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In today's modern wide-field galaxy surveys, there is the necessity forparametric surface brightness decomposition codes characterised by accuracy,small degree of user intervention, and high degree of parallelisation. We tryto address this necessity by introducing $\mathrm{morphofit}$, a highlyparallelisable $\mathrm{Python}$ package for the estimate of galaxy structuralparameters. The package makes use of wide-spread and reliable codes, namely$\mathrm{SExtractor}$ and $\mathrm{GALFIT}$. It has been optimised and testedin both low-density and crowded environments, where blending and diffuse lightmakes the structural parameters estimate particularly challenging.$\mathrm{morphofit}$ allows the user to fit multiple surface brightnesscomponents to each individual galaxy, among those currently implemented in thecode. Using simulated images of single S\'ersic and bulge plus disk galaxylight profiles with different bulge-to-total luminosity ($\mathrm{B/T}$)ratios, we show that $\mathrm{morphofit}$ is able to recover the inputstructural parameters of the simulated galaxies with good accuracy. We alsocompare its estimates against existing literature studies, finding consistencywithin the errors. We use the package in Tortorelli et al. 2023 to measure thestructural parameters of cluster galaxies in order to study the wavelengthdependence of the Kormendy relation of early-type galaxies. The package isavailable on github (https://github.com/torluca/morphofit) and on the Pypiserver (https://pypi.org/project/morphofit/).

$\mathrm{morphofit}$: An automated galaxy structural parameters fitting package