Python Iterators

In Python, an iterator is an object that implements the iterator protocol, which consists of the methods __iter__() and __next__(). The iterator protocol allows an object to be iterated (looped) over, and it provides a way to retrieve the next value in a sequence.

Basic Iterator Example:

class MyIterator:
    def __iter__(self):
        self.start = 1
        return self

    def __next__(self):
        if self.start <= 5:
            result = self.start
            self.start += 1
            return result
        else:
            raise StopIteration

# Using the iterator
my_iterator = MyIterator()

for value in my_iterator:
    print(value)

In this example, the MyIterator class implements the iterator protocol. The __iter__ method initializes the iterator, and the __next__ method provides the next value in the sequence. The iteration stops when the StopIteration exception is raised.

Iterable Objects:

An iterable is an object that can be iterated over. An iterable should implement the __iter__ method, which returns an iterator object.

class MyIterable:
    def __init__(self):
        self.start = 1

    def __iter__(self):
        return self

    def __next__(self):
        if self.start <= 5:
            result = self.start
            self.start += 1
            return result
        else:
            raise StopIteration

# Using the iterable
my_iterable = MyIterable()

for value in my_iterable:
    print(value)

In this example, MyIterable is an iterable class that returns an iterator object when the __iter__ method is called.

Using iter() and next() Functions:

The iter() function is used to get an iterator from an iterable, and the next() function is used to retrieve the next value from an iterator.

my_iterable = MyIterable()
my_iterator = iter(my_iterable)

print(next(my_iterator))  # Output: 1
print(next(my_iterator))  # Output: 2
print(next(my_iterator))  # Output: 3

Using Generators:

Generators are a concise way to create iterators in Python. A generator function uses the yield keyword to produce a sequence of values.

def my_generator():
    start = 1
    while start <= 5:
        yield start
        start += 1

# Using the generator
gen = my_generator()

for value in gen:
    print(value)

Generators automatically implement the iterator protocol, and they are a convenient way to create iterators without explicitly implementing the __iter__ and __next__ methods.

Iterators and iterables are fundamental concepts in Python, and they are extensively used in loops and other constructs that involve iterating over a sequence of values.