TimeGym: Debugging for Time Series Modeling in Python

TL;DR

TimeGym is a Python toolkit that facilitates testing and debugging of time series forecasting models through generic tests and a test-driven development approach, improving model reliability.

Contribution

It introduces a comprehensive debugging toolkit for time series forecasting in Python, enabling easier testing and validation of models with artificial data and oracles.

Findings

Simplifies debugging of time series models

Supports test-driven development for forecasting

Provides generic tests for common modeling challenges

Abstract

We introduce the TimeGym Forecasting Debugging Toolkit, a Python library for testing and debugging time series forecasting pipelines. TimeGym simplifies the testing forecasting pipeline by providing generic tests for forecasting pipelines fresh out of the box. These tests are based on common modeling challenges of time series. Our library enables forecasters to apply a Test-Driven Development approach to forecast modeling, using specified oracles to generate artificial data with noise.