#!/usr/bin/env python # # This library is free software, distributed under the terms of # the GNU Lesser General Public License Version 3, or any later version. # See the COPYING file included in this archive # # The docstrings in this module contain epytext markup; API documentation # may be created by processing this file with epydoc: http://epydoc.sf.net import hashlib, random, struct, time, math, binascii import argparse from twisted.internet import defer, error import constants import routingtable import datastore import protocol import twisted.internet.reactor import twisted.internet.threads import twisted.python.log from contact import Contact from hashwatcher import HashWatcher import logging log = logging.getLogger(__name__) def rpcmethod(func): """ Decorator to expose Node methods as remote procedure calls Apply this decorator to methods in the Node class (or a subclass) in order to make them remotely callable via the DHT's RPC mechanism. """ func.rpcmethod = True return func class Node(object): """ Local node in the Kademlia network This class represents a single local node in a Kademlia network; in other words, this class encapsulates an Entangled-using application's "presence" in a Kademlia network. In Entangled, all interactions with the Kademlia network by a client application is performed via this class (or a subclass). """ def __init__(self, id=None, udpPort=4000, dataStore=None, routingTableClass=None, networkProtocol=None, lbryid=None, externalIP=None): """ @param dataStore: The data store to use. This must be class inheriting from the C{DataStore} interface (or providing the same API). How the data store manages its data internally is up to the implementation of that data store. @type dataStore: entangled.kademlia.datastore.DataStore @param routingTable: The routing table class to use. Since there exists some ambiguity as to how the routing table should be implemented in Kademlia, a different routing table may be used, as long as the appropriate API is exposed. This should be a class, not an object, in order to allow the Node to pass an auto-generated node ID to the routingtable object upon instantiation (if necessary). @type routingTable: entangled.kademlia.routingtable.RoutingTable @param networkProtocol: The network protocol to use. This can be overridden from the default to (for example) change the format of the physical RPC messages being transmitted. @type networkProtocol: entangled.kademlia.protocol.KademliaProtocol """ if id != None: self.id = id else: self.id = self._generateID() self.lbryid = lbryid self.port = udpPort self._listeningPort = None # object implementing Twisted IListeningPort # This will contain a deferred created when joining the network, to enable publishing/retrieving information from # the DHT as soon as the node is part of the network (add callbacks to this deferred if scheduling such operations # before the node has finished joining the network) self._joinDeferred = None self.next_refresh_call = None self.next_change_token_call = None # Create k-buckets (for storing contacts) #self._buckets = [] #for i in range(160): # self._buckets.append(kbucket.KBucket()) if routingTableClass == None: self._routingTable = routingtable.OptimizedTreeRoutingTable(self.id) else: self._routingTable = routingTableClass(self.id) # Initialize this node's network access mechanisms if networkProtocol == None: self._protocol = protocol.KademliaProtocol(self) else: self._protocol = networkProtocol # Initialize the data storage mechanism used by this node self.token_secret = self._generateID() self.old_token_secret = None self.change_token() if dataStore == None: self._dataStore = datastore.DictDataStore() else: self._dataStore = dataStore # Try to restore the node's state... if 'nodeState' in self._dataStore: state = self._dataStore['nodeState'] self.id = state['id'] for contactTriple in state['closestNodes']: contact = Contact(contactTriple[0], contactTriple[1], contactTriple[2], self._protocol) self._routingTable.addContact(contact) self.externalIP = externalIP self.hash_watcher = HashWatcher() def __del__(self): #self._persistState() if self._listeningPort is not None: self._listeningPort.stopListening() def stop(self): #cancel callLaters: if self.next_refresh_call is not None: self.next_refresh_call.cancel() self.next_refresh_call = None if self.next_change_token_call is not None: self.next_change_token_call.cancel() self.next_change_token_call = None if self._listeningPort is not None: self._listeningPort.stopListening() self.hash_watcher.stop() def joinNetwork(self, knownNodeAddresses=None): """ Causes the Node to join the Kademlia network; normally, this should be called before any other DHT operations. @param knownNodeAddresses: A sequence of tuples containing IP address information for existing nodes on the Kademlia network, in the format: C{(, (udp port>)} @type knownNodeAddresses: tuple """ # Prepare the underlying Kademlia protocol if self.port is not None: try: self._listeningPort = twisted.internet.reactor.listenUDP(self.port, self._protocol) except error.CannotListenError as e: import traceback log.error("Couldn't bind to port %d. %s", self.port, traceback.format_exc()) raise ValueError("%s lbrynet may already be running." % str(e)) #IGNORE:E1101 # Create temporary contact information for the list of addresses of known nodes if knownNodeAddresses != None: bootstrapContacts = [] for address, port in knownNodeAddresses: contact = Contact(self._generateID(), address, port, self._protocol) bootstrapContacts.append(contact) else: bootstrapContacts = None # Initiate the Kademlia joining sequence - perform a search for this node's own ID self._joinDeferred = self._iterativeFind(self.id, bootstrapContacts) # #TODO: Refresh all k-buckets further away than this node's closest neighbour # def getBucketAfterNeighbour(*args): # for i in range(160): # if len(self._buckets[i]) > 0: # return i+1 # return 160 # df.addCallback(getBucketAfterNeighbour) # df.addCallback(self._refreshKBuckets) #protocol.reactor.callLater(10, self.printContacts) #self._joinDeferred.addCallback(self._persistState) #self._joinDeferred.addCallback(self.printContacts) # Start refreshing k-buckets periodically, if necessary self.next_refresh_call = twisted.internet.reactor.callLater(constants.checkRefreshInterval, self._refreshNode) #IGNORE:E1101 self.hash_watcher.tick() return self._joinDeferred def printContacts(self, *args): print '\n\nNODE CONTACTS\n===============' for i in range(len(self._routingTable._buckets)): for contact in self._routingTable._buckets[i]._contacts: print contact print '==================================' #twisted.internet.reactor.callLater(10, self.printContacts) def getApproximateTotalDHTNodes(self): # get the deepest bucket and the number of contacts in that bucket and multiply it # by the number of equivalently deep buckets in the whole DHT to get a really bad # estimate! bucket = self._routingTable._buckets[self._routingTable._kbucketIndex(self.id)] num_in_bucket = len(bucket._contacts) factor = (2**constants.key_bits) / (bucket.rangeMax - bucket.rangeMin) return num_in_bucket * factor def getApproximateTotalHashes(self): # Divide the number of hashes we know about by k to get a really, really, really # bad estimate of the average number of hashes per node, then multiply by the # approximate number of nodes to get a horrendous estimate of the total number # of hashes in the DHT num_in_data_store = len(self._dataStore._dict) if num_in_data_store == 0: return 0 return num_in_data_store * self.getApproximateTotalDHTNodes() / 8 def announceHaveBlob(self, key, port): return self.iterativeAnnounceHaveBlob(key, {'port': port, 'lbryid': self.lbryid}) def getPeersForBlob(self, blob_hash): def expand_and_filter(result): expanded_peers = [] if type(result) == dict: if blob_hash in result: for peer in result[blob_hash]: #print peer if self.lbryid != peer[6:]: host = ".".join([str(ord(d)) for d in peer[:4]]) if host == "127.0.0.1": if "from_peer" in result: if result["from_peer"] != "self": host = result["from_peer"] port, = struct.unpack('>H', peer[4:6]) expanded_peers.append((host, port)) return expanded_peers def find_failed(err): #print "An exception occurred in the DHT" #print err.getErrorMessage() return [] d = self.iterativeFindValue(blob_hash) d.addCallbacks(expand_and_filter, find_failed) return d def get_most_popular_hashes(self, num_to_return): return self.hash_watcher.most_popular_hashes(num_to_return) def iterativeAnnounceHaveBlob(self, blob_hash, value): known_nodes = {} def log_error(err, n): log.debug("error storing blob_hash %s at %s", binascii.hexlify(blob_hash), str(n)) log.debug(binascii.hexlify(err.getErrorMessage())) log.debug(err.getTraceback()) def log_success(res): log.debug("Response to store request: %s", str(res)) return res def announce_to_peer(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 not responseMsg.nodeID in known_nodes: return responseMsg.nodeID n = known_nodes[responseMsg.nodeID] result = responseMsg.response if 'token' in result: #print "Printing result...", result value['token'] = result['token'] d = n.store(blob_hash, value, self.id, 0) d.addCallback(log_success) d.addErrback(log_error, n) else: d = defer.succeed(False) #else: # print "result:", result # print "No token where it should be" return d def requestPeers(contacts): if self.externalIP is not None and len(contacts) >= constants.k: if self._routingTable.distance(blob_hash, self.id) < self._routingTable.distance(blob_hash, contacts[-1].id): contacts.pop() self.store(blob_hash, value, self_store=True, originalPublisherID=self.id) elif self.externalIP is not None: #print "attempting to self-store" self.store(blob_hash, value, self_store=True, originalPublisherID=self.id) ds = [] for contact in contacts: known_nodes[contact.id] = contact rpcMethod = getattr(contact, "findValue") df = rpcMethod(blob_hash, rawResponse=True) df.addCallback(announce_to_peer) df.addErrback(log_error, contact) ds.append(df) return defer.DeferredList(ds) d = self.iterativeFindNode(blob_hash) d.addCallbacks(requestPeers) return d def change_token(self): self.old_token_secret = self.token_secret self.token_secret = self._generateID() self.next_change_token_call = twisted.internet.reactor.callLater(constants.tokenSecretChangeInterval, self.change_token) def make_token(self, compact_ip): h = hashlib.new('sha384') h.update(self.token_secret + compact_ip) return h.digest() def verify_token(self, token, compact_ip): h = hashlib.new('sha384') h.update(self.token_secret + compact_ip) if not token == h.digest(): h = hashlib.new('sha384') h.update(self.old_token_secret + compact_ip) if not token == h.digest(): #print 'invalid token found' return False return True # def iterativeStore(self, key, value, originalPublisherID=None, age=0): # """ This is deprecated. Use iterativeAnnounceHaveBlob instead. # # The Kademlia store operation # # Call this to store/republish data in the DHT. # # @param key: The hashtable key of the data # @type key: str # @param value: The actual data (the value associated with C{key}) # @type value: str # @param originalPublisherID: The node ID of the node that is the # B{original} publisher of the data # @type originalPublisherID: str # @param age: The relative age of the data (time in seconds since it was # originally published). Note that the original publish time # isn't actually given, to compensate for clock skew between # different nodes. # @type age: int # """ # #print ' iterativeStore called' # if originalPublisherID == None: # originalPublisherID = self.id # # def log_error(err): # log.error(err.getErrorMessage()) # # # Prepare a callback for doing "STORE" RPC calls # def executeStoreRPCs(nodes): # #print ' .....execStoreRPCs called' # if len(nodes) >= constants.k: # # If this node itself is closer to the key than the last (furthest) node in the list, # # we should store the value at ourselves as well # if self._routingTable.distance(key, self.id) < self._routingTable.distance(key, nodes[-1].id): # nodes.pop() # self.store(key, value, originalPublisherID=originalPublisherID, age=age) # else: # self.store(key, value, originalPublisherID=originalPublisherID, age=age) # for contact in nodes: # d = contact.store(key, value, originalPublisherID, age) # d.addErrback(log_error) # return nodes # # Find k nodes closest to the key... # df = self.iterativeFindNode(key) # # ...and send them STORE RPCs as soon as they've been found # df.addCallback(executeStoreRPCs) # return df def iterativeFindNode(self, key): """ The basic Kademlia node lookup operation Call this to find a remote node in the P2P overlay network. @param key: the n-bit key (i.e. the node or value ID) to search for @type key: str @return: This immediately returns a deferred object, which will return a list of k "closest" contacts (C{kademlia.contact.Contact} objects) to the specified key as soon as the operation is finished. @rtype: twisted.internet.defer.Deferred """ return self._iterativeFind(key) def iterativeFindValue(self, key): """ The Kademlia search operation (deterministic) Call this to retrieve data from the DHT. @param key: the n-bit key (i.e. the value ID) to search for @type key: str @return: This immediately returns a deferred object, which will return either one of two things: - If the value was found, it will return a Python dictionary containing the searched-for key (the C{key} parameter passed to this method), and its associated value, in the format: C{key: data_value} - If the value was not found, it will return a list of k "closest" contacts (C{kademlia.contact.Contact} objects) to the specified key @rtype: twisted.internet.defer.Deferred """ # Prepare a callback for this operation outerDf = defer.Deferred() def checkResult(result): if type(result) == dict: # We have found the value; now see who was the closest contact without it... # if 'closestNodeNoValue' in result: # ...and store the key/value pair # contact = result['closestNodeNoValue'] # contact.store(key, result[key]) outerDf.callback(result) else: # The value wasn't found, but a list of contacts was returned # Now, see if we have the value (it might seem wasteful to search on the network # first, but it ensures that all values are properly propagated through the # network #if key in self._dataStore: if self._dataStore.hasPeersForBlob(key): # Ok, we have the value locally, so use that peers = self._dataStore.getPeersForBlob(key) # Send this value to the closest node without it #if len(result) > 0: # contact = result[0] # contact.store(key, value) outerDf.callback({key: peers, "from_peer": 'self'}) else: # Ok, value does not exist in DHT at all outerDf.callback(result) # Execute the search df = self._iterativeFind(key, rpc='findValue') df.addCallback(checkResult) return outerDf def addContact(self, contact): """ Add/update the given contact; simple wrapper for the same method in this object's RoutingTable object @param contact: The contact to add to this node's k-buckets @type contact: kademlia.contact.Contact """ self._routingTable.addContact(contact) def removeContact(self, contactID): """ Remove the contact with the specified node ID from this node's table of known nodes. This is a simple wrapper for the same method in this object's RoutingTable object @param contactID: The node ID of the contact to remove @type contactID: str """ self._routingTable.removeContact(contactID) def findContact(self, contactID): """ Find a entangled.kademlia.contact.Contact object for the specified cotact ID @param contactID: The contact ID of the required Contact object @type contactID: str @return: Contact object of remote node with the specified node ID, or None if the contact was not found @rtype: twisted.internet.defer.Deferred """ try: contact = self._routingTable.getContact(contactID) df = defer.Deferred() df.callback(contact) except ValueError: def parseResults(nodes): if contactID in nodes: contact = nodes[nodes.index(contactID)] return contact else: return None df = self.iterativeFindNode(contactID) df.addCallback(parseResults) return df @rpcmethod def ping(self): """ Used to verify contact between two Kademlia nodes @rtype: str """ return 'pong' @rpcmethod def store(self, key, value, originalPublisherID=None, self_store=False, **kwargs): """ Store the received data in this node's local hash table @param key: The hashtable key of the data @type key: str @param value: The actual data (the value associated with C{key}) @type value: str @param originalPublisherID: The node ID of the node that is the B{original} publisher of the data @type originalPublisherID: str @param age: The relative age of the data (time in seconds since it was originally published). Note that the original publish time isn't actually given, to compensate for clock skew between different nodes. @type age: int @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 == 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.id, self.externalIP, self.port, None, None) compact_ip = contact.compact_ip() elif '_rpcNodeContact' in kwargs: contact = kwargs['_rpcNodeContact'] #print contact.address compact_ip = contact.compact_ip() #print compact_ip else: return 'Not OK' #raise TypeError, 'No contact info available' if ((self_store is False) and (not 'token' in value or not self.verify_token(value['token'], compact_ip))): #if not 'token' in value: # print "Couldn't find token in value" #elif not self.verify_token(value['token'], contact.compact_ip()): # print "Token is invalid" 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: raise ValueError, 'Invalid lbryid' else: compact_address = compact_ip + compact_port + value['lbryid'] else: raise TypeError, 'No lbryid given' #if originalPublisherID == None: #if rpcSenderID != None: # originalPublisherID = rpcSenderID #else: # raise TypeError, 'No publisher specifed, and RPC caller ID not available. Data requires an original publisher.' #if self_store is True: # print "got this far" now = int(time.time()) originallyPublished = now# - age #print compact_address self._dataStore.addPeerToBlob(key, compact_address, now, originallyPublished, originalPublisherID) #if self_store is True: # print "looks like it was successful maybe" 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: rpcSenderID = kwargs['_rpcNodeID'] else: rpcSenderID = None contacts = self._routingTable.findCloseNodes(key, constants.k, rpcSenderID) contactTriples = [] for contact in contacts: contactTriples.append( (contact.id, contact.address, contact.port) ) return contactTriples @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: contactTriples = self.findNode(key, **kwargs) rval = {'contacts': contactTriples} 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, compact_ip) return rval # def _distance(self, keyOne, keyTwo): # """ Calculate the XOR result between two string variables # # @return: XOR result of two long variables # @rtype: long # """ # valKeyOne = long(keyOne.encode('hex'), 16) # valKeyTwo = long(keyTwo.encode('hex'), 16) # return valKeyOne ^ valKeyTwo def _generateID(self): """ Generates an n-bit pseudo-random identifier @return: A globally unique n-bit pseudo-random identifier @rtype: str """ hash = hashlib.sha384() hash.update(str(random.getrandbits(255))) return hash.digest() 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 """ if rpc != 'findNode': findValue = True else: findValue = False shortlist = [] if startupShortlist == None: shortlist = self._routingTable.findCloseNodes(key, constants.alpha) if key != self.id: # Update the "last accessed" timestamp for the appropriate k-bucket self._routingTable.touchKBucket(key) if len(shortlist) == 0: # This node doesn't know of any other nodes fakeDf = defer.Deferred() fakeDf.callback([]) return fakeDf else: # This is used during the bootstrap process; node ID's are most probably fake shortlist = startupShortlist # List of active queries; len() indicates number of active probes # - using lists for these variables, because Python doesn't allow binding a new value to a name in an enclosing (non-global) scope activeProbes = [] # List of contact IDs that have already been queried alreadyContacted = [] # Probes that were active during the previous iteration # A list of found and known-to-be-active remote nodes activeContacts = [] # This should only contain one entry; the next scheduled iteration call pendingIterationCalls = [] prevClosestNode = [None] findValueResult = {} slowNodeCount = [0] def extendShortlist(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 activeContacts or responseMsg.nodeID == self.id: return responseMsg.nodeID # Mark this node as active if responseMsg.nodeID in shortlist: # Get the contact information from the shortlist... aContact = shortlist[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 aContact = Contact(responseMsg.nodeID, originAddress[0], originAddress[1], self._protocol) activeContacts.append(aContact) # This makes sure "bootstrap"-nodes with "fake" IDs don't get queried twice if responseMsg.nodeID not in alreadyContacted: alreadyContacted.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 findValue is True and key in result and not 'contacts' in result: # We have found the value findValueResult[key] = result[key] findValueResult['from_peer'] = aContact.address else: if findValue is True: # 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 findValueResult: if self._routingTable.distance(key, responseMsg.nodeID) < self._routingTable.distance(key, activeContacts[0].id): findValueResult['closestNodeNoValue'] = aContact else: findValueResult['closestNodeNoValue'] = aContact contactTriples = result['contacts'] else: contactTriples = result for contactTriple in contactTriples: if isinstance(contactTriple, (list, tuple)) and len(contactTriple) == 3: testContact = Contact(contactTriple[0], contactTriple[1], contactTriple[2], self._protocol) if testContact not in shortlist: shortlist.append(testContact) return responseMsg.nodeID def removeFromShortlist(failure): """ @type failure: twisted.python.failure.Failure """ failure.trap(protocol.TimeoutError) deadContactID = failure.getErrorMessage() if deadContactID in shortlist: shortlist.remove(deadContactID) return deadContactID def cancelActiveProbe(contactID): activeProbes.pop() if len(activeProbes) <= constants.alpha/2 and len(pendingIterationCalls): # Force the iteration pendingIterationCalls[0].cancel() del pendingIterationCalls[0] #print 'forcing iteration =================' searchIteration() def log_error(err): log.error(err.getErrorMessage()) # Send parallel, asynchronous FIND_NODE RPCs to the shortlist of contacts def searchIteration(): #print '==> searchiteration' slowNodeCount[0] = len(activeProbes) # Sort the discovered active nodes from closest to furthest activeContacts.sort(lambda firstContact, secondContact, targetKey=key: cmp(self._routingTable.distance(firstContact.id, targetKey), self._routingTable.distance(secondContact.id, targetKey))) # This makes sure a returning probe doesn't force calling this function by mistake while len(pendingIterationCalls): del pendingIterationCalls[0] # See if should continue the search if key in findValueResult: #print '++++++++++++++ DONE (findValue found) +++++++++++++++\n\n' outerDf.callback(findValueResult) return elif len(activeContacts) and findValue == False: if (len(activeContacts) >= constants.k) or (activeContacts[0] == prevClosestNode[0] and len(activeProbes) == slowNodeCount[0]): # 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 #if len(activeContacts) >= constants.k: # print '++++++++++++++ DONE (test for k active contacts) +++++++++++++++\n\n' #else: # print '++++++++++++++ DONE (test for closest node) +++++++++++++++\n\n' outerDf.callback(activeContacts) return # The search continues... if len(activeContacts): prevClosestNode[0] = activeContacts[0] contactedNow = 0 shortlist.sort(lambda firstContact, secondContact, targetKey=key: cmp(self._routingTable.distance(firstContact.id, targetKey), self._routingTable.distance(secondContact.id, targetKey))) # Store the current shortList length before contacting other nodes prevShortlistLength = len(shortlist) for contact in shortlist: if contact.id not in alreadyContacted: activeProbes.append(contact.id) rpcMethod = getattr(contact, rpc) df = rpcMethod(key, rawResponse=True) df.addCallback(extendShortlist) df.addErrback(removeFromShortlist) df.addCallback(cancelActiveProbe) df.addErrback(log_error) alreadyContacted.append(contact.id) contactedNow += 1 if contactedNow == constants.alpha: break if len(activeProbes) > slowNodeCount[0] \ or (len(shortlist) < constants.k and len(activeContacts) < len(shortlist) and len(activeProbes) > 0): #print '----------- scheduling next call -------------' # Schedule the next iteration if there are any active calls (Kademlia uses loose parallelism) call = twisted.internet.reactor.callLater(constants.iterativeLookupDelay, searchIteration) #IGNORE:E1101 pendingIterationCalls.append(call) # Check for a quick contact response that made an update to the shortList elif prevShortlistLength < len(shortlist): # Ensure that the closest contacts are taken from the updated shortList searchIteration() else: #print '++++++++++++++ DONE (logically) +++++++++++++\n\n' # If no probes were sent, there will not be any improvement, so we're done outerDf.callback(activeContacts) outerDf = defer.Deferred() # Start the iterations searchIteration() return outerDf # def _kbucketIndex(self, key): # """ Calculate the index of the k-bucket which is responsible for the # specified key # # @param key: The key for which to find the appropriate k-bucket index # @type key: str # # @return: The index of the k-bucket responsible for the specified key # @rtype: int # """ # distance = self._distance(self.id, key) # bucketIndex = int(math.log(distance, 2)) # return bucketIndex # def _randomIDInBucketRange(self, bucketIndex): # """ Returns a random ID in the specified k-bucket's range # # @param bucketIndex: The index of the k-bucket to use # @type bucketIndex: int # """ # def makeIDString(distance): # id = hex(distance)[2:] # if id[-1] == 'L': # id = id[:-1] # if len(id) % 2 != 0: # id = '0' + id # id = id.decode('hex') # id = (20 - len(id))*'\x00' + id # return id # min = math.pow(2, bucketIndex) # max = math.pow(2, bucketIndex+1) # distance = random.randrange(min, max) # distanceStr = makeIDString(distance) # randomID = makeIDString(self._distance(distanceStr, self.id)) # return randomID # def _refreshKBuckets(self, startIndex=0, force=False): # """ Refreshes all k-buckets that need refreshing, starting at the # k-bucket with the specified index # # @param startIndex: The index of the bucket to start refreshing at; # this bucket and those further away from it will # be refreshed. For example, when joining the # network, this node will set this to the index of # the bucket after the one containing it's closest # neighbour. # @type startIndex: index # @param force: If this is C{True}, all buckets (in the specified range) # will be refreshed, regardless of the time they were last # accessed. # @type force: bool # """ # #print '_refreshKbuckets called with index:',startIndex # bucketIndex = [] # bucketIndex.append(startIndex + 1) # outerDf = defer.Deferred() # def refreshNextKBucket(dfResult=None): # #print ' refreshNexKbucket called; bucketindex is', bucketIndex[0] # bucketIndex[0] += 1 # while bucketIndex[0] < 160: # if force or (int(time.time()) - self._buckets[bucketIndex[0]].lastAccessed >= constants.refreshTimeout): # searchID = self._randomIDInBucketRange(bucketIndex[0]) # self._buckets[bucketIndex[0]].lastAccessed = int(time.time()) # #print ' refreshing bucket',bucketIndex[0] # df = self.iterativeFindNode(searchID) # df.addCallback(refreshNextKBucket) # return # else: # bucketIndex[0] += 1 # # If this is reached, we have refreshed all the buckets # #print ' all buckets refreshed; initiating outer deferred callback' # outerDf.callback(None) # #print '_refreshKbuckets starting cycle' # refreshNextKBucket() # #print '_refreshKbuckets returning' # return outerDf #def _persistState(self, *args): # state = {'id': self.id, # 'closestNodes': self.findNode(self.id)} # now = int(time.time()) # self._dataStore.setItem('nodeState', state, now, now, self.id) def _refreshNode(self): """ Periodically called to perform k-bucket refreshes and data replication/republishing as necessary """ #print 'refreshNode called' df = self._refreshRoutingTable() #df.addCallback(self._republishData) df.addCallback(self._removeExpiredPeers) df.addCallback(self._scheduleNextNodeRefresh) def _refreshRoutingTable(self): nodeIDs = self._routingTable.getRefreshList(0, False) outerDf = defer.Deferred() def searchForNextNodeID(dfResult=None): if len(nodeIDs) > 0: searchID = nodeIDs.pop() df = self.iterativeFindNode(searchID) df.addCallback(searchForNextNodeID) else: # If this is reached, we have finished refreshing the routing table outerDf.callback(None) # Start the refreshing cycle searchForNextNodeID() return outerDf #def _republishData(self, *args): # #print '---republishData() called' # df = twisted.internet.threads.deferToThread(self._threadedRepublishData) # return df def _scheduleNextNodeRefresh(self, *args): #print '==== sheduling next refresh' self.next_refresh_call = twisted.internet.reactor.callLater(constants.checkRefreshInterval, self._refreshNode) def _removeExpiredPeers(self, *args):#args put here because _refreshRoutingTable does outerDF.callback(None) df = twisted.internet.threads.deferToThread(self._dataStore.removeExpiredPeers) return df #def _threadedRepublishData(self, *args): # """ Republishes and expires any stored data (i.e. stored # C{(key, value pairs)} that need to be republished/expired # # This method should run in a deferred thread # """ # #print '== republishData called, node:',ord(self.id[0]) # expiredKeys = [] # for key in self._dataStore: # # Filter internal variables stored in the datastore # if key == 'nodeState': # continue # now = int(time.time()) # originalPublisherID = self._dataStore.originalPublisherID(key) # age = now - self._dataStore.originalPublishTime(key) # #print ' node:',ord(self.id[0]),'key:',ord(key[0]),'orig publishing time:',self._dataStore.originalPublishTime(key),'now:',now,'age:',age,'lastPublished age:',now - self._dataStore.lastPublished(key),'original pubID:', ord(originalPublisherID[0]) # if originalPublisherID == self.id: # # This node is the original publisher; it has to republish # # the data before it expires (24 hours in basic Kademlia) # if age >= constants.dataExpireTimeout: # #print ' REPUBLISHING key:', key # #self.iterativeStore(key, self._dataStore[key]) # twisted.internet.reactor.callFromThread(self.iterativeStore, key, self._dataStore[key]) # else: # # This node needs to replicate the data at set intervals, # # until it expires, without changing the metadata associated with it # # First, check if the data has expired # if age >= constants.dataExpireTimeout: # # This key/value pair has expired (and it has not been republished by the original publishing node # # - remove it # expiredKeys.append(key) # elif now - self._dataStore.lastPublished(key) >= constants.replicateInterval: # # ...data has not yet expired, and we need to replicate it # #print ' replicating key:', key,'age:',age # #self.iterativeStore(key=key, value=self._dataStore[key], originalPublisherID=originalPublisherID, age=age) # twisted.internet.reactor.callFromThread(self.iterativeStore, key=key, value=self._dataStore[key], originalPublisherID=originalPublisherID, age=age) # for key in expiredKeys: # #print ' expiring key:', key # del self._dataStore[key] # #print 'done with threadedDataRefresh()' def main(): parser = argparse.ArgumentParser(description="Launch a dht node") parser.add_argument("udp_port", help="The UDP port on which the node will listen", type=int) parser.add_argument("known_node_ip", help="The IP of a known node to be used to bootstrap into the network", nargs='?') parser.add_argument("known_node_port", help="The port of a known node to be used to bootstrap into the network", nargs='?', default=4000, type=int) args = parser.parse_args() if args.known_node_ip: known_nodes = [(args.known_node_ip, args.known_node_port)] else: known_nodes = [] node = Node(udpPort=args.udp_port) node.joinNetwork(known_nodes) twisted.internet.reactor.run() if __name__ == '__main__': main()