  We present TODS, an automated Time Series Outlier Detection System for
research and industrial applications. TODS is a highly modular system that
supports easy pipeline construction. The basic building block of TODS is
primitive, which is an implementation of a function with hyperparameters. TODS
currently supports 70 primitives, including data processing, time series
processing, feature analysis, detection algorithms, and a reinforcement module.
Users can freely construct a pipeline using these primitives and perform end-
to-end outlier detection with the constructed pipeline. TODS provides a
Graphical User Interface (GUI), where users can flexibly design a pipeline with
drag-and-drop. Moreover, a data-driven searcher is provided to automatically
discover the most suitable pipelines given a dataset. TODS is released under
Apache 2.0 license at https://github.com/datamllab/tods.
