root causes of anomalies.

Use cases

• detect anomalies in time series data
• find correlation between two time series
• automate root cause analysis of metric spikes
• rank correlated system metrics during an incident
• identify time windows where anomalies occurred

When to choose

• you need lightweight, threshold-free anomaly detection in Python
• you want to correlate a detected anomaly with other metrics for root cause analysis
• you need configurable detection algorithms with anomaly severity scores

When to avoid

• you need real-time streaming anomaly detection at scale
• you need deep learning based forecasting or multivariate models
• you need actively developed features beyond the 0.4 release

Facets

library · maturity maintenance

machine-learning analytics monitoring data-science analytics monitoring time-series python cross-platform anomaly-detection time-series-analysis correlation root-cause-analysis

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