def initWithDict(self, dict):
self._senderDict = dict
self.id = dict['id']
self.num = intify(self.id)
self.port = dict['port']
self.host = dict['host']
return self
def __init__(self, id, host=None, port=None):
"""Initialize the node.
@type id: C{string} or C{dictionary}
@param id: the node's ID in the DHT, or a dictionary containing the
node's id, host and port
@type host: C{string}
@param host: the IP address of the node
(optional, but must be specified if id is not a dictionary)
@type port: C{int}
@param port: the port of the node
(optional, but must be specified if id is not a dictionary)
"""
self.fails = 0
self.lastSeen = datetime(MINYEAR, 1, 1)
# Alternate method, init Node from dictionary
if isinstance(id, dict):
host = id["host"]
port = id["port"]
id = id["id"]
assert isinstance(id, str)
assert isinstance(host, str)
self.id = id
self.num = khash.intify(id)
self.host = host
self.port = int(port)
self.token = ""
self.num_values = 0
self._contactInfo = None
def init(self, id, host, port):
self.id = id
self.num = khash.intify(id)
self.host = host
self.port = port
self._senderDict = {'id': self.id, 'port' : self.port, 'host' : self.host}
return self
def init(self, id, host, port):
self.id = id
self.num = intify(id)
self.host = host
self.port = port
self._senderDict = {'id': self.id, 'port' : self.port, 'host' : self.host}
return self
def initWithDict(self, dict):
self._senderDict = dict
self.id = dict['id']
self.num = khash.intify(self.id)
self.port = dict['port']
self.host = dict['host']
return self
def findNodes(self, id):
"""
Return K nodes in our own local table closest to the ID.
"""
if isinstance(id, str):
num = intify(id)
elif isinstance(id, Node):
num = id.num
elif isinstance(id, int) or isinstance(id, long):
num = id
else:
raise TypeError, "findNodes requires an int, string, or Node"
nodes = []
i = self._bucketIndexForInt(num)
# Get the K closest nodes, even if we have the exact node we're looking for
nodes += self.buckets[i].l
if len(nodes) < K:
# need more nodes
min = i - 1
max = i + 1
while len(nodes) < K and (min >= 0 or max < len(self.buckets)):
#ASw: note that this requires K be even
if min >= 0:
nodes = nodes + self.buckets[min].l
if max < len(self.buckets):
nodes = nodes + self.buckets[max].l
min = min - 1
max = max + 1
nodes.sort(key = lambda x: num ^ x.num)
return nodes[:K]
def getNode(self, id):
"""
Return the node with that ID if it's in our own local table.
"""
if isinstance(id, str):
num = intify(id)
elif isinstance(id, Node):
num = id.num
elif isinstance(id, int) or isinstance(id, long):
num = id
else:
raise TypeError, "getNode requires an int, string, or Node"
i = self._bucketIndexForInt(num)
# if this node is already in our table then return it
try:
index = self.buckets[i].l.index(num)
except ValueError:
pass
else:
return self.buckets[i].l[index]
# don't have the node
return None
def initWithDict(self, dict):
self._senderDict = dict
self.id = dict['id']
self.num = khash.intify(self.id)
self.port = dict['port']
self.host = dict['host']
self.age = dict.get('age', self.age)
return self
def __init__(self,
caller,
target,
callback,
config,
stats,
action,
num_results=None):
"""Initialize the action.
@type caller: L{khashmir.Khashmir}
@param caller: the DHT instance that is performing the action
@type target: C{string}
@param target: the target of the action, usually a DHT key
@type callback: C{method}
@param callback: the method to call with the results
@type config: C{dictionary}
@param config: the configuration variables for the DHT
@type stats: L{stats.StatsLogger}
@param stats: the statistics gatherer
@type action: C{string}
@param action: the name of the action to call on remote nodes
@type num_results: C{int}
@param num_results: the minimum number of results that are needed before
the action should stop (optional, defaults to getting all the results)
"""
self.caller = caller
self.target = target
self.config = config
self.action = action
self.stats = stats
self.stats.startedAction(action)
self.num = intify(target)
self.queried = {}
self.answered = {}
self.failed = {}
self.found = {}
self.sorted_nodes = []
self.results = {}
self.desired_results = num_results
self.callback = callback
self.outstanding = {}
self.outstanding_results = 0
self.finished = False
self.started = datetime.now()
def sort(a, b, num=self.num):
"""Sort nodes relative to the ID we are looking for."""
x, y = num ^ a.num, num ^ b.num
if x > y:
return 1
elif x < y:
return -1
return 0
self.sort = sort
def __init__(self, table, target, callback, callLater):
self.table = table
self.target = target
self.callLater = callLater
self.num = intify(target)
self.found = {}
self.foundq = []
self.queried = {}
self.queriedip = {}
self.answered = {}
self.callback = callback
self.outstanding = 0
self.finished = 0
def __init__(self, table, target, callback, callLater):
self.table = table
self.target = target
self.callLater = callLater
self.num = intify(target)
self.found = {}
self.foundq = []
self.queried = {}
self.queriedip = {}
self.answered = {}
self.callback = callback
self.outstanding = 0
self.finished = 0
def __init__(self, caller, target, callback, config, stats, action, num_results = None):
"""Initialize the action.
@type caller: L{khashmir.Khashmir}
@param caller: the DHT instance that is performing the action
@type target: C{string}
@param target: the target of the action, usually a DHT key
@type callback: C{method}
@param callback: the method to call with the results
@type config: C{dictionary}
@param config: the configuration variables for the DHT
@type stats: L{stats.StatsLogger}
@param stats: the statistics gatherer
@type action: C{string}
@param action: the name of the action to call on remote nodes
@type num_results: C{int}
@param num_results: the minimum number of results that are needed before
the action should stop (optional, defaults to getting all the results)
"""
self.caller = caller
self.target = target
self.config = config
self.action = action
self.stats = stats
self.stats.startedAction(action)
self.num = intify(target)
self.queried = {}
self.answered = {}
self.failed = {}
self.found = {}
self.sorted_nodes = []
self.results = {}
self.desired_results = num_results
self.callback = callback
self.outstanding = {}
self.outstanding_results = 0
self.finished = False
self.started = datetime.now()
def sort(a, b, num=self.num):
"""Sort nodes relative to the ID we are looking for."""
x, y = num ^ a.num, num ^ b.num
if x > y:
return 1
elif x < y:
return -1
return 0
self.sort = sort
def findNodes(self, id, invalid=True):
"""
return K nodes in our own local table closest to the ID.
"""
# print 'id:',type(id)
if isinstance(id, str):
num = hash.intify(id)
elif isinstance(id, Node):
num = id.num
elif isinstance(id, int) or isinstance(id, long):
num = id
else:
raise TypeError, "findNodes requires an int, string, or Node"
nodes = []
i = self._bucketIndexForInt(num)
# if this node is already in our table then return it
try:
node = self.buckets[i].getNodeWithInt(num)
except ValueError:
pass
else:
return [node]
# don't have the node, get the K closest nodes
nodes = nodes + self.buckets[i].l
if not invalid:
nodes = [a for a in nodes if not a.invalid]
if len(nodes) < K:
# need more nodes
min = i - 1
max = i + 1
while len(nodes) < K and (min >= 0 or max < len(self.buckets)):
#ASw: note that this requires K be even
if min >= 0:
nodes = nodes + self.buckets[min].l
if max < len(self.buckets):
nodes = nodes + self.buckets[max].l
min = min - 1
max = max + 1
if not invalid:
nodes = [a for a in nodes if not a.invalid]
nodes.sort(lambda a, b, num=num: cmp(num ^ a.num, num ^ b.num))
return nodes[:K]
def findNodes(self, id, invalid=True):
"""
return K nodes in our own local table closest to the ID.
"""
if isinstance(id, str):
num = hash.intify(id)
elif isinstance(id, Node):
num = id.num
elif isinstance(id, int) or isinstance(id, long):
num = id
else:
raise TypeError, "findNodes requires an int, string, or Node"
nodes = []
i = self._bucketIndexForInt(num)
# if this node is already in our table then return it
try:
node = self.buckets[i].getNodeWithInt(num)
except ValueError:
pass
else:
return [node]
# don't have the node, get the K closest nodes
nodes = nodes + self.buckets[i].l
if not invalid:
nodes = [a for a in nodes if not a.invalid]
if len(nodes) < K:
# need more nodes
min = i - 1
max = i + 1
while len(nodes) < K and (min >= 0 or max < len(self.buckets)):
#ASw: note that this requires K be even
if min >= 0:
nodes = nodes + self.buckets[min].l
if max < len(self.buckets):
nodes = nodes + self.buckets[max].l
min = min - 1
max = max + 1
if not invalid:
nodes = [a for a in nodes if not a.invalid]
nodes.sort(lambda a, b, num=num: cmp(num ^ a.num, num ^ b.num))
return nodes[:K]
def _nodeNum(self, id):
"""Takes different types of input and converts to the node ID number.
@type id: C{string} or C{int} or L{node.Node}
@param id: the ID to find nodes that are close to
@raise TypeError: if id does not properly identify an ID
"""
# Get the ID number from the input
if isinstance(id, str):
return khash.intify(id)
elif isinstance(id, Node):
return id.num
elif isinstance(id, int) or isinstance(id, long):
return id
else:
raise TypeError, "requires an int, string, or Node input"
def __init__(self, table, target, callback):
self.table = table
self.target = target
self.num = intify(target)
self.found = {}
self.queried = {}
self.answered = {}
self.callback = callback
self.outstanding = 0
self.finished = 0
def sort(a, b, num=self.num):
""" this function is for sorting nodes relative to the ID we are looking for """
x, y = num ^ a.num, num ^ b.num
if x > y:
return 1
elif x < y:
return -1
return 0
self.sort = sort
