Given two sorted arrays, the task is to merge them in a sorted manner.
Input : arr1 = [1, 3, 4, 5] arr2 = [2, 4, 6, 8] Output : arr3 = [1, 2, 3, 4, 4, 5, 6, 8] Input : arr1 = [5, 8, 9] arr2 = [4, 7, 8] Output : arr3 = [4, 5, 7, 8, 8, 9]
This problem has existing solution please refer Merge two sorted arrays link. We will solve this problem in python using heapq.merge() in a single line of code.
[1, 2, 3, 4, 4, 5, 6, 8]
Properties of heapq module ?
This module provides an implementation of the heap queue algorithm, also known as the priority queue algorithm.
To create a heap, use a list initialized to , or you can transform a populated list into a heap via function heapify().The following functions are provided:
- heapq.heappush(heap,item) : Push the value item onto the heap, maintaining the heap invariant.
- heapq.heappop(heap) : Pop and return the smallest item from the heap, maintaining the heap invariant. If the heap is empty, IndexError is raised. To access the smallest item without popping it, use heap.
- heapq.heappushpop(heap, item) : Push item on the heap, then pop and return the smallest item from the heap. The combined action runs more efficiently than heappush() followed by a separate call to heappop().
- heapq.heapify(x) : Transform list x into a heap, in-place, in linear time.
- heapq.merge(*iterables) : Merge multiple sorted inputs into a single sorted output (for example, merge timestamped entries from multiple log files). Returns an iterator over the sorted values.
- heapq in Python to print all elements in sorted order from row and column wise sorted matrix
- Heap queue (or heapq) in Python
- Python heapq to find K'th smallest element in a 2D array
- Generate all possible sorted arrays from alternate elements of two given sorted arrays
- Merge two sorted arrays in constant space using Min Heap
- Merge k sorted arrays | Set 2 (Different Sized Arrays)
- Merge two sorted arrays with O(1) extra space
- Merge two sorted arrays
- Merge K sorted arrays | Set 3 ( Using Divide and Conquer Approach )
- Merge k sorted arrays | Set 1
- Merge 3 Sorted Arrays
- Merge K sorted arrays of different sizes | ( Divide and Conquer Approach )
- Merge k sorted linked lists | Set 2 (Using Min Heap)
- Number of ways to merge two arrays such retaining order
- Merge K sorted linked lists | Set 1
- Sorted merge in one array
- Median of two sorted arrays of same size
- Union and Intersection of two sorted arrays
- Find the closest pair from two sorted arrays
- K-th Element of Two Sorted Arrays
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