How to use the tiledb.DenseArray.load function in tiledb

dtype="int32")

    array_strs = np.array([[b"a", b"bb", b"e", b"ff"],
                           [b"ccc", b"dddd", b"ggg", b"hhhh"],
                           [b"i", b"jj", b"m", b"nn"],
                           [b"kkk", b"llll", b"ooo", b"pppp"]],
                           dtype="S4")

    array_pairs = np.array([[(0.1, 0.2), (1.1, 1.2), (4.1, 4.2), (5.1, 5.2)],
                            [(1.1, 1.2), (3.1, 3.2), (6.1, 6.2), (7.1, 7.2)],
                            [(8.1, 8.2), (9.1, 9.2), (12.1, 12.2), (13.1, 13.2)],
                            [(10.1, 10.2), (11.1, 11.2), (14.1, 14.2), (15.1, 15.2)]],
                           dtype="float32,float32")

    ctx = tiledb.Ctx()
    dense_example = tiledb.DenseArray.load(ctx, "my_dense_array")
    dense_example[:] = {"a1": array_ints,
                        "a2": array_strs,
                        "a3": array_pairs}

def main():
    # Create TileDB context
    ctx = tiledb.Ctx()

    # Load the dense array schema
    dense_example = tiledb.DenseArray.load(ctx, "my_dense_array")

    # Retrieve and print the non-empty domain
    nonempty = dense_example.nonempty_domain()
    print("Non-empty domain:")
    for i in range(dense_example.ndim):
        print("{0!s}: {1!r}".format(dense_example.domain.dim(i).name, nonempty[i]))

    # Read the entire array. `result` is a dict of numpy arrays
    result = dense_example[:]

    # Print the results
    result_num = result["a1"].size
    print("\nResult num: ", result_num)
    print()
    print("{:<5s}{:<10s}{:<10s}{:<10s}".format("a1", "a2", "a3[0]", "a3[1]"))
    print("------------------------------")

def main():
    # Create TileDB context
    ctx = tiledb.Ctx()

    # Load the dense array schema
    dense_example = tiledb.DenseArray.load(ctx, "my_dense_array")

    # Retrieve and print the non-empty domain
    nonempty = dense_example.nonempty_domain()
    print("Non-empty domain:")
    for i in range(dense_example.ndim):
        print("{0!s}: {1!r}".format(dense_example.domain.dim(i).name, nonempty[i]))

    # Read an array slice. `result` is a dict of numpy arrays
    result = dense_example[3:5, 3:5]

    # Print the results
    result_num = result["a1"].size
    print("\nResult num: ", result_num)
    print()
    print("{:<5s}{:<10s}{:<10s}{:<10s}".format("a1", "a2", "a3[0]", "a3[1]"))
    print("------------------------------")