python cosine similarity
# Example function using numpy: from numpy import dot from numpy.linalg import norm def cosine_similarity(list_1, list_2): cos_sim = dot(list_1, list_2) / (norm(list_1) * norm(list_2)) return cos_sim # Note, the dot product is only defined for lists of equal length. You # can use your_list.extend() to add elements to the shorter list # Example usage with identical lists/vectors: your_list_1 = [1, 1, 1] your_list_2 = [1, 1, 1] cosine_similarity(your_list_1, your_list_2) --> 1.0 # 1 = maximally similar lists/vectors # Example usage with opposite lists/vectors: your_list_1 = [1, 1, 1] your_list_2 = [-1, -1, -1] cosine_similarity(your_list_1, your_list_2) --> -1.0 # -1 = maximally dissimilar lists/vectors