In-place Merge Sort Implementation in Python - implementing Index Errors
I've been banging my head against this for hours... I'm working on a project and hit a roadblock. I am trying to implement an in-place merge sort algorithm in Python, but I keep working with index errors and unexpected behavior... The goal is to sort a list of integers without using additional space for another list, as I want to optimize memory usage. My current implementation is as follows: ```python def merge_sort(arr): if len(arr) > 1: mid = len(arr) // 2 # Finding the mid of the array L = arr[:mid] # Dividing the elements into 2 halves R = arr[mid:] merge_sort(L) # Sorting the first half merge_sort(R) # Sorting the second half i = j = k = 0 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 while i < len(L): arr[k] = L[i] i += 1 k += 1 while j < len(R): arr[k] = R[j] j += 1 k += 1 return arr ``` I noticed that when I try to sort an array of length 0 or 1, I receive an `IndexError: list assignment index out of range`. I’ve added some print statements, and it looks like the behavior occurs when I try to merge the two halves back together. I thought about using indices to track the original list when merging, but I’m unsure how to implement that correctly without using additional space. I've also tried handling the base case where the list has 0 or 1 elements by checking `if len(arr) <= 1:` right at the start, but that didn't resolve the scenario. Can someone guide to identify what I'm missing or how I should approach the merging step to avoid these index errors while adhering to the in-place requirement? I'm using Python 3.9.1, and I'm working within a Jupyter Notebook environment. Thanks in advance for any insights! Is there a better approach? The stack includes Python and several other technologies. Is this even possible? I'm working in a Windows 10 environment. What's the best practice here?