Given two sorted arrays, the task is to merge them in a sorted manner.

Examples:

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.

`# Function to merge two sorted arrays ` `from` `heapq ` `import` `merge ` ` ` `def` `mergeArray(arr1,arr2): ` ` ` `return` `list` `(merge(arr1, arr2)) ` ` ` `# Driver function ` `if` `__name__ ` `=` `=` `"__main__"` `: ` ` ` `arr1 ` `=` `[` `1` `,` `3` `,` `4` `,` `5` `] ` ` ` `arr2 ` `=` `[` `2` `,` `4` `,` `6` `,` `8` `] ` ` ` `print` `mergeArray(arr1, arr2) ` |

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Output:

[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:

Push the value item onto the heap, maintaining the heap invariant.__heapq.heappush(heap,item) :__Pop and return the smallest item from the heap, maintaining the heap invariant. If the heap is empty,__heapq.heappop(heap) :__**IndexError**is raised. To access the smallest item without popping it, use heap[0].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.heappushpop(heap, item) :__Transform list x into a heap, in-place, in linear time.__heapq.heapify(x) :__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.merge(*iterables) :__- 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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