Kortste-padalgoritme van Dijkstra

import heapq
from functools import total_ordering

@total_ordering
class SpecialSorted:

    def __init__(self, element, value):
        self.element = element
        self.value = value

    def __eq__(self, other):
        return self.value == other.value

    def __ne__(self, other):
        return self.value != other.value

    def __lt__(self, other):
        return self.value < other.value

class PriorityQueue:

    def __init__(self, sortkey = lambda x : x):
        self.content = []
        self.sortkey = sortkey

    def add(self, item):
        heapq.heappush(self.content, SpecialSorted(item, self.sortkey(item)))

    def peek(self):
        return self.content[0].element if self.content else None

    def poll(self):
        return heapq.heappop(self.content).element if len(self.content) > 0 else None

    def is_empty(self):
        return len(self.content) == 0

    def __str__(self):
        return str(heapq.nsmallest(len(self.content), [item.element for item in self.content]))

Je kunt zo vaak indienen als je wenst. Er wordt enkel rekening gehouden met je laatst ingediende oplossing.

Kortste-padalgoritme van Dijkstra

Python sandbox