The modular design of PySurf tries to match these basic building blocks, i.e. generating geometries, performing electronic structure calculations and analysing the results. For instance, geometries are needed for an unrelaxed PE scan along a reaction coordinate, for a semiclassical dynamics simulation or for the calculations of a spectrum. With the gen- eralized sampling and propagation modules many of these cases can be solved by adding small customized Plugins. At the moment the package comes with a Wigner 39 and a normal mode sampler as well as a Velocity-Verlet propagator with a Landau-Zener surface hopping algorithm. In most tasks the evaluation of properties at a given geometry is central, e.g. performing an electronic structure calculation for energies and gradients. Therefore, we introduce a corresponding module in the PySurf framework, namely the Surface Point Provider (SPP ). It is responsible for the provision of the properties in a standardized data format at a given geometry. There are already initiatives to provide generalized interfaces to a variety of electronic structure codes like the atomic simulation environment (ASE) or QCEngine. Existing generalized interfaces (as shown for the ASE in the SI) can be easily added as Plugins to the SPP as additional ab-initio methods. At this moment interfaces to the Q-Chem, 42 Turbomole, PySCF 44 and XTB program packages are provided. The SPP extends the idea of generalized interfaces further. Depending on the preferences, information is gathered by launching an electronic structure calculation, from a model system or from an interpolation scheme. For this work, an interpolator based on scipy's 46 radial-basis-function (Rbf) interpolator was implemented as Plugin. The use of machine learning techniques and methods, borrowed from the realm of artificial intelligence, offer a promising alternative for the interpolation procedure. Currently, work in this direction is in progress in our group.