An iterator in Python provides a uniform way to traverse collections without exposing underlying structure. It captures the current location during traversal and proceeds strictly forward, never backward. Every iterator exposes two essential functions: iter() to obtain the object and next() to retrieve successive items. Strings, lists, and tuples can all produce iterators.

animals = ["eagle", "fox", "shark", "panda", "lynx"]
iterator_obj = iter(animals)

for item in iterator_obj:
    print(item, end=" ")

Output:

eagle fox shark panda lynx

Alternatively, next() gives manual control over iteration, raising StopIteration once the collection is exhausted.

import sys
animals = ["eagle", "fox", "shark", "panda", "lynx"]
iterator_obj = iter(animals)

while True:
    try:
        print(next(iterator_obj))
    except StopIteration:
        sys.exit()

Output:

eagle
fox
shark
panda
lynx

Creating Custom Iterators

To turn a class into an iterator, implement __iter__() and __next__(). The constructor __init__() handles initial setup, while __iter__() returns the iterator object itself, which must provide the __next__() method. Iteration stops by raising StopIteration.

A counter satrting at 1 and incrementing by 1 can be built as follows:

class SimpleCounter:
    def __iter__(self):
        self.current = 1
        return self

    def __next__(self):
        val = self.current
        self.current += 1
        return val

counter = SimpleCounter()
counter_iter = iter(counter)
print(next(counter_iter))
print(next(counter_iter))
print(next(counter_iter))

Output:

1
2
3

Using StopIteration to Limit Iteration

The StopIteration exception prevents infinite loops. Implement logic inside __next__() so that after a specified number of steps the exception gets triggered. The following iterator stops after five values:

class BoundedCounter:
    def __iter__(self):
        self.current = 1
        return self

    def __next__(self):
        if self.current <= 5:
            val = self.current
            self.current += 1
            return val
        raise StopIteration

counter = BoundedCounter()
counter_iter = iter(counter)
for number in counter_iter:
    print(number)

Output:

1
2
3
4
5

Building Generators with yield

A generator function uses the yield statement to produce a series of values on demand. Unlike a typical function that returns a single value, a generator returned by such a function is itself an iterator. Each time yield is reached, the current state is preserved and the value is returned. Subsequent next() calls resume just past the yield.

def count_up_to(limit):
    n = 0
    while n < limit:
        yield n
        n += 1

numbers = count_up_to(3)
print(next(numbers))
print(next(numbers))
print(next(numbers))
# Next call raises StopIteration

Output:

0
1
2