thuml/Time-Series-Library

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

12923 stars · 2008 forks observed · 2026-10-01

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

TSLib is an open-source Python library providing a unified codebase of advanced deep learning models for general time series analysis. It supports long- and short-term forecasting, imputation, anomaly detection, and classification, and is widely used as a research benchmark.

Use cases

• benchmark deep time series forecasting models
• run anomaly detection on time series data
• impute missing values in time series
• classify time series with deep learning
• develop and evaluate a new time series model
• zero-shot forecasting with large time series models

When to choose

• you are a researcher evaluating or developing deep time series models
• you need consistent baselines across forecasting, imputation, anomaly detection, and classification tasks
• you want a neat, unified codebase for time series experiments

When to avoid

• you need production-ready time series pipelines rather than research code
• you require actively developed new features, since the project is no longer actively adding them
• you need up-to-date benchmarks, as many original ones may be saturated

Facets

library · maturity maintenance

deep-learning machine-learning benchmarking time-series deep-learning machine-learning data-science python time-series-forecasting anomaly-detection imputation classification research-benchmark deep-time-series-models

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