What is the difference between Iterator and 'Lazy Iterator' in Python?

In Python, an iterator is an object that enables you to iterate over a sequence of values, such as a list or tuple. It works by implementing two methods: __iter__() and __next__(). The __iter__() method returns the iterator object itself, while the __next__() method returns the next value in the sequence. When there are no more values ​​to return, it raises a StopIteration exception.

Standard custom iterator:

class Squares:
    def __init__(self, n):
        self.n = n
        self.current = 0
    
    def __iter__(self):
        return self
    
    def __next__(self):
        if self.current >= self.n:
            raise StopIteration
        else:
            result = self.current ** 2
            self.current += 1
            return result
 
# Using the iterator
squares = Squares(5)
for square in squares:
    print(square)

In Python, iter() is a built-in function that returns an iterator for a given iterable object.

An iterable object is any object that can be iterated over, such as a list, tuple, set, dictionary, or a custom object that defines the __iter__() method.

When iter() is called on an iterable object, it returns an iterator object that uses the next() method to provide a sequence of values ​​from the iterable object one at a time.

The iter() function is often used with loops and other iterators to perform tasks such as filtering, mapping, and reducing the elements of a sequence.

Iterator created with the iter() function:

numbers = [1, 2, 3, 4, 5]
iterator = iter(numbers)
 
print(next(iterator))  # Output: 1
print(next(iterator))  # Output: 2
print(next(iterator))  # Output: 3

lazy iterator:

A "lazy iterator" is a special type of iterator that does not Generates all values ​​in the sequence. Instead, it generates them when needed. This is useful when dealing with very large or infinite sequences, as it avoids generating all the values ​​at once and consuming a lot of memory.

In Python, lazy iterators are often implemented using generator functions (Generators are functions that use the yield keyword ), returning one value at a time. Each time a value is requested, the generator picks up where it left off and produces the next value in the sequence.

# Define a generator function that yields values lazily
def fibonacci():
    a, b = 0, 1
    while True:
        yield a
        a, b = b, a + b
 
# Use the lazy iterator to print the first 10 Fibonacci numbers
fib = fibonacci()
for i in range(10):
    print(next(fib))

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