You are given a sequence of distinct integers. Your task is to construct a Binary Search Tree (BST) using the standard insertion rule:
After constructing the BST, instead of performing a standard preorder traversal (Root → Left → Right), you must implement a Parity-Based Preorder Traversal defined as follows:
At each node during traversal:
1
Root -> Right -> Left
1
Root → Left → Right
This means that the traversal order dynamically changes depending on whether the current node contains an even or odd value.
The first line contains an integer n — the number of elements in the BST.
The second line contains n distinct integers.
Input
1
2
7
50 30 70 20 40 60 80
Output
1
50 70 80 60 30 40 20
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
# --FIXED PART - DO NOT EDIT ANY THINGS HERE--
# --START FIXED PART--------------------------
import sys
# --END FIXED PART--------------------------
# --SYSTEM MODULES - @STUDENT: IMPORT SYSTEM MODULES HERE:
# --YOUR-OWN MODULES - @STUDENT: IMPORT YOUR-OWN MODULES HERE:
# from <fileName> import <className>
# For example, the file Node.py contains a class named Node,
# The statement to import class Node is: from Node import Node
# --Change the name of input and output file based on practical paper
input_file = "input.txt"
output_file = "output.txt"
# --VARIABLES - @STUDENT: DECLARE YOUR GLOBAL VARIABLES HERE:
# --ALGORITHM - @STUDENT: ADD YOUR-OWN CLASS OR METHODS HERE (IF YOU NEED):
# --FIXED PART - DO NOT EDIT ANY THINGS HERE--
# --This part is used for Automated Marking Software
# --START FIXED PART--------------------------
def set_file():
global input_file, output_file
length = len(sys.argv)
input_file = input_file if length < 2 else sys.argv[1]
output_file = output_file if length < 2 else sys.argv[2]
all_lines_of_input = ""
result_for_output = ""
def read_file():
global input_file, all_lines_of_input # import more global variables your own (if you need)
with open(input_file, 'r') as file:
all_lines_of_input = file.readlines()
# --START FIXED PART--------------------------
def solve():
global all_lines_of_input, result_for_output # import more global variables your own (if you need)
result_for_output = ""
# --END FIXED PART--------------------------
# ALGORITHM - @STUDENT: ADD YOUR CODE HERE:
# --START FIXED PART--------------------------
def print_result():
global output_file, result_for_output # import more global variables your own (if you need)
with open(output_file, 'w') as file:
# --END FIXED PART--------------------------
# ALGORITHM - @STUDENT: ADD YOUR CODE HERE:
file.write(result_for_output)
# --START FIXED PART--------------------------
if __name__ == "__main__":
set_file()
read_file()
solve()
print_result()
# --END FIXED PART--------------------------
Add this inside:
1
2
3
4
5
6
# --ALGORITHM
class Node:
def __init__(self, value):
self.value = value
self.left = None
self.right = None
1
2
3
4
5
6
7
8
9
10
def insert(root, value):
if root is None:
return Node(value)
if value < root.value:
root.left = insert(root.left, value)
else:
root.right = insert(root.right, value)
return root
1
2
3
4
5
6
7
8
9
10
11
12
def parityPreorder(root, result):
if root is None:
return
result.append(str(root.value))
if root.value % 2 == 0:
parityPreorder(root.right, result)
parityPreorder(root.left, result)
else:
parityPreorder(root.left, result)
parityPreorder(root.right, result)
Replace:
1
# ALGORITHM - @STUDENT: ADD YOUR CODE HERE:
with:
1
2
3
4
5
6
7
8
9
10
11
12
13
14
lines = all_lines_of_input
n = int(lines[0].strip())
values = list(map(int, lines[1].split()))
root = None
for v in values:
root = insert(root, v)
result = []
parityPreorder(root, result)
result_for_output = " ".join(result)
1
2
7
50 30 70 20 40 60 80
Implement an Enhanced Binary Search Tree (BST) that is capable of:
In real-world systems such as:
Duplicate numeric values frequently occur.
A traditional BST typically does not handle duplicates efficiently.
In this assignment, instead of inserting duplicate values as separate nodes, you must:
Store only one node per unique value Maintain an additional field called: count
The input consists of:
Example Input:
Format
1
<command> <value>
1
2
3
4
Insert 50 30 70 30 90 70 20 30 60 80 70
Delete 30 70 100
Search 60
Range 30 80
1
value(count)
1
20(1) 30(3) 50(1) 60(1) 70(3) 80(1) 90(1)
Deletion Rules:
Example:
1
Found: 60(1)
or
1
Not Found
Return all nodes such that:
1
L ≤ value ≤ R
Format:
1
value(count)
Example:
1
30(2) 50(1) 60(1) 70(2) 80(1)
1
2
3
4
Insert 50 30 70 30 90 70 20 30 60 80 70
Delete 30 70 100
Search 60
Range 30 80
1
2
3
4
5
6
7
8
9
10
11
In-order 20(1) 30(3) 50(1) 60(1) 70(3) 80(1) 90(1)
---Deletion---
Value 100 not found
20(1) 30(2) 50(1) 60(1) 70(2) 80(1) 90(1)
---Search---
Found: 60(1)
---Range---
From 30 to 80: 30(2) 50(1) 60(1) 70(2) 80(1)