pyDAMPF is a tool oriented to the Atomic Force Microscopy (AFM) community, which allows the simulation of the physical properties of materials under variable relative humidity (RH). In particular, pyDAMPF is mainly focused on the mechanical properties of polymeric hygroscopic nanofibers that play an essential role in designing tissue scaffolds for implants and filtering devices. Those mechanical properties have been mostly studied from a very coarse perspective reaching a micrometer scale. However, at the nanoscale, the mechanical response of polymeric fibers becomes cumbersome due to both experimental and theoretical limitations. For example, the response of polymeric fibers to RH demands advanced models that consider sub-nanometric changes in the local structure of each single polymer chain. From an experimental viewpoint, choosing the optimal cantilevers to scan the fibers under variable RH is not trivial.In this article, we show how to use pyDAMPF to choose one optimal nanoprobe for planned experiments with a hygroscopic polymer. Along these lines, We show how to evaluate common and non-trivial operational parameters from an AFM cantilever of different manufacturers. Our results show in a stepwise approach the most relevant parameters to compare the cantilevers based on a non-invasive criterion of measurements. The computing engine is written in Fortran, and wrapped into Python. This aims to reuse physics code without losing interoperability with high-level packages. We have also introduced an in-house and transparent method for allowing multi-thread computations to the users of the pyDAMPF code, which we benchmarked for various computing architectures (PC, Google Colab and an HPC facility) and results in very favorable speed-up compared to former AFM simulators.