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Brute Force
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Bubble Sort - O(n²)
def bubble_sort(arr):
n = len(arr)
for i in range(n):
for j in range(0, n - i - 1):
if arr[j] > arr[j + 1]:
temp = arr[j]
arr[j] = arr[j + 1]
arr[j + 1] = temp
return arr
Selection Sort - O(n²)
def selection_sort(arr):
n = len(arr)
for i in range(n):
min_index = i
for j in range(i + 1, n):
if arr[j] < arr[min_index]:
min_index = j
temp = arr[i]
arr[i] = arr[min_index]
arr[min_index] = temp
return arr
Insertion Sort - O(n²)
def insertion_sort(arr):
n = len(arr)
for i in range(1, n):
key = arr[i]
j = i - 1
while j >= 0 and arr[j] > key:
arr[j + 1] = arr[j]
j -= 1
arr[j + 1] = key
return arr
Merge Sort - O(n log n)
def merge_sort(arr):
if len(arr) <= 1:
return
mid = len(arr) // 2
left = arr[:mid]
right = arr[mid:]
merge_sort(left)
merge_sort(right)
i = j = k = 0
while i < len(left) and j < len(right):
if left[i] < right[j]:
arr[k] = left[i]
i += 1
else:
arr[k] = right[j]
j += 1
k += 1
while i < len(left):
arr[k] = left[i]
i += 1
k += 1
while j < len(right):
arr[k] = right[j]
j += 1
k += 1
Quick Sort - O(n log n) average case
def quick_sort(arr):
if len(arr) <= 1:
return arr
pivot = arr[len(arr) // 2]
left = [x for x in arr if x < pivot]
middle = [x for x in arr if x == pivot]
right = [x for x in arr if x > pivot]
return quick_sort(left) + middle + quick_sort(right)
Heap Sort - O(n log n)
import heapq
def heap_sort(arr):
heapq.heapify(arr)
return [heapq.heappop(arr) for _ in range(len(arr))]
Shell Sort - O(n log n) (depends on gap sequence)
def shell_sort(arr):
n = len(arr)
gap = n // 2
while gap > 0:
for i in range(gap, n):
temp = arr[i]
j = i
while j >= gap and arr[j - gap] > temp:
arr[j] = arr[j - gap]
j -= gap
arr[j] = temp
gap //= 2
return arr