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The performance of organic optoelectronic devices, such as organic light-emitting diodes (OLEDs) and organic solar cells (OSCs), is intrinsically related to the molecular-scale morphology of the thin films from which they are composed. However, the experimental characterization of morphology at the molecular level is challenging due to the often amorphous or at best semicrystalline nature of these films. Classical molecular modeling techniques, such as molecular dynamics (MD) simulation, are increasingly used to understand the relationship between morphology and the properties of thin-film devices. PyThinFilm (github.com/ATB-UQ/PyThinFilm) is an open-source Python package which allows fully automated MD simulations of thin film growth to be performed using vacuum and/or solution deposition processes. PyThinFilm utilizes the GROMACS simulation package in combination with interaction parameters from the Automated Topology Builder (atb.uq.edu.au). Here, PyThinFilm is described along with an overview of applications in which PyThinFilm has been used to study the thin films of organic semiconductor materials typically used in OLEDs and OSCs.