Merging Sorted Arrays in Python: Best Practices and Optimal Solutions

Learn how to effectively merge sorted arrays in Python while adhering to best practices, optimizing your solution for potential pitfalls.
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Merging Sorted Arrays in Python: A Beginner's Guide

Merging sorted arrays is a common problem seen in algorithm challenges, particularly on platforms like LeetCode. It's essential to understand the requirements and utilize good practices to create efficient and functional code. In this article, we will explore a straightforward yet effective way to merge two sorted integer arrays, addressing common pitfalls that beginners may encounter.

Understanding the Problem

You are tasked with merging two integer arrays, nums1 and nums2, that are already sorted in non-decreasing order. The catch is that the result must be stored inside nums1, which has sufficient space to hold both input arrays (m + n length), where:

m is the number of elements in nums1

n is the number of elements in nums2

Example Scenario

Given the following input:

[[See Video to Reveal this Text or Code Snippet]]

Expected Output

After merging, nums1 should be:

[[See Video to Reveal this Text or Code Snippet]]

Common Pitfall with Merging Arrays

A common mistake beginners make is trying to replace the nums1 variable with a new sorted list instead of modifying it in place. A typical approach might look like this:

[[See Video to Reveal this Text or Code Snippet]]

Why This Fails

When using the sorted() function like above, you create a new list rather than modifying nums1 directly. This does not satisfy the problem's requirement to alter the original nums1 in place. Here’s an illustration:

[[See Video to Reveal this Text or Code Snippet]]

A Correct Approach to Merge Sorted Arrays

To correctly merge the arrays in place, utilize list methods such as pop() or append() instead of the sorted() function. Here’s an example solution that adheres to the requirement:

[[See Video to Reveal this Text or Code Snippet]]

Explanation of the Code

Pointers Initialization: Two pointers are initialized, i for nums1 and j for nums2, starting from the last valid elements.

Merging in Reverse: By comparing elements from the end of each array, we place the larger element at the back of nums1. This eliminates the need for extra space.

Handling Remaining Elements: If any elements remain in nums2, we copy them directly into nums1.

Conclusion

Merging sorted arrays may seem simple, but adhering to best practices is crucial for functionality and efficiency. Always remember to modify the original array in place without creating new lists, as demonstrated above. By applying these strategies, you’ll be well on your way to mastering algorithm challenges like the one on LeetCode.

Happy coding!