Python - Speed up an A Star Pathfinding Algorithm

Question

I've coded my first slightly-complex algorithm, an implementation of the A Star Pathfinding algorithm. I followed some Python.org advice on implementing graphs so a dictionary contains all the nodes each node is linked too. Now, since this is all for a game, each node is really just a tile in a grid of nodes, hence how I'm working out the heuristic and my occasional reference to them.

Thanks to timeit I know that I can run this function successfully a little over one hundred times a second. Understandably this makes me a little uneasy, this is without any other 'game stuff' going on, like graphics or calculating game logic. So I'd love to see whether any of you can speed up my algorithm, I am completely unfamiliar with Cython or it's kin, I can't code a line of C.

Without any more rambling, here is my A Star function.

def aStar(self, graph, current, end):
    openList = []
    closedList = []
    path = []

    def retracePath(c):
        path.insert(0,c)
        if c.parent == None:
            return
        retracePath(c.parent)

    openList.append(current)
    while len(openList) is not 0:
        current = min(openList, key=lambda inst:inst.H)
        if current == end:
            return retracePath(current)
        openList.remove(current)
        closedList.append(current)
        for tile in graph[current]:
            if tile not in closedList:
                tile.H = (abs(end.x-tile.x)+abs(end.y-tile.y))*10 
                if tile not in openList:
                    openList.append(tile)
                tile.parent = current
    return path

Answer 1

An easy optimization is to use sets instead of lists for the open and closed sets.

openSet   = set()
closedSet = set()

This will make all of the in and not in tests O(1) instead of O(n).