Dijkstra's algorithm in Python +info:https://jariasf.wordpress.com/2012/03/19/camino-mas-corto-algoritmo-de-dijkstra/

DijkstrasQueNoFunciona.py

# Dijkstra's algorithm for shortest paths
# David Eppstein, UC Irvine, 4 April 2002

# http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/117228
from priodict import priorityDictionary

def Dijkstra(G,start,end=None):
	D = {}	# dictionary of final distances
	P = {}	# dictionary of predecessors
	Q = priorityDictionary()   # est.dist. of non-final vert.
	Q[start] = 0
	
	for v in Q:
		D[v] = Q[v]
		if v == end: break
		
		for w in G[v]:
			vwLength = D[v] + G[v][w]
			if w in D:
				if vwLength < D[w]:
					raise ValueError, "Dijkstra: found better path to already-final vertex"
			elif w not in Q or vwLength < Q[w]:
				Q[w] = vwLength
				P[w] = v
	
	return (D,P)
			
def shortestPath(G,start,end):
	D,P = Dijkstra(G,start,end)
	Path = []
	while 1:
		Path.append(end)
		if end == start: break
		end = P[end]
	Path.reverse()
	return Path

priodict .py

# Priority dictionary using binary heaps
# David Eppstein, UC Irvine, 8 Mar 2002

from __future__ import generators

class priorityDictionary(dict):
    def __init__(self):
        '''Initialize priorityDictionary by creating binary heap
of pairs (value,key).  Note that changing or removing a dict entry will
not remove the old pair from the heap until it is found by smallest() or
until the heap is rebuilt.'''
        self.__heap = []
        dict.__init__(self)

    def smallest(self):
        '''Find smallest item after removing deleted items from heap.'''
        if len(self) == 0:
            raise IndexError, "smallest of empty priorityDictionary"
        heap = self.__heap
        while heap[0][1] not in self or self[heap[0][1]] != heap[0][0]:
            lastItem = heap.pop()
            insertionPoint = 0
            while 1:
                smallChild = 2*insertionPoint+1
                if smallChild+1 < len(heap) and \
                        heap[smallChild] > heap[smallChild+1]:
                    smallChild += 1
                if smallChild >= len(heap) or lastItem <= heap[smallChild]:
                    heap[insertionPoint] = lastItem
                    break
                heap[insertionPoint] = heap[smallChild]
                insertionPoint = smallChild
        return heap[0][1]
	
    def __iter__(self):
        '''Create destructive sorted iterator of priorityDictionary.'''
        def iterfn():
            while len(self) > 0:
                x = self.smallest()
                yield x
                del self[x]
        return iterfn()
	
    def __setitem__(self,key,val):
        '''Change value stored in dictionary and add corresponding
pair to heap.  Rebuilds the heap if the number of deleted items grows
too large, to avoid memory leakage.'''
        dict.__setitem__(self,key,val)
        heap = self.__heap
        if len(heap) > 2 * len(self):
            self.__heap = [(v,k) for k,v in self.iteritems()]
            self.__heap.sort()  # builtin sort likely faster than O(n) heapify
        else:
            newPair = (val,key)
            insertionPoint = len(heap)
            heap.append(None)
            while insertionPoint > 0 and \
                    newPair < heap[(insertionPoint-1)//2]:
                heap[insertionPoint] = heap[(insertionPoint-1)//2]
                insertionPoint = (insertionPoint-1)//2
            heap[insertionPoint] = newPair
	
    def setdefault(self,key,val):
        '''Reimplement setdefault to call our customized __setitem__.'''
        if key not in self:
            self[key] = val
        return self[key]

Pseudocodigo.txt

método Dijkstra(Grafo,origen):
2      creamos una cola de prioridad Q
3      agregamos origen a la cola de prioridad Q
4      mientras Q no este vacío:
5          sacamos un elemento de la cola Q llamado u
6          si u ya fue visitado continuo sacando elementos de Q    
7          marcamos como visitado u
8          para cada vértice v adyacente a u en el Grafo:
9              sea w el peso entre vértices ( u , v )  
10             si v no ah sido visitado:
11                Relajacion( u , v , w )

1  método Relajacion( actual , adyacente , peso ):
2      si distancia[ actual ] + peso < distancia[ adyacente ]
3         distancia[ adyacente ] = distancia[ actual ] + peso
4         agregamos adyacente a la cola de prioridad Q