How to use the networkit.distance function in networkit

def runProbGroup(probGroup):
    global graph, outLock, verbose, outFile

    (source, targets) = probGroup
    if len(targets) == 1:
        dijk = nk.distance.Dijkstra(graph, source, target=targets[0])
    else:
        dijk = nk.distance.Dijkstra(graph, source)

    dijk.run()

    outLock.acquire()
    for target in targets:
        path = dijk.getPath(target)
        outFile.write("{}\n".format(" ".join([str(x) for x in path])))
    outLock.release()

def runProbGroup(probGroup):
    global graph, outLock, verbose, outFile

    (source, targets) = probGroup
    if len(targets) == 1:
        dijk = nk.distance.Dijkstra(graph, source, target=targets[0])
    else:
        dijk = nk.distance.Dijkstra(graph, source)

    dijk.run()

    outLock.acquire()
    for target in targets:
        path = dijk.getPath(target)
        outFile.write("{}\n".format(" ".join([str(x) for x in path])))
    outLock.release()

def _get_pairwise_sp(self, source, target):
        return nk.distance.BidirectionalDijkstra(self.G, source, target).run().getDistance()

def run(self, G):
		return networkit.distance.ApproxNeighborhoodFunction(G).run().getNeighborhoodFunction()

def run(self, G):
		return networkit.distance.ApproxHopPlot(G).run().getHopPlot()

def run(self, G):
		return networkit.distance.Diameter(G, networkit.distance.DiameterAlgo.estimatedRange, error=0.1).run()

def run(self, G):
		return networkit.distance.Diameter(G, networkit.distance.DiameterAlgo.exact).run()

def run(self, G):
		return networkit.distance.EffectiveDiameter(G).run().getEffectiveDiameter()

def run(self, G):
		return networkit.distance.EffectiveDiameterApproximation(G).run().getEffectiveDiameter()

def run(self, G):
		return networkit.distance.NeighborhoodFunction(G).run().getNeighborhoodFunction()