01289nas a2200169   4500008004100000020001400041245009500055210006900150260001500219300000700234490000600241520074900247100002100996700001901017700001901036856006401055       2019                        eng d  a2364-822800aCDLIB: a python library to extract, compare and evaluate communities from complex networks0 aCDLIB a python library to extract compare and evaluate communiti  c2019/07/29  a520 v43 aCommunity Discovery is among the most studied problems in complex network analysis. During the last decade, many algorithms have been proposed to address such task; however, only a few of them have been integrated into a common framework, making it hard to use and compare different solutions. To support developers, researchers and practitioners, in this paper we introduce a python library - namely CDlib - designed to serve this need. The aim of CDlib is to allow easy and standardized access to a wide variety of network clustering algorithms, to evaluate and compare the results they provide, and to visualize them. It notably provides the largest available collection of community detection implementations, with a total of 39 algorithms.1 aRossetti, Giulio1 aMilli, Letizia1 aCazabet, Rémy  uhttps://link.springer.com/article/10.1007/s41109-019-0165-9