from statistics import median, mean, mode

def print_stats(array):
  print(array)
  print("median =", median(array))
  print("mean   =", mean(array))
  print("mode   =", mode(array))
  print()

print_stats([1, 2, 3, 3, 4])
print_stats([1, 2, 3, 3])

class Rectangle:
    pass

class Square(Rectangle):
    pass

rectangle = Rectangle()
square = Square()

print(isinstance(rectangle, Rectangle))  # True
print(isinstance(square, Rectangle))     # True
print(isinstance(square, Square))        # True
print(isinstance(rectangle, Square))     # False

#Python program to print topological sorting of a DAG
from collections import defaultdict
  
#Class to represent a graph
class Graph:
    def __init__(self,vertices):
        self.graph = defaultdict(list) #dictionary containing adjacency List
        self.V = vertices #No. of vertices
  
    # function to add an edge to graph
    def addEdge(self,u,v):
        self.graph[u].append(v)
  
    # A recursive function used by topologicalSort
    def topologicalSortUtil(self,v,visited,stack):
  
        # Mark the current node as visited.
        visited[v] = True
  
        # Recur for all the vertices adjacent to this vertex
        for i in self.graph[v]:
            if visited[i] == False:
                self.topologicalSortUtil(i,visited,stack)
  
        # Push current vertex to stack which stores result
        stack.insert(0,v)
  
    # The function to do Topological Sort. It uses recursive 
    # topologicalSortUtil()
    def topologicalSort(self):
        # Mark all the vertices as not visited
        visited = [False]*self.V
        stack =[]
  
        # Call the recursive helper function to store Topological
        # Sort starting from all vertices one by one
        for i in range(self.V):
            if visited[i] == False:
                self.topologicalSortUtil(i,visited,stack)
  
        # Print contents of stack
        print(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()

# question3.py
from itertools import product
V='∀'
E='∃'

def tt(f,n) :
  xss=product((0,1),repeat=n)
  print('function:',f.__name__)
  for xs in xss : print(*xs,':',int(f(*xs)))
  print('')

# this is the logic for part A (p\/q\/r) /\ (p\/q\/~r) /\ (p\/~q\/r) /\ (p\/~q\/~r) /\ (~p\/q\/r) /\ (~p\/q\/~r) /\ (~p\/~q\/r) /\ (~p\/~q\/~r)

def parta(p,q,r) :
  
  a=(p or q or r) and (p or q or not r) and (p or not q or r)and (p or not q or  not r)
  b=(not p or q or r ) and (not p or q or not r) and (not p or not q or r) and (not p or not q or not r)
  c= a and b
  return c

def partb(p,q,r) :
  a=(p or q and r) and (p or not q or not r) and (p or not q or not  r)and (p or q or  not r)
  b=(not p or q or r ) and (not p or q or not r) and (not p or not q or r) and (not p or not q or not r)
  c= a and b
  return c

print("part A:")
tt(parta,3)

print("part B:")
tt(partb,3)

def key_of_min(d):
  return min(d, key = d.get)

key_of_min({'a':4, 'b':0, 'c':13}) # b

https://codecatch.net/post/06c9f5b7-1e00-40dc-b436-b8cccc4b69be