In this work we present our generic framework to construct, simulate and calibrate dynamical
systems in Python 3. Its goal is to reduce the time it takes to implement a dynamical system
with n-dimensional states represented by coupled ordinary differential equations (ODEs),
simulate the system deterministically or stochastically, and, calibrate the system using n-
dimensional data. We demonstrate our code's capabilities by building three models in the
context of two case studies. First, we forecast the yields of the enzymatic esterification …