Using logic with sets
0 likes • Nov 18, 2022 • 0 views
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def check_prop(fn, prop):return lambda obj: fn(obj[prop])check_age = check_prop(lambda x: x >= 18, 'age')user = {'name': 'Mark', 'age': 18}check_age(user) # True
#Python 3: Fibonacci series up to ndef fib(n):a, b = 0, 1while a < n:print(a, end=' ')a, b = b, a+bprint()fib(1000)
""" Binary Search Algorithm----------------------------------------"""#iterative implementation of binary search in Pythondef binary_search(a_list, item):"""Performs iterative binary search to find the position of an integer in a given, sorted, list.a_list -- sorted list of integersitem -- integer you are searching for the position of"""first = 0last = len(a_list) - 1while first <= last:i = (first + last) / 2if a_list[i] == item:return ' found at position '.format(item=item, i=i)elif a_list[i] > item:last = i - 1elif a_list[i] < item:first = i + 1else:return ' not found in the list'.format(item=item)#recursive implementation of binary search in Pythondef binary_search_recursive(a_list, item):"""Performs recursive binary search of an integer in a given, sorted, list.a_list -- sorted list of integersitem -- integer you are searching for the position of"""first = 0last = len(a_list) - 1if len(a_list) == 0:return ' was not found in the list'.format(item=item)else:i = (first + last) // 2if item == a_list[i]:return ' found'.format(item=item)else:if a_list[i] < item:return binary_search_recursive(a_list[i+1:], item)else:return binary_search_recursive(a_list[:i], item)
print("hellur")
#Python program to print topological sorting of a DAGfrom collections import defaultdict#Class to represent a graphclass Graph:def __init__(self,vertices):self.graph = defaultdict(list) #dictionary containing adjacency Listself.V = vertices #No. of vertices# function to add an edge to graphdef addEdge(self,u,v):self.graph[u].append(v)# A recursive function used by topologicalSortdef topologicalSortUtil(self,v,visited,stack):# Mark the current node as visited.visited[v] = True# Recur for all the vertices adjacent to this vertexfor i in self.graph[v]:if visited[i] == False:self.topologicalSortUtil(i,visited,stack)# Push current vertex to stack which stores resultstack.insert(0,v)# The function to do Topological Sort. It uses recursive# topologicalSortUtil()def topologicalSort(self):# Mark all the vertices as not visitedvisited = [False]*self.Vstack =[]# Call the recursive helper function to store Topological# Sort starting from all vertices one by onefor i in range(self.V):if visited[i] == False:self.topologicalSortUtil(i,visited,stack)# Print contents of stackprint(stack)g= Graph(6)g.addEdge(5, 2);g.addEdge(5, 0);g.addEdge(4, 0);g.addEdge(4, 1);g.addEdge(2, 3);g.addEdge(3, 1);print("Following is a Topological Sort of the given graph")g.topologicalSort()
def max_n(lst, n = 1):return sorted(lst, reverse = True)[:n]max_n([1, 2, 3]) # [3]max_n([1, 2, 3], 2) # [3, 2]