Done Precourse-2

Exercise_1.py

@@ -3,20 +3,33 @@
 
 # It returns location of x in given array arr  
 # if present, else returns -1 
+
+# Time complexity - > O(log(n))
+# Space Complexity -> O1
 def binarySearch(arr, l, r, x): 
-
+  low  = l
+  high = r
+  while low <= high:
+     mid = (low+high)//2
+     if arr[mid] == x:
+        return mid
+     if arr[mid] > x:
+        high = mid-1
+     else:
+        low = mid+1
+  return -1
   #write your code here
 
 
 
 # Test array 
 arr = [ 2, 3, 4, 10, 40 ] 
-x = 10
+x = 5
 
 # Function call 
 result = binarySearch(arr, 0, len(arr)-1, x) 
 
 if result != -1: 
-    print "Element is present at index % d" % result 
+    print("Element is present at index % d" % result)
 else: 
-    print "Element is not present in array"
+    print("Element is not present in array")

Exercise_2.py

@@ -1,19 +1,46 @@
 # Python program for implementation of Quicksort Sort 
 
 # give you explanation for the approach
+# Quick sort is a devide and conqure approach. basically we choose a starting point and then try to place it in 
+# it's correct position, i.e all the numbers on left are small and right are big.
+# Once we that number is in correct place, we devide the array into 2 half from the point (not including that poin)
+# and recursively start finding the correct position of 1 elment in the sub array and so on untill all elments are 
+# in it's correct position
 def partition(arr,low,high):
+
+    # This helper is used to arrange 1 number in it's corrrect positino and return the new index of that point
+    # the new index will become point for breaking the array into sub arrays
 
-
-    #write your code here
+    j = low
+    i = low -1
+    pivot = arr[high] #the number we are trying to correct place, let's pick last element
+
+    while j<=high:
+        if arr[j]<=pivot:
+            i+=1
+            tmp = arr[j]
+            arr[j] = arr[i]
+            arr[i] = tmp
+        j+=1
+    return i
+
 
 
 # Function to do Quick sort 
 def quickSort(arr,low,high): 
 
+    if low>=high:
+        return
+
+    pivot = partition(arr,0,high)
+
+    quickSort(arr, low, pivot - 1)
+    quickSort(arr, pivot+1, high)
+
     #write your code here
 
 # Driver code to test above 
-arr = [10, 7, 8, 9, 1, 5] 
+arr = [6,5,4,3,2,1] 
 n = len(arr) 
 quickSort(arr,0,n-1) 
 print ("Sorted array is:") 

Exercise_3.py

@@ -3,18 +3,20 @@ class Node:
 
     # Function to initialise the node object  
     def __init__(self, data):  
+        self.data = data
 
 class LinkedList: 
 
     def __init__(self): 
-
+        self.arr=[]
 
     def push(self, new_data): 
-
+        self.arr.append(Node(new_data))
 
     # Function to get the middle of  
     # the linked list 
     def printMiddle(self): 
+        print(self.arr[(len(self.arr)-1)//2].data)
 
 # Driver code 
 list1 = LinkedList() 

Exercise_4.py

@@ -1,11 +1,63 @@
 # Python program for implementation of MergeSort 
-def mergeSort(arr):
-
+
+# Merge sort is also a devide and conqure approach. But in this the arrays are sorted during merging
+# Basically we keep on deviding the arrays in half untill thhe last 2 elements are left 1 in left array 
+# and 2nd in right array. Then from that we start rebuilding the array by comparing the values in 
+# both subarray and assigning to the actual array
+def mergeSort(arr, left=0, right=None):
+    if right == None:
+        right = len(arr) - 1
+
+    if left < right:
+        mid = (left+right)//2
+        mergeSort(arr, left, mid)
+        mergeSort(arr, mid+1, right)
+
+        merge(arr, left, mid, right)
+
+
+def merge(arr, left, mid, right):
+    arr1 = []
+    arr2 = []
+
+    for i in range(left, mid+1):
+        arr1.append(arr[i])
+
+    for j in range(mid+1, right+1):
+        arr2.append(arr[j])
+
+    i = 0
+    j = 0
+    k=left
+    while i < len(arr1) and j < len(arr2):
+        if arr1[i] < arr2[j]:
+            arr[k]=arr1[i]
+            i+=1
+        else:
+            arr[k] = arr2[j]
+            j+=1
+        k+=1
+
+    if i != len(arr1):
+        while i < len(arr1):
+            arr[k] = arr1[i]
+            i+=1
+            k+=1
+
+    if j != len(arr2):
+        while j < len(arr2):
+            arr[k] = arr2[j]
+            j+=1
+            k+=1
+    return
+
+
+
   #write your code here
 
 # Code to print the list 
 def printList(arr): 
-
+    print(arr)
     #write your code here
 
 # driver code to test the above code 

Exercise_5.py

@@ -3,8 +3,44 @@
 # This function is same in both iterative and recursive
 def partition(arr, l, h):
   #write your code here
+  pivot = arr[h]
+  i=l-1
+  j=l
+
+  while j<=h:
+    if arr[j]<=pivot:
+      i+=1
+      tmp = arr[i]
+      arr[i] = arr[j]
+      arr[j] = tmp
+    j+=1
+  return i
 
 
 def quickSortIterative(arr, l, h):
   #write your code here
+  stack = [0] * len(arr)
+  stack.append(l)
+  stack.append(h)
+
+  while len(stack) > 0:
+    high = stack.pop()
+    low = stack.pop()
+    pivotIndex = partition(arr, low, high)
+
+    if pivotIndex - low >0:
+      stack.append(low)
+      stack.append(pivotIndex-1)
+
+    if high - pivotIndex > 0:
+      stack.append(pivotIndex+1)
+      stack.append(high)
 
+arr = [3, 2, 1, 4]
+n = len(arr) 
+quickSortIterative(arr,0,n-1) 
+print ("Sorted array is:") 
+for i in range(n): 
+    print ("%d" %arr[i]), 
+
+