Non-Ideal System Identification (NisI) is a Python code developed for system identification of non-ideal systems using a single observed state. Non-Ideal System (NIS) exhibits significantly complex dynamic behavior due to the presence of nonlinear and discontinuous equations, resulting in chaotic behavior. Identifying parameters for NIS is more challenging when only certain states of the system are observable. The proposed method in this study uses a Particle Swarm Optimization (PSO) meta-heuristic to minimize the difference between experimental data and a proposed nonlinear model. This code has successfully identified all unknown parameters of the non-ideal system in experimental systems.