Python Iterators

In Python, an iterator is an object that enables traversal over a collection of items, one at a time.
It follows the iterator protocol, which involves implementing the __iter__() and __next__() methods.
The __iter__() method returns the iterator object itself, while __next__() retrieves the next element from the collection.
When there are no more elements, a StopIteration exception is raised.

Iterating over lists

Approach -1: Iterating over the list directly

list = [2, 4, 6, 8, 10]
for value in list:
    print(value, end=' ')
#Output = 2 4 6 8 10

In this approach, the entire list [2, 4, 6, 8, 10] is stored in memory.
The for loop iterates over each element of the list, processing them one by one.
Memory usage is relatively higher since the complete list is stored in memory throughout the loop execution.

Approach -2: Using an iterator object

list = [2, 4, 6, 8, 10]
iter_obj = iter(list) # <list_iterator object at 0x7fcf3519f670>
print(next(iter_obj)) # Output = 2
print(next(iter_obj))# Output = 4
print(next(iter_obj))# Output = 6
print(next(iter_obj))# Output = 8
print(next(iter_obj))# Output = 10

In this approach, an iterator object is explicitly created using iter(list).
Each call to next(iter_obj) retrieves the next element from the iterator, without storing the entire list in memory.
Only one element at a time is accessed and processed, reducing memory usage.
As elements are fetched one by one, the memory footprint is lower compared to

Built-in Iterators in Python

Python provides several built-in iterators and iterable objects that simplify common iteration tasks. Let's explore a few of them:

range()

The range() function generates a sequence of numbers within a specified range. It can be used directly as an iterator.
```
 for i in range(5):
     print(i,end = " ")
 #Output = 0 1 2 3 4 5
```

enumerate()

The enumerate() function is useful when we need both the index and value of each element while iterating over a sequence.

 my_list = ['Nirmal', 'Niraj', 'Retrica']
 for index, value in enumerate(my_list):
     print(f"Index: {index}, Value: {value}")

Output :

 Index: 0, Value: nirmal
 Index: 1, Value: niraj
 Index: 2, Value: retrica

zip():

The zip() function combines multiple iterables into a single iterator. It pairs up corresponding elements from each iterable.

 names =  ['Nirmal', 'Niraj', 'Retrica']
 ages = [23, 20, 27]

 for name, age in zip(names, ages):
     print(f"Name: {name}, Age: {age}")

Output :

 Name: Nirmal, Age: 23
 Name: Niraj, Age: 20
 Name: Retrica, Age: 27

Itertools Module

The itertools module is a powerful tool that provides various functions for efficient iteration and a combination of iterables. It extends the capabilities of built-in iterators.

Some modules are :

1. itertools.cycle()

This creates an iterator that cycles through elements of an iterable indefinitely.

import itertools

name = ["nirmal", "niraj", "retrica"]
myloopy = itertools.cycle(name)

print(next(myloopy))  # Output: nirmal
print(next(myloopy))  # Output: niraj
print(next(myloopy))  # Output: retrica

2. itertools.chain()

This combines multiple iterables into a single sequence.

import itertools

inter1 = itertools.chain("nirmal", "pandey")
print(list(inter1))  # Output: ['n', 'i', 'r', 'm', 'a', 'l', 'p', 'a', 'n', 'd', 'e', 'y']

itertools. accumulate()

This returns an iterator that produces accumulated sums of an iterable.

import itertools

num = [1, 2, 3, 4, 5, 6]
inter2 = itertools.accumulate(num)
print(list(inter2))  # Output: [1, 3, 6, 10, 15, 21]

4.itertools.repeat()

This generates an iterator that repeats a value a specified number of times.

import itertools

inter3 = itertools.repeat(10, 3)
print(list(inter3))  # Output: [10, 10, 10]

5: itertools.compress()

This filters an iterable based on the truth value of corresponding selectors.

import itertools

inter4 = itertools.compress("nirmal", [1, 0, 1, 0, 1, 1])
print(list(inter4))  # Output: ['n', 'r', 'a', 'l']

Custom Iterator

class MyIterator:
    def __init__(self, data):
        self.data = data
        self.index = 0

    def __iter__(self):
        return self

    def __next__(self):
        if self.index >= len(self.data):
            raise StopIteration
        value = self.data[self.index]
        self.index += 1
        return value


my_list = [1, 2, 3, 4, 5]
my_iter = MyIterator(my_list)

for item in my_iter:
    print(item)

In this example, we create a custom iterator MyIterator takes a list as input. The __iter__() method returns the iterator object itself, and __next__() fetches the next element from the list. Once there are no more elements, a StopIteration exception is raised.

Iterators

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List comprehension, zip(), & enumerate( )

More from this blog

Iterating over lists

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