The need to iterate over a list in chunks arises in various programming scenarios, such as processing large datasets. This article delves into the most efficient and Pythonic ways to achieve this task.
Traditionally, a C-style approach using a range loop with explicit index manipulation was employed:
for i in range(0, len(ints), 4): # dummy op for example code foo += ints[i] * ints[i + 1] + ints[i + 2] * ints[i + 3]
While this method may be straightforward, it lacks Pythonic elegance.
A more Pythonic alternative was proposed:
while ints: foo += ints[0] * ints[1] + ints[2] * ints[3] ints[0:4] = []
This approach leverages Python's list slicing to remove the processed elements, presenting a cleaner solution.
Python 3.12's Introduction of chunker()
With the release of Python 3.12, the highly anticipated chunker() function was introduced:
from itertools import islice def chunker(seq, size): it = iter(seq) while True: chunk = list(islice(it, size)) if not chunk: break yield chunk
This function elegantly iterates over any type of sequence, splitting it into chunks of the desired size. The following examples illustrate its versatility:
text = "I am a very, very helpful text" for group in chunker(text, 7): print(repr(group),) # 'I am a ' 'very, v' 'ery hel' 'pful te' 'xt' print('|'.join(chunker(text, 10))) # I am a ver|y, very he|lpful text animals = ['cat', 'dog', 'rabbit', 'duck', 'bird', 'cow', 'gnu', 'fish'] for group in chunker(animals, 3): print(group) # ['cat', 'dog', 'rabbit'] # ['duck', 'bird', 'cow'] # ['gnu', 'fish']
The chunker() function enhances Python's already rich ecosystem of list manipulation and further exemplifies its user-friendliness.
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