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)) ` |

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) :__

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