Abstract
<jats:p>In this article, we present EL-PASO (ELaborative Particle Analysis from Satellite Observations), an open-source Python library for processing and standardizing in-situ particle measurements taken in space. EL-PASO aims to address the challenges posed by the diverse data formats and metadata standards used by different space missions. Its main purpose is the conversion of non-standardized particle data into a common data format with standardized metadata, and the calculation of derived products, such as adiabatic invariants and phase space density. EL-PASO supports multiple file formats such as cdf, netcdf4, ascii-based formats, and json, for both reading and saving data. Here, we describe the software architecture and design of EL-PASO, display small code snippets as examples, and show how EL-PASO is verified against published data from other sources, such as the Van Allen Probes team and previous results obtained at GFZ. By providing a unified library for data processing, EL-PASO facilitates the comparison and integration of particle measurements from various sources, ultimately enabling multi-mission studies on a larger scale, and enhancing our understanding of space weather phenomena.</jats:p>