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().



In [1]:

    
from heapq import *

1 function

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[0].
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.heapreplace(heap, item)
Pop and return the smallest item from the heap, and also push the new item. The heap size doesn’t change. If the heap is empty, IndexError is raised. This one step operation is more efficient than a heappop() followed by heappush() and can be more appropriate when using a fixed-size heap. The pop/push combination always returns an element from the heap and replaces it with item. The value returned may be larger than the item added. If that isn’t desired, consider using heappushpop() instead. Its push/pop combination returns the smaller of the two values, leaving the larger value on the heap.
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.nlargest(n, iterable[, key])
Return a list with the n largest elements from the dataset defined by iterable. key, if provided, specifies a function of one argument that is used to extract a comparison key from each element in the iterable: key=str.lower Equivalent to: sorted(iterable, key=key, reverse=True)[:n]
heapq.nsmallest(n, iterable[, key])
Return a list with the n smallest elements from the dataset defined by iterable. key, if provided, specifies a function of one argument that is used to extract a comparison key from each element in the iterable: key=str.lower Equivalent to: sorted(iterable, key=key)[:n]

2 heapq exmaple



In [16]:

    
h = [2, 1, 4,9,7,6]
heapify(h)
print h









    



[1, 2, 4, 9, 7, 6]



In [19]:

    
h = []
heappush(h, (5, 'write code'))
heappush(h, (7, 'release product'))
heappush(h, (1, 'write spec'))
heappush(h, (3, 'create tests'))



In [22]:

    
heapify(h)
h[0]









    Out[22]:





(1, 'write spec')



In [23]:

    
heappop(h)









    Out[23]:





(1, 'write spec')



In [27]:

    
heappushpop(h,(4,'gaufung'))









    Out[27]:





(3, 'create tests')



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