Describing the swdatatoolkit: A Space Weather Data Analysis Library

TL;DR

swdatatoolkit is a Python library that streamlines the acquisition, preprocessing, and analysis of solar and space weather data, facilitating reproducible research and machine learning applications.

Contribution

It introduces a modular, comprehensive toolkit that consolidates various space weather data analysis functions into a single Python library.

Findings

Supports data downloading from multiple heliophysics sources

Includes image preprocessing and magnetic field analysis tools

Enables reproducible workflows for space weather research

Abstract

swdatatoolkit is a Python-based scientific software library designed to support the acquisition, preprocessing, and analysis of solar and space weather data. The toolkit consolidates functionality across multiple domains, including data downloading from established heliophysics sources, image preprocessing, edge detection, image texture quantification, magnetic field analysis, and the derivation of higher-level parameters commonly used in solar physics research. Its modular structure reflects the heterogeneous nature of space weather data and enables reproducible, extensible workflows for both exploratory analysis and machine-learning-driven studies. This paper presents an overview of the library's available capabilities, its scientific motivations, and its role in the broader space weather research ecosystem.