chat

🔍

question:You are provided with the implementation of a singly linked list and two functions, `remove_dups` and `remove_dups_without_set`, for removing duplicate elements from the list. Your task is to build upon this functionality to solve the following problem: # Task: Implement a function `remove_dups_from_unsorted_list(head, use_set=True)` that removes duplicates from an unsorted linked list. The function should use `remove_dups` if `use_set` is True, and `remove_dups_without_set` otherwise. # Function Signature: ```python def remove_dups_from_unsorted_list(head: Node, use_set: bool = True) -> Node: pass ``` # Input: * `head`: A pointer/reference to the head of the singly linked list. * `use_set`: A boolean value that indicates which removal method to use - `True` for `remove_dups` and `False` for `remove_dups_without_set`. # Output: * The head of the modified linked list with duplicates removed. # Example: ```python # Input list: A -> A -> B -> C -> D -> C -> F -> G a1 = Node("A") a2 = Node("A") b = Node("B") c1 = Node("C") d = Node("D") c2 = Node("C") f = Node("F") g = Node("G") a1.next = a2 a2.next = b b.next = c1 c1.next = d d.next = c2 c2.next = f f.next = g new_head = remove_dups_from_unsorted_list(a1, use_set=True) print_linked_list(new_head) # Expected Output: A -> B -> C -> D -> F -> G ``` # Constraints: * The linked list contains at most 10^4 elements. * Node values are unique strings with lengths between 1 and 100. # Notes: * The function should handle all edge cases efficiently. * Ensure proper memory management and pointer updates to maintain the structural integrity of the linked list.

answer:class Node: def __init__(self, value): self.value = value self.next = None def remove_dups(head): if not head: return head node_set = set() current = head node_set.add(current.value) while current.next: if current.next.value in node_set: current.next = current.next.next else: node_set.add(current.next.value) current = current.next return head def remove_dups_without_set(head): if not head: return head current = head while current: runner = current while runner.next: if runner.next.value == current.value: runner.next = runner.next.next else: runner = runner.next current = current.next return head def remove_dups_from_unsorted_list(head: Node, use_set: bool = True) -> Node: if use_set: return remove_dups(head) else: return remove_dups_without_set(head)

question:Implement a Binary Search Tree (BST) to support the following operations: * Insert a value into the BST. * Search for a value in the BST. * Delete a value from the BST. * Check if the BST is balanced. # Constraints * Nodes will only contain integer values. * The BST should not allow duplicate values. Functions to Implement ```python class BST: def __init__(self): # Initialize an empty BST pass def insert(self, val: int) -> None: # Insert val into the BST. If val already exists, it should not be inserted again. pass def search(self, val: int) -> bool: # Search for val in the BST and return True if found, otherwise False. pass def delete(self, val: int) -> None: # Delete val from the BST. If val does not exist, do nothing. pass def is_balanced(self) -> bool: # Return True if the BST is balanced, otherwise False. # A balanced tree is defined here as a tree where the height of two subtrees of every node never differs by more than 1. pass ``` # Example ```python # Example Usage: bst = BST() bst.insert(10) bst.insert(5) bst.insert(15) bst.insert(3) bst.insert(7) assert bst.search(10) == True assert bst.search(6) == False bst.delete(10) assert bst.search(10) == False assert bst.is_balanced() == True ``` **Performance Requirements**: * Your solution should aim to maintain average case time complexity of O(log n) for insert, search, and delete operations. Ensure the `is_balanced` operation runs efficiently. # Additional Notes * Focus on correctly managing pointers and edge cases. * Thoroughly test with balanced and unbalanced tree scenarios.

answer:class TreeNode: def __init__(self, val=0): self.val = val self.left = None self.right = None class BST: def __init__(self): self.root = None def insert(self, val: int) -> None: if not self.root: self.root = TreeNode(val) else: self._insert(self.root, val) def _insert(self, node, val): if val < node.val: if node.left: self._insert(node.left, val) else: node.left = TreeNode(val) elif val > node.val: if node.right: self._insert(node.right, val) else: node.right = TreeNode(val) def search(self, val: int) -> bool: return self._search(self.root, val) def _search(self, node, val): if not node: return False if node.val == val: return True elif val < node.val: return self._search(node.left, val) else: return self._search(node.right, val) def delete(self, val: int) -> None: self.root = self._delete(self.root, val) def _delete(self, node, val): if not node: return node if val < node.val: node.left = self._delete(node.left, val) elif val > node.val: node.right = self._delete(node.right, val) else: if not node.left: return node.right elif not node.right: return node.left temp = self._find_min(node.right) node.val = temp.val node.right = self._delete(node.right, temp.val) return node def _find_min(self, node): while node.left: node = node.left return node def is_balanced(self) -> bool: def height_and_balance(node): if not node: return 0, True left_height, left_balanced = height_and_balance(node.left) right_height, right_balanced = height_and_balance(node.right) balanced = left_balanced and right_balanced and abs(left_height - right_height) <= 1 return max(left_height, right_height) + 1, balanced _, is_bal = height_and_balance(self.root) return is_bal

question:Next Prime Number Generator Context Given the fundamental concept of checking for a prime number, let's extend this concept to generate the next prime number after a given integer `m`. Task Write a function `next_prime_after(m)` that takes an integer `m` and returns the smallest prime number greater than `m`. Input and Output Formats - Input: - An integer `m` (1 ≤ m ≤ 10^6) - Output: - An integer representing the next prime number after `m` Function Signature ```python def next_prime_after(m: int) -> int: pass ``` Constraints - Your function should be efficient and capable of handling the upper limits within a reasonable time frame. Example ```python print(next_prime_after(10)) # Output: 11 print(next_prime_after(14)) # Output: 17 ``` Make sure to handle edge cases efficiently and avoid unnecessary computations.

answer:def is_prime(n): if n <= 1: return False if n <= 3: return True if n % 2 == 0 or n % 3 == 0: return False i = 5 while i * i <= n: if n % i == 0 or n % (i + 2) == 0: return False i += 6 return True def next_prime_after(m: int) -> int: num = m + 1 while not is_prime(num): num += 1 return num

question:Scenario You are developing a software for a new programming language that supports base conversion of numbers. To ease the developers, you must provide functions that can convert an integer to any base between 2 and 36, and vice versa. Problem Statement Implement two functions: 1. `convert_to_base(num, base)`: - **Input**: An integer `num` and a base `base` (2 <= base <= 36). - **Output**: A string representing the number in the given base. 2. `convert_from_base(str_num, base)`: - **Input**: A string `str_num` representing a number in a certain base, and a base `base` (2 <= base <= 36). - **Output**: An integer representing the decimal equivalent of the given number. Function Signatures ```python def convert_to_base(num: int, base: int) -> str: pass def convert_from_base(str_num: str, base: int) -> int: pass ``` Example Usage ```python print(convert_to_base(5, 2)) # Output: '101' print(convert_to_base(-27, 16)) # Output: '-1B' print(convert_from_base('101', 2)) # Output: 5 print(convert_from_base('1B', 16)) # Output: 27 ``` Constraints and Considerations * The base `base` will always be between 2 and 36 inclusive. * The functions should handle edge cases such as converting zero. * The `convert_to_base` function should manage negative numbers correctly. * Performance should be optimized for large numbers.

answer:def convert_to_base(num: int, base: int) -> str: Converts an integer 'num' to its string representation in a specified 'base'. if base < 2 or base > 36: raise ValueError("Base must be between 2 and 36.") if num == 0: return '0' digits = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ" is_negative = num < 0 num = abs(num) result = [] while num: result.append(digits[num % base]) num = num // base if is_negative: result.append('-') result.reverse() return ''.join(result) def convert_from_base(str_num: str, base: int) -> int: Converts a string representation of a number 'str_num' in a specified 'base' to its decimal (base-10) integer equivalent. if base < 2 or base > 36: raise ValueError("Base must be between 2 and 36.") digits = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ" str_num = str_num.upper().strip() is_negative = str_num[0] == '-' if is_negative: str_num = str_num[1:] num = 0 for char in str_num: num = num * base + digits.index(char) return -num if is_negative else num