Sorting Algorithms
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]:
arr[j], arr[j + 1] = arr[j + 1], arr[j]
return arr
def selection_sort(arr):
n = len(arr)
for i in range(n):
min_idx = i
for j in range(i + 1, n):
if arr[j] < arr[min_idx]:
min_idx = j
arr[i], arr[min_idx] = arr[min_idx], arr[i]
return arr
def insertion_sort(arr):
for i in range(1, len(arr)):
key = arr[i]
j = i - 1
while j >= 0 and key < arr[j]:
arr[j + 1] = arr[j]
j -= 1
arr[j + 1] = key
return arr
def merge_sort(arr):
if len(arr) > 1:
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
return arr
BFS & DFS
def bfs(graph, start):
visited = set()
queue = [start]
result = []
while queue:
node = queue.pop(0)
if node not in visited:
visited.add(node)
result.append(node)
queue.extend(graph[node] - visited)
return result
def dfs(graph, start, visited=None):
if visited is None:
visited = set()
visited.add(start)
result = [start]
for neighbor in graph[start] - visited:
result.extend(dfs(graph, neighbor, visited))
return result