Python Online Test

Your company is analyzing malware which targets numerical record files.

The malware uses a sliding window over the array of numbers in a file, and tries to match the following pattern:

T, -, -, X, -, -, -, T

Where the position ‘X' is compared to each position 'T'. The window is moved so 'X’ passes through all the values.

The malware has the following rules:

• If any of the ‘T' positions in the pattern are bigger or equal to 'X’ the malware replaces 'X' with 0.
• If the 'X' position in the pattern is near the left or right border and is missing a 'T' position neighbor, only the other side is considered.
• The malware finds all the positions first and only then sets them to 0.

For example, if the values in a record file are the following:

[1, 2, 0, 5, 0, 2, 4, 3, 3, 3]

The expected values after the malware runs are:

[1, 0, 0, 5, 0, 0, 0, 3, 3, 0]

In this example, number 4 was set to 0 because 5 is the bigger number.

Implement the simulate function so that the malware behavior is replicated for further study.

A user interface contains two types of user input controls: TextInput, which accepts all characters and NumericInput, which accepts only digits.

Implement the class TextInput that contains:

• Method add(self, character) - adds the given character to the current value
• Method get_value(self) - returns the current value

Implement the class NumericInput that:

• Inherits TextInput
• Overrides the add method so that each non-numeric character is ignored

For example, the following code should output "10":

input = NumericInput()
input.add("1")
input.add("a")
input.add("0")
print(input.get_value())

Implement the function find_roots to find the roots of the quadratic equation: ax² + bx + c = 0. The function should return a tuple containing roots in any order. If the equation has only one solution, the function should return that solution as both elements of the tuple. The equation will always have at least one solution.

The roots of the quadratic equation can be found with the following formula:

For example, find_roots(2, 10, 8) should return (-1, -4) or (-4, -1) as the roots of the equation 2x² + 10x + 8 = 0 are -1 and -4.

Binary search tree (BST) is a binary tree where the value of each node is larger or equal to the values in all the nodes in that node's left subtree and is smaller than the values in all the nodes in that node's right subtree.

Write a function that, efficiently with respect to time used, checks if a given binary search tree contains a given value.

For example, for the following tree:

• n1 (Value: 1, Left: null, Right: null)
• n2 (Value: 2, Left: n1, Right: n3)
• n3 (Value: 3, Left: null, Right: null)

Call to contains(n2, 3) should return True since a tree with root at n2 contains number 3.

As a part of the route planner, the route_exists method is used as a quick filter if the destination is reachable, before using more computationally intensive procedures for finding the optimal route.

The roads on the map are rasterized and produce a matrix of boolean values - True if the road is present or False if it is not. The roads in the matrix are connected only if the road is immediately left, right, below or above it.

Finish the route_exists method so that it returns True if the destination is reachable or False if it is not. The from_row and from_column parameters are the starting row and column in the map_matrix. The to_row and to_column are the destination row and column in the map_matrix. The map_matrix parameter is the above mentioned matrix produced from the map.

For example, for the given rasterized map, the code below should return True since the destination is reachable:

map_matrix = [
    [True, False, False],
    [True, True, False],
    [False, True, True]
];

route_exists(0, 0, 2, 2, map_matrix)

A TrainComposition is built by attaching and detaching wagons from the left and the right sides, efficiently with respect to time used.

For example, if we start by attaching wagon 7 from the left followed by attaching wagon 13, again from the left, we get a composition of two wagons (13 and 7 from left to right). Now the first wagon that can be detached from the right is 7 and the first that can be detached from the left is 13.

Implement a TrainComposition that models this problem.

Write a function that, when passed a list and a target sum, returns, efficiently with respect to time used, two distinct zero-based indices of any two of the numbers, whose sum is equal to the target sum. If there are no two numbers, the function should return None.

For example, find_two_sum([3, 1, 5, 7, 5, 9], 10) should return a single tuple containing any of the following pairs of indices:

• 0 and 3 (or 3 and 0) as 3 + 7 = 10
• 1 and 5 (or 5 and 1) as 1 + 9 = 10
• 2 and 4 (or 4 and 2) as 5 + 5 = 10

Implement the IceCreamMachine's scoops method so that it returns all combinations of one ingredient and one topping. If there are no ingredients or toppings, the method should return an empty list.

For example, IceCreamMachine(["vanilla", "chocolate"], ["chocolate sauce"]).scoops() should return [['vanilla', 'chocolate sauce'], ['chocolate', 'chocolate sauce']].

As part of a data processing pipeline, complete the implementation of the pipeline method:

• The pipeline method should accept a variable number of functions, and it should return a new function that accepts one parameter arg.
• The returned function should call the first function in pipeline with the parameter arg, and call the second function with the result of the first function.
• The returned function should continue calling each function in pipeline in order, following the same pattern, and return the value from the last function.

For example, calling pipeline(lambda x: x * 3, lambda x: x + 1, lambda x: x / 2), and then calling the returned function with 3 should return 5.0.

Implement the unique_names method. When passed two lists of names, it will return a list containing the names that appear in either or both lists. The returned list should have no duplicates.

For example, calling unique_names(['Ava', 'Emma', 'Olivia'], ['Olivia', 'Sophia', 'Emma']) should return a list containing Ava, Emma, Olivia, and Sophia in any order.

Implement function count_numbers that accepts a sorted list of unique integers and, efficiently with respect to time used, counts the number of list elements that are less than the parameter less_than.

For example, count_numbers([1, 3, 5, 7], 4) should return 2 because there are two list elements less than 4.

A playlist is considered a repeating playlist if any of the songs contain a reference to a previous song in the playlist. Otherwise, the playlist will end with the last song which points to None.

Implement a function is_in_repeating_playlist that, efficiently with respect to time used, returns true if a playlist is repeating or false if it is not.

For example, the following code prints "True" as both songs point to each other.

first = Song("Hello")
second = Song("Eye of the tiger")
    
first.next_song(second)
second.next_song(first)
    
print(first.is_in_repeating_playlist())

The LeagueTable class tracks the score of each player in a league. After each game, the player records their score with the record_result function. 

The player's rank in the league is calculated using the following logic:

1. The player with the highest score is ranked first (rank 1). The player with the lowest score is ranked last.
2. If two players are tied on score, then the player who has played the fewest games is ranked higher.
3. If two players are tied on score and number of games played, then the player who was first in the list of players is ranked higher.

Implement the player_rank function that returns the player at the given rank.

For example:

table = LeagueTable(['Mike', 'Chris', 'Arnold'])
table.record_result('Mike', 2)
table.record_result('Mike', 3)
table.record_result('Arnold', 5)
table.record_result('Chris', 5)
print(table.player_rank(1))

All players have the same score. However, Arnold and Chris have played fewer games than Mike, and as Chris is before Arnold in the list of players, he is ranked first. Therefore, the code above should display "Chris".

Implement a group_by_owners function that:

• Accepts a dictionary containing the file owner name for each file name.
• Returns a dictionary containing a list of file names for each owner name, in any order.

For example, for dictionary {'Input.txt': 'Randy', 'Code.py': 'Stan', 'Output.txt': 'Randy'} the group_by_owners function should return {'Randy': ['Input.txt', 'Output.txt'], 'Stan': ['Code.py']}.

A university's Office of Admission keeps track of student majors. Each student can have a single major. Below is an example of how their system stores students, majors, and how it manipulates them:

students = [("Allen Anderson", "Computer Science"),
            ("Edgar Einstein", "Engineering"),
            ("Farrah Finn", "Fine Arts")]
     
def add_new_student(students, name, major):
    students.append((name, major))

def update_student(students, index, name, major):
    students[index] = (name, major)

def find_students_by_name(students, name):
    return [student for student in students if name in student[0]]

def get_all_majors(students):
    return [student[1] for student in students]

What can be concluded from the code snippet above?