Heap
Last updated
Last updated
heapqimplementation of the heap queue algorithm, also known as the priority queue algorithm
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, 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 followed by a separate call to .
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, is raised.
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]