Discussion on Big Sorting Challenge

2 weeks ago+ 0 comments

MERGE SORT IS still the fastest algorithm since o(n) complexity

def merge(left, right):
    merged = []
    i = j = 0
    while i < len(left) and j < len(right):
        if compare_numbers(left[i], right[j]) <= 0:
            merged.append(left[i])
            i += 1
        else:
            merged.append(right[j])
            j += 1
    merged.extend(left[i:])
    merged.extend(right[j:])
    return merged
def compare_numbers(a, b):
    # First, compare by length.
    if len(a) != len(b):
        return len(a) - len(b)
    if a < b:
        return -1
    elif a > b:
        return 1
    else:
        return 0
        
def merge_sort(arr):
    if len(arr) <= 1:
        return arr
    mid = len(arr) // 2
    left = merge_sort(arr[:mid])
    right = merge_sort(arr[mid:])
    return merge(left, right)

this is insertion sort (0)^2 ` def compare(res, current): if len(res) == 0: res = [current] return res for idx, pip in enumerate(res): if pip >= current: rep = idx if rep<0: rep = 0 res.insert(rep, current) return res res.append(current) print("final", res) return res

def bigSorting(unsorted): # Write your code here res =[] for datas in unsorted: data = int(datas) res = compare(res,data) fix = [] for bub in res: fix.append(str(bub)) print(bub) return fix `

Cookie support is required to access HackerRank