py-libp2p/kademlia/node.py

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2018-10-14 22:32:27 +08:00
from operator import itemgetter
import heapq
class Node:
def __init__(self, node_id, ip=None, port=None):
self.id = node_id
self.ip = ip
self.port = port
self.long_id = int(node_id.hex(), 16)
def sameHomeAs(self, node):
return self.ip == node.ip and self.port == node.port
def distanceTo(self, node):
"""
Get the distance between this node and another.
"""
return self.long_id ^ node.long_id
def __iter__(self):
"""
Enables use of Node as a tuple - i.e., tuple(node) works.
"""
return iter([self.id, self.ip, self.port])
def __repr__(self):
return repr([self.long_id, self.ip, self.port])
def __str__(self):
return "%s:%s" % (self.ip, str(self.port))
class NodeHeap(object):
"""
A heap of nodes ordered by distance to a given node.
"""
def __init__(self, node, maxsize):
"""
Constructor.
@param node: The node to measure all distnaces from.
@param maxsize: The maximum size that this heap can grow to.
"""
self.node = node
self.heap = []
self.contacted = set()
self.maxsize = maxsize
def remove(self, peerIDs):
"""
Remove a list of peer ids from this heap. Note that while this
heap retains a constant visible size (based on the iterator), it's
actual size may be quite a bit larger than what's exposed. Therefore,
removal of nodes may not change the visible size as previously added
nodes suddenly become visible.
"""
peerIDs = set(peerIDs)
if len(peerIDs) == 0:
return
nheap = []
for distance, node in self.heap:
if node.id not in peerIDs:
heapq.heappush(nheap, (distance, node))
self.heap = nheap
def getNodeById(self, node_id):
for _, node in self.heap:
if node.id == node_id:
return node
return None
def allBeenContacted(self):
return len(self.getUncontacted()) == 0
def getIDs(self):
return [n.id for n in self]
def markContacted(self, node):
self.contacted.add(node.id)
def popleft(self):
if len(self) > 0:
return heapq.heappop(self.heap)[1]
return None
def push(self, nodes):
"""
Push nodes onto heap.
@param nodes: This can be a single item or a C{list}.
"""
if not isinstance(nodes, list):
nodes = [nodes]
for node in nodes:
if node not in self:
distance = self.node.distanceTo(node)
heapq.heappush(self.heap, (distance, node))
def __len__(self):
return min(len(self.heap), self.maxsize)
def __iter__(self):
nodes = heapq.nsmallest(self.maxsize, self.heap)
return iter(map(itemgetter(1), nodes))
def __contains__(self, node):
for _, n in self.heap:
if node.id == n.id:
return True
return False
def getUncontacted(self):
return [n for n in self if n.id not in self.contacted]