forked from LBRYCommunity/lbry-sdk
446c3a88dc
-use looping call for running manage function rather than a scheduled
callLater
-track announce speed
-retry store requests that failed up to 3 times
-return a dict of {blob_hash: [storing_node_id]} results from
_announce_hashes
_refreshRoutingTable inline cb refactor
-add and use DeferredLockContextManager
-don't trap errback from iterativeFindNode in iterativeAnnounceHaveBlob
906 lines
38 KiB
Python
906 lines
38 KiB
Python
#!/usr/bin/env python
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#
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# This library is free software, distributed under the terms of
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# the GNU Lesser General Public License Version 3, or any later version.
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# See the COPYING file included in this archive
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#
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# The docstrings in this module contain epytext markup; API documentation
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# may be created by processing this file with epydoc: http://epydoc.sf.net
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import binascii
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import hashlib
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import operator
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import struct
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import time
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from twisted.internet import defer, error, reactor, task
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import constants
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import routingtable
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import datastore
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import protocol
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from contact import Contact
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from hashwatcher import HashWatcher
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from distance import Distance
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import logging
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from lbrynet.core.utils import generate_id
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log = logging.getLogger(__name__)
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def rpcmethod(func):
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""" Decorator to expose Node methods as remote procedure calls
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Apply this decorator to methods in the Node class (or a subclass) in order
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to make them remotely callable via the DHT's RPC mechanism.
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"""
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func.rpcmethod = True
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return func
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class Node(object):
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""" Local node in the Kademlia network
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This class represents a single local node in a Kademlia network; in other
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words, this class encapsulates an Entangled-using application's "presence"
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in a Kademlia network.
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In Entangled, all interactions with the Kademlia network by a client
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application is performed via this class (or a subclass).
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"""
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def __init__(self, node_id=None, udpPort=4000, dataStore=None,
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routingTableClass=None, networkProtocol=None,
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externalIP=None, peerPort=None):
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"""
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@param dataStore: The data store to use. This must be class inheriting
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from the C{DataStore} interface (or providing the
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same API). How the data store manages its data
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internally is up to the implementation of that data
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store.
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@type dataStore: entangled.kademlia.datastore.DataStore
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@param routingTable: The routing table class to use. Since there exists
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some ambiguity as to how the routing table should be
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implemented in Kademlia, a different routing table
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may be used, as long as the appropriate API is
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exposed. This should be a class, not an object,
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in order to allow the Node to pass an
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auto-generated node ID to the routingtable object
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upon instantiation (if necessary).
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@type routingTable: entangled.kademlia.routingtable.RoutingTable
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@param networkProtocol: The network protocol to use. This can be
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overridden from the default to (for example)
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change the format of the physical RPC messages
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being transmitted.
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@type networkProtocol: entangled.kademlia.protocol.KademliaProtocol
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@param externalIP: the IP at which this node can be contacted
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@param peerPort: the port at which this node announces it has a blob for
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"""
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self.node_id = node_id or self._generateID()
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self.port = udpPort
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self._listeningPort = None # object implementing Twisted
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# IListeningPort This will contain a deferred created when
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# joining the network, to enable publishing/retrieving
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# information from the DHT as soon as the node is part of the
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# network (add callbacks to this deferred if scheduling such
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# operations before the node has finished joining the network)
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self._joinDeferred = None
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self.change_token_lc = task.LoopingCall(self.change_token)
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self.refresh_node_lc = task.LoopingCall(self._refreshNode)
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# Create k-buckets (for storing contacts)
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if routingTableClass is None:
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self._routingTable = routingtable.OptimizedTreeRoutingTable(self.node_id)
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else:
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self._routingTable = routingTableClass(self.node_id)
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# Initialize this node's network access mechanisms
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if networkProtocol is None:
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self._protocol = protocol.KademliaProtocol(self)
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else:
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self._protocol = networkProtocol
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# Initialize the data storage mechanism used by this node
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self.token_secret = self._generateID()
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self.old_token_secret = None
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if dataStore is None:
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self._dataStore = datastore.DictDataStore()
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else:
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self._dataStore = dataStore
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# Try to restore the node's state...
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if 'nodeState' in self._dataStore:
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state = self._dataStore['nodeState']
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self.node_id = state['id']
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for contactTriple in state['closestNodes']:
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contact = Contact(
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contactTriple[0], contactTriple[1], contactTriple[2], self._protocol)
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self._routingTable.addContact(contact)
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self.externalIP = externalIP
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self.peerPort = peerPort
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self.hash_watcher = HashWatcher()
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# will be used later
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self._can_store = True
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def __del__(self):
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if self._listeningPort is not None:
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self._listeningPort.stopListening()
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@property
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def can_store(self):
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return self._can_store is True
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def stop(self):
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# stop LoopingCalls:
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if self.refresh_node_lc.running:
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self.refresh_node_lc.stop()
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if self.change_token_lc.running:
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self.change_token_lc.stop()
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if self._listeningPort is not None:
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self._listeningPort.stopListening()
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self.hash_watcher.stop()
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def startNetwork(self):
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""" Causes the Node to start all the underlying components needed for the DHT
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to work. This should be called before any other DHT operations.
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"""
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log.info("Starting DHT underlying components")
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# Prepare the underlying Kademlia protocol
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if self.port is not None:
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try:
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self._listeningPort = reactor.listenUDP(self.port, self._protocol)
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except error.CannotListenError as e:
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import traceback
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log.error("Couldn't bind to port %d. %s", self.port, traceback.format_exc())
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raise ValueError("%s lbrynet may already be running." % str(e))
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# Start the token looping call
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self.change_token_lc.start(constants.tokenSecretChangeInterval)
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# #TODO: Refresh all k-buckets further away than this node's closest neighbour
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# Start refreshing k-buckets periodically, if necessary
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self.next_refresh_call = reactor.callLater(constants.checkRefreshInterval,
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self._refreshNode)
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self.hash_watcher.tick()
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@defer.inlineCallbacks
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def joinNetwork(self, knownNodeAddresses=None):
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""" Causes the Node to attempt to join the DHT network by contacting the
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known DHT nodes. This can be called multiple times if the previous attempt
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has failed or if the Node has lost all the contacts.
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@param knownNodeAddresses: A sequence of tuples containing IP address
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information for existing nodes on the
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Kademlia network, in the format:
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C{(<ip address>, (udp port>)}
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@type knownNodeAddresses: tuple
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"""
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log.info("Attempting to join the DHT network")
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# IGNORE:E1101
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# Create temporary contact information for the list of addresses of known nodes
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if knownNodeAddresses != None:
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bootstrapContacts = []
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for address, port in knownNodeAddresses:
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contact = Contact(self._generateID(), address, port, self._protocol)
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bootstrapContacts.append(contact)
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else:
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bootstrapContacts = None
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# Initiate the Kademlia joining sequence - perform a search for this node's own ID
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self._joinDeferred = self._iterativeFind(self.node_id, bootstrapContacts)
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# #TODO: Refresh all k-buckets further away than this node's closest neighbour
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# Start refreshing k-buckets periodically, if necessary
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self.hash_watcher.tick()
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yield self._joinDeferred
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self.refresh_node_lc.start(constants.checkRefreshInterval)
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@property
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def contacts(self):
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def _inner():
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for i in range(len(self._routingTable._buckets)):
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for contact in self._routingTable._buckets[i]._contacts:
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yield contact
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return list(_inner())
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def printContacts(self, *args):
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print '\n\nNODE CONTACTS\n==============='
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for i in range(len(self._routingTable._buckets)):
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print "bucket %i" % i
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for contact in self._routingTable._buckets[i]._contacts:
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print " %s:%i" % (contact.address, contact.port)
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print '=================================='
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def hasContacts(self):
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for bucket in self._routingTable._buckets:
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if bucket._contacts:
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return True
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return False
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def getApproximateTotalDHTNodes(self):
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# get the deepest bucket and the number of contacts in that bucket and multiply it
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# by the number of equivalently deep buckets in the whole DHT to get a really bad
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# estimate!
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bucket = self._routingTable._buckets[self._routingTable._kbucketIndex(self.node_id)]
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num_in_bucket = len(bucket._contacts)
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factor = (2 ** constants.key_bits) / (bucket.rangeMax - bucket.rangeMin)
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return num_in_bucket * factor
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def getApproximateTotalHashes(self):
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# Divide the number of hashes we know about by k to get a really, really, really
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# bad estimate of the average number of hashes per node, then multiply by the
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# approximate number of nodes to get a horrendous estimate of the total number
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# of hashes in the DHT
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num_in_data_store = len(self._dataStore._dict)
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if num_in_data_store == 0:
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return 0
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return num_in_data_store * self.getApproximateTotalDHTNodes() / 8
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def announceHaveBlob(self, key):
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return self.iterativeAnnounceHaveBlob(key, {'port': self.peerPort, 'lbryid': self.node_id})
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@defer.inlineCallbacks
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def getPeersForBlob(self, blob_hash):
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result = yield self.iterativeFindValue(blob_hash)
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expanded_peers = []
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if result:
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if blob_hash in result:
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for peer in result[blob_hash]:
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host = ".".join([str(ord(d)) for d in peer[:4]])
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port, = struct.unpack('>H', peer[4:6])
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if (host, port) not in expanded_peers:
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expanded_peers.append((host, port))
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defer.returnValue(expanded_peers)
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def get_most_popular_hashes(self, num_to_return):
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return self.hash_watcher.most_popular_hashes(num_to_return)
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def get_bandwidth_stats(self):
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return self._protocol.bandwidth_stats
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def iterativeAnnounceHaveBlob(self, blob_hash, value):
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known_nodes = {}
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@defer.inlineCallbacks
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def announce_to_peer(responseTuple):
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""" @type responseMsg: kademlia.msgtypes.ResponseMessage """
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# The "raw response" tuple contains the response message,
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# and the originating address info
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responseMsg = responseTuple[0]
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originAddress = responseTuple[1] # tuple: (ip adress, udp port)
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# Make sure the responding node is valid, and abort the operation if it isn't
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if not responseMsg.nodeID in known_nodes:
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log.warning("Responding node was not expected")
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defer.returnValue(responseMsg.nodeID)
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n = known_nodes[responseMsg.nodeID]
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result = responseMsg.response
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announced = False
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if 'token' in result:
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value['token'] = result['token']
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try:
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res = yield n.store(blob_hash, value, self.node_id)
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log.debug("Response to store request: %s", str(res))
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announced = True
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except protocol.TimeoutError:
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log.debug("Timeout while storing blob_hash %s at %s",
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blob_hash.encode('hex')[:16], n.id.encode('hex'))
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except Exception as err:
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log.error("Unexpected error while storing blob_hash %s at %s: %s",
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blob_hash.encode('hex')[:16], n.id.encode('hex'), err)
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else:
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log.warning("missing token")
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defer.returnValue(announced)
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@defer.inlineCallbacks
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def requestPeers(contacts):
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if self.externalIP is not None and len(contacts) >= constants.k:
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is_closer = Distance(blob_hash).is_closer(self.node_id, contacts[-1].id)
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if is_closer:
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contacts.pop()
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yield self.store(blob_hash, value, originalPublisherID=self.node_id,
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self_store=True)
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elif self.externalIP is not None:
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yield self.store(blob_hash, value, originalPublisherID=self.node_id,
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self_store=True)
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else:
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raise Exception("Cannot determine external IP: %s" % self.externalIP)
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contacted = []
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for contact in contacts:
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known_nodes[contact.id] = contact
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rpcMethod = getattr(contact, "findValue")
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try:
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response = yield rpcMethod(blob_hash, rawResponse=True)
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stored = yield announce_to_peer(response)
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if stored:
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contacted.append(contact)
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except protocol.TimeoutError:
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log.debug("Timeout while storing blob_hash %s at %s",
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binascii.hexlify(blob_hash), contact)
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except Exception as err:
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log.error("Unexpected error while storing blob_hash %s at %s: %s",
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binascii.hexlify(blob_hash), contact, err)
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log.debug("Stored %s to %i of %i attempted peers", blob_hash.encode('hex')[:16],
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len(contacted), len(contacts))
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contacted_node_ids = [c.id.encode('hex') for c in contacts]
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defer.returnValue(contacted_node_ids)
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d = self.iterativeFindNode(blob_hash)
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d.addCallback(requestPeers)
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return d
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def change_token(self):
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self.old_token_secret = self.token_secret
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self.token_secret = self._generateID()
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def make_token(self, compact_ip):
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h = hashlib.new('sha384')
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h.update(self.token_secret + compact_ip)
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return h.digest()
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def verify_token(self, token, compact_ip):
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h = hashlib.new('sha384')
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h.update(self.token_secret + compact_ip)
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if not token == h.digest():
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h = hashlib.new('sha384')
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h.update(self.old_token_secret + compact_ip)
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if not token == h.digest():
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return False
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return True
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def iterativeFindNode(self, key):
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""" The basic Kademlia node lookup operation
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Call this to find a remote node in the P2P overlay network.
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@param key: the n-bit key (i.e. the node or value ID) to search for
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@type key: str
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@return: This immediately returns a deferred object, which will return
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a list of k "closest" contacts (C{kademlia.contact.Contact}
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objects) to the specified key as soon as the operation is
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finished.
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@rtype: twisted.internet.defer.Deferred
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"""
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return self._iterativeFind(key)
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@defer.inlineCallbacks
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def iterativeFindValue(self, key):
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""" The Kademlia search operation (deterministic)
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Call this to retrieve data from the DHT.
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@param key: the n-bit key (i.e. the value ID) to search for
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@type key: str
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@return: This immediately returns a deferred object, which will return
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either one of two things:
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- If the value was found, it will return a Python
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dictionary containing the searched-for key (the C{key}
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parameter passed to this method), and its associated
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value, in the format:
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C{<str>key: <str>data_value}
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- If the value was not found, it will return a list of k
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"closest" contacts (C{kademlia.contact.Contact} objects)
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to the specified key
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@rtype: twisted.internet.defer.Deferred
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"""
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# Prepare a callback for this operation
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outerDf = defer.Deferred()
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def checkResult(result):
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if isinstance(result, dict):
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# We have found the value; now see who was the closest contact without it...
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# ...and store the key/value pair
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outerDf.callback(result)
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else:
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# The value wasn't found, but a list of contacts was returned
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# Now, see if we have the value (it might seem wasteful to search on the network
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# first, but it ensures that all values are properly propagated through the
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# network
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if self._dataStore.hasPeersForBlob(key):
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# Ok, we have the value locally, so use that
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peers = self._dataStore.getPeersForBlob(key)
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# Send this value to the closest node without it
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outerDf.callback({key: peers})
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else:
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# Ok, value does not exist in DHT at all
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outerDf.callback(result)
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# Execute the search
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iterative_find_result = yield self._iterativeFind(key, rpc='findValue')
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checkResult(iterative_find_result)
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result = yield outerDf
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defer.returnValue(result)
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def addContact(self, contact):
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""" Add/update the given contact; simple wrapper for the same method
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in this object's RoutingTable object
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@param contact: The contact to add to this node's k-buckets
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@type contact: kademlia.contact.Contact
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"""
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self._routingTable.addContact(contact)
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def removeContact(self, contactID):
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""" Remove the contact with the specified node ID from this node's
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table of known nodes. This is a simple wrapper for the same method
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in this object's RoutingTable object
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@param contactID: The node ID of the contact to remove
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@type contactID: str
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"""
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self._routingTable.removeContact(contactID)
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def findContact(self, contactID):
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""" Find a entangled.kademlia.contact.Contact object for the specified
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cotact ID
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@param contactID: The contact ID of the required Contact object
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@type contactID: str
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@return: Contact object of remote node with the specified node ID,
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or None if the contact was not found
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@rtype: twisted.internet.defer.Deferred
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"""
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try:
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contact = self._routingTable.getContact(contactID)
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df = defer.Deferred()
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df.callback(contact)
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except ValueError:
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def parseResults(nodes):
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if contactID in nodes:
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contact = nodes[nodes.index(contactID)]
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return contact
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else:
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return None
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df = self.iterativeFindNode(contactID)
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df.addCallback(parseResults)
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return df
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@rpcmethod
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def ping(self):
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""" Used to verify contact between two Kademlia nodes
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@rtype: str
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"""
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return 'pong'
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@rpcmethod
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def store(self, key, value, originalPublisherID=None, self_store=False, **kwargs):
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""" Store the received data in this node's local hash table
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@param key: The hashtable key of the data
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@type key: str
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@param value: The actual data (the value associated with C{key})
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@type value: str
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@param originalPublisherID: The node ID of the node that is the
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B{original} publisher of the data
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@type originalPublisherID: str
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@param age: The relative age of the data (time in seconds since it was
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originally published). Note that the original publish time
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isn't actually given, to compensate for clock skew between
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different nodes.
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@type age: int
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|
|
@rtype: str
|
|
|
|
@todo: Since the data (value) may be large, passing it around as a buffer
|
|
(which is the case currently) might not be a good idea... will have
|
|
to fix this (perhaps use a stream from the Protocol class?)
|
|
"""
|
|
# Get the sender's ID (if any)
|
|
if originalPublisherID is None:
|
|
if '_rpcNodeID' in kwargs:
|
|
originalPublisherID = kwargs['_rpcNodeID']
|
|
else:
|
|
raise TypeError, 'No NodeID given. Therefore we can\'t store this node'
|
|
|
|
if self_store is True and self.externalIP:
|
|
contact = Contact(self.node_id, self.externalIP, self.port, None, None)
|
|
compact_ip = contact.compact_ip()
|
|
elif '_rpcNodeContact' in kwargs:
|
|
contact = kwargs['_rpcNodeContact']
|
|
compact_ip = contact.compact_ip()
|
|
else:
|
|
raise TypeError, 'No contact info available'
|
|
|
|
if ((self_store is False) and
|
|
('token' not in value or not self.verify_token(value['token'], compact_ip))):
|
|
raise ValueError('Invalid or missing token')
|
|
|
|
if 'port' in value:
|
|
port = int(value['port'])
|
|
if 0 <= port <= 65536:
|
|
compact_port = str(struct.pack('>H', port))
|
|
else:
|
|
raise TypeError, 'Invalid port'
|
|
else:
|
|
raise TypeError, 'No port available'
|
|
|
|
if 'lbryid' in value:
|
|
if len(value['lbryid']) != constants.key_bits / 8:
|
|
raise ValueError('Invalid lbryid (%i bytes): %s' % (len(value['lbryid']),
|
|
value['lbryid'].encode('hex')))
|
|
else:
|
|
compact_address = compact_ip + compact_port + value['lbryid']
|
|
else:
|
|
raise TypeError, 'No lbryid given'
|
|
|
|
now = int(time.time())
|
|
originallyPublished = now # - age
|
|
self._dataStore.addPeerToBlob(key, compact_address, now, originallyPublished,
|
|
originalPublisherID)
|
|
return 'OK'
|
|
|
|
@rpcmethod
|
|
def findNode(self, key, **kwargs):
|
|
""" Finds a number of known nodes closest to the node/value with the
|
|
specified key.
|
|
|
|
@param key: the n-bit key (i.e. the node or value ID) to search for
|
|
@type key: str
|
|
|
|
@return: A list of contact triples closest to the specified key.
|
|
This method will return C{k} (or C{count}, if specified)
|
|
contacts if at all possible; it will only return fewer if the
|
|
node is returning all of the contacts that it knows of.
|
|
@rtype: list
|
|
"""
|
|
|
|
# Get the sender's ID (if any)
|
|
if '_rpcNodeID' in kwargs:
|
|
rpc_sender_id = kwargs['_rpcNodeID']
|
|
else:
|
|
rpc_sender_id = None
|
|
contacts = self._routingTable.findCloseNodes(key, constants.k, rpc_sender_id)
|
|
contact_triples = []
|
|
for contact in contacts:
|
|
contact_triples.append((contact.id, contact.address, contact.port))
|
|
return contact_triples
|
|
|
|
@rpcmethod
|
|
def findValue(self, key, **kwargs):
|
|
""" Return the value associated with the specified key if present in
|
|
this node's data, otherwise execute FIND_NODE for the key
|
|
|
|
@param key: The hashtable key of the data to return
|
|
@type key: str
|
|
|
|
@return: A dictionary containing the requested key/value pair,
|
|
or a list of contact triples closest to the requested key.
|
|
@rtype: dict or list
|
|
"""
|
|
|
|
if self._dataStore.hasPeersForBlob(key):
|
|
rval = {key: self._dataStore.getPeersForBlob(key)}
|
|
else:
|
|
contact_triples = self.findNode(key, **kwargs)
|
|
rval = {'contacts': contact_triples}
|
|
if '_rpcNodeContact' in kwargs:
|
|
contact = kwargs['_rpcNodeContact']
|
|
compact_ip = contact.compact_ip()
|
|
rval['token'] = self.make_token(compact_ip)
|
|
self.hash_watcher.add_requested_hash(key, contact)
|
|
return rval
|
|
|
|
def _generateID(self):
|
|
""" Generates an n-bit pseudo-random identifier
|
|
|
|
@return: A globally unique n-bit pseudo-random identifier
|
|
@rtype: str
|
|
"""
|
|
return generate_id()
|
|
|
|
@defer.inlineCallbacks
|
|
def _iterativeFind(self, key, startupShortlist=None, rpc='findNode'):
|
|
""" The basic Kademlia iterative lookup operation (for nodes/values)
|
|
|
|
This builds a list of k "closest" contacts through iterative use of
|
|
the "FIND_NODE" RPC, or if C{findValue} is set to C{True}, using the
|
|
"FIND_VALUE" RPC, in which case the value (if found) may be returned
|
|
instead of a list of contacts
|
|
|
|
@param key: the n-bit key (i.e. the node or value ID) to search for
|
|
@type key: str
|
|
@param startupShortlist: A list of contacts to use as the starting
|
|
shortlist for this search; this is normally
|
|
only used when the node joins the network
|
|
@type startupShortlist: list
|
|
@param rpc: The name of the RPC to issue to remote nodes during the
|
|
Kademlia lookup operation (e.g. this sets whether this
|
|
algorithm should search for a data value (if
|
|
rpc='findValue') or not. It can thus be used to perform
|
|
other operations that piggy-back on the basic Kademlia
|
|
lookup operation (Entangled's "delete" RPC, for instance).
|
|
@type rpc: str
|
|
|
|
@return: If C{findValue} is C{True}, the algorithm will stop as soon
|
|
as a data value for C{key} is found, and return a dictionary
|
|
containing the key and the found value. Otherwise, it will
|
|
return a list of the k closest nodes to the specified key
|
|
@rtype: twisted.internet.defer.Deferred
|
|
"""
|
|
findValue = rpc != 'findNode'
|
|
|
|
if startupShortlist is None:
|
|
shortlist = self._routingTable.findCloseNodes(key, constants.k)
|
|
if key != self.node_id:
|
|
# Update the "last accessed" timestamp for the appropriate k-bucket
|
|
self._routingTable.touchKBucket(key)
|
|
if len(shortlist) == 0:
|
|
log.warning("This node doesnt know any other nodes")
|
|
# This node doesn't know of any other nodes
|
|
fakeDf = defer.Deferred()
|
|
fakeDf.callback([])
|
|
result = yield fakeDf
|
|
defer.returnValue(result)
|
|
else:
|
|
# This is used during the bootstrap process; node ID's are most probably fake
|
|
shortlist = startupShortlist
|
|
|
|
outerDf = defer.Deferred()
|
|
|
|
helper = _IterativeFindHelper(self, outerDf, shortlist, key, findValue, rpc)
|
|
# Start the iterations
|
|
helper.searchIteration()
|
|
result = yield outerDf
|
|
defer.returnValue(result)
|
|
|
|
@defer.inlineCallbacks
|
|
def _refreshNode(self):
|
|
""" Periodically called to perform k-bucket refreshes and data
|
|
replication/republishing as necessary """
|
|
|
|
yield self._refreshRoutingTable()
|
|
self._dataStore.removeExpiredPeers()
|
|
defer.returnValue(None)
|
|
|
|
@defer.inlineCallbacks
|
|
def _refreshRoutingTable(self):
|
|
nodeIDs = self._routingTable.getRefreshList(0, False)
|
|
while nodeIDs:
|
|
searchID = nodeIDs.pop()
|
|
yield self.iterativeFindNode(searchID)
|
|
defer.returnValue(None)
|
|
|
|
|
|
# This was originally a set of nested methods in _iterativeFind
|
|
# but they have been moved into this helper class in-order to
|
|
# have better scoping and readability
|
|
class _IterativeFindHelper(object):
|
|
# TODO: use polymorphism to search for a value or node
|
|
# instead of using a find_value flag
|
|
def __init__(self, node, outer_d, shortlist, key, find_value, rpc):
|
|
self.node = node
|
|
self.outer_d = outer_d
|
|
self.shortlist = shortlist
|
|
self.key = key
|
|
self.find_value = find_value
|
|
self.rpc = rpc
|
|
# all distance operations in this class only care about the distance
|
|
# to self.key, so this makes it easier to calculate those
|
|
self.distance = Distance(key)
|
|
# List of active queries; len() indicates number of active probes
|
|
#
|
|
# n.b: using lists for these variables, because Python doesn't
|
|
# allow binding a new value to a name in an enclosing
|
|
# (non-global) scope
|
|
self.active_probes = []
|
|
# List of contact IDs that have already been queried
|
|
self.already_contacted = []
|
|
# Probes that were active during the previous iteration
|
|
# A list of found and known-to-be-active remote nodes
|
|
self.active_contacts = []
|
|
# This should only contain one entry; the next scheduled iteration call
|
|
self.pending_iteration_calls = []
|
|
self.prev_closest_node = [None]
|
|
self.find_value_result = {}
|
|
self.slow_node_count = [0]
|
|
|
|
def extendShortlist(self, responseTuple):
|
|
""" @type responseMsg: kademlia.msgtypes.ResponseMessage """
|
|
# The "raw response" tuple contains the response message,
|
|
# and the originating address info
|
|
responseMsg = responseTuple[0]
|
|
originAddress = responseTuple[1] # tuple: (ip adress, udp port)
|
|
# Make sure the responding node is valid, and abort the operation if it isn't
|
|
if responseMsg.nodeID in self.active_contacts or responseMsg.nodeID == self.node.node_id:
|
|
return responseMsg.nodeID
|
|
|
|
# Mark this node as active
|
|
aContact = self._getActiveContact(responseMsg, originAddress)
|
|
self.active_contacts.append(aContact)
|
|
|
|
# This makes sure "bootstrap"-nodes with "fake" IDs don't get queried twice
|
|
if responseMsg.nodeID not in self.already_contacted:
|
|
self.already_contacted.append(responseMsg.nodeID)
|
|
|
|
# Now grow extend the (unverified) shortlist with the returned contacts
|
|
result = responseMsg.response
|
|
# TODO: some validation on the result (for guarding against attacks)
|
|
# If we are looking for a value, first see if this result is the value
|
|
# we are looking for before treating it as a list of contact triples
|
|
if self.find_value is True and self.key in result and not 'contacts' in result:
|
|
# We have found the value
|
|
self.find_value_result[self.key] = result[self.key]
|
|
else:
|
|
if self.find_value is True:
|
|
self._setClosestNodeValue(responseMsg, aContact)
|
|
self._keepSearching(result)
|
|
return responseMsg.nodeID
|
|
|
|
def _getActiveContact(self, responseMsg, originAddress):
|
|
if responseMsg.nodeID in self.shortlist:
|
|
# Get the contact information from the shortlist...
|
|
return self.shortlist[self.shortlist.index(responseMsg.nodeID)]
|
|
else:
|
|
# If it's not in the shortlist; we probably used a fake ID to reach it
|
|
# - reconstruct the contact, using the real node ID this time
|
|
return Contact(
|
|
responseMsg.nodeID, originAddress[0], originAddress[1], self.node._protocol)
|
|
|
|
def _keepSearching(self, result):
|
|
contactTriples = self._getContactTriples(result)
|
|
for contactTriple in contactTriples:
|
|
self._addIfValid(contactTriple)
|
|
|
|
def _getContactTriples(self, result):
|
|
if self.find_value is True:
|
|
return result['contacts']
|
|
else:
|
|
return result
|
|
|
|
def _setClosestNodeValue(self, responseMsg, aContact):
|
|
# We are looking for a value, and the remote node didn't have it
|
|
# - mark it as the closest "empty" node, if it is
|
|
if 'closestNodeNoValue' in self.find_value_result:
|
|
if self._is_closer(responseMsg):
|
|
self.find_value_result['closestNodeNoValue'] = aContact
|
|
else:
|
|
self.find_value_result['closestNodeNoValue'] = aContact
|
|
|
|
def _is_closer(self, responseMsg):
|
|
return self.distance.is_closer(responseMsg.nodeID, self.active_contacts[0].id)
|
|
|
|
def _addIfValid(self, contactTriple):
|
|
if isinstance(contactTriple, (list, tuple)) and len(contactTriple) == 3:
|
|
testContact = Contact(
|
|
contactTriple[0], contactTriple[1], contactTriple[2], self.node._protocol)
|
|
if testContact not in self.shortlist:
|
|
self.shortlist.append(testContact)
|
|
|
|
def removeFromShortlist(self, failure, deadContactID):
|
|
""" @type failure: twisted.python.failure.Failure """
|
|
failure.trap(protocol.TimeoutError)
|
|
if len(deadContactID) != constants.key_bits / 8:
|
|
raise ValueError("invalid lbry id")
|
|
if deadContactID in self.shortlist:
|
|
self.shortlist.remove(deadContactID)
|
|
return deadContactID
|
|
|
|
def cancelActiveProbe(self, contactID):
|
|
self.active_probes.pop()
|
|
if len(self.active_probes) <= constants.alpha / 2 and len(self.pending_iteration_calls):
|
|
# Force the iteration
|
|
self.pending_iteration_calls[0].cancel()
|
|
del self.pending_iteration_calls[0]
|
|
self.searchIteration()
|
|
|
|
def sortByDistance(self, contact_list):
|
|
"""Sort the list of contacts in order by distance from key"""
|
|
ExpensiveSort(contact_list, self.distance.to_contact).sort()
|
|
|
|
# Send parallel, asynchronous FIND_NODE RPCs to the shortlist of contacts
|
|
def searchIteration(self):
|
|
self.slow_node_count[0] = len(self.active_probes)
|
|
# Sort the discovered active nodes from closest to furthest
|
|
self.sortByDistance(self.active_contacts)
|
|
# This makes sure a returning probe doesn't force calling this function by mistake
|
|
while len(self.pending_iteration_calls):
|
|
del self.pending_iteration_calls[0]
|
|
# See if should continue the search
|
|
if self.key in self.find_value_result:
|
|
self.outer_d.callback(self.find_value_result)
|
|
return
|
|
elif len(self.active_contacts) and self.find_value is False:
|
|
if self._is_all_done():
|
|
# TODO: Re-send the FIND_NODEs to all of the k closest nodes not already queried
|
|
#
|
|
# Ok, we're done; either we have accumulated k active
|
|
# contacts or no improvement in closestNode has been
|
|
# noted
|
|
self.outer_d.callback(self.active_contacts)
|
|
return
|
|
|
|
# The search continues...
|
|
if len(self.active_contacts):
|
|
self.prev_closest_node[0] = self.active_contacts[0]
|
|
contactedNow = 0
|
|
self.sortByDistance(self.shortlist)
|
|
# Store the current shortList length before contacting other nodes
|
|
prevShortlistLength = len(self.shortlist)
|
|
for contact in self.shortlist:
|
|
if contact.id not in self.already_contacted:
|
|
self._probeContact(contact)
|
|
contactedNow += 1
|
|
if contactedNow == constants.alpha:
|
|
break
|
|
if self._should_lookup_active_calls():
|
|
# Schedule the next iteration if there are any active
|
|
# calls (Kademlia uses loose parallelism)
|
|
call = reactor.callLater(constants.iterativeLookupDelay, self.searchIteration)
|
|
self.pending_iteration_calls.append(call)
|
|
# Check for a quick contact response that made an update to the shortList
|
|
elif prevShortlistLength < len(self.shortlist):
|
|
# Ensure that the closest contacts are taken from the updated shortList
|
|
self.searchIteration()
|
|
else:
|
|
# If no probes were sent, there will not be any improvement, so we're done
|
|
self.outer_d.callback(self.active_contacts)
|
|
|
|
def _probeContact(self, contact):
|
|
self.active_probes.append(contact.id)
|
|
rpcMethod = getattr(contact, self.rpc)
|
|
df = rpcMethod(self.key, rawResponse=True)
|
|
df.addCallback(self.extendShortlist)
|
|
df.addErrback(self.removeFromShortlist, contact.id)
|
|
df.addCallback(self.cancelActiveProbe)
|
|
df.addErrback(lambda _: log.exception('Failed to contact %s', contact))
|
|
self.already_contacted.append(contact.id)
|
|
|
|
def _should_lookup_active_calls(self):
|
|
return (
|
|
len(self.active_probes) > self.slow_node_count[0] or
|
|
(
|
|
len(self.shortlist) < constants.k and
|
|
len(self.active_contacts) < len(self.shortlist) and
|
|
len(self.active_probes) > 0
|
|
)
|
|
)
|
|
|
|
def _is_all_done(self):
|
|
return (
|
|
len(self.active_contacts) >= constants.k or
|
|
(
|
|
self.active_contacts[0] == self.prev_closest_node[0] and
|
|
len(self.active_probes) == self.slow_node_count[0]
|
|
)
|
|
)
|
|
|
|
|
|
class ExpensiveSort(object):
|
|
"""Sort a list in place.
|
|
|
|
The result of `key(item)` is cached for each item in the `to_sort`
|
|
list as an optimization. This can be useful when `key` is
|
|
expensive.
|
|
|
|
Attributes:
|
|
to_sort: a list of items to sort
|
|
key: callable, like `key` in normal python sort
|
|
attr: the attribute name used to cache the value on each item.
|
|
"""
|
|
|
|
def __init__(self, to_sort, key, attr='__value'):
|
|
self.to_sort = to_sort
|
|
self.key = key
|
|
self.attr = attr
|
|
|
|
def sort(self):
|
|
self._cacheValues()
|
|
self._sortByValue()
|
|
self._removeValue()
|
|
|
|
def _cacheValues(self):
|
|
for item in self.to_sort:
|
|
setattr(item, self.attr, self.key(item))
|
|
|
|
def _sortByValue(self):
|
|
self.to_sort.sort(key=operator.attrgetter(self.attr))
|
|
|
|
def _removeValue(self):
|
|
for item in self.to_sort:
|
|
delattr(item, self.attr)
|