题解 | 实现压缩行稀疏矩阵（CSR）格式转换

def compressed_row_sparse_matrix(dense_matrix):
    vocter = [item for subvc in dense_matrix for item in subvc]
    vals = []
    col_idx = []
    row_ptr = [0]
    p  = 0
    for k, i in enumerate(vocter):
        
        if i != 0:
            col_idx.append(k%len(dense_matrix[0]))
            vals.append(i)            
            p += 1
            if k >= len(dense_matrix[0]) and vocter[k-1] == 0:
                row_ptr.append(p-1)

    row_ptr.append(len(vals))

    return vals, col_idx, row_ptr


if __name__ == "__main__":
    dense_matrix = eval(input())
    vals, col_idx, row_ptr = compressed_row_sparse_matrix(dense_matrix)
    print(vals)
    print(col_idx)
    print(row_ptr)