# heapq library

# heap is one kind of a priority queue data structure.

# it is a binary tree implementation of priority queue

# where each values are ordered by the key.

# python has a built in library which is called heapq to work with heap data structures

# first lets import the heapq library.

import heapq

# lets see the all functions of heapq module.

print(dir(heapq))

# we can se that we have-

['__about__', '__all__', '__builtins__', '__cached__', '__doc__', '__file__',

'__loader__', '__name__', '__package__', '__spec__', '_heapify_max',

'_heappop_max', '_heapreplace_max', '_siftdown', '_siftdown_max', '_siftup',

'_siftup_max', 'heapify', 'heappop', 'heappush', 'heappushpop', 'heapreplace',

'merge', 'nlargest', 'nsmallest']

# lets see what the public methods do.

# first lets define a heap. It is basically a list of python.

heap = []

# now lets add couple of key-value pairs to our list using heappush() method

heapq.heappush(heap,(9,"a"))

heapq.heappush(heap,(0,"b"))

heapq.heappush(heap,(6,"c"))

heapq.heappush(heap,(8,"d"))

heapq.heappush(heap,(4,"e"))

heapq.heappush(heap,(2,"f"))

heapq.heappush(heap,(5,"g"))

print(heap)

# now lets delete the smallest key-value pair from the heap using heappop() method.

small = heapq.heappop(heap)

print(small)

print(heap)

# do that again-

small = heapq.heappop(heap)

print(small)

print(heap)

# now lets add a value to the heap and then pop a value from it.

# we can do that by heappushpop() method.

small=heapq.heappushpop(heap,(0,"p"))

print(small)

print(heap)

# do that again-

small=heapq.heappushpop(heap,(8,"t"))

print(small)

print(heap)

# we can do the same operation by heappreplace() method.

small=heapq.heappushpop(heap,(0,"k"))

print(small)

print(heap)

# do that again-

small=heapq.heappushpop(heap,(3,"n"))

print(small)

print(heap)

# the difference between heappushpop() and heappreplace() is:

# in heappushpop() the pop being performed after the push.

# in heappreplace() the pop being performed before the push (in other words, the new

# element cannot be returned as the smallest).

# we can transform a unordered list to a heap using heapify() method.

unordered = [(2,"k"),(0,"g"),(1,"f")]

heapq.heapify(unordered)

print(unordered)

# we can print first n-th largest pair from the heap using nlargest() method.

print(heapq.nlargest(3,heap))

# we can print first n-th smallest pair from the heap using nsmallest() method.

print(heapq.nsmallest(2,heap))

# we can merge two heap and make them one.

merged = list(heapq.merge(heap,unordered)) # NOTE that we have to convert it to list.

print(merged)