advanced patterns in Merge Sort Implementation in Python - scenarios for Large Inputs
I've searched everywhere and can't find a clear answer. I'm dealing with This might be a silly question, but I'm working with an scenario with my implementation of the Merge Sort algorithm in Python, which seems to produce incorrect results for large input arrays... The merge function is supposed to combine two sorted halves, but when I test it with large lists, I occasionally get a list that isn't fully sorted. Here's the code I'm using: ```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 arr = [38, 27, 43, 3, 9, 82, 10] * 1000 # Large test case sorted_arr = merge_sort(arr) print(sorted_arr) ``` The function seems to perform well for smaller arrays, but when I multiply the array to simulate larger data, I occasionally see duplicates and misplaced elements in the sorted output. For instance, I expect a sorted list from `merge_sort(arr)`, but the output sometimes has elements out of order, especially around the transition between the two halves. I've confirmed that the input is valid and sorted individually before merging, so I'm not sure where the logic is failing. I tried adding debug print statements to check values of `L`, `R`, and `arr` at various stages, but I didn't see anything obvious. Any insights into what might be going wrong or how to effectively debug this? Also, Iām using Python 3.9.1. Thanks in advance for your help! For context: I'm using Python on Windows. Any help would be greatly appreciated! The project is a microservice built with Python. I appreciate any insights! Any ideas what could be causing this?