iterators | TheAILearner

Iterators, this name might be new for most of us, but What if I tell you that you have already used this within for loops, comprehensions etc. So, in this blog, let’s see what are iterators, how they work and how we can build our own iterator.

What is an iterator and how it works?

To understand this, we first need to know what is an iterable

Iterable: It is anything that you are able to loop over like lists, tuples, strings etc.

Iterator: It is the object that does the actual iterating.

So, in order to iterate, you must first convert an iterable into an iterator. This is done by using built-in iter() function.

>>> my_list = [1,2,3,4]
>>> iter_obj = iter(my_list)
>>> iter_obj
<list_iterator object at 0x000000E7431745F8>

>>> my_list = [1,2,3,4]

>>> iter_obj = iter(my_list)

>>> iter_obj

<list_iterator object at 0x000000E7431745F8>

To get the next element, use built-in next() function on that iterator. next() function raises a StopIteration exception when there are no more elements in that iterator.

>>> next(iter_obj)
1
>>> next(iter_obj)
2

>>> next(iter_obj)

Note: If we directly apply next() on iterable like lists etc. it will give a typeerror as

>>> next(my_list)
Traceback (most recent call last):
  File "<pyshell#5>", line 1, in <module>
    next(my_list)
TypeError: 'list' object is not an iterator

>>> next(my_list)

Traceback (most recent call last):

File "<pyshell#5>", line 1, in <module>

next(my_list)

TypeError: 'list' object is not an iterator

Thus, __iter__() and __ next__() (called the iterator protocol)are the two special methods implemented by the iterator.

Pros: Iterators are lazy, meaning, they don’t determine what their next item is until you ask them for it. This saves memory, time and can work with infinite sequences.

Building our own iterator:

To build an iterator, we only need the methods __iter__() and __next__(). Below, we show an example that will give us the next Fibonacci term in each iteration.

class Fib:
    
    def __init__(self, max = 0):
        self.max = max
        self.a = 0
        self.b = 1
        self.n = 0

    def __iter__(self):
        return self

    def __next__(self):
        if self.n <= self.max:
            result = self.a + self.b
            self.a,self.b=self.b,result
            self.n+=1
            return result
        else:
            raise StopIteration

class Fib:

def __init__(self, max = 0):

self.max = max

self.a = 0

self.b = 1

self.n = 0

def __iter__(self):

return self

def __next__(self):

if self.n <= self.max:

result = self.a + self.b

self.a,self.b=self.b,result

self.n+=1

return result

else:

raise StopIteration

Now we can create an iterator and iterate through it as follows.

>>> a = Fib(3)
>>> next(a)
1
>>> next(a)
2
>>> next(a)
3
>>> next(a)
5
>>> next(a)
Traceback (most recent call last):
  File "<pyshell#6>", line 1, in <module>
    next(a)
  File "C:\New folder\pp.py", line 19, in __next__
    raise StopIteration
StopIteration

>>> a = Fib(3)

>>> next(a)

Traceback (most recent call last):

File "<pyshell#6>", line 1, in <module>

next(a)

File "C:\New folder\pp.py", line 19, in __next__

raise StopIteration

StopIteration

Here, I haven’t called the iter() method because it returns the object itself. You may call this, as this will not affect anything.

We can also use for loop to iterate over our Fib Class as:

>>> for i in Fib(3):
	print(i)
	
1
2
3
5

>>> for i in Fib(3):

print(i)

Here, for loop doesn’t give stopiteration exception because it uses try-except statement(See here how the for loop works)

Now, you might have got some feeling about the Python iterators and iterable. Hope you enjoy reading.

If you have any doubt/suggestion please feel free to ask and I will do my best to help or improve myself. Good-bye until next time.

Have you ever wondered how ‘for’ loop is automatically able to iterate over iterable like lists, strings etc? What if I tell you that Python for loop is actually an infinite while loop. Most of us might not believe but as is this beautiful Python.

There must be something inside ‘for’ loop that helps it to iterate over any iterable. In this blog, we will see how the for loop is actually implemented in python. Let’s understand this with an example.

Suppose we want to sum the elements of a list [1,2,3,4]. This can be done as

for number in my_list:
    sum += number

1 2	for number in my_list: sum += number

Actually what happens inside for loop is this

iter_object = iter(my_list)
while True:
    try:
        number = next(iter_object)
    except StopIteration:
        break
    sum += number
print(sum)

iter_object = iter(my_list)

while True:

try:

number = next(iter_object)

except StopIteration:

break

sum += number

print(sum)

To understand this, we first need to know what iterable and iterators are

Iterable: It is anything that you are able to loop over like lists, tuples, strings etc.
Iterator: It is the object that does the actual iterating.

So, in order to iterate, you must first convert an iterable into an iterator. This is done by using built-in iter() function. To get the next item, use next() function on that iterator (not on iterable). If there are 100 elements in an iterable then we need to call next() 100 times. To avoid this, we use an infinite while loop. next() function raises a StopIteration exception when there are no more elements in that iterable. So, to avoid this exception, we have used try-except statement and in this way, we break out from the infinite loop.

This is how the for loop actually works in python.

Now, you might have got some feeling about the Python for loop, iterator and iterable. Hope you enjoy reading.

If you have any doubt/suggestion please feel free to ask and I will do my best to help or improve myself. Good-bye until next time.

TheAILearner

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