116 lines
3.1 KiB
Python
116 lines
3.1 KiB
Python
from operator import itemgetter
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import heapq
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class Node:
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def __init__(self, node_id, ip=None, port=None):
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self.id = node_id
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self.ip = ip
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self.port = port
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self.long_id = int(node_id.hex(), 16)
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def sameHomeAs(self, node):
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return self.ip == node.ip and self.port == node.port
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def distanceTo(self, node):
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"""
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Get the distance between this node and another.
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"""
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return self.long_id ^ node.long_id
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def __iter__(self):
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"""
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Enables use of Node as a tuple - i.e., tuple(node) works.
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"""
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return iter([self.id, self.ip, self.port])
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def __repr__(self):
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return repr([self.long_id, self.ip, self.port])
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def __str__(self):
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return "%s:%s" % (self.ip, str(self.port))
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class NodeHeap:
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"""
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A heap of nodes ordered by distance to a given node.
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"""
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def __init__(self, node, maxsize):
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"""
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Constructor.
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@param node: The node to measure all distnaces from.
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@param maxsize: The maximum size that this heap can grow to.
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"""
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self.node = node
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self.heap = []
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self.contacted = set()
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self.maxsize = maxsize
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def remove(self, peerIDs):
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"""
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Remove a list of peer ids from this heap. Note that while this
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heap retains a constant visible size (based on the iterator), it's
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actual size may be quite a bit larger than what's exposed. Therefore,
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removal of nodes may not change the visible size as previously added
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nodes suddenly become visible.
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"""
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peerIDs = set(peerIDs)
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if len(peerIDs) == 0:
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return
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nheap = []
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for distance, node in self.heap:
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if node.id not in peerIDs:
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heapq.heappush(nheap, (distance, node))
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self.heap = nheap
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def getNodeById(self, node_id):
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for _, node in self.heap:
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if node.id == node_id:
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return node
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return None
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def allBeenContacted(self):
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return len(self.getUncontacted()) == 0
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def getIDs(self):
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return [n.id for n in self]
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def markContacted(self, node):
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self.contacted.add(node.id)
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def popleft(self):
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if len(self) > 0:
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return heapq.heappop(self.heap)[1]
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return None
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def push(self, nodes):
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"""
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Push nodes onto heap.
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@param nodes: This can be a single item or a C{list}.
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"""
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if not isinstance(nodes, list):
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nodes = [nodes]
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for node in nodes:
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if node not in self:
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distance = self.node.distanceTo(node)
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heapq.heappush(self.heap, (distance, node))
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def __len__(self):
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return min(len(self.heap), self.maxsize)
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def __iter__(self):
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nodes = heapq.nsmallest(self.maxsize, self.heap)
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return iter(map(itemgetter(1), nodes))
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def __contains__(self, node):
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for _, n in self.heap:
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if node.id == n.id:
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return True
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return False
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def getUncontacted(self):
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return [n for n in self if n.id not in self.contacted]
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