FreeOpcUa / python-opcua

    __repr__ = __str__

class AnonymousIdentityToken(FrozenClass):

    '''

    A token representing an anonymous user.

    :ivar PolicyId:

    :vartype PolicyId: String

    '''

    def __init__(self, binary=None):

        if binary is not None:

            self._binary_init(binary)

            self._freeze = True

            return

        self.PolicyId = None

        self._freeze = True

    def to_binary(self):

        packet = []

        packet.append(pack_string(self.PolicyId))

        return b''.join(packet)

    @staticmethod

    def from_binary(data):

        return AnonymousIdentityToken(data)

    def _binary_init(self, data):

        self.PolicyId = unpack_string(data)

    def __str__(self):

        return 'AnonymousIdentityToken(' + 'PolicyId:' + str(self.PolicyId) + ')'

    __repr__ = __str__

class UserNameIdentityToken(FrozenClass):

    __repr__ = __str__

class UserIdentityToken(FrozenClass):

    '''

    A base type for a user identity token.

    :ivar PolicyId:

    :vartype PolicyId: String

    '''

    def __init__(self, binary=None):

        if binary is not None:

            self._binary_init(binary)

            self._freeze = True

            return

        self.PolicyId = None

        self._freeze = True

    def to_binary(self):

        packet = []

        packet.append(pack_string(self.PolicyId))

        return b''.join(packet)

    @staticmethod

    def from_binary(data):

        return UserIdentityToken(data)

    def _binary_init(self, data):

        self.PolicyId = unpack_string(data)

    def __str__(self):

        return 'UserIdentityToken(' + 'PolicyId:' + str(self.PolicyId) + ')'

    __repr__ = __str__

class AnonymousIdentityToken(FrozenClass):

    subsize = 1

    for i in subdims:

        if i == 0:

            i = 1

        subsize *= i

    while dims[0] * subsize > len(flat):

        flat.append([])

    if not subdims or subdims == [0]:

        return flat

    return [reshape(flat[i: i + subsize], subdims) for i in range(0, len(flat), subsize)]

def _split_list(l, n):

    n = max(1, n)

    return [l[i:i + n] for i in range(0, len(l), n)]

def flatten_and_get_shape(mylist):

    dims = []

    dims.append(len(mylist))

    while isinstance(mylist[0], (list, tuple)):

        dims.append(len(mylist[0]))

        mylist = [item for sublist in mylist for item in sublist]

        if len(mylist) == 0:

            break

    return mylist, dims

def flatten(mylist):

    if len(mylist) == 0:

        return mylist

    while isinstance(mylist[0], (list, tuple)):