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Merge pull request TheAlgorithms#97 from OmkarPathak/added_programs
Added Stack implementation and some traditional Stack problems
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‎data_structures/Graph/Graph.py‎

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# Author: OMKAR PATHAK
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# We can use Python's dictionary for constructing the graph
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classAdjacencyList(object):
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def__init__(self):
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self.List={}
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defaddEdge(self, fromVertex, toVertex):
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# check if vertex is already present
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iffromVertexinself.List.keys():
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self.List[fromVertex].append(toVertex)
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else:
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self.List[fromVertex] = [toVertex]
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defprintList(self):
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foriinself.List:
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print(i,'->',' -> '.join([str(j) forjinself.List[i]]))
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if__name__=='__main__':
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al=AdjacencyList()
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al.addEdge(0, 1)
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al.addEdge(0, 4)
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al.addEdge(4, 1)
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al.addEdge(4, 3)
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al.addEdge(1, 0)
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al.addEdge(1, 4)
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al.addEdge(1, 3)
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al.addEdge(1, 2)
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al.addEdge(2, 3)
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al.addEdge(3, 4)
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al.printList()
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# OUTPUT:
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# 0 -> 1 -> 4
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# 1 -> 0 -> 4 -> 3 -> 2
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# 2 -> 3
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# 3 -> 4
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# 4 -> 1 -> 3

‎data_structures/Graph/P01_BreadthFirstSearch.py‎

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

‎data_structures/Graph/P02_DepthFirstSearch.py‎

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# Author: OMKAR PATHAK
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classGraph():
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def__init__(self):
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self.vertex={}
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# for printing the Graph vertexes
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defprintGraph(self):
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print(self.vertex)
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foriinself.vertex.keys():
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print(i,' -> ', ' -> '.join([str(j) forjinself.vertex[i]]))
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# for adding the edge beween two vertexes
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defaddEdge(self, fromVertex, toVertex):
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# check if vertex is already present,
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iffromVertexinself.vertex.keys():
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self.vertex[fromVertex].append(toVertex)
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else:
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# else make a new vertex
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self.vertex[fromVertex] = [toVertex]
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defDFS(self):
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# visited array for storing already visited nodes
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visited= [False] *len(self.vertex)
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# call the recursive helper function
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foriinrange(len(self.vertex)):
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ifvisited[i] ==False:
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self.DFSRec(i, visited)
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defDFSRec(self, startVertex, visited):
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# mark start vertex as visited
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visited[startVertex] =True
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print(startVertex, end=' ')
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# Recur for all the vertexes that are adjacent to this node
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foriinself.vertex.keys():
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ifvisited[i] ==False:
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self.DFSRec(i, visited)
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if__name__=='__main__':
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g=Graph()
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g.addEdge(0, 1)
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g.addEdge(0, 2)
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g.addEdge(1, 2)
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g.addEdge(2, 0)
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g.addEdge(2, 3)
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g.addEdge(3, 3)
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g.printGraph()
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print('DFS:')
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g.DFS()
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# OUTPUT:
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# 0 -> 1 -> 2
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# 1 -> 2
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# 2 -> 0 -> 3
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# 3 -> 3
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# DFS:
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# 0 1 2 3

‎data_structures/Stacks/Balanced_Parentheses.py‎

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# Author: OMKAR PATHAK
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importStack
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defparseParenthesis(string):
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balanced=1
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index=0
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myStack=Stack.Stack(len(string))
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while (index<len(string)) and (balanced==1):
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check=string[index]
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ifcheck=='(':
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myStack.push(check)
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else:
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ifmyStack.isEmpty():
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balanced=0
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else:
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myStack.pop()
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index+=1
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ifbalanced==1andmyStack.isEmpty():
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returnTrue
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else:
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returnFalse
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if__name__=='__main__':
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print(parseParenthesis('((()))')) # True
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print(parseParenthesis('((())')) # False

‎data_structures/Stacks/Infix_To_Postfix_Conversion.py‎

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# Author: OMKAR PATHAK
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importStack
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defisOperand(char):
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return (ord(char) >=ord('a') andord(char) <=ord('z')) or (ord(char) >=ord('A') andord(char) <=ord('Z'))
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defprecedence(char):
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ifchar=='+'orchar=='-':
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return1
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elifchar=='*'orchar=='/':
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return2
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elifchar=='^':
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return3
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else:
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return-1
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definfixToPostfix(myExp, myStack):
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postFix= []
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foriinrange(len(myExp)):
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if (isOperand(myExp[i])):
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postFix.append(myExp[i])
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elif(myExp[i] =='('):
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myStack.push(myExp[i])
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elif(myExp[i] ==')'):
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topOperator=myStack.pop()
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while(notmyStack.isEmpty() andtopOperator!='('):
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postFix.append(topOperator)
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topOperator=myStack.pop()
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else:
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while (notmyStack.isEmpty()) and (precedence(myExp[i]) <=precedence(myStack.peek())):
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postFix.append(myStack.pop())
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myStack.push(myExp[i])
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while(notmyStack.isEmpty()):
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postFix.append(myStack.pop())
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return' '.join(postFix)
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if__name__=='__main__':
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myExp='a+b*(c^d-e)^(f+g*h)-i'
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myExp= [iforiinmyExp]
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print('Infix:',' '.join(myExp))
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myStack=Stack.Stack(len(myExp))
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print('Postfix:',infixToPostfix(myExp, myStack))
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# OUTPUT:
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# Infix: a + b * ( c ^ d - e ) ^ ( f + g * h ) - i
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# Postfix: a b c d ^ e - f g h * + ^ * + i -

‎data_structures/Stacks/Stack.py‎

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# Author: OMKAR PATHAK
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classStack(object):
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def__init__(self, limit=10):
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self.stack= []
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self.limit=limit
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# for printing the stack contents
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def__str__(self):
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return' '.join([str(i) foriinself.stack])
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# for pushing an element on to the stack
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defpush(self, data):
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iflen(self.stack) >=self.limit:
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print('Stack Overflow')
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else:
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self.stack.append(data)
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# for popping the uppermost element
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defpop(self):
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iflen(self.stack) <=0:
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return-1
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else:
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returnself.stack.pop()
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# for peeking the top-most element of the stack
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defpeek(self):
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iflen(self.stack) <=0:
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return-1
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else:
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returnself.stack[len(self.stack) -1]
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# to check if stack is empty
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defisEmpty(self):
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returnself.stack== []
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# for checking the size of stack
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defsize(self):
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returnlen(self.stack)
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if__name__=='__main__':
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myStack=Stack()
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foriinrange(10):
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myStack.push(i)
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print(myStack)
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myStack.pop() # popping the top element
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print(myStack)
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myStack.peek() # printing the top element
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myStack.isEmpty()
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myStack.size()

‎sorts/bucket_sort.py‎

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#!/usr/bin/env python
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# Author: OMKAR PATHAK
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# This program will illustrate how to implement bucket sort algorithm
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# Wikipedia says: Bucket sort, or bin sort, is a sorting algorithm that works by distributing the
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# elements of an array into a number of buckets. Each bucket is then sorted individually, either using
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# a different sorting algorithm, or by recursively applying the bucket sorting algorithm. It is a
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# distribution sort, and is a cousin of radix sort in the most to least significant digit flavour.
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# Bucket sort is a generalization of pigeonhole sort. Bucket sort can be implemented with comparisons
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# and therefore can also be considered a comparison sort algorithm. The computational complexity estimates
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# involve the number of buckets.
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# Time Complexity of Solution:
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# Best Case O(n); Average Case O(n); Worst Case O(n)
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fromP26_InsertionSortimportinsertionSort
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importmath
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DEFAULT_BUCKET_SIZE=5
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defbucketSort(myList, bucketSize=DEFAULT_BUCKET_SIZE):
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if(len(myList) ==0):
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print('You don\'t have any elements in array!')
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minValue=myList[0]
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maxValue=myList[0]
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# For finding minimum and maximum values
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foriinrange(0, len(myList)):
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ifmyList[i] <minValue:
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minValue=myList[i]
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elifmyList[i] >maxValue:
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maxValue=myList[i]
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# Initialize buckets
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bucketCount=math.floor((maxValue-minValue) /bucketSize) +1
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buckets= []
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foriinrange(0, bucketCount):
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buckets.append([])
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# For putting values in buckets
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foriinrange(0, len(myList)):
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buckets[math.floor((myList[i] -minValue) /bucketSize)].append(myList[i])
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# Sort buckets and place back into input array
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sortedArray= []
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foriinrange(0, len(buckets)):
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insertionSort(buckets[i])
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forjinrange(0, len(buckets[i])):
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sortedArray.append(buckets[i][j])
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returnsortedArray
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if__name__=='__main__':
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sortedArray=bucketSort([12, 23, 4, 5, 3, 2, 12, 81, 56, 95])
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print(sortedArray)

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