Maximum Product Subarray LeetCode Solution

Problem – Maximum Product Subarray

Given an integer array nums, find a contiguous non-empty subarray within the array that has the largest product, and return the product.

The test cases are generated so that the answer will fit in a 32-bit integer.

A subarray is a contiguous subsequence of the array.

Example 1:

Input: nums = [2,3,-2,4]
Output: 6
Explanation: [2,3] has the largest product 6.

Example 2:

Input: nums = [-2,0,-1]
Output: 0
Explanation: The result cannot be 2, because [-2,-1] is not a subarray.

Constraints:

• 1 <= nums.length <= 2 * 104
• -10 <= nums[i] <= 10
• The product of any prefix or suffix of nums is guaranteed to fit in a 32-bit integer.

Maximum Product Subarray LeetCode Solution in Python

    def maxProduct(self, A):
        B = A[::-1]
        for i in range(1, len(A)):
            A[i] *= A[i - 1] or 1
            B[i] *= B[i - 1] or 1
        return max(A + B)

Maximum Product Subarray LeetCode Solution in C++

    int maxProduct(vector<int> A) {
        int n = A.size(), res = A[0], l = 0, r = 0;
        for (int i = 0; i < n; i++) {
            l =  (l ? l : 1) * A[i];
            r =  (r ? r : 1) * A[n - 1 - i];
            res = max(res, max(l, r));
        }
        return res;
    }

Maximum Product Subarray LeetCode Solution in Java

    public int maxProduct(int[] A) {
        int n = A.length, res = A[0], l = 0, r = 0;
        for (int i = 0; i < n; i++) {
            l =  (l == 0 ? 1 : l) * A[i];
            r =  (r == 0 ? 1 : r) * A[n - 1 - i];
            res = Math.max(res, Math.max(l, r));
        }
        return res;
    }

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