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# http://code.activestate.com/recipes/522995/
# https://gist.github.com/matteodellamico/4451520
# http://code.activestate.com/recipes/522995-priority-dict-a-priority-queue-with-updatable-prio/
# This is free and unencumbered software released into the public domain.
#
# Anyone is free to copy, modify, publish, use, compile, sell, or
# distribute this software, either in source code form or as a compiled
# binary, for any purpose, commercial or non-commercial, and by any
# means.
#
# In jurisdictions that recognize copyright laws, the author or authors
# of this software dedicate any and all copyright interest in the
# software to the public domain. We make this dedication for the benefit
# of the public at large and to the detriment of our heirs and
# successors. We intend this dedication to be an overt act of
# relinquishment in perpetuity of all present and future rights to this
# software under copyright law.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
# IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR
# OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
# ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
# OTHER DEALINGS IN THE SOFTWARE.
#
# For more information, please refer to <http://unlicense.org/>
# By Matteo Dell'Amico
from heapq import heapify, heappush, heappop
class priority_dict(dict):
"""Dictionary that can be used as a priority queue.
Keys of the dictionary are items to be put into the queue, and values
are their respective priorities. All dictionary methods work as expected.
The advantage over a standard heapq-based priority queue is
that priorities of items can be efficiently updated (amortized O(1))
using code as 'thedict[item] = new_priority.'
The 'smallest' method can be used to return the object with lowest
priority, and 'pop_smallest' also removes it.
The 'sorted_iter' method provides a destructive sorted iterator.
"""
def __init__(self, *args, **kwargs):
super(priority_dict, self).__init__(*args, **kwargs)
self._rebuild_heap()
def _rebuild_heap(self):
self._heap = [(v, k) for k, v in self.items()]
heapify(self._heap)
def smallest(self):
"""Return the item with the lowest priority.
Raises IndexError if the object is empty.
"""
heap = self._heap
v, k = heap[0]
while k not in self or self[k] != v:
heappop(heap)
v, k = heap[0]
return k
def pop_smallest(self):
"""Return the item with the lowest priority and remove it.
Raises IndexError if the object is empty.
"""
heap = self._heap
v, k = heappop(heap)
while k not in self or self[k] != v:
v, k = heappop(heap)
del self[k]
return k
def __setitem__(self, key, val):
# We are not going to remove the previous value from the heap,
# since this would have a cost O(n).
super(priority_dict, self).__setitem__(key, val)
if len(self._heap) < 2 * len(self):
heappush(self._heap, (val, key))
else:
# When the heap grows larger than 2 * len(self), we rebuild it
# from scratch to avoid wasting too much memory.
self._rebuild_heap()
def setdefault(self, key, val):
if key not in self:
self[key] = val
return val
return self[key]
def update(self, *args, **kwargs):
# Reimplementing dict.update is tricky -- see e.g.
# http://mail.python.org/pipermail/python-ideas/2007-May/000744.html
# We just rebuild the heap from scratch after passing to super.
super(priority_dict, self).update(*args, **kwargs)
self._rebuild_heap()
def sorted_iter(self):
"""Sorted iterator of the priority dictionary items.
Beware: this will destroy elements as they are returned.
"""
while self:
yield self.pop_smallest() |
