In this paper, we present an updated version of the roger code, called roger v2.0, developed to perform the orbital classification of galaxies residing in and around galaxy groups and clusters. In addition to the projected phase-space coordinates, the new version incorporates the host halo mass as an additional input parameter. Although the inclusion of the halo mass leads to only modest changes in the classification, it contributes to improving the overall robustness of the method. We also extend the range of host halo masses over which roger can be applied, enabling the analysis of systems with masses down to . We further provide a Python implementation of the new code, which will be made publicly available. This implementation enables users to efficiently and robustly classify arbitrary galaxy samples using either version of the method. Moreover, it allows users to train a customized classifier on an alternative training set, providing the flexibility to adapt the method to different datasets and scientific applications.

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