高效压缩，比标准答案更快

def compressed_col_sparse_matrix(dense_matrix):
    dense_matrix_T = [list(a) for a in zip(*dense_matrix)]
    vocter = [item for sublist in dense_matrix_T for item in sublist]
    vals = []
    row_idx = []
    col_ptr = [0]
    p = 0
    for i, K in enumerate(vocter):
        if K != 0:
            vals.append(K)
            row_idx.append(i%len(dense_matrix[0]))
            p += 1
            if i >= len(dense_matrix_T[0]) and vocter[i-1] == 0:
                col_ptr.append(p-1)
    col_ptr.append(len(vals))
    return vals, row_idx, col_ptr


if __name__ == "__main__":
    dense_matrix = eval(input())
    vals, row_idx, col_ptr = compressed_col_sparse_matrix(dense_matrix)
    print(vals)
    print(row_idx)
    print(col_ptr)