PNet: A Python Library for Petri Net Modeling and Simulation

Zhu En Chay, Bing Feng Goh, Maurice HT Ling

Abstract


Petri Net is a formalism to describe changes between 2 or more states across discrete time and has been used to model many systems. We present PNet – a pure Python library for Petri Net modeling and simulation in Python programming language. The design of PNet focuses on reducing the learning curve needed to define a Petri Net by using a text-based language rather than programming constructs to define transition rules. Complex transition rules can be refined as regular Python functions. To demonstrate the simplicity of PNet, we present 2 examples – bread baking, and epidemiological models.


Keywords


Network modeling; Time-step simulation; Petri Net; Ordinary Differential Equation; Python

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References


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