This Python package generates synthetic graphs with a fixed graph edit distance. The generated datasets can be used to robustly train deep learning algorithms to compute the graph edit distance between two graphs. The same datasets can be used to compare different graph edit distance algorithms. Two methods are implemented: Once and All. In the Once method, the input parameters are an input graph called the seed and a stay probability (a numerical value between zero and one). The All method requires an input graph called Seed and a flip probability (a numerical value between zero and one). For the Once and All methods, it is also possible to specify the number of samples that each method must generate. The code is written in Python and can be run on modest hardware. edit distance of two graphs (GED)