Improved Code and removed warnings (#482)

Improved Code and removed warnings

Graphs/ArticulationPoints.py

@@ -37,7 +37,7 @@ def computeAP(l):
 
     for x in range(len(isArt)):
         if isArt[x] == True:
-            print(x, end=" ")
+            print(x)
 
 # Adjacency list of graph
 l = {0:[1,2], 1:[0,2], 2:[0,1,3,5], 3:[2,4], 4:[3], 5:[2,6,8], 6:[5,7], 7:[6,8], 8:[5,7]}

Graphs/MinimumSpanningTree_Prims.py

@@ -101,8 +101,8 @@ def PrimsAlgorithm(l):
     return TreeEdges
 
 # < --------- Prims Algorithm --------- >
-n = int(input("Enter number of vertices: "))
-e = int(input("Enter number of edges: "))
+n = int(raw_input("Enter number of vertices: "))
+e = int(raw_input("Enter number of edges: "))
 adjlist = defaultdict(list)
 for x in range(e):
     l = [int(x) for x in input().split()]

Maths/FibonacciSequenceRecursion.py

@@ -9,7 +9,7 @@ def isPositiveInteger(limit):
 def main():
     limit = int(input("How many terms to include in fibonacci series: "))
     if isPositiveInteger(limit):
-        print(f"The first {limit} terms of the fibonacci series are as follows:")
+        print("The first {limit} terms of the fibonacci series are as follows:")
         print([recur_fibo(n) for n in range(limit)])
     else:
         print("Please enter a positive integer: ")

Neural_Network/bpnn.py

@@ -1,3 +1,6 @@
+#!/usr/bin/python
+# encoding=utf8
+
 '''
 
 A Framework of Back Propagation Neural Network（BP） model

Project Euler/Problem 02/sol2.py

@@ -9,4 +9,4 @@ T = int(input().strip())
 ls = []
 for _ in range(T):
     fib(int(input().strip()))
-print(*ls, sep = '\n')
+print(ls, sep = '\n')

Project Euler/Problem 03/sol1.py

@@ -3,7 +3,7 @@ Problem:
 The prime factors of 13195 are 5,7,13 and 29. What is the largest prime factor of a given number N?
 e.g. for 10, largest prime factor = 5. For 17, largest prime factor = 17.
 '''
-from __future__ import print_function
+from __future__ import print_function, division
 
 import math
 

data_structures/Graph/BreadthFirstSearch.py

@@ -1,4 +1,8 @@
-# Author: OMKAR PATHAK
+#!/usr/bin/python
+# encoding=utf8
+
+""" Author: OMKAR PATHAK """
+
 from __future__ import print_function
 
 

data_structures/Graph/DepthFirstSearch.py

@@ -1,4 +1,7 @@
-# Author: OMKAR PATHAK
+#!/usr/bin/python
+# encoding=utf8
+
+""" Author: OMKAR PATHAK """
 from __future__ import print_function
 
 

data_structures/Graph/Graph.py

@@ -1,3 +1,6 @@
+#!/usr/bin/python
+# encoding=utf8
+
 from __future__ import print_function
 # Author: OMKAR PATHAK
 

data_structures/Heap/heap.py

@@ -1,6 +1,6 @@
 #!/usr/bin/python
 
-from __future__ import print_function
+from __future__ import print_function, division
 
 try:
     raw_input          # Python 2

dynamic_programming/fastfibonacci.py

@@ -1,3 +1,6 @@
+#!/usr/bin/python
+# encoding=utf8
+
 """
 This program calculates the nth Fibonacci number in O(log(n)).
 It's possible to calculate F(1000000) in less than a second.

machine_learning/gradient_descent.py

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

other/Fischer-Yates_Shuffle.py

@@ -1,8 +1,10 @@
-'''
+#!/usr/bin/python
+# encoding=utf8
+"""
 The Fisher–Yates shuffle is an algorithm for generating a random permutation of a finite sequence.
 For more details visit
 wikipedia/Fischer-Yates-Shuffle.
-'''
+"""
 import random
 
 def FYshuffle(LIST):

other/sierpinski_triangle.py

@@ -1,3 +1,6 @@
+#!/usr/bin/python
+# encoding=utf8
+
 '''Author Anurag Kumar | anuragkumarak95@gmail.com | git/anuragkumarak95
 
 Simple example of Fractal generation using recursive function.