Appearance
question:# Task: Implement a Custom Sorting Algorithm with Custom Comparator Scenario You are tasked with implementing a custom sorting algorithm using a provided comparator function. The comparator function defines how to compare two elements and must be used with your sorting algorithm. Core Requirements Create a custom sorting function that accepts a list of elements and a comparator function. Your sorting function should be able to sort any list of elements based on the rules defined in the comparator function. Function Specifications You need to implement the following function: 1. `custom_sort(arr: list, comparator: Callable[[Any, Any], int]) -> list` Input - `arr` (list): The list of elements to be sorted. The elements can be of any type, depending on the comparator. - `comparator` (Callable[[Any, Any], int]): A comparator function that takes two arguments and returns a negative number if the first argument is less than the second, zero if they are equal, and a positive number if the first argument is greater. Output - Returns a list of elements sorted according to the comparator function. Constraints - The function should handle edge cases such as an empty list or lists with only one element. - The comparator function should be used to define the order of the elements. - Assume the comparator function will be provided and correctly implemented. Performance Requirements - The sorting algorithm should aim for an average time complexity of (O(n log n)) where `n` is the number of elements in the list. Example ```python # Custom comparator function for sorting numbers in descending order def descending_comparator(x, y): return y - x # Example usage arr = [5, 3, 8, 1, 2] sorted_arr = custom_sort(arr, descending_comparator) print(sorted_arr) # Output should be [8, 5, 3, 2, 1] # Custom comparator function for sorting strings by length def length_comparator(x, y): return len(x) - len(y) # Example usage arr = ["apple", "banana", "pear", "kiwi"] sorted_arr = custom_sort(arr, length_comparator) print(sorted_arr) # Output should be ["pear", "kiwi", "apple", "banana"] ``` # Explanation In this task, your custom sorting function should use the provided comparator to determine the order of elements in the list. The output should be a list of elements sorted according to the comparator's logic. Test cases must verify that the sorting adheres to the comparator's rules under different types and orders of input data.
answer:from typing import List, Callable, Any def custom_sort(arr: List[Any], comparator: Callable[[Any, Any], int]) -> List[Any]: Custom sort function that sorts an array based on a provided comparator. Parameters: arr (list): The list of elements to be sorted. comparator (function): A comparator function that takes two arguments and returns a negative number if the first argument is less than the second, zero if they are equal, and a positive number if the first argument is greater. Returns: list: Sorted list according to the comparator function. def merge_sort(arr): if len(arr) <= 1: return arr mid = len(arr) // 2 left = merge_sort(arr[:mid]) right = merge_sort(arr[mid:]) return merge(left, right) def merge(left, right): sorted_list = [] i = j = 0 while i < len(left) and j < len(right): if comparator(left[i], right[j]) <= 0: sorted_list.append(left[i]) i += 1 else: sorted_list.append(right[j]) j += 1 sorted_list.extend(left[i:]) sorted_list.extend(right[j:]) return sorted_list return merge_sort(arr)
question:# Coding Question: Merge Two Sorted Arrays **Scenario**: You are working on a project that requires combining data from two different sorted sources. Your task is to merge two sorted arrays into a single sorted array without using any additional libraries. This operation is critical for maintaining the overall data consistency and performance of the system. **Problem Statement**: Implement a function `merge_sorted_arrays` that takes two sorted arrays and returns a single sorted array by merging them. # Requirements: - **Input**: - Two sorted arrays of integers, `array1` and `array2`. - **Output**: - A single sorted array containing all elements from `array1` and `array2`. # Constraints: 1. Both input arrays are sorted in non-decreasing order. 2. The output array must be sorted in non-decreasing order. 3. The function should handle empty arrays gracefully. # Function Signature: ```python def merge_sorted_arrays(array1: list[int], array2: list[int]) -> list[int]: pass ``` # Implementation Details: Your function should handle various edge cases including: - Both arrays are empty. - One array is empty and the other is non-empty. - Both arrays contain elements. - Arrays of different lengths. # Examples: 1. **Example 1**: ```python array1 = [1, 3, 5] array2 = [2, 4, 6] assert merge_sorted_arrays(array1, array2) == [1, 2, 3, 4, 5, 6] ``` 2. **Example 2**: ```python array1 = [] array2 = [1, 2, 3] assert merge_sorted_arrays(array1, array2) == [1, 2, 3] ``` 3. **Example 3**: ```python array1 = [5, 10, 15] array2 = [10, 20, 30] assert merge_sorted_arrays(array1, array2) == [5, 10, 10, 15, 20, 30] ``` 4. **Example 4**: ```python array1 = [1, 2, 2] array2 = [2, 2, 3] assert merge_sorted_arrays(array1, array2) == [1, 2, 2, 2, 2, 3] ``` **Note**: Consider using a two-pointer technique to merge the arrays efficiently in terms of time complexity.
answer:def merge_sorted_arrays(array1: list[int], array2: list[int]) -> list[int]: Merges two sorted arrays into a single sorted array. Parameters: array1 (list of int): First sorted array. array2 (list of int): Second sorted array. Returns: list of int: Merged sorted array. merged_array = [] i = 0 j = 0 while i < len(array1) and j < len(array2): if array1[i] < array2[j]: merged_array.append(array1[i]) i += 1 else: merged_array.append(array2[j]) j += 1 while i < len(array1): merged_array.append(array1[i]) i += 1 while j < len(array2): merged_array.append(array2[j]) j += 1 return merged_array
question:# Context You are given a list of integers, and you need to find the maximum sum that can be obtained by summing up a subsequence of the list such that no two elements in the subsequence are adjacent in the original list. # Function Signature Write a function called `max_non_adjacent_sum` that takes in a list of integers and returns an integer. # Input * A list ( nums ) of integers. - ( 0 leq |nums| leq 10^5 ) - ( -10^4 leq text{nums}[i] leq 10^4 ) # Output * Returns an integer representing the maximum sum of a non-adjacent subsequence. # Constraints 1. Your implementation should strive for efficient time and space complexity. 2. Consider edge cases such as an empty list or a list with a single element. # Examples * `max_non_adjacent_sum([3, 2, 5, 10, 7])` should return `15`. * `max_non_adjacent_sum([-1, 2, 4, 6, -3, 2])` should return `10`. * `max_non_adjacent_sum([2, 1, 4, 9, 7])` should return `13`. * `max_non_adjacent_sum([5, 5, 10, 100, 10, 5])` should return `110`. # Implementation Ensure to handle edge cases appropriately and aim for clear and efficient code.
answer:def max_non_adjacent_sum(nums): Returns the maximum sum of a non-adjacent subsequence. Args: nums (list of int): Input list of integers. Returns: int: Maximum sum of a non-adjacent subsequence. if not nums: return 0 if len(nums) == 1: return max(0, nums[0]) include = 0 # Maximum sum including the current element exclude = 0 # Maximum sum excluding the current element for num in nums: new_exclude = max(include, exclude) include = exclude + num exclude = new_exclude return max(include, exclude)
question:# Scenario You are developing a data manipulation library designed to handle various data structures. The library currently supports basic operations such as adding or removing elements from lists, but it lacks the ability to perform advanced list transformations. Your task is to implement a function that efficiently flattens a nested list of arbitrary depth. # Problem Statement Implement a function `flatten_list(nested_list: List[Any]) -> List[Any]` that takes a nested list and returns a single flat list containing all the elements. The original order of elements must be preserved, and only the nesting structure should be removed. # Specifications * **Input**: A nested list `nested_list` which can contain elements of any type, including other lists, and is potentially deeply nested. * **Output**: A single flat list with all elements from the input list in the same order. * **Constraints**: * The nested list can have elements of various depths and data types. * The function should handle lists with up to 10^5 total elements efficiently. * **Performance**: Aim for a time complexity of O(n), where n is the total number of elements in the nested list. # Example ```python # Example 1 input_list = [1, [2, [3, 4]], 5] output_list = flatten_list(input_list) print(output_list) # Expected output: [1, 2, 3, 4, 5] # Example 2 input_list = [[['a'], 'b'], 'c', [[['d']]]] output_list = flatten_list(input_list) print(output_list) # Expected output: ['a', 'b', 'c', 'd'] # Example 3 input_list = [1, [2, [3, [4, [5, [6]]]]]] output_list = flatten_list(input_list) print(output_list) # Expected output: [1, 2, 3, 4, 5, 6] ``` # Bonus Enhance the function to support flattening generators or other iterable types, making it more flexible for different use cases.
answer:from typing import Any, List def flatten_list(nested_list: List[Any]) -> List[Any]: This function takes in a nested list and returns a single flat list containing all the elements. flat_list = [] def _flatten(inner_list): for element in inner_list: if isinstance(element, list): _flatten(element) else: flat_list.append(element) _flatten(nested_list) return flat_list