Simplify code by dropping support for legacy Python (#1143)

* Simplify code by dropping support for legacy Python

* sort() --> sorted()

CONTRIBUTING.md

@@ -56,7 +56,7 @@ We want your work to be readable by others; therefore, we encourage you to note
 
   ```python
       """
-  	This function sums a and b    
+  	This function sums a and b
   """
   def sum(a, b):
       return a + b
@@ -82,13 +82,13 @@ We want your work to be readable by others; therefore, we encourage you to note
   The following "testing" approaches are **not** encouraged:
 
   ```python
-  input('Enter your input:') 
+  input('Enter your input:')
   # Or even worse...
-  input = eval(raw_input("Enter your input: "))
+  input = eval(input("Enter your input: "))
   ```
-  
+
   However, if your code uses __input()__ then we encourage you to gracefully deal with leading and trailing whitespace in user input by adding __.strip()__ to the end as in:
-  
+
   ```python
   starting_value = int(input("Please enter a starting value: ").strip())
   ```
@@ -99,13 +99,13 @@ We want your work to be readable by others; therefore, we encourage you to note
   def sumab(a, b):
       return a + b
   # Write tests this way:
-  print(sumab(1,2))	# 1+2 = 3
-  print(sumab(6,4))	# 6+4 = 10
+  print(sumab(1, 2))	# 1+2 = 3
+  print(sumab(6, 4))	# 6+4 = 10
   # Or this way:
-  print("1 + 2 = ", sumab(1,2))	# 1+2 = 3
-  print("6 + 4 = ", sumab(6,4))	# 6+4 = 10
+  print("1 + 2 = ", sumab(1, 2))	# 1+2 = 3
+  print("6 + 4 = ", sumab(6, 4))	# 6+4 = 10
   ```
-  
+
   Better yet, if you know how to write [__doctests__](https://docs.python.org/3/library/doctest.html), please consider adding them.
 
 - Avoid importing external libraries for basic algorithms. Only use those libraries for complicated algorithms.

ciphers/affine_cipher.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 import sys, random, cryptomath_module as cryptoMath
 
 SYMBOLS = r""" !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~"""

ciphers/atbash.py

@@ -1,23 +1,15 @@
-try:               # Python 2
-    raw_input
-    unichr
-except NameError:  # Python 3
-    raw_input = input
-    unichr = chr
-
-
-def Atbash():
+def atbash():
     output=""
-    for i in raw_input("Enter the sentence to be encrypted ").strip():
+    for i in input("Enter the sentence to be encrypted ").strip():
         extract = ord(i)
         if 65 <= extract <= 90:
-            output += unichr(155-extract)
+            output += chr(155-extract)
         elif 97 <= extract <= 122:
-            output += unichr(219-extract)
+            output += chr(219-extract)
         else:
-            output+=i
+            output += i
     print(output)
 
 
 if __name__ == '__main__':
-    Atbash()
+    atbash()

ciphers/brute_force_caesar_cipher.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 def decrypt(message):
     """
     >>> decrypt('TMDETUX PMDVU')

ciphers/onepad_cipher.py

@@ -1,5 +1,3 @@
-from __future__ import print_function
-
 import random
 
 
@@ -15,7 +13,7 @@ class Onepad:
             cipher.append(c)
             key.append(k)
         return cipher, key
-    
+
     def decrypt(self, cipher, key):
         '''Function to decrypt text using psedo-random numbers.'''
         plain = []

ciphers/rabin_miller.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 # Primality Testing with the Rabin-Miller Algorithm
 
 import random

ciphers/rot13.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 def dencrypt(s, n):
     out = ''
     for c in s:

ciphers/rsa_cipher.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 import sys, rsa_key_generator as rkg, os
 
 DEFAULT_BLOCK_SIZE = 128
@@ -16,7 +15,7 @@ def main():
     if mode == 'encrypt':
         if not os.path.exists('rsa_pubkey.txt'):
             rkg.makeKeyFiles('rsa', 1024)
-            
+
         message = input('\nEnter message: ')
         pubKeyFilename = 'rsa_pubkey.txt'
         print('Encrypting and writing to %s...' % (filename))

ciphers/rsa_key_generator.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 import random, sys, os
 import rabin_miller as rabinMiller, cryptomath_module as cryptoMath
 

ciphers/simple_substitution_cipher.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 import sys, random
 
 LETTERS = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
@@ -18,7 +17,7 @@ def main():
         translated = decryptMessage(key, message)
 
     print('\n%sion: \n%s' % (mode.title(), translated))
-    
+
 def checkValidKey(key):
     keyList = list(key)
     lettersList = list(LETTERS)
@@ -49,7 +48,7 @@ def translateMessage(key, message, mode):
 
     if mode == 'decrypt':
         charsA, charsB = charsB, charsA
-        
+
     for symbol in message:
         if symbol.upper() in charsA:
             symIndex = charsA.find(symbol.upper())

ciphers/transposition_cipher.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 import math
 
 def main():

ciphers/transposition_cipher_encrypt_decrypt_file.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 import time, os, sys
 import transposition_cipher as transCipher
 
@@ -16,7 +15,7 @@ def main():
         response = input('> ')
         if not response.lower().startswith('y'):
             sys.exit()
-            
+
     startTime = time.time()
     if mode.lower().startswith('e'):
         with open(inputFile) as f:
@@ -29,9 +28,9 @@ def main():
 
     with open(outputFile, 'w') as outputObj:
         outputObj.write(translated)
-    
+
     totalTime = round(time.time() - startTime, 2)
     print(('Done (', totalTime, 'seconds )'))
-    
+
 if __name__ == '__main__':
     main()

ciphers/vigenere_cipher.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 LETTERS = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
 
 def main():

data_structures/binary_tree/binary_search_tree.py

@@ -1,7 +1,6 @@
 '''
 A binary search Tree
 '''
-from __future__ import print_function
 class Node:
 
     def __init__(self, label, parent):
@@ -66,8 +65,8 @@ class BinarySearchTree:
             else:
                 parent_node.setRight(new_node)
             #Set parent to the new node
-            new_node.setParent(parent_node)      
-    
+            new_node.setParent(parent_node)
+
     def delete(self, label):
         if (not self.empty()):
             #Look for the node with that label
@@ -92,7 +91,7 @@ class BinarySearchTree:
                     self.delete(tmpNode.getLabel())
                     #Assigns the value to the node to delete and keesp tree structure
                     node.setLabel(tmpNode.getLabel())
-    
+
     def getNode(self, label):
         curr_node = None
         #If the tree is not empty
@@ -177,7 +176,7 @@ class BinarySearchTree:
             #Returns a list of nodes in the order that the users wants to
             return traversalFunction(self.root)
 
-    #Returns an string of all the nodes labels in the list 
+    #Returns an string of all the nodes labels in the list
     #In Order Traversal
     def __str__(self):
         list = self.__InOrderTraversal(self.root)
@@ -203,7 +202,7 @@ def testBinarySearchTree():
                / \    \
               1   6    14
                  / \   /
-                4   7 13 
+                4   7 13
     '''
 
     r'''
@@ -236,11 +235,11 @@ def testBinarySearchTree():
         print("The label -1 exists")
     else:
         print("The label -1 doesn't exist")
-    
+
     if(not t.empty()):
         print(("Max Value: ", t.getMax().getLabel()))
         print(("Min Value: ", t.getMin().getLabel()))
-    
+
     t.delete(13)
     t.delete(10)
     t.delete(8)

data_structures/binary_tree/fenwick_tree.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 class FenwickTree:
 
     def __init__(self, SIZE): # create fenwick tree with size SIZE

data_structures/binary_tree/lazy_segment_tree.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 import math
 
 class SegmentTree:

data_structures/binary_tree/segment_tree.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 import math
 
 class SegmentTree:

data_structures/heap/heap.py

@@ -1,15 +1,8 @@
 #!/usr/bin/python
 
-from __future__ import print_function, division
-
-try:
-    raw_input          # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
-#This heap class start from here.
+# This heap class start from here.
 class Heap:
-	def __init__(self): #Default constructor of heap class.
+	def __init__(self): # Default constructor of heap class.
 	    self.h = []
 	    self.currsize = 0
 
@@ -79,7 +72,7 @@ class Heap:
 		print(self.h)
 
 def main():
-	l = list(map(int, raw_input().split()))
+	l = list(map(int, input().split()))
 	h = Heap()
 	h.buildHeap(l)
 	h.heapSort()

data_structures/linked_list/doubly_linked_list.py

@@ -4,14 +4,13 @@
 - Each link references the next link and the previous one.
 - A Doubly Linked List (DLL) contains an extra pointer, typically called previous pointer, together with next pointer and data which are there in singly linked list.
  - Advantages over SLL - IT can be traversed in both forward and backward direction.,Delete operation is more efficent'''
-from __future__ import print_function
 
 
 class LinkedList:           #making main class named linked list
     def __init__(self):
         self.head = None
         self.tail = None
-        
+
     def insertHead(self, x):
         newLink = Link(x)                            #Create a new link with a value attached to it
         if(self.isEmpty() == True):                  #Set the first element added to be the tail
@@ -20,52 +19,52 @@ class LinkedList:           #making main class named linked list
             self.head.previous = newLink             # newLink <-- currenthead(head)
         newLink.next = self.head                     # newLink <--> currenthead(head)
         self.head = newLink                          # newLink(head) <--> oldhead
-    
+
     def deleteHead(self):
         temp = self.head
-        self.head = self.head.next                   # oldHead <--> 2ndElement(head) 
+        self.head = self.head.next                   # oldHead <--> 2ndElement(head)
         self.head.previous = None                    # oldHead --> 2ndElement(head) nothing pointing at it so the old head will be removed
         if(self.head is None):
             self.tail = None                         #if empty linked list
         return temp
-    
+
     def insertTail(self, x):
         newLink = Link(x)
         newLink.next = None                         # currentTail(tail)    newLink -->
         self.tail.next = newLink                    # currentTail(tail) --> newLink -->
         newLink.previous = self.tail                #currentTail(tail) <--> newLink -->
         self.tail = newLink                         # oldTail <--> newLink(tail) -->
-    
+
     def deleteTail(self):
         temp = self.tail
         self.tail = self.tail.previous              # 2ndLast(tail) <--> oldTail --> None
         self.tail.next = None                       # 2ndlast(tail) --> None
         return temp
-    
+
     def delete(self, x):
         current = self.head
-        
+
         while(current.value != x):                  # Find the position to delete
             current = current.next
-            
+
         if(current == self.head):
             self.deleteHead()
-            
+
         elif(current == self.tail):
             self.deleteTail()
-            
+
         else: #Before: 1 <--> 2(current) <--> 3
             current.previous.next = current.next # 1 --> 3
             current.next.previous = current.previous # 1 <--> 3
-    
+
     def isEmpty(self):                               #Will return True if the list is empty
         return(self.head is None)
-        
+
     def display(self):                                #Prints contents of the list
         current = self.head
         while(current != None):
             current.displayLink()
-            current = current.next  
+            current = current.next
         print()
 
 class Link:

data_structures/linked_list/singly_linked_list.py

@@ -1,6 +1,3 @@
-from __future__ import print_function
-
-
 class Node:  # create a Node
     def __init__(self, data):
         self.data = data  # given data
@@ -10,7 +7,7 @@ class Node:  # create a Node
 class Linked_List:
     def __init__(self):
         self.Head = None    # Initialize Head to None
-        
+
     def insert_tail(self, data):
         if(self.Head is None): self.insert_head(data)    #If this is first node, call insert_head
         else:
@@ -37,7 +34,7 @@ class Linked_List:
             self.Head = self.Head.next
             temp.next = None
         return temp
-        
+
     def delete_tail(self):  # delete from tail
         tamp = self.Head
         if self.Head != None:
@@ -46,7 +43,7 @@ class Linked_List:
             else:
                 while tamp.next.next is not None:  # find the 2nd last element
                     tamp = tamp.next
-                tamp.next, tamp = None, tamp.next    #(2nd last element).next = None and tamp = last element 
+                tamp.next, tamp = None, tamp.next    #(2nd last element).next = None and tamp = last element
         return tamp
 
     def isEmpty(self):
@@ -79,7 +76,7 @@ def main():
     print("\nPrint List : ")
     A.printList()
     print("\nInserting 1st at Tail")
-    a3=input()    
+    a3=input()
     A.insert_tail(a3)
     print("Inserting 2nd at Tail")
     a4=input()
@@ -96,6 +93,6 @@ def main():
     A.reverse()
     print("\nPrint List : ")
     A.printList()
-    
+
 if __name__ == '__main__':
 	main()

data_structures/queue/double_ended_queue.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 # Python code to demonstrate working of
 # extend(), extendleft(), rotate(), reverse()
 

data_structures/stacks/balanced_parentheses.py

@@ -1,6 +1,3 @@
-from __future__ import print_function
-from __future__ import absolute_import
-
 from .stack import Stack
 
 __author__ = 'Omkar Pathak'

data_structures/stacks/infix_to_postfix_conversion.py

@@ -1,5 +1,3 @@
-from __future__ import print_function
-from __future__ import absolute_import
 import string
 
 from .stack import Stack

data_structures/stacks/next_greater_element.py

@@ -1,17 +1,16 @@
-from __future__ import print_function
 # Function to print element and NGE pair for all elements of list
 def printNGE(arr):
- 
+
     for i in range(0, len(arr), 1):
- 
+
         next = -1
         for j in range(i+1, len(arr), 1):
             if arr[i] < arr[j]:
                 next = arr[j]
                 break
-             
+
         print(str(arr[i]) + " -- " + str(next))
- 
+
 # Driver program to test above function
 arr = [11,13,21,3]
 printNGE(arr)

data_structures/stacks/stack.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 __author__ = 'Omkar Pathak'
 
 

data_structures/stacks/stock_span_problem.py

@@ -6,7 +6,6 @@ The span Si of the stock's price on a given day i is defined as the maximum
 number of consecutive days just before the given day, for which the price of the stock
 on the current day is less than or equal to its price on the given day.
 '''
-from __future__ import print_function
 def calculateSpan(price, S):
 
     n = len(price)

divide_and_conquer/convex_hull.py

@@ -1,18 +1,16 @@
-from __future__ import print_function, absolute_import, division
-
 from numbers import Number
 """
-The convex hull problem is problem of finding all the vertices of convex polygon, P of 
+The convex hull problem is problem of finding all the vertices of convex polygon, P of
 a set of points in a plane such that all the points are either on the vertices of P or
-inside P. TH convex hull problem has several applications in geometrical problems, 
-computer graphics and game development. 
+inside P. TH convex hull problem has several applications in geometrical problems,
+computer graphics and game development.
 
-Two algorithms have been implemented for the convex hull problem here. 
+Two algorithms have been implemented for the convex hull problem here.
 1. A brute-force algorithm which runs in O(n^3)
 2. A divide-and-conquer algorithm which runs in O(n^3)
 
 There are other several other algorithms for the convex hull problem
-which have not been implemented here, yet. 
+which have not been implemented here, yet.
 
 """
 

divide_and_conquer/inversions.py

@@ -1,15 +1,13 @@
-from __future__ import print_function, absolute_import, division
-
 """
 Given an array-like data structure A[1..n], how many pairs
-(i, j) for all 1 <= i < j <= n such that A[i] > A[j]? These pairs are 
-called inversions. Counting the number of such inversions in an array-like 
-object is the important. Among other things, counting inversions  can help 
+(i, j) for all 1 <= i < j <= n such that A[i] > A[j]? These pairs are
+called inversions. Counting the number of such inversions in an array-like
+object is the important. Among other things, counting inversions  can help
 us determine how close a given array is to being sorted
- 
+
 In this implementation, I provide two algorithms, a divide-and-conquer
-algorithm which runs in nlogn and the brute-force n^2 algorithm. 
- 
+algorithm which runs in nlogn and the brute-force n^2 algorithm.
+
 """
 
 

dynamic_programming/bitmask.py

@@ -9,27 +9,26 @@ Find the total no of ways in which the tasks can be distributed.
 
 
 """
-from __future__ import print_function
 from collections import defaultdict
 
 
 class AssignmentUsingBitmask:
     def __init__(self,task_performed,total):
-        
+
         self.total_tasks = total    #total no of tasks (N)
-        
+
         # DP table will have a dimension of (2^M)*N
         # initially all values are set to -1
         self.dp = [[-1 for i in range(total+1)] for j in range(2**len(task_performed))]
-        
+
         self.task = defaultdict(list)   #stores the list of persons for each task
-        
+
         #finalmask is used to check if all persons are included by setting all bits to 1
         self.finalmask = (1<<len(task_performed)) - 1
-    
-    
+
+
     def CountWaysUtil(self,mask,taskno):
-        
+
         # if mask == self.finalmask all persons are distributed tasks, return 1
         if mask == self.finalmask:
             return 1
@@ -48,18 +47,18 @@ class AssignmentUsingBitmask:
         # now assign the tasks one by one to all possible persons and recursively assign for the remaining tasks.
         if taskno in self.task:
             for p in self.task[taskno]:
-                
+
                 # if p is already given a task
                 if mask & (1<<p):
                     continue
-                
+
                 # assign this task to p and change the mask value. And recursively assign tasks with the new mask value.
                 total_ways_util+=self.CountWaysUtil(mask|(1<<p),taskno+1)
-        
+
         # save the value.
         self.dp[mask][taskno] = total_ways_util
-        
-        return self.dp[mask][taskno] 
+
+        return self.dp[mask][taskno]
 
     def countNoOfWays(self,task_performed):
 
@@ -67,17 +66,17 @@ class AssignmentUsingBitmask:
         for i in range(len(task_performed)):
             for j in task_performed[i]:
                 self.task[j].append(i)
-        
+
         # call the function to fill the DP table, final answer is stored in dp[0][1]
         return self.CountWaysUtil(0,1)
-        
+
 
 if __name__ == '__main__':
-    
+
     total_tasks = 5    #total no of tasks (the value of N)
-    
+
     #the list of tasks that can be done by M persons.
-    task_performed = [ 
+    task_performed = [
         [ 1 , 3 , 4 ],
         [ 1 , 2 , 5 ],
         [ 3 , 4 ]

dynamic_programming/coin_change.py

@@ -5,9 +5,6 @@ Can you determine number of ways of making change for n units using
 the given types of coins?
 https://www.hackerrank.com/challenges/coin-change/problem
 """
-from __future__ import print_function
-
-
 def dp_count(S, m, n):
 
     # table[i] represents the number of ways to get to amount i

dynamic_programming/edit_distance.py

@@ -7,7 +7,6 @@ This is a pure Python implementation of Dynamic Programming solution to the edit
 The problem is :
 Given two strings A and B. Find the minimum number of operations to string B such that A = B. The permitted operations are removal,  insertion, and substitution.
 """
-from __future__ import print_function
 
 
 class EditDistance:
@@ -67,14 +66,14 @@ def min_distance_bottom_up(word1: str, word2: str) -> int:
     dp = [[0 for _ in range(n+1) ] for _ in range(m+1)]
     for i in range(m+1):
         for j in range(n+1):
-            
+
             if i == 0:  #first string is empty
                 dp[i][j] = j
-            elif j == 0: #second string is empty 
-                dp[i][j] = i 
+            elif j == 0: #second string is empty
+                dp[i][j] = i
             elif word1[i-1] == word2[j-1]: #last character of both substing is equal
                 dp[i][j] = dp[i-1][j-1]
-            else: 
+            else:
                 insert = dp[i][j-1]
                 delete = dp[i-1][j]
                 replace = dp[i-1][j-1]
@@ -82,21 +81,13 @@ def min_distance_bottom_up(word1: str, word2: str) -> int:
     return dp[m][n]
 
 if __name__ == '__main__':
-        try:
-            raw_input          # Python 2
-        except NameError:
-            raw_input = input  # Python 3
-
         solver = EditDistance()
 
         print("****************** Testing Edit Distance DP Algorithm ******************")
         print()
 
-        print("Enter the first string: ", end="")
-        S1 = raw_input().strip()
-
-        print("Enter the second string: ", end="")
-        S2 = raw_input().strip()
+        S1 = input("Enter the first string: ").strip()
+        S2 = input("Enter the second string: ").strip()
 
         print()
         print("The minimum Edit Distance is: %d" % (solver.solve(S1, S2)))
@@ -106,4 +97,4 @@ if __name__ == '__main__':
 
 
 
- 
+

dynamic_programming/fast_fibonacci.py

@@ -5,7 +5,6 @@
 This program calculates the nth Fibonacci number in O(log(n)).
 It's possible to calculate F(1000000) in less than a second.
 """
-from __future__ import print_function
 import sys
 
 

dynamic_programming/fibonacci.py

@@ -1,7 +1,6 @@
 """
 This is a pure Python implementation of Dynamic Programming solution to the fibonacci sequence problem.
 """
-from __future__ import print_function
 
 
 class Fibonacci:
@@ -29,21 +28,16 @@ class Fibonacci:
 
 if __name__ == '__main__':
     print("\n********* Fibonacci Series Using Dynamic Programming ************\n")
-    try:
-        raw_input          # Python 2
-    except NameError:
-        raw_input = input  # Python 3
-
     print("\n Enter the upper limit for the fibonacci sequence: ", end="")
     try:
-        N = eval(raw_input().strip())
+        N = int(input().strip())
         fib = Fibonacci(N)
         print(
-            "\n********* Enter different values to get the corresponding fibonacci sequence, enter any negative number to exit. ************\n")
+            "\n********* Enter different values to get the corresponding fibonacci "
+            "sequence, enter any negative number to exit. ************\n")
         while True:
-            print("Enter value: ", end=" ")
             try:
-                i = eval(raw_input().strip())
+                i = int(input("Enter value: ").strip())
                 if i < 0:
                     print("\n********* Good Bye!! ************\n")
                     break

dynamic_programming/integer_partition.py

@@ -1,27 +1,15 @@
-from __future__ import print_function
-
-try:
-	xrange		#Python 2
-except NameError:
-	xrange = range	#Python 3
-
-try:
-	raw_input		#Python 2
-except NameError:
-	raw_input = input	#Python 3
-
 '''
 The number of partitions of a number n into at least k parts equals the number of partitions into exactly k parts
 plus the number of partitions into at least k-1 parts. Subtracting 1 from each part of a partition of n into k parts
 gives a partition of n-k into k parts. These two facts together are used for this algorithm.
 '''
 def partition(m):
-	memo = [[0 for _ in xrange(m)] for _ in xrange(m+1)]
-	for i in xrange(m+1):
+	memo = [[0 for _ in range(m)] for _ in range(m+1)]
+	for i in range(m+1):
 		memo[i][0] = 1
 
-	for n in xrange(m+1):
-		for k in xrange(1, m):
+	for n in range(m+1):
+		for k in range(1, m):
 			memo[n][k] += memo[n][k-1]
 			if n-k > 0:
 				memo[n][k] += memo[n-k-1][k]
@@ -33,7 +21,7 @@ if __name__ == '__main__':
 
 	if len(sys.argv) == 1:
 		try:
-			n = int(raw_input('Enter a number: '))
+			n = int(input('Enter a number: ').strip())
 			print(partition(n))
 		except ValueError:
 			print('Please enter a number.')

dynamic_programming/longest_common_subsequence.py

@@ -3,7 +3,6 @@ LCS Problem Statement: Given two sequences, find the length of longest subsequen
 A subsequence is a sequence that appears in the same relative order, but not necessarily continuous.
 Example:"abc", "abg" are subsequences of "abcdefgh".
 """
-from __future__ import print_function
 
 
 def longest_common_subsequence(x: str, y: str):
@@ -80,4 +79,3 @@ if __name__ == '__main__':
     assert expected_ln == ln
     assert expected_subseq == subseq
     print("len =", ln, ", sub-sequence =", subseq)
-

dynamic_programming/longest_increasing_subsequence.py

@@ -7,10 +7,8 @@ The problem is  :
 Given an ARRAY, to find the longest and increasing sub ARRAY in that given ARRAY and return it.
 Example: [10, 22, 9, 33, 21, 50, 41, 60, 80] as input will return [10, 22, 33, 41, 60, 80] as output
 '''
-from __future__ import print_function
-
 def longestSub(ARRAY): 			#This function is recursive
-	
+
 	ARRAY_LENGTH = len(ARRAY)
 	if(ARRAY_LENGTH <= 1):  	#If the array contains only one element, we return it (it's the stop condition of recursion)
 		return ARRAY

dynamic_programming/longest_increasing_subsequence_o(nlogn).py

@@ -1,9 +1,8 @@
-from __future__ import print_function
 #############################
 # Author: Aravind Kashyap
 # File: lis.py
 # comments: This programme outputs the Longest Strictly Increasing Subsequence in O(NLogN)
-#           Where N is the Number of elements in the list 
+#           Where N is the Number of elements in the list
 #############################
 def CeilIndex(v,l,r,key):
 	while r-l > 1:
@@ -12,30 +11,30 @@ def CeilIndex(v,l,r,key):
 			r = m
 		else:
 			l = m
-	
+
 	return r
-	
+
 
 def LongestIncreasingSubsequenceLength(v):
 	if(len(v) == 0):
-		return 0	
-	
+		return 0
+
 	tail = [0]*len(v)
 	length = 1
-	
+
 	tail[0] = v[0]
-	
+
 	for i in range(1,len(v)):
 		if v[i] < tail[0]:
 			tail[0] = v[i]
 		elif v[i] > tail[length-1]:
 			tail[length] = v[i]
-			length += 1			
+			length += 1
 		else:
 			tail[CeilIndex(tail,-1,length-1,v[i])] = v[i]
-	
+
 	return length
-	
+
 
 if __name__ == "__main__":
 	v = [2, 5, 3, 7, 11, 8, 10, 13, 6]

dynamic_programming/longest_sub_array.py

@@ -6,7 +6,6 @@ This is a pure Python implementation of Dynamic Programming solution to the long
 The problem is  :
 Given an array, to find the longest and continuous sub array and get the max sum of the sub array in the given array.
 '''
-from __future__ import print_function
 
 
 class SubArray:

dynamic_programming/matrix_chain_order.py

@@ -1,5 +1,3 @@
-from __future__ import print_function
-
 import sys
 '''
 Dynamic Programming

dynamic_programming/max_sub_array.py

@@ -1,7 +1,6 @@
 """
 author : Mayank Kumar Jha (mk9440)
 """
-from __future__ import print_function
 from typing import List
 import time
 import matplotlib.pyplot as plt
@@ -10,7 +9,7 @@ def find_max_sub_array(A,low,high):
     if low==high:
         return low,high,A[low]
     else :
-        mid=(low+high)//2        
+        mid=(low+high)//2
         left_low,left_high,left_sum=find_max_sub_array(A,low,mid)
         right_low,right_high,right_sum=find_max_sub_array(A,mid+1,high)
         cross_left,cross_right,cross_sum=find_max_cross_sum(A,low,mid,high)
@@ -30,7 +29,7 @@ def find_max_cross_sum(A,low,mid,high):
         if summ > left_sum:
             left_sum=summ
             max_left=i
-    summ=0        
+    summ=0
     for i in range(mid+1,high+1):
         summ+=A[i]
         if summ > right_sum:
@@ -40,7 +39,7 @@ def find_max_cross_sum(A,low,mid,high):
 
 def max_sub_array(nums: List[int]) -> int:
     """
-     Finds the contiguous subarray (can be empty array) 
+     Finds the contiguous subarray (can be empty array)
      which has the largest sum and return its sum.
 
     >>> max_sub_array([-2,1,-3,4,-1,2,1,-5,4])
@@ -50,14 +49,14 @@ def max_sub_array(nums: List[int]) -> int:
     >>> max_sub_array([-1,-2,-3])
     0
     """
-    best = 0 
-    current = 0 
-    for i in nums: 
-        current += i 
+    best = 0
+    current = 0
+    for i in nums:
+        current += i
         if current < 0:
             current = 0
         best = max(best, current)
-    return best 
+    return best
 
 if __name__=='__main__':
     inputs=[10,100,1000,10000,50000,100000,200000,300000,400000,500000]
@@ -68,8 +67,8 @@ if __name__=='__main__':
         (find_max_sub_array(li,0,len(li)-1))
         end=time.time()
         tim.append(end-strt)
-    print("No of Inputs       Time Taken")    
-    for i in range(len(inputs)):    
+    print("No of Inputs       Time Taken")
+    for i in range(len(inputs)):
         print(inputs[i],'\t\t',tim[i])
     plt.plot(inputs,tim)
     plt.xlabel("Number of Inputs");plt.ylabel("Time taken in seconds ")
@@ -77,4 +76,4 @@ if __name__=='__main__':
 
 
 
-        
+

graphs/a_star.py

@@ -1,5 +1,3 @@
-from __future__ import print_function
-
 grid = [[0, 1, 0, 0, 0, 0],
         [0, 1, 0, 0, 0, 0],#0 are free path whereas 1's are obstacles
         [0, 1, 0, 0, 0, 0],
@@ -14,13 +12,13 @@ heuristic = [[9, 8, 7, 6, 5, 4],
              [5, 4, 3, 2, 1, 0]]'''
 
 init = [0, 0]
-goal = [len(grid)-1, len(grid[0])-1] #all coordinates are given in format [y,x] 
+goal = [len(grid)-1, len(grid[0])-1] #all coordinates are given in format [y,x]
 cost = 1
 
 #the cost map which pushes the path closer to the goal
 heuristic = [[0 for row in range(len(grid[0]))] for col in range(len(grid))]
-for i in range(len(grid)):    
-    for j in range(len(grid[0])):            
+for i in range(len(grid)):
+    for j in range(len(grid[0])):
         heuristic[i][j] = abs(i - goal[0]) + abs(j - goal[1])
         if grid[i][j] == 1:
             heuristic[i][j] = 99 #added extra penalty in the heuristic map
@@ -62,7 +60,7 @@ def search(grid,init,goal,cost,heuristic):
             g = next[1]
             f = next[0]
 
-            
+
             if x == goal[0] and y == goal[1]:
                 found = True
             else:
@@ -93,10 +91,10 @@ def search(grid,init,goal,cost,heuristic):
     print("ACTION MAP")
     for i in range(len(action)):
         print(action[i])
-                  
+
     return path
-    
+
 a = search(grid,init,goal,cost,heuristic)
 for i in range(len(a)):
-	print(a[i]) 
+	print(a[i])
 

graphs/basic_graphs.py

@@ -1,23 +1,10 @@
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
-try:
-    xrange  # Python 2
-except NameError:
-    xrange = range  # Python 3
-
-
 if __name__ == "__main__":
     # Accept No. of Nodes and edges
-    n, m = map(int, raw_input().split(" "))
+    n, m = map(int, input().split(" "))
 
     # Initialising Dictionary of edges
     g = {}
-    for i in xrange(n):
+    for i in range(n):
         g[i + 1] = []
 
     """
@@ -25,8 +12,8 @@ if __name__ == "__main__":
         Accepting edges of Unweighted Directed Graphs
     ----------------------------------------------------------------------------
     """
-    for _ in xrange(m):
-        x, y = map(int, raw_input().strip().split(" "))
+    for _ in range(m):
+        x, y = map(int, input().strip().split(" "))
         g[x].append(y)
 
     """
@@ -34,8 +21,8 @@ if __name__ == "__main__":
         Accepting edges of Unweighted Undirected Graphs
     ----------------------------------------------------------------------------
     """
-    for _ in xrange(m):
-        x, y = map(int, raw_input().strip().split(" "))
+    for _ in range(m):
+        x, y = map(int, input().strip().split(" "))
         g[x].append(y)
         g[y].append(x)
 
@@ -44,8 +31,8 @@ if __name__ == "__main__":
         Accepting edges of Weighted Undirected Graphs
     ----------------------------------------------------------------------------
     """
-    for _ in xrange(m):
-        x, y, r = map(int, raw_input().strip().split(" "))
+    for _ in range(m):
+        x, y, r = map(int, input().strip().split(" "))
         g[x].append([y, r])
         g[y].append([x, r])
 
@@ -170,10 +157,10 @@ def topo(G, ind=None, Q=[1]):
 
 
 def adjm():
-    n = raw_input().strip()
+    n = input().strip()
     a = []
-    for i in xrange(n):
-        a.append(map(int, raw_input().strip().split()))
+    for i in range(n):
+        a.append(map(int, input().strip().split()))
     return a, n
 
 
@@ -193,10 +180,10 @@ def adjm():
 def floy(A_and_n):
     (A, n) = A_and_n
     dist = list(A)
-    path = [[0] * n for i in xrange(n)]
-    for k in xrange(n):
-        for i in xrange(n):
-            for j in xrange(n):
+    path = [[0] * n for i in range(n)]
+    for k in range(n):
+        for i in range(n):
+            for j in range(n):
                 if dist[i][j] > dist[i][k] + dist[k][j]:
                     dist[i][j] = dist[i][k] + dist[k][j]
                     path[i][k] = k
@@ -245,10 +232,10 @@ def prim(G, s):
 
 
 def edglist():
-    n, m = map(int, raw_input().split(" "))
+    n, m = map(int, input().split(" "))
     l = []
-    for i in xrange(m):
-        l.append(map(int, raw_input().split(' ')))
+    for i in range(m):
+        l.append(map(int, input().split(' ')))
     return l, n
 
 
@@ -272,10 +259,10 @@ def krusk(E_and_n):
             break
         print(s)
         x = E.pop()
-        for i in xrange(len(s)):
+        for i in range(len(s)):
             if x[0] in s[i]:
                 break
-        for j in xrange(len(s)):
+        for j in range(len(s)):
             if x[1] in s[j]:
                 if i == j:
                     break

graphs/bellman_ford.py

@@ -1,5 +1,3 @@
-from __future__ import print_function
-
 def printDist(dist, V):
 	print("\nVertex Distance")
 	for i in range(V):

graphs/breadth_first_search.py

@@ -3,8 +3,6 @@
 
 """ Author: OMKAR PATHAK """
 
-from __future__ import print_function
-
 
 class Graph():
     def __init__(self):

graphs/depth_first_search.py

@@ -2,7 +2,6 @@
 # encoding=utf8
 
 """ Author: OMKAR PATHAK """
-from __future__ import print_function
 
 
 class Graph():

graphs/dijkstra_2.py

@@ -1,5 +1,3 @@
-from __future__ import print_function
-
 def printDist(dist, V):
 	print("\nVertex Distance")
 	for i in range(V):

graphs/dijkstra_algorithm.py

@@ -2,7 +2,6 @@
 # Author: Shubham Malik
 # References: https://en.wikipedia.org/wiki/Dijkstra%27s_algorithm
 
-from __future__ import print_function
 import math
 import sys
 # For storing the vertex set to retreive node with the lowest distance

graphs/even_tree.py

@@ -12,7 +12,6 @@ Constraints
 Note: The tree input will be such that it can always be decomposed into
 components containing an even number of nodes.
 """
-from __future__ import print_function
 # pylint: disable=invalid-name
 from collections import defaultdict
 

graphs/graph_list.py

@@ -1,7 +1,6 @@
 #!/usr/bin/python
 # encoding=utf8
 
-from __future__ import print_function
 # Author: OMKAR PATHAK
 
 # We can use Python's dictionary for constructing the graph.

graphs/graph_matrix.py

@@ -1,6 +1,3 @@
-from __future__ import print_function
-
-
 class Graph:
 
     def __init__(self, vertex):

graphs/graphs_floyd_warshall.py

@@ -4,8 +4,6 @@
     have negative edge weights.
 """
 
-from __future__ import print_function
-
 
 def _print_dist(dist, v):
 	print("\nThe shortest path matrix using Floyd Warshall algorithm\n")
@@ -34,9 +32,9 @@ def floyd_warshall(graph, v):
     4. The above is repeated for each vertex k in the graph.
     5. Whenever distance[i][j] is given a new minimum value, next vertex[i][j] is updated to the next vertex[i][k].
     """
-		
+
 	dist=[[float('inf') for _ in range(v)] for _ in range(v)]
-	
+
 	for i in range(v):
 		for j in range(v):
 			dist[i][j] = graph[i][j]
@@ -53,7 +51,7 @@ def floyd_warshall(graph, v):
 	_print_dist(dist, v)
 	return dist, v
 
-			
+
 
 if __name__== '__main__':
 	v = int(input("Enter number of vertices: "))

graphs/minimum_spanning_tree_kruskal.py

@@ -1,5 +1,3 @@
-from __future__ import print_function
-
 if __name__ == "__main__":
     num_nodes, num_edges = list(map(int, input().strip().split()))
 

graphs/multi_hueristic_astar.py

@@ -1,12 +1,6 @@
-from __future__ import print_function
 import heapq
 import numpy as np
 
-try:
-    xrange          # Python 2
-except NameError:
-    xrange = range  # Python 3
-
 
 class PriorityQueue:
 	def __init__(self):
@@ -96,7 +90,7 @@ def do_something(back_pointer, goal, start):
 	grid[(n-1)][0] = "-"
 
 
-	for i in xrange(n):
+	for i in range(n):
 		for j in range(n):
 			if (i, j) == (0, n-1):
 				print(grid[i][j], end=' ')

graphs/scc_kosaraju.py

@@ -1,6 +1,3 @@
-from __future__ import print_function
-
-
 def dfs(u):
     global g, r, scc, component, visit, stack
     if visit[u]: return

hashes/chaos_machine.py

@@ -1,10 +1,4 @@
 """example of simple chaos machine"""
-from __future__ import print_function
-
-try:
-  input = raw_input  # Python 2
-except NameError:
-  pass               # Python 3
 
 # Chaos Machine (K, t, m)
 K = [0.33, 0.44, 0.55, 0.44, 0.33]; t = 3; m = 5
@@ -96,7 +90,7 @@ message = random.sample(range(0xFFFFFFFF), 100)
 for chunk in message:
   push(chunk)
 
-# for controlling 
+# for controlling
 inp = ""
 
 # Pulling Data (Output)

hashes/enigma_machine.py

@@ -1,5 +1,3 @@
-from __future__ import print_function
-
 alphabets = [chr(i) for i in range(32, 126)]
 gear_one = [i for i in range(len(alphabets))]
 gear_two = [i for i in range(len(alphabets))]

hashes/md5.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 import math
 
 
@@ -66,7 +65,7 @@ def getBlock(bitString):
     """[summary]
     Iterator:
             Returns by each call a list of length 16 with the 32 bit
-            integer blocks. 
+            integer blocks.
 
     Arguments:
             bitString {[string]} -- [binary string >= 512]
@@ -95,7 +94,7 @@ def not32(i):
 
 def sum32(a, b):
     '''
-    
+
     '''
     return (a + b) % 2**32
 

machine_learning/decision_tree.py

@@ -1,10 +1,8 @@
 """
 Implementation of a basic regression decision tree.
 Input data set: The input data set must be 1-dimensional with continuous labels.
-Output: The decision tree maps a real number input to a real number output. 
+Output: The decision tree maps a real number input to a real number output.
 """
-from __future__ import print_function
-
 import numpy as np
 
 class Decision_Tree:
@@ -19,7 +17,7 @@ class Decision_Tree:
     def mean_squared_error(self, labels, prediction):
         """
         mean_squared_error:
-        @param labels: a one dimensional numpy array 
+        @param labels: a one dimensional numpy array
         @param prediction: a floating point value
         return value: mean_squared_error calculates the error if prediction is used to estimate the labels
         """
@@ -32,7 +30,7 @@ class Decision_Tree:
         """
         train:
         @param X: a one dimensional numpy array
-        @param y: a one dimensional numpy array. 
+        @param y: a one dimensional numpy array.
         The contents of y are the labels for the corresponding X values
 
         train does not have a return value
@@ -135,6 +133,6 @@ def main():
     print("Predictions: " + str(predictions))
     print("Average error: " + str(avg_error))
 
-            
+
 if __name__ == '__main__':
     main()

machine_learning/gradient_descent.py

@@ -1,7 +1,6 @@
 """
 Implementation of gradient descent algorithm for minimizing cost of a linear hypothesis function.
 """
-from __future__ import print_function, division
 import numpy
 
 # List of input, output pairs

machine_learning/k_means_clust.py

@@ -17,36 +17,35 @@ Inputs:
 
 Usage:
   1. define 'k' value, 'X' features array and 'hetrogeneity' empty list
-  
+
   2. create initial_centroids,
         initial_centroids = get_initial_centroids(
-            X, 
-            k, 
+            X,
+            k,
             seed=0 # seed value for initial centroid generation, None for randomness(default=None)
             )
 
   3. find centroids and clusters using kmeans function.
-  
+
         centroids, cluster_assignment = kmeans(
-            X, 
-            k, 
-            initial_centroids, 
+            X,
+            k,
+            initial_centroids,
             maxiter=400,
-            record_heterogeneity=heterogeneity, 
+            record_heterogeneity=heterogeneity,
             verbose=True # whether to print logs in console or not.(default=False)
             )
-  
-  
+
+
   4. Plot the loss function, hetrogeneity values for every iteration saved in hetrogeneity list.
         plot_heterogeneity(
-            heterogeneity, 
+            heterogeneity,
             k
         )
-  
+
   5. Have fun..
-  
+
 '''
-from __future__ import print_function
 from sklearn.metrics import pairwise_distances
 import numpy as np
 
@@ -57,30 +56,30 @@ def get_initial_centroids(data, k, seed=None):
     if seed is not None: # useful for obtaining consistent results
         np.random.seed(seed)
     n = data.shape[0] # number of data points
-        
+
     # Pick K indices from range [0, N).
     rand_indices = np.random.randint(0, n, k)
-    
+
     # Keep centroids as dense format, as many entries will be nonzero due to averaging.
     # As long as at least one document in a cluster contains a word,
     # it will carry a nonzero weight in the TF-IDF vector of the centroid.
     centroids = data[rand_indices,:]
-    
+
     return centroids
 
 def centroid_pairwise_dist(X,centroids):
     return pairwise_distances(X,centroids,metric='euclidean')
 
 def assign_clusters(data, centroids):
-    
+
     # Compute distances between each data point and the set of centroids:
     # Fill in the blank (RHS only)
     distances_from_centroids = centroid_pairwise_dist(data,centroids)
-    
+
     # Compute cluster assignments for each data point:
     # Fill in the blank (RHS only)
     cluster_assignment = np.argmin(distances_from_centroids,axis=1)
-    
+
     return cluster_assignment
 
 def revise_centroids(data, k, cluster_assignment):
@@ -92,23 +91,23 @@ def revise_centroids(data, k, cluster_assignment):
         centroid = member_data_points.mean(axis=0)
         new_centroids.append(centroid)
     new_centroids = np.array(new_centroids)
-    
+
     return new_centroids
 
 def compute_heterogeneity(data, k, centroids, cluster_assignment):
-    
+
     heterogeneity = 0.0
     for i in range(k):
-        
+
         # Select all data points that belong to cluster i. Fill in the blank (RHS only)
         member_data_points = data[cluster_assignment==i, :]
-        
+
         if member_data_points.shape[0] > 0: # check if i-th cluster is non-empty
             # Compute distances from centroid to data points (RHS only)
             distances = pairwise_distances(member_data_points, [centroids[i]], metric='euclidean')
             squared_distances = distances**2
             heterogeneity += np.sum(squared_distances)
-        
+
     return heterogeneity
 
 from matplotlib import pyplot as plt
@@ -129,36 +128,36 @@ def kmeans(data, k, initial_centroids, maxiter=500, record_heterogeneity=None, v
        verbose: if True, print how many data points changed their cluster labels in each iteration'''
     centroids = initial_centroids[:]
     prev_cluster_assignment = None
-    
-    for itr in range(maxiter):        
+
+    for itr in range(maxiter):
         if verbose:
             print(itr, end='')
-        
+
         # 1. Make cluster assignments using nearest centroids
         cluster_assignment = assign_clusters(data,centroids)
-            
+
         # 2. Compute a new centroid for each of the k clusters, averaging all data points assigned to that cluster.
         centroids = revise_centroids(data,k, cluster_assignment)
-            
+
         # Check for convergence: if none of the assignments changed, stop
         if prev_cluster_assignment is not None and \
           (prev_cluster_assignment==cluster_assignment).all():
             break
-        
-        # Print number of new assignments 
+
+        # Print number of new assignments
         if prev_cluster_assignment is not None:
             num_changed = np.sum(prev_cluster_assignment!=cluster_assignment)
             if verbose:
-                print('    {0:5d} elements changed their cluster assignment.'.format(num_changed))   
-        
+                print('    {0:5d} elements changed their cluster assignment.'.format(num_changed))
+
         # Record heterogeneity convergence metric
         if record_heterogeneity is not None:
             # YOUR CODE HERE
             score = compute_heterogeneity(data,k,centroids,cluster_assignment)
             record_heterogeneity.append(score)
-        
+
         prev_cluster_assignment = cluster_assignment[:]
-        
+
     return centroids, cluster_assignment
 
 # Mock test below

machine_learning/linear_regression.py

@@ -7,8 +7,6 @@ We try to set these Feature weights, over many iterations, so that they best
 fits our dataset. In this particular code, i had used a CSGO dataset (ADR vs
 Rating). We try to best fit a line through dataset and estimate the parameters.
 """
-from __future__ import print_function
-
 import requests
 import numpy as np
 

maths/simpson_rule.py

@@ -8,9 +8,6 @@ method 2:
 "Simpson Rule"
 
 """
-from __future__ import print_function
-
-
 def method_2(boundary, steps):
 # "Simpson Rule"
 # int(f) = delta_x/2 * (b-a)/3*(f1 + 4f2 + 2f_3 + ... + fn)

maths/trapezoidal_rule.py

@@ -7,8 +7,6 @@ method 1:
 "extended trapezoidal rule"
 
 """
-from __future__ import print_function
-
 def method_1(boundary, steps):
 # "extended trapezoidal rule"
 # int(f) = dx/2 * (f1 + 2f2 + ... + fn)
@@ -19,7 +17,7 @@ def method_1(boundary, steps):
 	y = 0.0
 	y += (h/2.0)*f(a)
 	for i in x_i:
-		#print(i)	
+		#print(i)
 		y += h*f(i)
 	y += (h/2.0)*f(b)
 	return y

maths/zellers_congruence.py

@@ -1,4 +1,3 @@
-from __future__ import annotations
 import datetime
 import argparse
 
@@ -7,7 +6,7 @@ def zeller(date_input: str) -> str:
 
     """
     Zellers Congruence Algorithm
-    Find the day of the week for nearly any Gregorian or Julian calendar date 
+    Find the day of the week for nearly any Gregorian or Julian calendar date
 
     >>> zeller('01-31-2010')
     'Your date 01-31-2010, is a Sunday!'
@@ -108,7 +107,7 @@ def zeller(date_input: str) -> str:
     # Validate
     if not 0 < d < 32:
         raise ValueError("Date must be between 1 - 31")
-    
+
     # Get second seperator
     sep_2: str = date_input[5]
     # Validate

matrix/nth_fibonacci_using_matrix_exponentiation.py

@@ -13,9 +13,6 @@ Converting to matrix,
 So we just need the n times multiplication of the matrix [1,1],[1,0]].
 We can decrease the n times multiplication by following the divide and conquer approach.
 """
-from __future__ import print_function
-
-
 def multiply(matrix_a, matrix_b):
     matrix_c = []
     n = len(matrix_a)

neural_network/convolution_neural_network.py

@@ -15,8 +15,6 @@
     Date: 2017.9.20
     - - - - - -- - - - - - - - - - - - - - - - - - - - - - -
 '''
-from __future__ import print_function
-
 import pickle
 import numpy as np
 import matplotlib.pyplot as plt

neural_network/perceptron.py

@@ -9,8 +9,6 @@
     p2 = 1
 
 '''
-from __future__ import print_function
-
 import random
 
 

other/anagrams.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 import collections, pprint, time, os
 
 start_time = time.time()

other/euclidean_gcd.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 # https://en.wikipedia.org/wiki/Euclidean_algorithm
 
 def euclidean_gcd(a, b):

other/linear_congruential_generator.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 __author__ = "Tobias Carryer"
 
 from time import time
@@ -7,11 +6,11 @@ class LinearCongruentialGenerator(object):
     """
     A pseudorandom number generator.
     """
-    
+
     def __init__( self, multiplier, increment, modulo, seed=int(time()) ):
         """
         These parameters are saved and used when nextNumber() is called.
-     
+
         modulo is the largest number that can be generated (exclusive). The most
         efficent values are powers of 2. 2^32 is a common value.
         """
@@ -19,7 +18,7 @@ class LinearCongruentialGenerator(object):
         self.increment = increment
         self.modulo = modulo
         self.seed = seed
-        
+
     def next_number( self ):
         """
         The smallest number that can be generated is zero.

other/nested_brackets.py

@@ -13,9 +13,6 @@ The function called is_balanced takes as input a string S which is a sequence of
 returns true if S is nested and false otherwise.
 
 '''
-from __future__ import print_function
-
-
 def is_balanced(S):
 
     stack = []

other/password_generator.py

@@ -1,5 +1,4 @@
 """Password generator allows you to generate a random password of length N."""
-from __future__ import print_function
 from random import choice
 from string import ascii_letters, digits, punctuation
 

other/tower_of_hanoi.py

@@ -1,5 +1,4 @@
-from __future__ import print_function
-def moveTower(height, fromPole, toPole, withPole):  
+def moveTower(height, fromPole, toPole, withPole):
     '''
     >>> moveTower(3, 'A', 'B', 'C')
     moving disk from A to B

other/two_sum.py

@@ -9,8 +9,6 @@ Given nums = [2, 7, 11, 15], target = 9,
 Because nums[0] + nums[1] = 2 + 7 = 9,
 return [0, 1].
 """
-from __future__ import print_function
-
 def twoSum(nums, target):
     """
     :type nums: List[int]
@@ -20,7 +18,7 @@ def twoSum(nums, target):
     chk_map = {}
     for index, val in enumerate(nums):
       compl = target - val
-      if compl in chk_map: 
+      if compl in chk_map:
         indices = [chk_map[compl], index]
         print(indices)
         return [indices]

other/word_patterns.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 import pprint, time
 
 def getWordPattern(word):

project_euler/problem_01/sol1.py

@@ -4,17 +4,9 @@ If we list all the natural numbers below 10 that are multiples of 3 or 5,
 we get 3,5,6 and 9. The sum of these multiples is 23.
 Find the sum of all the multiples of 3 or 5 below N.
 """
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
-
 def solution(n):
     """Returns the sum of all the multiples of 3 or 5 below n.
-    
+
     >>> solution(3)
     0
     >>> solution(4)
@@ -31,4 +23,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_01/sol2.py

@@ -4,17 +4,11 @@ If we list all the natural numbers below 10 that are multiples of 3 or 5,
 we get 3,5,6 and 9. The sum of these multiples is 23.
 Find the sum of all the multiples of 3 or 5 below N.
 """
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
 
 
 def solution(n):
     """Returns the sum of all the multiples of 3 or 5 below n.
-    
+
     >>> solution(3)
     0
     >>> solution(4)
@@ -36,4 +30,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_01/sol3.py

@@ -4,20 +4,12 @@ If we list all the natural numbers below 10 that are multiples of 3 or 5,
 we get 3,5,6 and 9. The sum of these multiples is 23.
 Find the sum of all the multiples of 3 or 5 below N.
 """
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
-
 def solution(n):
     """
     This solution is based on the pattern that the successive numbers in the
     series follow: 0+3,+2,+1,+3,+1,+2,+3.
     Returns the sum of all the multiples of 3 or 5 below n.
-    
+
     >>> solution(3)
     0
     >>> solution(4)
@@ -63,4 +55,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_01/sol4.py

@@ -4,17 +4,9 @@ If we list all the natural numbers below 10 that are multiples of 3 or 5,
 we get 3,5,6 and 9. The sum of these multiples is 23.
 Find the sum of all the multiples of 3 or 5 below N.
 """
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
-
 def solution(n):
     """Returns the sum of all the multiples of 3 or 5 below n.
-    
+
     >>> solution(3)
     0
     >>> solution(4)
@@ -50,4 +42,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_01/sol5.py

@@ -4,19 +4,13 @@ If we list all the natural numbers below 10 that are multiples of 3 or 5,
 we get 3,5,6 and 9. The sum of these multiples is 23.
 Find the sum of all the multiples of 3 or 5 below N.
 """
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
 
 """A straightforward pythonic solution using list comprehension"""
 
 
 def solution(n):
     """Returns the sum of all the multiples of 3 or 5 below n.
-    
+
     >>> solution(3)
     0
     >>> solution(4)
@@ -31,4 +25,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_01/sol6.py

@@ -4,17 +4,9 @@ If we list all the natural numbers below 10 that are multiples of 3 or 5,
 we get 3,5,6 and 9. The sum of these multiples is 23.
 Find the sum of all the multiples of 3 or 5 below N.
 """
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
-
 def solution(n):
     """Returns the sum of all the multiples of 3 or 5 below n.
-    
+
     >>> solution(3)
     0
     >>> solution(4)
@@ -37,4 +29,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_02/sol1.py

@@ -9,18 +9,10 @@ By considering the terms in the Fibonacci sequence whose values do not exceed
 n, find the sum of the even-valued terms. e.g. for n=10, we have {2,8}, sum is
 10.
 """
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
-
 def solution(n):
     """Returns the sum of all fibonacci sequence even elements that are lower
     or equals to n.
-    
+
     >>> solution(10)
     10
     >>> solution(15)
@@ -44,4 +36,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_02/sol2.py

@@ -9,18 +9,10 @@ By considering the terms in the Fibonacci sequence whose values do not exceed
 n, find the sum of the even-valued terms. e.g. for n=10, we have {2,8}, sum is
 10.
 """
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
-
 def solution(n):
     """Returns the sum of all fibonacci sequence even elements that are lower
     or equals to n.
-    
+
     >>> solution(10)
     [2, 8]
     >>> solution(15)
@@ -42,4 +34,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_02/sol3.py

@@ -9,18 +9,10 @@ By considering the terms in the Fibonacci sequence whose values do not exceed
 n, find the sum of the even-valued terms. e.g. for n=10, we have {2,8}, sum is
 10.
 """
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
-
 def solution(n):
     """Returns the sum of all fibonacci sequence even elements that are lower
     or equals to n.
-    
+
     >>> solution(10)
     10
     >>> solution(15)
@@ -44,4 +36,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_02/sol4.py

@@ -9,20 +9,14 @@ By considering the terms in the Fibonacci sequence whose values do not exceed
 n, find the sum of the even-valued terms. e.g. for n=10, we have {2,8}, sum is
 10.
 """
-from __future__ import print_function
 import math
 from decimal import Decimal, getcontext
 
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
 
 def solution(n):
     """Returns the sum of all fibonacci sequence even elements that are lower
     or equals to n.
-    
+
     >>> solution(10)
     10
     >>> solution(15)
@@ -68,4 +62,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_03/sol1.py

@@ -5,14 +5,8 @@ of a given number N?
 
 e.g. for 10, largest prime factor = 5. For 17, largest prime factor = 17.
 """
-from __future__ import print_function, division
 import math
 
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
 
 def isprime(no):
     if no == 2:
@@ -81,4 +75,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_03/sol2.py

@@ -5,12 +5,6 @@ of a given number N?
 
 e.g. for 10, largest prime factor = 5. For 17, largest prime factor = 17.
 """
-from __future__ import print_function, division
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
 
 
 def solution(n):
@@ -60,4 +54,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_04/sol1.py

@@ -6,18 +6,10 @@ the product of two 2-digit numbers is 9009 = 91 x 99.
 Find the largest palindrome made from the product of two 3-digit numbers which
 is less than N.
 """
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
-
 def solution(n):
     """Returns the largest palindrome made from the product of two 3-digit
     numbers which is less than n.
-    
+
     >>> solution(20000)
     19591
     >>> solution(30000)
@@ -47,4 +39,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_04/sol2.py

@@ -6,18 +6,10 @@ the product of two 2-digit numbers is 9009 = 91 x 99.
 Find the largest palindrome made from the product of two 3-digit numbers which
 is less than N.
 """
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
-
 def solution(n):
     """Returns the largest palindrome made from the product of two 3-digit
     numbers which is less than n.
-    
+
     >>> solution(20000)
     19591
     >>> solution(30000)
@@ -35,4 +27,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_05/sol1.py

@@ -6,14 +6,6 @@ to 10 without any remainder.
 What is the smallest positive number that is evenly divisible(divisible with no
 remainder) by all of the numbers from 1 to N?
 """
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
-
 def solution(n):
     """Returns the smallest positive number that is evenly divisible(divisible
     with no remainder) by all of the numbers from 1 to n.
@@ -66,4 +58,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_05/sol2.py

@@ -6,13 +6,6 @@ to 10 without any remainder.
 What is the smallest positive number that is evenly divisible(divisible with no
 remainder) by all of the numbers from 1 to N?
 """
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
 """ Euclidean GCD Algorithm """
 
 
@@ -30,7 +23,7 @@ def lcm(x, y):
 def solution(n):
     """Returns the smallest positive number that is evenly divisible(divisible
     with no remainder) by all of the numbers from 1 to n.
-    
+
     >>> solution(10)
     2520
     >>> solution(15)
@@ -47,4 +40,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_06/sol1.py

@@ -14,18 +14,10 @@ numbers and the square of the sum is 3025 − 385 = 2640.
 Find the difference between the sum of the squares of the first N natural
 numbers and the square of the sum.
 """
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
-
 def solution(n):
     """Returns the difference between the sum of the squares of the first n
     natural numbers and the square of the sum.
- 
+
     >>> solution(10)
     2640
     >>> solution(15)
@@ -45,4 +37,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_06/sol2.py

@@ -14,18 +14,10 @@ numbers and the square of the sum is 3025 − 385 = 2640.
 Find the difference between the sum of the squares of the first N natural
 numbers and the square of the sum.
 """
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
-
 def solution(n):
     """Returns the difference between the sum of the squares of the first n
     natural numbers and the square of the sum.
- 
+
     >>> solution(10)
     2640
     >>> solution(15)
@@ -42,4 +34,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_06/sol3.py

@@ -14,19 +14,13 @@ numbers and the square of the sum is 3025 − 385 = 2640.
 Find the difference between the sum of the squares of the first N natural
 numbers and the square of the sum.
 """
-from __future__ import print_function
 import math
 
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
 
 def solution(n):
     """Returns the difference between the sum of the squares of the first n
     natural numbers and the square of the sum.
- 
+
     >>> solution(10)
     2640
     >>> solution(15)
@@ -42,4 +36,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_07/sol1.py

@@ -6,14 +6,8 @@ By listing the first six prime numbers:
 
 We can see that the 6th prime is 13. What is the Nth prime number?
 """
-from __future__ import print_function
 from math import sqrt
 
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
 
 def isprime(n):
     if n == 2:
@@ -30,7 +24,7 @@ def isprime(n):
 
 def solution(n):
     """Returns the n-th prime number.
- 
+
     >>> solution(6)
     13
     >>> solution(1)
@@ -58,4 +52,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_07/sol2.py

@@ -6,14 +6,6 @@ By listing the first six prime numbers:
 
 We can see that the 6th prime is 13. What is the Nth prime number?
 """
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
-
 def isprime(number):
     for i in range(2, int(number ** 0.5) + 1):
         if number % i == 0:
@@ -23,7 +15,7 @@ def isprime(number):
 
 def solution(n):
     """Returns the n-th prime number.
- 
+
     >>> solution(6)
     13
     >>> solution(1)
@@ -73,4 +65,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_07/sol3.py

@@ -6,15 +6,9 @@ By listing the first six prime numbers:
 
 We can see that the 6th prime is 13. What is the Nth prime number?
 """
-from __future__ import print_function
 import math
 import itertools
 
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
 
 def primeCheck(number):
     if number % 2 == 0 and number > 2:
@@ -32,7 +26,7 @@ def prime_generator():
 
 def solution(n):
     """Returns the n-th prime number.
- 
+
     >>> solution(6)
     13
     >>> solution(1)
@@ -50,4 +44,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_09/sol1.py

@@ -7,7 +7,6 @@ For example, 3^2 + 4^2 = 9 + 16 = 25 = 5^2.
 There exists exactly one Pythagorean triplet for which a + b + c = 1000.
 Find the product abc.
 """
-from __future__ import print_function
 
 
 def solution():
@@ -17,7 +16,7 @@ def solution():
      1. a < b < c
      2. a**2 + b**2 = c**2
      3. a + b + c = 1000
-    
+
     # The code below has been commented due to slow execution affecting Travis.
     # >>> solution()
     # 31875000

project_euler/problem_09/sol2.py

@@ -7,14 +7,6 @@ For example, 3^2 + 4^2 = 9 + 16 = 25 = 5^2.
 There exists exactly one Pythagorean triplet for which a + b + c = 1000.
 Find the product abc.
 """
-from __future__ import print_function
-
-try:
-    raw_input  # Python 2
-except NameError:
-    raw_input = input  # Python 3
-
-
 def solution(n):
     """
      Return the product of a,b,c which are Pythagorean Triplet that satisfies
@@ -22,7 +14,7 @@ def solution(n):
      1. a < b < c
      2. a**2 + b**2 = c**2
      3. a + b + c = 1000
-    
+
     >>> solution(1000)
     31875000
     """
@@ -41,4 +33,4 @@ def solution(n):
 
 
 if __name__ == "__main__":
-    print(solution(int(raw_input().strip())))
+    print(solution(int(input().strip())))

project_euler/problem_09/sol3.py

@@ -10,9 +10,6 @@ For example, 3^2 + 4^2 = 9 + 16 = 25 = 5^2.
 There exists exactly one Pythagorean triplet for which a + b + c = 1000.
 Find the product abc.
 """
-from __future__ import print_function
-
-
 def solution():
     """
      Returns the product of a,b,c which are Pythagorean Triplet that satisfies