Hi all,
This is my first thread on Daniweb!. I was wondering if someone would help nudge me in the right direction on this one. I'm new to python, been using it for about 6 months or so trying to develop a network simulator for school. This is not an assignment for a class, there is no grade tied to it, it's a bit of research I'm involved in.
I was tasked with writing a network simulator that would eventually be used to simulate peer-to-peer networks for traffic research. Basically the script reads in a network topology file generated by BRITE (a network topology generator written in java/c++) and creates nodes and edges based on this information. The script does this just fine.
The next step sets up the routing table so all the nodes in the network can start talking to each other. Whenever I initialize my routing tables, I add routing table entries to the node's incoming routes list. The node then update's it's list as it would normally, using whatever metric to judge which routes to change. Because the list, the node's routing table, should be empty, it should add the contents of the incoming routes list to the node's routing table.
Each node has three lists of routing table entries: the one that represents it's actual routing table, the one that represents outgoing route changes, and the one that represents incoming route changes. Each routing table entry is a tuple representing where it came from, the route, the next_hop (via), and the cost. When I initialize the lists, though, they not only share the same values (all 3 lists per node), but every node that I initialize shares those values, so when I change one list it changes everywhere. This smacks of a shared memory address, but I fear I don't know enough python to figure out whats up. I'll post the code in the thread, as well as the graph input file.
If anyone could point me in the right direction, even insofar as a text to read to find the answer myself, I'd be very grateful.
Thanks for reading.
Here's the code!
class node(dict):
""" Node class, contains edge list, node name, and other node info
"""
def __init__(self, iD, xPos, yPos, InDeg, OutDeg, ASId, Type, EdgeList = None):
""" Initialize everything, likely read in from a file
"""
self["nodeData"] = {
"id" : iD,
"xpos" : xPos,
"ypos" : yPos,
"inDeg" : InDeg,
"outDeg" : OutDeg,
"ASid" : ASId,
"type" : Type
}
if EdgeList is None:
self["edgeList"] = []
else:
self["edgeList"] = EdgeList
self["incRTE"] = None#RTable()
self["outRTE"] = None#RTable()
self["myRTable"] = None#RTable()
def tick(self, number = 1):
""" Either tick once, or tick number times
"""
#thisTickDo = self.msgQ.pop(0)
#testext = thisTickDo.getMessage()
#print testext
#while number > 0:
#Do tick things here
# number = number - 1
def addEdge(self, target):
""" Appends the edge to the end of edgeList. This may be extended to order the edges
on insert.
"""
li = target
self["edgeList"].append(li)
def initRTable(self):
if self["incRTE"] is None:
self["incRTE"] = RTable()
for curr in self["edgeList"]:
foo = rtEntry(int(curr["to"]), int(self["nodeData"]["id"]), int(curr["length"]), int(curr["from"]))
self["incRTE"].addRTE(foo)
def updateRTable(self):
if self["outRTE"] is None:
self["outRTE"] = RTable()
if self["incRTE"] is None:
self["incRTE"] = RTable()
for curr1 in self["incRTE"]:
if len(self["myRTable"]) is 0:
self["myRTable"].addRTE(curr1)
else:
for curr2 in self["myRTable"]:
if curr2[0] == curr1[0]:
if curr1.getCost() < curr2.getCost():
del curr2
self["myRTable"].addRTE(curr1)
self["incRTE"] = None
self["outRTE"] = None # Might be a problem later!!
def isNeighborRoute(self, targetRTE):
if targetRTE[1] == targetRTE[3]:
return True
else:
return False
class rtEntry(list):
def __init__(self, dest, origin, cost, via):
self.entry = [dest, origin, cost, via]
def getDest(self): return self.entry[0]
def getOrigin(self): return self.entry[1]
def getCost(self): return self.entry[2]
def getVia(self): return self.entry[3]
def __repr__(self):
foo = str(self.getDest())+", "+str(self.getOrigin())+", "+str(self.getCost())+", "+str(self.getVia())
return foo
class RTable(list):
internalRTable = None
def __init__(self, rtbl=None):
if self.internalRTable == None:
self.internalRTable = []
if rtbl is not None:
for rtentry in rtbl:
self.addRTE([rtentry])
def addRTE(self, rteToAdd):
if self.internalRTable is None:
self.internalRTable = []
self.internalRTable.append([rteToAdd])
def __repr__(self):
ret = ""
if self.internalRTable is None:
return ret
else:
for curr in self.internalRTable:
if curr is not None:
ret = ret + str(curr)+"\n"
return ret
def clearRTList(self):
self.internalRTable = None
#for rte in self.internalRTable:
#del rte
class edge(dict):
"""An edge object. Each node has a set of edge objects.
Each graph has a set of all the edges that will supply
each node with edges to populate the edge lists over time
"""
def __init__(self, edgeId, From, To, Length, Delay, Bandwidth, ASFrom, ASTo, Type):
self.edgeData = {
"edgeId" : edgeId,
"from" : From,
"to" : To,
"length" : Length,
"delay" : Delay,
"bandwidth" : Bandwidth,
"ASfrom" : ASFrom,
"ASto" : ASTo,
"type" : Type
}
self.load = 0
def __getitem__(self, key): return self.edgeData[key]
def __setitem__(self, key, item): self.edgeData[key] = item
def __repr__(self):
ret = ""
for k,v in self.edgeData.iteritems():
ret = ret + str(k) + ": " + str(v) + "; "
return ret
def addLoad(self, Load = 5):
""" If called without any parameters, adds 5 units to the edge's current load.
Otherwise, add Load units to the current load. If an add would increase
the current load over the edge's bandwidth, set the edge's current load to it's
max load (bandwidth). Then, return the value of the current load.
"""
if ((self.load + Load) > self.edgeData["bandwidth"]):
self.load = self.edgeData["bandwidth"]
else:
self.load = self.load + Load
return self.load
def remLoad(self, Load = 5):
""" If called without any parameters, removes 5 units from the edge's
current load. Otherwise, remove Load units from the current load.
If a remove would make the current load zero or less, set the
edge's current load to zero. Then, return the value of the current load.
"""
if ((self.load - Load) < 0):
self.load = 0
else:
self.load = self.load - Load
return self.load
def isFull(self):
if self.load == self.edgeData["bandwidth"]:
return True
else:
return FalseAnd the second file, Network.py:
from Node import *
class Network:
""" This is a class that will hold a network's hardware description.
Eventually, many network objects will be able to be instantiated
and communicate with each other. These will be controlled in
another class, NetManager. The interaction between each network
will be handled by another configuration file suited for EGPs.
"""
def __init__(self, filename = "", NodeList = [], ModelInfo = [""], EdgeList = []):
""" This function prepares the network. It reads all the
configuration info from the infile and initializes all the main
lists and node lists. The edge distribution will be taken care
of by the driver program, as this may vary from simulation to
simulation.
"""
self.nodeList = NodeList
self.modelInfo = ModelInfo
self.sourcefile = filename
self.fullEdgeList = EdgeList
self.routingProtocol = ""
if self.sourcefile == "":
self.sourcefile = \
raw_input("Please enter the path and filename \
of the configuration file: ")
infile = open(self.sourcefile, 'r')
buffer = infile.readline()
helper = buffer.split(" ")
self.numNodes = int(helper[2])
self.numEdges = int(helper[4])
buffer = infile.readline()
self.modelInfo = buffer.split(" ") # No functionality yet
# Read in all the node info, a line at a time.
buffer = infile.readline() #Nodes:(blah)\n
i = 0
while i < self.numNodes:
buffer = infile.readline()
helper = buffer.split("\t")
self.nodeList.append(node(int(helper[0]), int(helper[1]), \
int(helper[2]), int(helper[3]), int(helper[4]), \
int(helper[5]), helper[6], []))
i+=1
buffer = infile.readline() #"\n"
buffer = infile.readline() #"\n"
buffer = infile.readline() #Edges:(blah)\n
#helper = buffer.split(" ")
i = 0
while i < self.numEdges:
buffer = infile.readline()
helper = buffer.split("\t")
self.fullEdgeList.append(edge(int(helper[0]), int(helper[1]),\
int(helper[2]), float(helper[3]), float(helper[4]), \
float(helper[5]), int(helper[6]), int(helper[7]), \
helper[8]))
i+=1
infile.close()
# End __init__()
def setRoutingType(self, lsProto = "OSPF"):
if (lsProto == "OSPF"): # Add other protocols later
self.routingProtocol = "OSPF"
""" Here is where I would call an object seperate from the
Network object to preserve the
physical network configuration. This is an attempt to
isolate the hardware from the protocol.
# #############################################################
# #####################NOT FINISHED!!!!########################
"""
pass
def addAllEdges(self):
""" addAllEdges() adds every edge in the edge list to the node
who's id is in it's from field
"""
for edge in self.fullEdgeList:
for node in self.nodeList:
if node["nodeData"]["id"] == edge["from"]:
node.addEdge(edge)
def addNode(self, targetNode):
self.nodeList.append(targetNode)
self.numNodes = self.numNodes + 1
def initAllRTables(self):
for rtable in self.nodeList:
rtable.initRTable()
rtable.updateRTable()
#print rtableAnd here's the .brite file, you don't have to save it as a .brite, but that's the program that generated it, BRITE:
Topology: ( 50 Nodes, 100 Edges )
Model (7 - Imported From BRITE format file /home/ich1/Desktop/BRITE/router50wax.brite ): Model (1 - RTWaxman): 50 1000 100 1 2 0.15000000596046448 0.20000000298023224 1 3 10.0 1024.0
Nodes: ( 50 )
0 604 820 2 2 -1 RT_NODE
1 161 651 5 5 -1 RT_NODE
2 175 671 2 2 -1 RT_NODE
3 723 140 5 5 -1 RT_NODE
4 542 626 2 2 -1 RT_NODE
5 768 945 3 3 -1 RT_NODE
6 429 108 2 2 -1 RT_NODE
7 649 828 6 6 -1 RT_NODE
8 123 390 3 3 -1 RT_NODE
9 835 523 3 3 -1 RT_NODE
10 360 95 2 2 -1 RT_NODE
11 698 906 3 3 -1 RT_NODE
12 903 147 4 4 -1 RT_NODE
13 975 184 2 2 -1 RT_NODE
14 541 487 6 6 -1 RT_NODE
15 738 897 7 7 -1 RT_NODE
16 893 867 5 5 -1 RT_NODE
17 886 214 4 4 -1 RT_NODE
18 394 681 4 4 -1 RT_NODE
19 261 895 2 2 -1 RT_NODE
20 286 113 2 2 -1 RT_NODE
21 525 249 5 5 -1 RT_NODE
22 250 837 3 3 -1 RT_NODE
23 803 655 4 4 -1 RT_NODE
24 580 135 3 3 -1 RT_NODE
25 957 474 4 4 -1 RT_NODE
26 419 562 2 2 -1 RT_NODE
27 56 699 4 4 -1 RT_NODE
28 647 250 5 5 -1 RT_NODE
29 229 325 3 3 -1 RT_NODE
30 461 498 8 8 -1 RT_NODE
31 662 200 6 6 -1 RT_NODE
32 554 574 4 4 -1 RT_NODE
33 888 73 2 2 -1 RT_NODE
34 68 533 5 5 -1 RT_NODE
35 924 679 4 4 -1 RT_NODE
36 178 442 2 2 -1 RT_NODE
37 11 935 3 3 -1 RT_NODE
38 240 582 8 8 -1 RT_NODE
39 925 762 2 2 -1 RT_NODE
40 926 110 5 5 -1 RT_NODE
41 849 616 7 7 -1 RT_NODE
42 681 157 4 4 -1 RT_NODE
43 796 538 12 12 -1 RT_NODE
44 102 550 2 2 -1 RT_NODE
45 458 424 4 4 -1 RT_NODE
46 593 168 2 2 -1 RT_NODE
47 111 273 5 5 -1 RT_NODE
48 726 442 5 5 -1 RT_NODE
49 931 338 3 3 -1 RT_NODE
Edges: ( 100 )
0 43 30 337.3796081542969 1.1253772373229511 10.0 -1 -1 E_RT U
1 43 15 363.6550598144531 1.2130227099123791 10.0 -1 -1 E_RT U
2 16 15 157.8765411376953 0.5266194559760917 10.0 -1 -1 E_RT U
3 16 43 343.00146484375 1.1441297327224622 10.0 -1 -1 E_RT U
4 31 43 363.5931701660156 1.2128162682665473 10.0 -1 -1 E_RT U
5 31 30 359.4509582519531 1.1989993365742146 10.0 -1 -1 E_RT U
6 48 43 118.81077575683594 0.3963100891511952 10.0 -1 -1 E_RT U
7 48 31 250.31979370117188 0.8349769549611947 10.0 -1 -1 E_RT U
8 32 48 216.8132781982422 0.7232112496914188 10.0 -1 -1 E_RT U
9 32 30 120.10411834716797 0.4006242156604486 10.0 -1 -1 E_RT U
10 34 31 680.9735717773438 2.271483333237635 10.0 -1 -1 E_RT U
11 34 32 487.7263488769531 1.6268799826743912 10.0 -1 -1 E_RT U
12 41 15 302.1291198730469 1.007794265034669 10.0 -1 -1 E_RT U
13 41 16 254.827392578125 0.8500126863702655 10.0 -1 -1 E_RT U
14 1 34 150.24313354492188 0.5011571490064699 10.0 -1 -1 E_RT U
15 1 30 336.7625427246094 1.1233189286056335 10.0 -1 -1 E_RT U
16 29 48 510.5859375 1.703131362630877 10.0 -1 -1 E_RT U
17 29 15 765.679443359375 2.5540317073599463 10.0 -1 -1 E_RT U
18 14 41 333.92364501953125 1.1138493851620885 10.0 -1 -1 E_RT U
19 14 32 87.96590423583984 0.2934226725471521 10.0 -1 -1 E_RT U
20 47 41 813.8138427734375 2.7145907812445285 10.0 -1 -1 E_RT U
21 47 30 416.0829162597656 1.3879032148959718 10.0 -1 -1 E_RT U
22 18 34 358.0223388671875 1.1942339752495958 10.0 -1 -1 E_RT U
23 18 29 392.3786315917969 1.3088342322200677 10.0 -1 -1 E_RT U
24 3 14 391.8328857421875 1.3070138200147368 10.0 -1 -1 E_RT U
25 3 43 404.63934326171875 1.3497315641666967 10.0 -1 -1 E_RT U
26 12 14 496.6326599121094 1.6565882384943433 10.0 -1 -1 E_RT U
27 12 41 472.0985107421875 1.5747511258011284 10.0 -1 -1 E_RT U
28 27 47 429.5357971191406 1.4327771952126316 10.0 -1 -1 E_RT U
29 27 15 710.1605224609375 2.3688405212012955 10.0 -1 -1 E_RT U
30 44 47 277.14617919921875 0.9244601450221231 10.0 -1 -1 E_RT U
31 44 14 443.4974670410156 1.4793483131620864 10.0 -1 -1 E_RT U
32 17 12 69.12307739257812 0.23056976767767162 10.0 -1 -1 E_RT U
33 17 43 336.26776123046875 1.1216685151914954 10.0 -1 -1 E_RT U
34 2 30 334.2528991699219 1.1149476587897413 10.0 -1 -1 E_RT U
35 2 27 122.24974060058594 0.40778124111643244 10.0 -1 -1 E_RT U
36 13 43 396.6824951171875 1.3231903756471002 10.0 -1 -1 E_RT U
37 13 48 358.55963134765625 1.196026190050639 10.0 -1 -1 E_RT U
38 28 3 133.70115661621094 0.4459790533363282 10.0 -1 -1 E_RT U
39 28 43 324.2607116699219 1.0816173089648635 10.0 -1 -1 E_RT U
40 38 34 178.843505859375 0.5965577221404783 10.0 -1 -1 E_RT U
41 38 47 334.8462219238281 1.1169267704654136 10.0 -1 -1 E_RT U
42 37 41 896.6632690429688 2.9909467203573503 10.0 -1 -1 E_RT U
43 37 27 240.251953125 0.8013942536372947 10.0 -1 -1 E_RT U
44 8 38 224.83995056152344 0.749985346734518 10.0 -1 -1 E_RT U
45 8 18 397.64556884765625 1.3264028438222293 10.0 -1 -1 E_RT U
46 23 17 448.74267578125 1.4968444462377035 10.0 -1 -1 E_RT U
47 23 1 642.012451171875 2.1415230238109424 10.0 -1 -1 E_RT U
48 40 3 205.20477294921875 0.6844894441914838 10.0 -1 -1 E_RT U
49 40 28 312.1553955078125 1.0412383206378477 10.0 -1 -1 E_RT U
50 35 23 123.35720825195312 0.4114753555673276 10.0 -1 -1 E_RT U
51 35 16 190.53871154785156 0.635568729176808 10.0 -1 -1 E_RT U
52 7 35 312.771484375 1.0432933718932982 10.0 -1 -1 E_RT U
53 7 14 357.6940002441406 1.1931387554924435 10.0 -1 -1 E_RT U
54 49 28 297.3213806152344 0.9917573730798603 10.0 -1 -1 E_RT U
55 49 16 530.3630981445312 1.769100869590693 10.0 -1 -1 E_RT U
56 22 17 890.294921875 2.9697042007474383 10.0 -1 -1 E_RT U
57 22 8 464.6912841796875 1.5500432775386481 10.0 -1 -1 E_RT U
58 9 12 382.0994567871094 1.2745465957889754 10.0 -1 -1 E_RT U
59 9 41 94.04785919189453 0.3137098905666751 10.0 -1 -1 E_RT U
60 21 22 649.12939453125 2.165262591533407 10.0 -1 -1 E_RT U
61 21 1 542.3098754882812 1.8089510293427102 10.0 -1 -1 E_RT U
62 33 40 53.037723541259766 0.17691480264410042 10.0 -1 -1 E_RT U
63 33 43 474.0137023925781 1.5811395175010645 10.0 -1 -1 E_RT U
64 6 38 510.2911071777344 1.702147914534042 10.0 -1 -1 E_RT U
65 6 7 752.8612060546875 2.5112746700742137 10.0 -1 -1 E_RT U
66 24 7 696.4265747070312 2.3230290026409914 10.0 -1 -1 E_RT U
67 24 40 346.9020080566406 1.1571405443983538 10.0 -1 -1 E_RT U
68 42 3 45.31004333496094 0.15113803608415305 10.0 -1 -1 E_RT U
69 42 1 717.241943359375 2.3924615987483415 10.0 -1 -1 E_RT U
70 4 38 305.1884765625 1.0179991804947275 10.0 -1 -1 E_RT U
71 4 21 377.3830871582031 1.2588144801101138 10.0 -1 -1 E_RT U
72 19 38 313.70367431640625 1.0464028228368782 10.0 -1 -1 E_RT U
73 19 43 643.1749267578125 2.1454006249810744 10.0 -1 -1 E_RT U
74 36 40 818.3690795898438 2.729785415715307 10.0 -1 -1 E_RT U
75 36 49 760.1480102539062 2.5355808325701985 10.0 -1 -1 E_RT U
76 26 42 482.3577575683594 1.6089722896509937 10.0 -1 -1 E_RT U
77 26 7 351.6475524902344 1.172969976750497 10.0 -1 -1 E_RT U
78 11 37 687.61181640625 2.2936261338710864 10.0 -1 -1 E_RT U
79 11 23 272.07720947265625 0.9075518820178466 10.0 -1 -1 E_RT U
80 39 9 255.38401794433594 0.8518693887367105 10.0 -1 -1 E_RT U
81 39 7 283.7816162109375 0.946593580452706 10.0 -1 -1 E_RT U
82 45 38 269.2359619140625 0.8980745003066838 10.0 -1 -1 E_RT U
83 45 24 313.6957092285156 1.0463762541635242 10.0 -1 -1 E_RT U
84 20 31 385.9339294433594 1.2873370198104161 10.0 -1 -1 E_RT U
85 20 21 274.9854431152344 0.9172527052539606 10.0 -1 -1 E_RT U
86 46 38 544.0634155273438 1.8148002093079465 10.0 -1 -1 E_RT U
87 46 31 76.05918884277344 0.253706145078451 10.0 -1 -1 E_RT U
88 25 28 382.46044921875 1.2757507369273113 10.0 -1 -1 E_RT U
89 25 45 501.4987487792969 1.6728197637957152 10.0 -1 -1 E_RT U
90 10 42 326.9327087402344 1.0905301318161726 10.0 -1 -1 E_RT U
91 10 45 343.28558349609375 1.1450774505344419 10.0 -1 -1 E_RT U
92 5 25 507.50567626953125 1.6928567171277247 10.0 -1 -1 E_RT U
93 5 35 308.3699035644531 1.028611278688182 10.0 -1 -1 E_RT U
94 0 18 251.83526611328125 0.840032026800625 10.0 -1 -1 E_RT U
95 0 43 341.1568603515625 1.1379767944381125 10.0 -1 -1 E_RT U
96 15 11 41.0 0.13676127903124233 10.0 -1 -1 E_RT U
97 15 25 476.3297119140625 1.588864893706107 10.0 -1 -1 E_RT U
98 30 5 542.2711791992188 1.8088219524162237 10.0 -1 -1 E_RT U
99 30 21 257.0933532714844 0.8575711176546155 10.0 -1 -1 E_RT U