Performance Issues When Sorting a Large List of Dictionaries in Python 3.10 Using Key Functions
I need some guidance on I'm having trouble with I'm experiencing severe performance issues when trying to sort a large list of dictionaries in Python 3.10. The list can contain upwards of a million entries, and I'm using a custom key function. The sort completes, but it takes an inordinate amount of time, and I'm concerned about efficiency. Here's a simplified version of my code: ```python import random # Generating a large list of dictionaries large_list = [{ 'name': f'Name {i}', 'age': random.randint(0, 100) } for i in range(1000000)] # Custom sorting function def custom_sort(item): return item['age'] # Sorting the list using the custom key t_sorted = sorted(large_list, key=custom_sort) ``` When I run this code, it can take several seconds to sort the list. I've considered using optimized algorithms, but since Python's built-in sort is based on Timsort, I thought it would be effective enough for this use case. However, I suspect that the overhead from the custom function might be causing the slowdown. I've tried using a lambda function directly inside the `sorted()` call: ```python t_sorted = sorted(large_list, key=lambda item: item['age']) ``` This did not improve performance significantly. I also profiled the sorting process using the `time` module and found that the custom key function is called an excessive number of times, which seems to be the bottleneck. Is there a more efficient way to sort this large dataset or a way to improve the performance of my current approach? Any suggestions or insights would be greatly appreciated! My development environment is Linux. I'm working on a mobile app that needs to handle this. Any advice would be much appreciated. For reference, this is a production web app.