The 33-, 119-, and 136-bus datasets are commonly used in the field of power systems and electrical engineering to train reinforcement learning-based algorithms for distribution network reconfiguration. Distribution network reconfiguration involves altering the topology of the electrical distribution grid by opening or closing switches to optimize certain objectives, such as minimizing power losses, improving voltage profiles, or enhancing overall system efficiency. This process is essential for maintaining a reliable and cost-effective power distribution system.