Abstract
Abstract We present MERLIS , a Python-based pipeline for the automated measurement of stellar spectral-line parameters in medium-resolution spectra. The framework provides a unified approach to determining equivalent width, line depth, and full width at half-maximum for both narrow metallic lines and broad Balmer features, enabling homogeneous analysis across line profiles of substantially different morphology. The method combines local continuum renormalization, multimodel analytic profile fitting, adaptive determination of line-integration boundaries, and Monte Carlo uncertainty estimation. Broad hydrogen lines are treated using a dedicated fitting strategy designed to account for their extended wings and core-wing structure, while narrower features are analyzed through automated model selection among several candidate profile families. For multiepoch datasets, the pipeline also incorporates radial velocity consistency checks and weighted spectrum combination to reduce profile smearing and improve the robustness of the final measurements. We describe the methodology and validate its performance using both synthetic and observed stellar spectra. The workflow is further applied to 137 individual spectra of Galactic BA-type supergiants, producing a homogeneous catalog of line-profile measurements for subsequent temperature-sensitive spectroscopic analyses. The pipeline delivers reproducible line measurements, homogeneous uncertainty estimates, and fit-quality diagnostics suitable for precision studies of spectral-line variability in stellar spectroscopy.