How to Efficiently Filter a Large Dictionary by Multiple Criteria in Python?
After trying multiple solutions online, I still can't figure this out. I'm trying to implement I've been struggling with this for a few days now and could really use some help. I'm currently working on a project where I need to filter a large dictionary based on multiple criteria, but I'm running into performance optimization. My dictionary contains about 100,000 entries, where each entry is structured as follows: ```python my_dict = { 'item1': {'category': 'A', 'value': 10}, 'item2': {'category': 'B', 'value': 15}, 'item3': {'category': 'A', 'value': 20}, ... } ``` I need to extract all items that belong to category 'A' and have a value greater than 15. Initially, I tried using a list comprehension: ```python filtered_items = {k: v for k, v in my_dict.items() if v['category'] == 'A' and v['value'] > 15} ``` Though this works, I noticed it's quite slow when I run it on larger datasets. I also experimented with using `filter()` combined with `lambda`, but it didn't improve the performance significantly: ```python filtered_items = dict(filter(lambda item: item[1]['category'] == 'A' and item[1]['value'] > 15, my_dict.items())) ``` I received a `RuntimeWarning: OverflowWarning` when testing with a larger dataset. I suspect that creating filtered dictionaries using comprehensions or filters is contributing to high memory usage. Is there a more efficient way to perform this operation, especially in terms of both speed and memory? I am using Python 3.9, and any advice on best practices for filtering large dictionaries would be greatly appreciated. This is part of a larger API I'm building. Any help would be greatly appreciated! Any examples would be super helpful. For context: I'm using Python on CentOS. Has anyone else encountered this?