👀 Views: 43 💬 Answers: 1 📅 Created: 2025-08-22

python-2.7 itertools memory-management combinations Python

I'm relatively new to this, so bear with me. I'm confused about I'm writing unit tests and I've been researching this but I'm working on a project in Python 2.7 that involves generating combinations of a large iterable, but I'm running into important memory issues..... I need to generate combinations for a list that can potentially have thousands of elements, and when I try to use `itertools.combinations`, it seems to consume an enormous amount of memory, leading to 'MemoryError'. I've tried the following approach: ```python import itertools large_list = range(10000) # A list of 10,000 elements comb_size = 3 # We want combinations of size 3 combinations = itertools.combinations(large_list, comb_size) result = list(combinations) # This line causes MemoryError ``` I understand that `itertools.combinations` is supposed to be memory efficient since it returns an iterator, but the line where I convert it to a list seems to be the culprit. The behavior message I receive is: ``` MemoryError: Unable to allocate array with shape (10000, 3) and data type int64 ``` How can I efficiently work with combinations of a large iterable without running out of memory? Is there a better way to process these combinations without converting them into a list all at once? I need to be able to iterate through them one by one while managing memory consumption effectively. I'm working on a web app that needs to handle this. Any help would be greatly appreciated! Any advice would be much appreciated. This is happening in both development and production on macOS. Cheers for any assistance!