PySME v1.0: Improved modelling of stellar spectra for survey-scale applications

Stellar abundance analysis relies on flexible, high-performance spectral synthesis. To meet these needs, we present v1.0, an updated Python implementation of Spectroscopy Made Easy (SME) designed for precise and survey-scale modelling of stellar spectra. A central challenge in SME-based synthesis is the efficient treatment of very large line lists, including both the pre-selection of negligible lines and the subsequent formal synthesis. v1.0 introduces a revised line-selection framework based on opacity ratio and line depth, together with dynamic line-list construction and control of the effective wavelength span over which each line contributes to the synthetic spectrum. These workflows support parallel preprocessing of weak-line selection and reduce the line list passed to the synthesis core, thereby improving scalability while preserving synthetic accuracy. v1.0 also incorporates an updated equation-of-state treatment that improves the modelling of hydrogen lines (particularly Balmer features) while maintaining close agreement with previous SME results for metal lines. The Python interface has been further extended to support parameter-dependent derived quantities updated during optimisation, and provides non-local thermodynamic equilibrium (NLTE) departure-coefficient grids for 17 elements. Together, these developments establish v1.0 as a robust and efficient framework for high-precision stellar abundance analyses in large spectroscopic surveys.