GalaPy—Implementation strategies of the spectral modelling tool for galaxies in Python

We present the computational design and implementation of GalaPy, a hybrid C++/Python library for the spectral energy distribution (SED) modelling of galaxies. Originally introduced in Ronconi et al. (2024), GalaPy has been developed within the Italian galaxy formation and cosmology community as part of the ICSC – Centro Nazionale di Ricerca in High Performance Computing, Big Data e Quantum Computing. The library combines the performance of compiled C++ routines with the flexibility of Python, enabling efficient generation and fitting of physically motivated SED models. We describe the object-oriented architecture of the code, its hybrid parallelisation strategy, and the optimisations that ensure portability and minimal memory overhead. Parallel execution relies on a combination of vectorised array programming, shared-memory concurrency, and distributed-memory message passing. Recent updates include Bayesian evidence-based model selection and a fully analytical, panchromatic active galactic nucleus component. These additions further improve the physical realism and the statistical power of the framework. GalaPy thus provides a modular and extensible platform for galaxy modelling, designed to interface and adapt seamlessly to the next generation of large-scale astrophysical analyses.