Python - Iterators

An iterator is an object that produces a sequence of values one at a time.

Instead of storing the entire sequence in memory, an iterator remembers its current position and produces the next value only when asked.

Iterators are the mechanism Python uses internally whenever a sequence is looped over.

These two terms are often confused, but they are different.

Feature	Iterable	Iterator
Meaning	An object that can be iterated over	An object that produces the values
Examples	List, tuple, string, dictionary, set	Result of iter(), generator, file object
Key Method	__iter__()	__next__()
Can Be Reused	Yes	No, an iterator is exhausted after its values end

In Python, any object is an iterator if it implements two methods. Together these two methods are called the Iterator Protocol.

• __iter__() returns the iterator object itself.
• __next__() returns the next value, and raises StopIteration when no more values remain.

Python provides two built-in functions to work with iterators.

• iter(iterable) converts an iterable into an iterator.
• next(iterator) fetches the next value from the iterator.

Every call to next() advances the iterator by one position.

Here, iter(l) converts the list l into an iterator i.

Each call to next(i) returns the next element of the list.

When an iterator has no more values to produce, calling next() raises a StopIteration exception.

This exception signals that the iteration is complete.

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Traceback (most recent call last):
  File "test.py", line 7, in 
    print(next(i))
StopIteration

When we write a for loop, Python performs the following steps internally:

1. It calls iter() on the iterable to obtain an iterator.
2. It repeatedly calls next() on the iterator.
3. When StopIteration is raised, the loop ends.

So a for loop over a list is internally an iterator using next().

This program manually replicates what a for loop does:

• iter(l) creates the iterator.
• The while True loop keeps calling next(i).
• When StopIteration is raised, break ends the loop.

We can create our own iterator by defining a class that implements both __iter__() and __next__().

The following class creates an iterator that produces the first n natural numbers.

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• __init__() stores the limit n and initializes current to 0.
• __iter__() returns self, which is the iterator itself.
• __next__() raises StopIteration when the limit is reached, otherwise it returns the next number.
• The for loop works because the object implements the iterator protocol.

• Values are produced one at a time instead of storing the whole sequence.
• Very memory efficient for large sequences.
• They provide a uniform way to loop over any sequence.
• They are lazy: values are created only when requested.