How to Efficiently Create a Rolling Window Iterator in Python?

Rolling Window Iterators: A Python Implementation

Iterating over data in a rolling window (or sliding window) fashion proves highly useful in various data analysis and machine learning applications. This question showcases a technique for creating a rolling window iterator for a given sequence or iterator in Python.

The primary Python implementation provided is as follows:

def rolling_window(seq, window_size):
    it = iter(seq)
    win = [it.next() for _ in range(window_size)]
    yield win
    for e in it:
        win = win[1:] + (e,)
        yield win

This approach iterates through the sequence, creating the initial window, and then updating the window in subsequent iterations. However, some Python enthusiasts suggest alternative methods for greater elegance and efficiency.

One such suggestion involves utilizing the itertools module:

from itertools import islice

def window(seq, n=2):
    it = iter(seq)
    result = tuple(islice(it, n))
    if len(result) == n:
        yield result
    for elem in it:
        result = result[1:] + (elem,)
        yield result

This method leverages the powerful itertools module to implement the rolling window functionality succinctly.

Another alternative, particularly suitable for lists or tuples, employs a straightforward approach:

seq = [0, 1, 2, 3, 4, 5]
window_size = 3

for i in range(len(seq) - window_size + 1):
    print(seq[i: i + window_size])

Depending on the specific requirements and performance considerations, these alternative implementations can provide flexibility in implementing rolling window iterators for various applications.

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