Stack Overflow scenarios in Recursive Merge Sort Implementation in Python with Large Data Sets
I'm implementing a merge sort algorithm recursively in Python, but I encounter a stack overflow behavior when sorting large data sets. My implementation looks like this: ```python def merge_sort(arr): if len(arr) > 1: mid = len(arr) // 2 # Find the middle L = arr[:mid] # Divide the array elements R = arr[mid:] merge_sort(L) # Sort the first half merge_sort(R) # Sort the second half i = j = k = 0 # Copy data to temp arrays L[] and R[] while i < len(L) and j < len(R): if L[i] < R[j]: arr[k] = L[i] i += 1 else: arr[k] = R[j] j += 1 k += 1 # Checking if any element was left while i < len(L): arr[k] = L[i] i += 1 k += 1 while j < len(R): arr[k] = R[j] j += 1 k += 1 ``` I'm using Python 3.9 and I noticed that for large lists (like 10,000+ elements), when I try to sort them, it raises a `RecursionError: maximum recursion depth exceeded in comparison`. I tried adjusting the recursion limit using `sys.setrecursionlimit(1500)`, but I still encounter the same scenario. I've also considered optimizing my merge function or switching to an iterative approach to avoid deep recursion, but I want to ensure my recursive approach is sound. Is there a way to handle larger data sets more efficiently with recursion, or should I switch to an iterative merge sort? Any advice on improving recursion depth handling would be appreciated!