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, node_id=None, udpPort=4000, dataStore=None,
routingTableClass=None, networkProtocol=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
"""
self.node_id = node_id or self._generateID()
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.change_token_lc = task.LoopingCall(self.change_token)
# Create k-buckets (for storing contacts)
if routingTableClass is None:
self._routingTable = routingtable.OptimizedTreeRoutingTable(self.node_id)
else:
self._routingTable = routingTableClass(self.node_id)
# Initialize this node's network access mechanisms
if networkProtocol is 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
if dataStore is 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.node_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):
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.change_token_lc.running:
self.change_token_lc.stop()
if self._listeningPort is not None:
self._listeningPort.stopListening()
self.hash_watcher.stop()
@defer.inlineCallbacks
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{(<ip address>, (udp port>)}
@type knownNodeAddresses: tuple
"""
# Prepare the underlying Kademlia protocol
if self.port is not None:
try:
self._listeningPort = 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
# Start the token looping call
self.change_token_lc.start(constants.tokenSecretChangeInterval)
# Initiate the Kademlia joining sequence - perform a search for this node's own ID
self._joinDeferred = self._iterativeFind(self.node_id, bootstrapContacts)
# #TODO: Refresh all k-buckets further away than this node's closest neighbour
# Start refreshing k-buckets periodically, if necessary
self.next_refresh_call = reactor.callLater(constants.checkRefreshInterval,
self._refreshNode)
self.hash_watcher.tick()
yield self._joinDeferred
@property
def contacts(self):
def _inner():
for i in range(len(self._routingTable._buckets)):
for contact in self._routingTable._buckets[i]._contacts:
yield contact
return list(_inner())
def printContacts(self, *args):
print '\n\nNODE CONTACTS\n==============='
for i in range(len(self._routingTable._buckets)):
print "bucket %i" % i
for contact in self._routingTable._buckets[i]._contacts:
print " %s:%i" % (contact.address, contact.port)
print '=================================='
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.node_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.node_id})
@defer.inlineCallbacks
def getPeersForBlob(self, blob_hash):
result = yield self.iterativeFindValue(blob_hash)
expanded_peers = []
if result:
if blob_hash in result:
for peer in result[blob_hash]:
if self.node_id != peer[6:]:
host = ".".join([str(ord(d)) for d in peer[:4]])
if host == "127.0.0.1" and "from_peer" in result \
and result["from_peer"] != "self":
host = result["from_peer"]
port, = struct.unpack('>H', peer[4:6])
if (host, port) not in expanded_peers:
expanded_peers.append((host, port))
defer.returnValue(expanded_peers)
def get_most_popular_hashes(self, num_to_return):
return self.hash_watcher.most_popular_hashes(num_to_return)
def get_bandwidth_stats(self):
return self._protocol.bandwidth_stats
def iterativeAnnounceHaveBlob(self, blob_hash, value):
known_nodes = {}
def log_error(err, n):
if err.check(protocol.TimeoutError):
log.debug(
"Timeout while storing blob_hash %s at %s",
binascii.hexlify(blob_hash), n)
else:
log.error(
"Unexpected error while storing blob_hash %s at %s: %s",
binascii.hexlify(blob_hash), n, err.getErrorMessage())
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:
value['token'] = result['token']
d = n.store(blob_hash, value, self.node_id, 0)
d.addCallback(log_success)
d.addErrback(log_error, n)
else:
d = defer.succeed(False)
return d
def requestPeers(contacts):
if self.externalIP is not None and len(contacts) >= constants.k:
is_closer = Distance(blob_hash).is_closer(self.node_id, contacts[-1].id)
if is_closer:
contacts.pop()
self.store(blob_hash, value, self_store=True, originalPublisherID=self.node_id)
elif self.externalIP is not None:
self.store(blob_hash, value, self_store=True, originalPublisherID=self.node_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()
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():
return False
return True
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)
@defer.inlineCallbacks
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{<str>key: <str>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 isinstance(result, dict):
# We have found the value; now see who was the closest contact without it...
# ...and store the key/value pair
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 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
outerDf.callback({key: peers, "from_peer": 'self'})
else:
# Ok, value does not exist in DHT at all
outerDf.callback(result)
# Execute the search
iterative_find_result = yield self._iterativeFind(key, rpc='findValue')
checkResult(iterative_find_result)
result = yield outerDf
defer.returnValue(result)
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 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)
def _refreshNode(self):
""" Periodically called to perform k-bucket refreshes and data
replication/republishing as necessary """
df = self._refreshRoutingTable()
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 _scheduleNextNodeRefresh(self, *args):
self.next_refresh_call = reactor.callLater(constants.checkRefreshInterval,
self._refreshNode)
# args put here because _refreshRoutingTable does outerDF.callback(None)
def _removeExpiredPeers(self, *args):
df = threads.deferToThread(self._dataStore.removeExpiredPeers)
return df
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)
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):
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{(<ip address>, (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
# 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 '=================================='
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]:
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):
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):
if err.check(protocol.TimeoutError):
log.debug(
"Timeout while storing blob_hash %s at %s",
binascii.hexlify(blob_hash), n)
else:
log.error(
"Unexpected error while storing blob_hash %s at %s: %s",
binascii.hexlify(blob_hash), n, err.getErrorMessage())
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:
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)
return d
def requestPeers(contacts):
if self.externalIP is not None and len(contacts) >= constants.k:
is_closer = Distance(blob_hash).is_closer(self.id, contacts[-1].id)
if is_closer:
contacts.pop()
self.store(blob_hash, value, self_store=True, originalPublisherID=self.id)
elif self.externalIP is not None:
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():
return False
return True
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{<str>key: <str>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...
# ...and store the key/value pair
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 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
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']
compact_ip = contact.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))):
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'
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:
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 _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
outerDf = defer.Deferred()
helper = _IterativeFindHelper(self, outerDf, shortlist, key, findValue, rpc)
# Start the iterations
helper.searchIteration()
return outerDf
def _refreshNode(self):
""" Periodically called to perform k-bucket refreshes and data
replication/republishing as necessary """
df = self._refreshRoutingTable()
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 _scheduleNextNodeRefresh(self, *args):
self.next_refresh_call = twisted.internet.reactor.callLater(
constants.checkRefreshInterval, self._refreshNode)
#args put here because _refreshRoutingTable does outerDF.callback(None)
def _removeExpiredPeers(self, *args):
df = twisted.internet.threads.deferToThread(self._dataStore.removeExpiredPeers)
return df
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{(<ip address>, (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.error("error storing blob_hash %s at %s", binascii.hexlify(blob_hash), str(n))
log.error(binascii.hexlify(err.getErrorMessage()))
log.error(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{<str>key: <str>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 is not None:
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
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{(<ip address>, (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(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{<str>key: <str>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