In this paper, we present the Large Network Generator: a simple, intuitive, and efficient random walk network generation algorithm. It does not require any global information about the entire network, such as the node degrees or their coordinates in some Euclidean space. The algorithm is efficient, i.e. linear in the number of network nodes, and flexible, generating networks with different clustering coefficients and a range of average distances between nodes. Additionally, we provide the full implementation of the algorithm in a publicly accessible GitHub repository, as well as a PyPI package, to facilitate its adoption, support reproducibility, and strengthen further research.
