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What is the Most Efficient Way to Combine Sorted Lists in Python?

Mary-Kate Olsen
Release: 2024-10-21 20:57:02
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What is the Most Efficient Way to Combine Sorted Lists in Python?

Efficiently Combining Sorted Lists in Python

Combining multiple sorted lists into a single ordered list is a common task in Python programming. To achieve this, one might typically consider using the built-in sort() function. However, there exists a more efficient approach known as the merge algorithm.

The Merge Algorithm

The merge algorithm operates by recursively dividing the input lists into smaller subsets, sorting them, and then merging the results. This approach has a computational complexity of O(n log n), where n is the total number of elements in the combined list.

Implementing the merge algorithm in Python involves the following steps:

<code class="python">def merge(list1, list2):
    """Merge two sorted lists into a single sorted list."""
    result = []
    while list1 and list2:
        if list1[0] < list2[0]:
            result.append(list1[0])
            del list1[0]
        else:
            result.append(list2[0])
            del list2[0]
    result.extend(list1)
    result.extend(list2)
    return result</code>
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An Alternative Approach: The Heapq Module

Another efficient solution for combining sorted lists in Python is to use the merge function from the heapq module. This function was designed specifically for merging sorted iterables and has a time complexity of O(n), where n is the total number of elements.

The following code demonstrates how to use the heapq.merge() function:

<code class="python">import heapq

list1 = [1, 5, 8, 10, 50]
list2 = [3, 4, 29, 41, 45, 49]
result = list(heapq.merge(list1, list2))
print(result)  # Output: [1, 3, 4, 5, 8, 10, 29, 41, 45, 49, 50]</code>
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Conclusion

Whether implementing the merge algorithm or utilizing the heapq.merge() function, Python provides efficient solutions for combining sorted lists with minimal computational complexity.

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