Solving Leetcode Interviews in Seconds with AI: Count Number of Nice Subarrays
Introduction
In this blog post, we will explore how to solve the LeetCode problem "1248" using AI. LeetCode is a popular platform for preparing for coding interviews, and with the help of AI tools like Chatmagic, we can generate solutions quickly and efficiently - helping you pass the interviews and get the job offer without having to study for months.
Problem Statement
Given an array of integers nums and an integer k. A continuous subarray is called nice if there are k odd numbers on it. Return the number of nice sub-arrays. Example 1: Input: nums = [1,1,2,1,1], k = 3 Output: 2 Explanation: The only sub-arrays with 3 odd numbers are [1,1,2,1] and [1,2,1,1]. Example 2: Input: nums = [2,4,6], k = 1 Output: 0 Explanation: There are no odd numbers in the array. Example 3: Input: nums = [2,2,2,1,2,2,1,2,2,2], k = 2 Output: 16 Constraints: 1 <= nums.length <= 50000 1 <= nums[i] <= 10^5 1 <= k <= nums.length
Explanation
Here's a breakdown of the approach, followed by the Python code:
- Prefix Sum of Odd Counts: The core idea is to transform the problem into counting subarrays where the difference between the number of odd numbers encountered at two indices equals
k. We can maintain a prefix sum array where each element represents the cumulative count of odd numbers up to that index in the original array. - Hash Map for Efficient Counting: Use a hash map (dictionary in Python) to store the frequency of each prefix sum value. When we encounter a prefix sum
prefix_sum, we check how many timesprefix_sum - khas appeared before. This count gives us the number of subarrays ending at the current index with exactlykodd numbers. Sliding Window (Alternative but generally less efficient): While a sliding window approach could be used, the prefix sum + hashmap is generally more performant, especially when the number of even numbers is large, as it avoids repeated iterations and window adjustments.
Runtime & Storage Complexity: O(n), O(n)
Code
def numberOfSubarrays(nums, k):
"""
Counts the number of "nice" subarrays in the given array.
A "nice" subarray is defined as a continuous subarray containing exactly k odd numbers.
Args:
nums: A list of integers.
k: An integer representing the required number of odd numbers in a subarray.
Returns:
The number of nice subarrays in nums.
"""
prefix_sums = {0: 1} # Initialize with 0:1 to handle cases starting from index 0
current_sum = 0
count = 0
for num in nums:
if num % 2 != 0: # Check if the number is odd
current_sum += 1
diff = current_sum - k
if diff in prefix_sums:
count += prefix_sums[diff]
if current_sum in prefix_sums:
prefix_sums[current_sum] += 1
else:
prefix_sums[current_sum] = 1
return count