Heap queue (or heapq) in Python
Heap data structure is mainly used to represent a priority queue. In Python, it is available using the “heapq” module. The property of this data structure in Python is that each time the smallest heap element is popped(min-heap). Whenever elements are pushed or popped, heap structure is maintained. The heap[0] element also returns the smallest element each time. Let’s see various Operations on the heap in Python.
Creating a simple heap
The heapify(iterable):- This function is used to convert the iterable into a heap data structure. i.e. in heap order.
Python3
# importing "heapq" to implement heap queueimport heapq# initializing listli = [5, 7, 9, 1, 3]# using heapify to convert list into heapheapq.heapify(li)# printing created heapprint ("The created heap is : ",(list(li))) |
Output:
The created heap is : [1, 3, 9, 7, 5]
Appending and Popping Items Efficiently
- heappush(heap, ele): This function is used to insert the element mentioned in its arguments into a heap. The order is adjusted, so that heap structure is maintained.
- heappop(heap): This function is used to remove and return the smallest element from the heap. The order is adjusted, so that heap structure is maintained.
Python3
# importing "heapq" to implement heap queueimport heapq# initializing listli = [5, 7, 9, 1, 3]# using heapify to convert list into heapheapq.heapify(li)# printing created heapprint("The created heap is : ", end="")print(list(li))# using heappush() to push elements into heap# pushes 4heapq.heappush(li, 4)# printing modified heapprint("The modified heap after push is : ", end="")print(list(li))# using heappop() to pop smallest elementprint("The popped and smallest element is : ", end="")print(heapq.heappop(li)) |
Output :
The created heap is : [1, 3, 9, 7, 5] The modified heap after push is : [1, 3, 4, 7, 5, 9] The popped and smallest element is : 1
Appending and Popping simultaneously
- heappushpop(heap, ele):- This function combines the functioning of both push and pop operations in one statement, increasing efficiency. Heap order is maintained after this operation.
- heapreplace(heap, ele):- This function also inserts and pops elements in one statement, but it is different from the above function. In this, the element is first popped, then the element is pushed. i.e, the value larger than the pushed value can be returned. heapreplace() returns the smallest value originally in the heap regardless of the pushed element as opposed to heappushpop().
Python3
# importing "heapq" to implement heap queueimport heapq# initializing list 1li1 = [5, 1, 9, 4, 3]# initializing list 2li2 = [5, 7, 9, 4, 3]# using heapify() to convert list into heapheapq.heapify(li1)heapq.heapify(li2)# using heappushpop() to push and pop items simultaneously# pops 2print("The popped item using heappushpop() is : ", end="")print(heapq.heappushpop(li1, 2))# using heapreplace() to push and pop items simultaneously# pops 3print("The popped item using heapreplace() is : ", end="")print(heapq.heapreplace(li2, 2)) |
Output:
The popped item using heappushpop() is : 1 The popped item using heapreplace() is : 3
Find the largest and smallest elements from Heap in Python
- nlargest(k, iterable, key = fun): This function is used to return the k largest elements from the iterable specified and satisfy the key if mentioned.
- nsmallest(k, iterable, key = fun): This function is used to return the k smallest elements from the iterable specified and satisfy the key if mentioned.
Python3
# Python code to demonstrate working of# nlargest() and nsmallest()# importing "heapq" to implement heap queueimport heapq# initializing listli1 = [6, 7, 9, 4, 3, 5, 8, 10, 1]# using heapify() to convert list into heapheapq.heapify(li1)# using nlargest to print 3 largest numbers# prints 10, 9 and 8print("The 3 largest numbers in list are : ", end="")print(heapq.nlargest(3, li1))# using nsmallest to print 3 smallest numbers# prints 1, 3 and 4print("The 3 smallest numbers in list are : ", end="")print(heapq.nsmallest(3, li1)) |
Output :
The 3 largest numbers in list are : [10, 9, 8] The 3 smallest numbers in list are : [1, 3, 4]
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