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How to get Python iterators not to communicate with each other?

Here's a simple iterator through the characters of a string.
class MyString:
def __init__(self,s):
self.s = s
self._ix = 0
def __iter__(self):
return self
def __next__(self):
try:
item = self.s[self._ix]
except IndexError:
self._ix = 0
raise StopIteration
self._ix += 1
return item
string = MyString('abcd')
iter1 = iter(string)
iter2 = iter(string)
print(next(iter1))
print(next(iter2))
Trying to get this iterator to function like it should. There are a few requirements. First, the __next__ method MUST raise StopIteration and multiple iterators running at the same time must not interact with each other.
I accomplished objective 1, but need help on objective 2. As of right now the output is:
'a'
'b'
When it should be:
'a'
'a'
Any advice would be appreciated.
Thank you!

MyString acts as its own iterator much like a file object
>>> f = open('deleteme', 'w')
>>> iter(f) is f
True
You use this pattern when you want all iterators to affect each other - in this case advancing through the lines of a file.
The other pattern is to use a separate class to iterate much like a list whose iterators are independent.
>>> l = [1, 2, 3]
>>> iter(l) is l
False
To do this, move the _ix indexer to a separate class that references MyString. Have MyString.__iter__ create an instance of the class. Now you have a separate indexer per iterator.
class MyString:
def __init__(self,s):
self.s = s
def __iter__(self):
return MyStringIter(self)
class MyStringIter:
def __init__(self, my_string):
self._ix = 0
self.my_string = my_string
def __iter__(self):
return self
def __next__(self):
try:
item = self.my_string.s[self._ix]
except IndexError:
raise StopIteration
self._ix += 1
return item
string = MyString('abcd')
iter1 = iter(string)
iter2 = iter(string)
print(next(iter1))
print(next(iter2))

Your question title asks how to get iterators, plural, to not communicate with each other, but you don't have multiple iterators, you only have one. If you want to be able to get distinct iterators from MyString, you can add a copy method:
class MyString:
def __init__(self,s):
self.s = s
self._ix = 0
def __iter__(self):
return self
def __next__(self):
try:
item = self.s[self._ix]
except IndexError:
self._ix = 0
raise StopIteration
self._ix += 1
return item
def copy(self):
return MyString(self.s)
string = MyString('abcd')
iter1 = string.copy()
iter2 = string.copy()
print(next(iter1))
print(next(iter2))

Understanding Stacks and Queues in python

So i was given this question. Consider the Stack and the Queue class with standard set of operations. Using the Stack and Queue class, what items are contained in them just before the mysteryFunction is called AND just after the mysteryFunction is called?
Here is the code:
def mysteryFunction(s, q):
q.enqueue('csc148')
q.enqueue(True)
q.enqueue(q.front())
q.enqueue('abstract data type')
for i in range(q.size()):
s.push(q.dequeue())
while not s.is_empty():
q.enqueue(s.pop())
if __name__ == '__main__':
s=Stack()
q=Queue()
#About to call mysteryFunction
#What are contents of s and q at this point?
mysteryFunction(s, q)
#mysteryFunction has been called.
#What are contents of s and q at this point?
I'm having trouble understanding object oriented programming as i'm new to this topic. Is there any link that breaks down Stacks and Queues and what they do?

In general, stacks are LIFO and queues are FIFO.
In Python, you can use the collections module to experiment with stacks and queues:
>>> from collections import deque
>>> stack = deque()
>>> stack.append(10)
>>> stack.append(20)
>>> stack.append(30)
>>> stack
deque([10, 20, 30])
>>> stack.pop() # LIFO
30
>>> stack.pop()
20
>>>
>>> queue = deque()
>>> queue.append(10)
>>> queue.append(20)
>>> queue.append(30)
>>> queue
deque([10, 20, 30])
>>> queue.popleft() # FIFO
10
>>> queue.popleft()
20

See following links for more information:
Stack
Queue
Visually these two data structures can be seen in a following way:
Stack:
Description:
There are variations of this data structure. However, in simple terms - as one can observe in the image provided, when you add to this data structure you place on top of what is already there and when you remove you also take from the top. You can view it as a stack of books which you go through one by one starting from the top and all the way down.
Queue
Description:
There are also variations on this particular data structure, however in simple terms - as you can see in the image provided, when you add to this data structure the new element goes in the begining and when you remove its the last element from the list which is being removed. You can imagine it as a queue you got in a shop where you stand behind a lot of people waiting for your turn to come to the counter to pay for your items.

To test this line by line, here are implementations of the classes (wrappers around deque) that are used in the task:
from collections import deque
class Queue(deque):
enqueue = deque.append
dequeue = deque.popleft
def front(self):
return self[-1]
def size(self):
return len(self)
class Stack(deque):
push = deque.append
def is_empty(self):
return not self

STACK #LIFO
class stack(object):
def __init__(self):
self.items = []
def isEmpty(self):
return self.items==[]
def push(self,item):
self.items.append(item)
def pop (self):
return self.items.pop()
def peek(self):
return self.items[len(self.items) - 1]
def size(self):
return (len(self.items))
s = stack()
print (s.isEmpty())
>> True
s.push(1)
s.push('3')
s.peek()
>>'3'
s.size()
>> 2
Queue #FIFO
class Queue(object):
def __init__(self):
self.items = []
def isEmpty(self):
return self.items==[]
def enqueue(self,item):
self.items.insert(0,item)
def dequeue(self):
return self.items.pop()
def size(self):
return (len(self.items))
q = Queue()
q.isEmpty()
>>True
q.enqueue(1)
q.enqueue(2)
q.dequeue()
>>1

The first code explains about the stack , we need to create a list and while pushing the element use append and fill the list , similar to what we have in array stack. While pop , pop out the end from where you pushed it.
class Stack:
def __init__(self):
self.stack = []
def push_element(self,dataval):
self.stack.append(dataval)
return self.stack
def pop_element(self):
if len(self.stack) ==0:
print("Stack is empty")
else:
self.stack.pop()
return self.stack
def peek_element(self):
return self.stack[0]
class Queue:
def __init__(self):
self.stack = []
def push_ele(self,data):
self.stack.append(data)
def pop_ele(self):
self.stack.pop(0)
def display(self):
print(self.stack)

class stack:
def __init__(self,n): #constructor
self.no = n # size of stack
self.Stack = [] # list for store stack items
self.top = -1
def push(self): # push method
if self.top == self.no - 1: # check full condition
print("Stack Overflow.....")
else:
n = int(input("enter an element :: "))
self.Stack.append(n) # in list add stack items use of append method
self.top += 1. # increment top by 1
def pop(self): # pop method
if self.top == -1: # check empty condition
print("Stack Underflow....")
else:
self.Stack.pop(). # delete item from top of stack using pop method
self.top -= 1 # decrement top by 1
def peep(self): #peep method
print(self.top,"\t",self.Stack[-1]) #display top item
def disp (self): # display method
if self.top == -1: # check empty condition
print("Stack Underflow....")
else:
print("TOP \tELEMENT")
for i in range(self.top,-1,-1): # print items and top
print(i," \t",self.Stack[i])
n = int(input("Enter Size :: ")) # size of stack
stk = stack(n) # object and pass n as size
while(True): # loop for choice as a switch case
print(" 1: PUSH ")
print(" 2: POP ")
print(" 3: PEEP ")
print(" 4: PRINT ")
print(" 5: EXIT ")
option = int(input("enter your choice :: "))
if option == 1:
stk.push()
elif option == 2:
stk.pop()
elif option == 3:
stk.peep()
elif option == 4:
stk.disp()
elif option == 5:
print("you are exit!!!!!")
break
else:
print("Incorrect option")

Python Deque Array adding to array crashes python

I am working on a double ended queue in python and everything seems to be working fine except for my preappend(adding to the front) method. When I call upon this method in main it crashes python and I am super confused as to why, here is my code:
import ctypes
class dequeArray:
def __init__(self):
"""Create an empty Array """
self._capacity = 4
self._data = self.makeArray(self._capacity)
self._dataSize = 0
self._front = 0
def makeArray(self, capacity):
capacity = self._capacity
return (self._capacity * ctypes.py_object)()
def isEmpty(self):
return self._dataSize == 0
def __len__(self):
return self._dataSize
def _userIndex2BlockIndex(self, userIndex):
return (self._front + userIndex)% self._capacity
def __getitem__(self, userIndex):
return self._data[userIndex]
def __setitem__(self, userIndex, value):
self._data[self._front(userIndex)] = value
def preappend(self, item):
if self._dataSize == 0:
self._data[self._front] = item
self._dataSize += 1
elif self._dataSize != self._capacity:
for e in range(self._dataSize-1,0,-1):
self._data[e] = self._data[e-1]
self._data[self._front] = item
self._dataSize += 1
else:
for e in range(self._capacity-1,0,-1):
self._data[e] = self._data[e-1]
self._data[self._front] = item
in main I create an empty deque
d = dequeArray()
then test len(d) and that works fine but when I do
d.preappend(2)
it crashes python... Please help

In the general, deques() never crash when used with normal Python objects.
With ctypes, all bets are off because C calls by pass all the invariant checks, type safety checks, pointer/index range checks etc.
Deques only access limited features for an object created with ctypes. At a minimum, it needs to support reference counting. To display, it needs a repr. To remove() or index(), it needs to support eq().

Python Printing a Deque

I have an entire Deque Array class that looks like this:
from collections import deque
import ctypes
class dequeArray:
DEFAULT_CAPACITY = 10 #moderate capacity for all new queues
def __init__(self):
self.capacity = 5
capacity = self.capacity
self._data = self._make_array(self.capacity)
self._size = 0
self._front = 0
def __len__(self):
return self._size
def __getitem__(self, k): #Return element at index k
if not 0 <= k < self._size:
raise IndexError('invalid index')
return self._data[k]
def isEmpty(self):
if self._data == 0:
return False
else:
return True
def append(self, item): #add an element to the back of the queue
if self._size == self.capacity:
self._data.pop(0)
else:
avail = (self._front + self._size) % len(self._data)
self._data[avail] = item
self._size += 1
#def _resize(self, c):
#B = self._make_array(c)
#for k in range(self._size):
#B[k] = self._A[k]
#self._data = B
#self.capacity = capacity
def _make_array(self, c):
capacity = self.capacity
return (capacity * ctypes.py_object)()
def removeFirst(self):
if self._size == self.capacity:
self._data.pop(0)
else:
answer = self._data[self._front]
self._data[self._front] = None
self._front = (self._front + 1) % len(self._data)
self._size -= 1
print(answer)
def removeLast(self):
return self._data.popleft()
def __str__(self):
return str(self._data)
and when I try to print the deque in the main it prints out something like this,
<bound method dequeArray.__str__ of <__main__.dequeArray object at 0x1053aec88>>
when it should be printing the entire array. I think i need to use the str function and i tried adding
def __str__(self):
return str(self._data)
and that failed to give me the output. I also tried just
def __str__(self):
return str(d)
d being the deque array but I still am not having any success. How do I do i get it to print correctly?

you should call the str function of each element of the array that is not NULL, can be done with the following str function:
def __str__(self):
contents = ", ".join(map(str, self._data[:self._size]))
return "dequeArray[{}]".format(contents)

What I get when I try to q = dequeArray(); print(q) is <__main__.py_object_Array_5 object at 0x006188A0> which makes sense. If you want it list-like, use something like this (print uses __str__ method implicitly):
def __str__(self):
values = []
for i in range(5):
try:
values.append(self._data[i])
except ValueError: # since accessing ctypes array by index
# prior to assignment to this index raises
# the exception
values.append('NULL (never used)')
return repr(values)
Also, several things about the code:
from collections import deque
This import is never user and should be removed.
DEFAULT_CAPACITY = 10
is never used. Consider using it in the __init__:
def __init__(self, capacity=None):
self.capacity = capacity or self.DEFAULT_CAPACITY
This variable inside __init__ is never user and should be removed:
capacity = self.capacity
def _make_array(self, c):
capacity = self.capacity
return (capacity * ctypes.py_object)()
Though this is a valid code, you're doing it wrong unless you're absolutely required to do it in your assignment. Ctypes shouldn't be used like this, Python is a language with automated memory management. Just return [] would be fine. And yes, variable c is never used and should be removed from the signature.
if self._data == 0
In isEmpty always evaluates to False because you're comparing ctypes object with zero, and ctypes object is definitely not a zero.

stay on same value in python iterator

I'm creating an interator like so:
some_list = [1,2,5,12,30,75,180,440]
iter(some_list)
I have a need to access the current value of an iterator again. Is there a current() method that allows me to stay on the same position?

You certainly can make a class which will allow you to do this:
from collections import deque
class RepeatableIter(object):
def __init__(self,iterable):
self.iter = iter(iterable)
self.deque = deque([])
def __iter__(self):
return self
#define `next` and `__next__` for forward/backward compatability
def next(self):
if self.deque:
return self.deque.popleft()
else:
return next(self.iter)
__next__ = next
def requeue(self,what):
self.deque.append(what)
x = RepeatableIter([1, 2, 3, 4, 5, 6])
count = 0
for i in x:
print i
if i == 4 and count == 0:
count += 1
x.requeue(i)
The question is really why would you want to?

You can use numpy.nditer to build your iterator, then you have many amazing options including the current value.
import numpy
rng = range(100)
itr = numpy.nditer([rng])
print itr.next() #0
print itr.next() #1
print itr.next() #2
print itr.value #2 : current iterator value

Adapting the third example from this answer:
class CurrentIterator():
_sentinal = object()
_current = _sentinal
#property
def current(self):
if self._current is self._sentinal:
raise ValueError('No current value')
return self._current
def __init__(self, iterable):
self.it = iter(iterable)
def __iter__(self):
return self
def __next__(self):
try:
self._current = current = next(self.it)
except StopIteration:
self._current = self._sentinal
raise
return current
next = __next__ # for python2.7 compatibility
Some interesting points:
use of _sentinal so an error can be raised if no current value exists
use of property so current looks like a simple attribute
use of __next__ and next = __next__ for Python 2&3 compatibility