Merge pull request TheAlgorithms#97 from OmkarPathak/added_programs

Added Stack implementation and some traditional Stack problems

Author: 0oo0

data_structures/Graph/Graph.py

@@ -0,0 +1,40 @@
+# Author: OMKAR PATHAK
+
+# We can use Python's dictionary for constructing the graph
+
+class AdjacencyList(object):
+    def __init__(self):
+        self.List = {}
+
+    def addEdge(self, fromVertex, toVertex):
+        # check if vertex is already present
+        if fromVertex in self.List.keys():
+            self.List[fromVertex].append(toVertex)
+        else:
+            self.List[fromVertex] = [toVertex]
+
+    def printList(self):
+        for i  in self.List:
+            print(i,'->',' -> '.join([str(j) for j in self.List[i]]))
+
+if __name__ == '__main__':
+    al = AdjacencyList()
+    al.addEdge(0, 1)
+    al.addEdge(0, 4)
+    al.addEdge(4, 1)
+    al.addEdge(4, 3)
+    al.addEdge(1, 0)
+    al.addEdge(1, 4)
+    al.addEdge(1, 3)
+    al.addEdge(1, 2)
+    al.addEdge(2, 3)
+    al.addEdge(3, 4)
+
+    al.printList()
+
+    # OUTPUT:
+    # 0 -> 1 -> 4
+    # 1 -> 0 -> 4 -> 3 -> 2
+    # 2 -> 3
+    # 3 -> 4
+    # 4 -> 1 -> 3

data_structures/Graph/P01_BreadthFirstSearch.py

@@ -0,0 +1,61 @@
+# Author: OMKAR PATHAK
+
+class Graph():
+    def __init__(self):
+        self.vertex = {}
+
+    # for printing the Graph vertexes
+    def printGraph(self):
+        for i in self.vertex.keys():
+            print(i,' -> ', ' -> '.join([str(j) for j in self.vertex[i]]))
+
+    # for adding the edge beween two vertexes
+    def addEdge(self, fromVertex, toVertex):
+        # check if vertex is already present,
+        if fromVertex in self.vertex.keys():
+            self.vertex[fromVertex].append(toVertex)
+        else:
+            # else make a new vertex
+            self.vertex[fromVertex] = [toVertex]
+
+    def BFS(self, startVertex):
+        # Take a list for stoting already visited vertexes
+        visited = [False] * len(self.vertex)
+
+        # create a list to store all the vertexes for BFS
+        queue = []
+
+        # mark the source node as visited and enqueue it
+        visited[startVertex] = True
+        queue.append(startVertex)
+
+        while queue:
+            startVertex = queue.pop(0)
+            print(startVertex, end = ' ')
+
+            # mark all adjacent nodes as visited and print them
+            for i in self.vertex[startVertex]:
+                if visited[i] == False:
+                    queue.append(i)
+                    visited[i] = True
+
+if __name__ == '__main__':
+    g = Graph()
+    g.addEdge(0, 1)
+    g.addEdge(0, 2)
+    g.addEdge(1, 2)
+    g.addEdge(2, 0)
+    g.addEdge(2, 3)
+    g.addEdge(3, 3)
+
+    g.printGraph()
+    print('BFS:')
+    g.BFS(2)
+
+    # OUTPUT:
+    # 0  ->  1 -> 2
+    # 1  ->  2
+    # 2  ->  0 -> 3
+    # 3  ->  3
+    # BFS:
+    # 2 0 3 1

data_structures/Graph/P02_DepthFirstSearch.py

@@ -0,0 +1,61 @@
+# Author: OMKAR PATHAK
+
+class Graph():
+    def __init__(self):
+        self.vertex = {}
+
+    # for printing the Graph vertexes
+    def printGraph(self):
+        print(self.vertex)
+        for i in self.vertex.keys():
+            print(i,' -> ', ' -> '.join([str(j) for j in self.vertex[i]]))
+
+    # for adding the edge beween two vertexes
+    def addEdge(self, fromVertex, toVertex):
+        # check if vertex is already present,
+        if fromVertex in self.vertex.keys():
+            self.vertex[fromVertex].append(toVertex)
+        else:
+            # else make a new vertex
+            self.vertex[fromVertex] = [toVertex]
+
+    def DFS(self):
+        # visited array for storing already visited nodes
+        visited = [False] * len(self.vertex)
+
+        # call the recursive helper function
+        for i in range(len(self.vertex)):
+            if visited[i] == False:
+                self.DFSRec(i, visited)
+
+    def DFSRec(self, startVertex, visited):
+        # mark start vertex as visited
+        visited[startVertex] = True
+
+        print(startVertex, end = ' ')
+
+        # Recur for all the vertexes that are adjacent to this node
+        for i in self.vertex.keys():
+            if visited[i] == False:
+                self.DFSRec(i, visited)
+
+if __name__ == '__main__':
+    g = Graph()
+    g.addEdge(0, 1)
+    g.addEdge(0, 2)
+    g.addEdge(1, 2)
+    g.addEdge(2, 0)
+    g.addEdge(2, 3)
+    g.addEdge(3, 3)
+
+    g.printGraph()
+    print('DFS:')
+    g.DFS()
+
+    # OUTPUT:
+    # 0  ->  1 -> 2
+    # 1  ->  2
+    # 2  ->  0 -> 3
+    # 3  ->  3
+    # DFS:
+    # 0 1 2 3

data_structures/Stacks/Balanced_Parentheses.py

@@ -0,0 +1,27 @@
+# Author: OMKAR PATHAK
+
+import Stack
+
+def parseParenthesis(string):
+    balanced = 1
+    index = 0
+    myStack = Stack.Stack(len(string))
+    while (index < len(string)) and (balanced == 1):
+        check = string[index]
+        if check == '(':
+            myStack.push(check)
+        else:
+            if myStack.isEmpty():
+                balanced = 0
+            else:
+                myStack.pop()
+        index += 1
+
+    if balanced == 1 and myStack.isEmpty():
+        return True
+    else:
+        return False
+
+if __name__ == '__main__':
+    print(parseParenthesis('((()))'))   # True
+    print(parseParenthesis('((())'))    # False

data_structures/Stacks/Infix_To_Postfix_Conversion.py

@@ -0,0 +1,48 @@
+# Author: OMKAR PATHAK
+
+import Stack
+
+def isOperand(char):
+    return (ord(char) >= ord('a') and ord(char) <= ord('z')) or (ord(char) >= ord('A') and ord(char) <= ord('Z'))
+
+def precedence(char):
+    if char == '+' or char == '-':
+        return 1
+    elif char == '*' or char  == '/':
+        return 2
+    elif char == '^':
+        return 3
+    else:
+        return -1
+
+def infixToPostfix(myExp, myStack):
+    postFix = []
+    for i in range(len(myExp)):
+        if (isOperand(myExp[i])):
+            postFix.append(myExp[i])
+        elif(myExp[i] == '('):
+            myStack.push(myExp[i])
+        elif(myExp[i] == ')'):
+            topOperator = myStack.pop()
+            while(not myStack.isEmpty() and topOperator != '('):
+                postFix.append(topOperator)
+                topOperator = myStack.pop()
+        else:
+            while (not myStack.isEmpty()) and (precedence(myExp[i]) <= precedence(myStack.peek())):
+                postFix.append(myStack.pop())
+            myStack.push(myExp[i])
+
+    while(not myStack.isEmpty()):
+        postFix.append(myStack.pop())
+    return ' '.join(postFix)
+
+if __name__ == '__main__':
+    myExp = 'a+b*(c^d-e)^(f+g*h)-i'
+    myExp = [i for i in myExp]
+    print('Infix:',' '.join(myExp))
+    myStack = Stack.Stack(len(myExp))
+    print('Postfix:',infixToPostfix(myExp, myStack))
+
+    # OUTPUT:
+    # Infix: a + b * ( c ^ d - e ) ^ ( f + g * h ) - i
+    # Postfix: a b c d ^ e - f g h * + ^ * + i -

data_structures/Stacks/Stack.py

@@ -0,0 +1,50 @@
+# Author: OMKAR PATHAK
+
+class Stack(object):
+    def __init__(self, limit = 10):
+        self.stack = []
+        self.limit = limit
+
+    # for printing the stack contents
+    def __str__(self):
+        return ' '.join([str(i) for i in self.stack])
+
+    # for pushing an element on to the stack
+    def push(self, data):
+        if len(self.stack) >= self.limit:
+            print('Stack Overflow')
+        else:
+            self.stack.append(data)
+
+    # for popping the uppermost element
+    def pop(self):
+        if len(self.stack) <= 0:
+            return -1
+        else:
+            return self.stack.pop()
+
+    # for peeking the top-most element of the stack
+    def peek(self):
+        if len(self.stack) <= 0:
+            return -1
+        else:
+            return self.stack[len(self.stack) - 1]
+
+    # to check if stack is empty
+    def isEmpty(self):
+        return self.stack == []
+
+    # for checking the size of stack
+    def size(self):
+        return len(self.stack)
+
+if __name__ == '__main__':
+    myStack = Stack()
+    for i in range(10):
+        myStack.push(i)
+    print(myStack)
+    myStack.pop()           # popping the top element
+    print(myStack)
+    myStack.peek()          # printing the top element
+    myStack.isEmpty()
+    myStack.size()

sorts/bucket_sort.py

@@ -0,0 +1,56 @@
+#!/usr/bin/env python
+# Author: OMKAR PATHAK
+# This program will illustrate how to implement bucket sort algorithm
+
+# Wikipedia says: Bucket sort, or bin sort, is a sorting algorithm that works by distributing the
+# elements of an array into a number of buckets. Each bucket is then sorted individually, either using 
+# a different sorting algorithm, or by recursively applying the bucket sorting algorithm. It is a
+# distribution sort, and is a cousin of radix sort in the most to least significant digit flavour.
+# Bucket sort is a generalization of pigeonhole sort. Bucket sort can be implemented with comparisons
+# and therefore can also be considered a comparison sort algorithm. The computational complexity estimates
+# involve the number of buckets.
+
+#  Time Complexity of Solution:
+#  Best Case O(n); Average Case O(n); Worst Case O(n)
+
+from P26_InsertionSort import insertionSort
+import math
+
+DEFAULT_BUCKET_SIZE = 5
+
+def bucketSort(myList, bucketSize=DEFAULT_BUCKET_SIZE):
+    if(len(myList) == 0):
+        print('You don\'t have any elements in array!')
+
+    minValue = myList[0]
+    maxValue = myList[0]
+
+    # For finding minimum and maximum values
+    for i in range(0, len(myList)):
+        if myList[i] < minValue:
+            minValue = myList[i]
+        elif myList[i] > maxValue:
+            maxValue = myList[i]
+
+    # Initialize buckets
+    bucketCount = math.floor((maxValue - minValue) / bucketSize) + 1
+    buckets = []
+    for i in range(0, bucketCount):
+        buckets.append([])
+
+    # For putting values in buckets
+    for i in range(0, len(myList)):
+        buckets[math.floor((myList[i] - minValue) / bucketSize)].append(myList[i])
+
+    # Sort buckets and place back into input array
+    sortedArray = []
+    for i in range(0, len(buckets)):
+        insertionSort(buckets[i])
+        for j in range(0, len(buckets[i])):
+            sortedArray.append(buckets[i][j])
+
+    return sortedArray
+
+if __name__ == '__main__':
+    sortedArray = bucketSort([12, 23, 4, 5, 3, 2, 12, 81, 56, 95])
+    print(sortedArray)