Generator vs. iterator in Python

An iterator in Python serves as a holder for objects so that they can be iterated over,a generator facilitates the creation of a custom iterator.

A generator is always an Iterator but Iterator is not always a generator.

A list is iterable but not an iterator, but if we run dunder iter method(__iter__()) on a list, it returns an iterator.

Any object that has a __next__() method is an iterator.

The following are some main differences between Generator and iterator:

Example:

Generator :

Remember that a return statement terminates the execution of a function entirely, whereas, the yield statement saves the function state and resumes its execution, from this point, upon subsequent calls.

def my_range(start, end):
    current = start
    while current < end:
        yield current
        current += 1

Note -Generators are iterators in which __iter__ and __next__ are created automatically by yield keyword.

Iterator:

The __iter__() method returns the iterator object. This is required to allow an iterator to be used with the for and in statements.

The __next__() method returns the next element in the sequence. In the case of a finite iterator, once it reaches the end (defined by the termination condition), all of the subsequent calls to this method should raise an exception.

class MyRange:
    def __init__(self, start, end):
        self.value = start
        self.end = end

    def __iter__(self):  # For something to be iterable, it needs to have __iter__() method
        return self

    def __next__(self):  # For something to be iterator, it needs to have __next__() method
        if self.value >= self.end:
            raise StopIteration
        current = self.value
        self.value += 1
        return current

nums = MyRange(1, 10)
for num in nums:
    print(num)