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The R arules package implements a comprehensive infrastructure forrepresenting, manipulating, and analyzing transaction data and patterns usingfrequent itemsets and association rules. The package also provides a wide rangeof interest measures and mining algorithms, including the code of ChristianBorgelt's popular and efficient C implementations of the association miningalgorithms Apriori and Eclat, and optimized C/C++ code for mining andmanipulating association rules using sparse matrix representation. Thisdocument describes the new Python package arulespy, which makes thisinfrastructure available for Python users.

ARULESPY: Exploring Association Rules and Frequent Itemsets in Python