{('q0', ('1', '#')): [('q0', (('1', 'R'), ('1', 'R')))],
 ('q0', ('0', '#')): [('q0', (('0', 'R'), ('#', 'S')))],
 ('q0', ('#', '#')): [('q1', (('#', 'S'), ('#', 'S')))]}

Add the TM instance to the queue
While queue is not empty:
   Fetch the first TM from the queue
   If there is no transition for the current state and read symbols:
      If the TM is in a final state: return TM
   Else:
      If the transition is nondeterministic:
         Create replicas of the TM and add them to the queue
      Execute the transition in the current TM and add it to the queue

% HEADER: mandatory
start_state final_state blank number_of_tapes
% TRANSITIONS
state read_symbols new_state write_symbol, move write_symbol, move ...

% HEADER
q0 q1 # 2
% TRANSITIONS
q0 1, # q0 1, R 1, R
q0 0, # q0 0, R #, S
q0 #, # q1 #, S #, S

from NDTM import NDTM
tm = NDTM.parse('2sum.tm')
print(tm.accepts('11011101'))

Output :
q1: ['1', '1', '0', '1', '1', '1', '0', '1']['#']
q1: ['1', '1', '1', '1', '1', '1']['#']

####
# NDTM.py: a nondeterministic Turing Machine Simulator
# Author: David Gil del Rosal (dgilros@yahoo.com)
#### from collections import defaultdict, deque

class Tape:
    # Constructor. Sets the blank symbol, the
    # string to load and the position of the tape head
    def __init__(self, blank, string ='', head = 0):
        self.blank = blank
        self.loadString(string, head)

    # Loads a new string and sets the tape head   
    def loadString(self, string, head):
        self.symbols = list(string)
        self.head = head

    # Returns the symbol on the current cell, or the blank
    # if the head is on the start of the infinite blanks
    def readSymbol(self):
        if self.head < len(self.symbols):
            return self.symbols[self.head]
        else:
            return self.blank

    # Writes a symbol in the current cell, extending
    # the list if necessary
    def writeSymbol(self, symbol):
        if self.head < len(self.symbols):
            self.symbols[self.head] = symbol
        else:
            self.symbols.append(symbol)

    # Moves the head left (-1), stay (0) or right (1)
    def moveHead(self, direction):
        if direction == 'L': inc = -1
        elif direction == 'R': inc = 1
        else: inc = 0
        self.head+= inc

    # Creates a new tape with the same attributes than this
    def clone(self):
        return Tape(self.blank, self.symbols, self.head)

    # String representation of the tape
    def __str__(self):
        return str(self.symbols[:self.head]) + \
               str(self.symbols[self.head:])

class NDTM:
    # Constructor. Sets the start and final states and
    # inits the TM tapes
    def __init__(self, start, final, blank ='#', ntapes = 1):
        self.start = self.state = start
        self.final = final
        self.tapes = [Tape(blank) for _ in range(ntapes)]
        self.trans = defaultdict(list)

    # Puts the TM in the start state and loads an input
    # string into the first tape
    def restart(self, string):
        self.state = self.start
        self.tapes[0].loadString(string, 0)
        for tape in self.tapes[1:]:
            tape.loadString('', 0)

    # Returns a tuple with the current symbols read
    def readSymbols(self):
        return tuple(tape.readSymbol() for tape in self.tapes)

    # Add an entry to the transaction table
    def addTrans(self, state, read_sym, new_state, moves):
        self.trans[(state, read_sym)].append((new_state, moves))

    # Returns the transaction that corresponds to the
    # current state & read symbols, or None if there is not
    def getTrans(self):
        key = (self.state, self.readSymbols())
        return self.trans[key] if key in self.trans else None

    # Executes a transaction updating the state and the
    # tapes. Returns the TM object to allow chaining   
    def execTrans(self, trans):
        self.state, moves = trans
        for tape, move in zip(self.tapes, moves):
            symbol, direction = move
            tape.writeSymbol(symbol)
            tape.moveHead(direction)
        return self

    # Returns a copy of the current TM
    def clone(self):
        tm = NDTM(self.start, self.final)
        tm.state = self.state
        tm.tapes = [tape.clone() for tape in self.tapes]
        tm.trans = self.trans        # shallow copy
        return tm

    # Simulates the TM computation. Returns the TM that
    # accepted the input string if any, or None.
    def accepts(self, string):
        self.restart(string)
        queue = deque([self])
        while len(queue) > 0:
            tm = queue.popleft()
            transitions = tm.getTrans()
            if transitions is None:
                # there are not transactions. Exit
                # if the TM is in the final state
                if tm.state == tm.final: return tm
            else:
                # If the transaction is not deterministic
                # add replicas of the TM to the queue
                for trans in transitions[1:]:
                    queue.append(tm.clone().execTrans(trans))
                # execute the current transition
                queue.append(tm.execTrans(transitions[0]))
        return None

    def __str__(self):
        out = ''
        for tape in self.tapes:
            out+= self.state + ': ' + str(tape)  + '\n'
        return out

    # Simple parser that builds a TM from a text file
    @staticmethod
    def parse(filename):
        tm = None
        with open(filename) as file:
            for line in file:
                spec = line.strip()
                if len(spec) == 0 or spec[0] == '%': continue
                if tm is None:
                    start, final, blank, ntapes = spec.split()
                    ntapes = int(ntapes)
                    tm = NDTM(start, final, blank, ntapes)
                else:
                    fields = line.split()
                    state = fields[0]
                    symbols = tuple(fields[1].split(', '))
                    new_st = fields[2]
                    moves = tuple(tuple(m.split(', '))
                                  for m in fields[3:])
                    tm.addTrans(state, symbols, new_st, moves)
        return tm

if __name__ == '__main__':
    # Example TM that performs unary complement
    tm = NDTM('q0', 'q1', '#')
    tm.addTrans('q0', ('0', ), 'q0', (('1', 'R'), ))
    tm.addTrans('q0', ('1', ), 'q0', (('0', 'R'), ))
    tm.addTrans('q0', ('#', ), 'q1', (('#', 'S'), ))
    acc_tm = tm.accepts('11011101')
    if acc_tm: print(acc_tm)
    else: print('NOT ACCEPTED')   

% 3-tape NDTM that recognizes L={ ww | w in {0, 1}* }
q0 q4 # 3
% TRANSITIONS
% put left endmarkers on tapes #2 and #3
q0 0, #, # q1 0, S $, R $, R
q0 1, #, # q1 1, S $, R $, R
% first half of string: copy symbols on tape #2
q1 0, #, # q1 0, R 0, R #, S
q1 1, #, # q1 1, R 1, R #, S
% guess second half of string: copy symbols on tape #3
q1 0, #, # q2 0, R #, S 0, R
q1 1, #, # q2 1, R #, S 1, R
q2 0, #, # q2 0, R #, S 0, R
q2 1, #, # q2 1, R #, S 1, R
% reached end of input string: switch to compare state
q2 #, #, # q3 #, S #, L #, L
% compare strings on tapes #2 and #3
q3 #, 0, 0 q3 #, S 0, L 0, L
q3 #, 1, 1 q3 #, S 1, L 1, L
% if both strings are equal switch to final state
q3 #, $, $ q4 #, S $, S $, S

from NDTM import NDTM
tm = NDTM.parse('3ww.tm')
print(tm.accepts('11001100'))

Output :
q4: ['1', '1', '0', '0', '1', '1', '0', '0']['#']
q4: []['{content}apos;, '1', '1', '0', '0', '#']
q4: []['{content}apos;, '1', '1', '0', '0', '#']