Master Python Iterators and Generators: From Basics to Advanced Examples

Iterator

Iteration is one of Python's most powerful features, providing a way to access elements of a collection.

An iterator is an object that remembers its current position in the traversal.

It starts from the first element of a collection and proceeds forward until all elements have been visited; it cannot move backward.

Iterators have two fundamental methods: iter() and next().

Strings, lists, or tuples can be used to create iterators.

Example (Python 3.0+)

list = [1, 2, 3, 4]
it = iter(list)  # create iterator object
print(next(it))  # 1
print(next(it))  # 2

The iterator object can also be traversed with a regular for loop.

Example (Python 3.0+)

#!/usr/bin/python3
list = [1, 2, 3, 4]
it = iter(list)
for x in it:
    print(x, end=" ")
# Output: 1 2 3 4

Using next() directly:

#!/usr/bin/python3
import sys
list = [1, 2, 3, 4]
it = iter(list)
while True:
    try:
        print(next(it))
    except StopIteration:
        sys.exit()

Creating a custom iterator class requires implementing __iter__() and __next__() methods, and optionally __init__() for initialization.

class MyNumbers:
    def __iter__(self):
        self.a = 1
        return self
    def __next__(self):
        x = self.a
        self.a += 1
        return x

myclass = MyNumbers()
myiter = iter(myclass)
print(next(myiter))  # 1
print(next(myiter))  # 2
print(next(myiter))  # 3
print(next(myiter))  # 4

When the iterator reaches a predefined limit, it should raise StopIteration to end the iteration.

class MyNumbers:
    def __iter__(self):
        self.a = 1
        return self
    def __next__(self):
        if self.a <= 20:
            x = self.a
            self.a += 1
            return x
        else:
            raise StopIteration

myclass = MyNumbers()
for x in myclass:
    print(x)
# Prints numbers 1 through 20

Generator

In Python, a function that contains the yield keyword is called a generator. Generators return an iterator and can be paused and resumed, yielding values each time next() is called.

Example: Fibonacci sequence generator.

#!/usr/bin/python3
import sys
def fibonacci(n):
    a, b, counter = 0, 1, 0
    while True:
        if counter > n:
            return
        yield a
        a, b = b, a + b
        counter += 1

f = fibonacci(10)
while True:
    try:
        print(next(f), end=" ")
    except StopIteration:
        sys.exit()
# Output: 0 1 1 2 3 5 8 13 21 34 55