To showcase the flexibility of having a script-based library of electrochemical equations, I am using the calculate module to obtain linear sweep voltammograms of an ultramicrodisc electrode with varying concentrations of the reduced species, Figure shows the results (please see Section 6 for the script used here). I have included a value for the normally distributed random noise to include variation in the currents; this is done by giving a value to the noise parameter in the LSV function, by default this is set to zero. Figure shows the obtained voltammograms for each concentration, small variations in the current are due to the added noise. Figure shows the voltammograms normalized by their respective limiting currents, where the added noise is more evident. Although the MicroDisc class calculates the expected limiting current by default, here it was obtained by averaging the currents from 0.2 to 0.5 V to account for the variation given by the noise. Figure shows the limiting currents as a function of the bulk concentrations, as well as the linear fitting obtained using the linregress function of the scipy Python library. This showcases the flexibility provided by softpotato, as it can be interfaced with third-party libraries to perform data analysis, plotting, etc. The electrochemical equations implemented in softpotato can even be used to fit experimental results by using the curve fit function from scipy.optimize, which requires the user to write their own objective function. In this way, any function from the sofpotato.calculate library can be used as a parameter in curve fit to estimate electrochemical parameters from experimental results.