import asyncio
import random
import logging
import typing
import itertools
from prometheus_client import Gauge
from lbry import utils
from lbry.dht import constants
from lbry.dht.error import RemoteException
from lbry.dht.protocol.distance import Distance
if typing.TYPE_CHECKING:
from lbry.dht.peer import KademliaPeer, PeerManager
log = logging.getLogger(__name__)
class KBucket:
"""
Kademlia K-bucket implementation.
"""
peer_in_routing_table_metric = Gauge(
"peers_in_routing_table", "Number of peers on routing table", namespace="dht_node",
labelnames=("scope",)
)
peer_with_x_bit_colliding_metric = Gauge(
"peer_x_bit_colliding", "Number of peers with at least X bits colliding with this node id",
namespace="dht_node", labelnames=("amount",)
)
def __init__(self, peer_manager: 'PeerManager', range_min: int, range_max: int,
node_id: bytes, capacity: int = constants.K):
"""
@param range_min: The lower boundary for the range in the n-bit ID
space covered by this k-bucket
@param range_max: The upper boundary for the range in the ID space
covered by this k-bucket
"""
self._peer_manager = peer_manager
self.range_min = range_min
self.range_max = range_max
self.peers: typing.List['KademliaPeer'] = []
self._node_id = node_id
self._distance_to_self = Distance(node_id)
self.capacity = capacity
def add_peer(self, peer: 'KademliaPeer') -> bool:
""" Add contact to _contact list in the right order. This will move the
contact to the end of the k-bucket if it is already present.
@raise kademlia.kbucket.BucketFull: Raised when the bucket is full and
the contact isn't in the bucket
already
@param peer: The contact to add
@type peer: dht.contact._Contact
"""
if peer in self.peers:
# Move the existing contact to the end of the list
# - using the new contact to allow add-on data
# (e.g. optimization-specific stuff) to pe updated as well
self.peers.remove(peer)
self.peers.append(peer)
return True
else:
for i, _ in enumerate(self.peers):
local_peer = self.peers[i]
if local_peer.node_id == peer.node_id:
self.peers.remove(local_peer)
self.peers.append(peer)
return True
if len(self.peers) < self.capacity:
self.peers.append(peer)
self.peer_in_routing_table_metric.labels("global").inc()
bits_colliding = utils.get_colliding_prefix_bits(peer.node_id, self._node_id)
self.peer_with_x_bit_colliding_metric.labels(amount=bits_colliding).inc()
return True
else:
return False
def get_peer(self, node_id: bytes) -> 'KademliaPeer':
for peer in self.peers:
if peer.node_id == node_id:
return peer
def get_peers(self, count=-1, exclude_contact=None, sort_distance_to=None) -> typing.List['KademliaPeer']:
""" Returns a list containing up to the first count number of contacts
@param count: The amount of contacts to return (if 0 or less, return
all contacts)
@type count: int
@param exclude_contact: A node node_id to exclude; if this contact is in
the list of returned values, it will be
discarded before returning. If a C{str} is
passed as this argument, it must be the
contact's ID.
@type exclude_contact: str
@param sort_distance_to: Sort distance to the node_id, defaulting to the parent node node_id. If False don't
sort the contacts
@raise IndexError: If the number of requested contacts is too large
@return: Return up to the first count number of contacts in a list
If no contacts are present an empty is returned
@rtype: list
"""
peers = [peer for peer in self.peers if peer.node_id != exclude_contact]
# Return all contacts in bucket
if count <= 0:
count = len(peers)
# Get current contact number
current_len = len(peers)
# If count greater than k - return only k contacts
if count > constants.K:
count = constants.K
if not current_len:
return peers
if sort_distance_to is False:
pass
else:
sort_distance_to = sort_distance_to or self._node_id
peers.sort(key=lambda c: Distance(sort_distance_to)(c.node_id))
return peers[:min(current_len, count)]
def get_bad_or_unknown_peers(self) -> typing.List['KademliaPeer']:
peer = self.get_peers(sort_distance_to=False)
return [
peer for peer in peer
if self._peer_manager.contact_triple_is_good(peer.node_id, peer.address, peer.udp_port) is not True
]
def remove_peer(self, peer: 'KademliaPeer') -> None:
self.peers.remove(peer)
self.peer_in_routing_table_metric.labels("global").dec()
bits_colliding = utils.get_colliding_prefix_bits(peer.node_id, self._node_id)
self.peer_with_x_bit_colliding_metric.labels(amount=bits_colliding).dec()
def key_in_range(self, key: bytes) -> bool:
""" Tests whether the specified key (i.e. node ID) is in the range
of the n-bit ID space covered by this k-bucket (in otherwords, it
returns whether or not the specified key should be placed in this
k-bucket)
@param key: The key to test
@type key: str or int
@return: C{True} if the key is in this k-bucket's range, or C{False}
if not.
@rtype: bool
"""
return self.range_min <= self._distance_to_self(key) < self.range_max
def __len__(self) -> int:
return len(self.peers)
def __contains__(self, item) -> bool:
return item in self.peers
class TreeRoutingTable:
""" This class implements a routing table used by a Node class.
The Kademlia routing table is a binary tree whose leaves are k-buckets,
where each k-bucket contains nodes with some common prefix of their IDs.
This prefix is the k-bucket's position in the binary tree; it therefore
covers some range of ID values, and together all of the k-buckets cover
the entire n-bit ID (or key) space (with no overlap).
@note: In this implementation, nodes in the tree (the k-buckets) are
added dynamically, as needed; this technique is described in the 13-page
version of the Kademlia paper, in section 2.4. It does, however, use the
ping RPC-based k-bucket eviction algorithm described in section 2.2 of
that paper.
BOOTSTRAP MODE: if set to True, we always add all peers. This is so a
bootstrap node does not get a bias towards its own node id and replies are
the best it can provide (joining peer knows its neighbors immediately).
Over time, this will need to be optimized so we use the disk as holding
everything in memory won't be feasible anymore.
See: https://github.com/bittorrent/bootstrap-dht
"""
bucket_in_routing_table_metric = Gauge(
"buckets_in_routing_table", "Number of buckets on routing table", namespace="dht_node",
labelnames=("scope",)
)
def __init__(self, loop: asyncio.AbstractEventLoop, peer_manager: 'PeerManager', parent_node_id: bytes,
split_buckets_under_index: int = constants.SPLIT_BUCKETS_UNDER_INDEX, is_bootstrap_node: bool = False):
self._loop = loop
self._peer_manager = peer_manager
self._parent_node_id = parent_node_id
self._split_buckets_under_index = split_buckets_under_index
self.buckets: typing.List[KBucket] = [
KBucket(
self._peer_manager, range_min=0, range_max=2 ** constants.HASH_BITS, node_id=self._parent_node_id,
capacity=1 << 32 if is_bootstrap_node else constants.K
)
]
def get_peers(self) -> typing.List['KademliaPeer']:
return list(itertools.chain.from_iterable(map(lambda bucket: bucket.peers, self.buckets)))
def _should_split(self, bucket_index: int, to_add: bytes) -> bool:
# https://stackoverflow.com/questions/32129978/highly-unbalanced-kademlia-routing-table/32187456#32187456
if bucket_index < self._split_buckets_under_index:
return True
contacts = self.get_peers()
distance = Distance(self._parent_node_id)
contacts.sort(key=lambda c: distance(c.node_id))
kth_contact = contacts[-1] if len(contacts) < constants.K else contacts[constants.K - 1]
return distance(to_add) < distance(kth_contact.node_id)
def find_close_peers(self, key: bytes, count: typing.Optional[int] = None,
sender_node_id: typing.Optional[bytes] = None) -> typing.List['KademliaPeer']:
exclude = [self._parent_node_id]
if sender_node_id:
exclude.append(sender_node_id)
count = count or constants.K
distance = Distance(key)
contacts = self.get_peers()
contacts = [c for c in contacts if c.node_id not in exclude]
if contacts:
contacts.sort(key=lambda c: distance(c.node_id))
return contacts[:min(count, len(contacts))]
return []
def get_peer(self, contact_id: bytes) -> 'KademliaPeer':
return self.buckets[self._kbucket_index(contact_id)].get_peer(contact_id)
def get_refresh_list(self, start_index: int = 0, force: bool = False) -> typing.List[bytes]:
refresh_ids = []
for offset, _ in enumerate(self.buckets[start_index:]):
refresh_ids.append(self._midpoint_id_in_bucket_range(start_index + offset))
# if we have 3 or fewer populated buckets get two random ids in the range of each to try and
# populate/split the buckets further
buckets_with_contacts = self.buckets_with_contacts()
if buckets_with_contacts <= 3:
for i in range(buckets_with_contacts):
refresh_ids.append(self._random_id_in_bucket_range(i))
refresh_ids.append(self._random_id_in_bucket_range(i))
return refresh_ids
def remove_peer(self, peer: 'KademliaPeer') -> None:
if not peer.node_id:
return
bucket_index = self._kbucket_index(peer.node_id)
try:
self.buckets[bucket_index].remove_peer(peer)
self._join_buckets()
except ValueError:
return
def _kbucket_index(self, key: bytes) -> int:
i = 0
for bucket in self.buckets:
if bucket.key_in_range(key):
return i
else:
i += 1
return i
def _random_id_in_bucket_range(self, bucket_index: int) -> bytes:
random_id = int(random.randrange(self.buckets[bucket_index].range_min, self.buckets[bucket_index].range_max))
return Distance(
self._parent_node_id
)(random_id.to_bytes(constants.HASH_LENGTH, 'big')).to_bytes(constants.HASH_LENGTH, 'big')
def _midpoint_id_in_bucket_range(self, bucket_index: int) -> bytes:
half = int((self.buckets[bucket_index].range_max - self.buckets[bucket_index].range_min) // 2)
return Distance(self._parent_node_id)(
int(self.buckets[bucket_index].range_min + half).to_bytes(constants.HASH_LENGTH, 'big')
).to_bytes(constants.HASH_LENGTH, 'big')
def _split_bucket(self, old_bucket_index: int) -> None:
""" Splits the specified k-bucket into two new buckets which together
cover the same range in the key/ID space
@param old_bucket_index: The index of k-bucket to split (in this table's
list of k-buckets)
@type old_bucket_index: int
"""
# Resize the range of the current (old) k-bucket
old_bucket = self.buckets[old_bucket_index]
split_point = old_bucket.range_max - (old_bucket.range_max - old_bucket.range_min) // 2
# Create a new k-bucket to cover the range split off from the old bucket
new_bucket = KBucket(self._peer_manager, split_point, old_bucket.range_max, self._parent_node_id)
old_bucket.range_max = split_point
# Now, add the new bucket into the routing table tree
self.buckets.insert(old_bucket_index + 1, new_bucket)
# Finally, copy all nodes that belong to the new k-bucket into it...
for contact in old_bucket.peers:
if new_bucket.key_in_range(contact.node_id):
new_bucket.add_peer(contact)
# ...and remove them from the old bucket
for contact in new_bucket.peers:
old_bucket.remove_peer(contact)
self.bucket_in_routing_table_metric.labels("global").set(len(self.buckets))
def _join_buckets(self):
if len(self.buckets) == 1:
return
to_pop = [i for i, bucket in enumerate(self.buckets) if len(bucket) == 0]
if not to_pop:
return
log.info("join buckets %i", len(to_pop))
bucket_index_to_pop = to_pop[0]
assert len(self.buckets[bucket_index_to_pop]) == 0
can_go_lower = bucket_index_to_pop - 1 >= 0
can_go_higher = bucket_index_to_pop + 1 < len(self.buckets)
assert can_go_higher or can_go_lower
bucket = self.buckets[bucket_index_to_pop]
if can_go_lower and can_go_higher:
midpoint = ((bucket.range_max - bucket.range_min) // 2) + bucket.range_min
self.buckets[bucket_index_to_pop - 1].range_max = midpoint - 1
self.buckets[bucket_index_to_pop + 1].range_min = midpoint
elif can_go_lower:
self.buckets[bucket_index_to_pop - 1].range_max = bucket.range_max
elif can_go_higher:
self.buckets[bucket_index_to_pop + 1].range_min = bucket.range_min
self.buckets.remove(bucket)
self.bucket_in_routing_table_metric.labels("global").set(len(self.buckets))
return self._join_buckets()
def buckets_with_contacts(self) -> int:
count = 0
for bucket in self.buckets:
if len(bucket) > 0:
count += 1
return count
async def add_peer(self, peer: 'KademliaPeer', probe: typing.Callable[['KademliaPeer'], typing.Awaitable]):
if not peer.node_id:
log.warning("Tried adding a peer with no node id!")
return False
for my_peer in self.get_peers():
if (my_peer.address, my_peer.udp_port) == (peer.address, peer.udp_port) and my_peer.node_id != peer.node_id:
self.remove_peer(my_peer)
self._join_buckets()
bucket_index = self._kbucket_index(peer.node_id)
if self.buckets[bucket_index].add_peer(peer):
return True
# The bucket is full; see if it can be split (by checking if its range includes the host node's node_id)
if self._should_split(bucket_index, peer.node_id):
self._split_bucket(bucket_index)
# Retry the insertion attempt
result = await self.add_peer(peer, probe)
self._join_buckets()
return result
else:
# We can't split the k-bucket
#
# The 13 page kademlia paper specifies that the least recently contacted node in the bucket
# shall be pinged. If it fails to reply it is replaced with the new contact. If the ping is successful
# the new contact is ignored and not added to the bucket (sections 2.2 and 2.4).
#
# A reasonable extension to this is BEP 0005, which extends the above:
#
# Not all nodes that we learn about are equal. Some are "good" and some are not.
# Many nodes using the DHT are able to send queries and receive responses,
# but are not able to respond to queries from other nodes. It is important that
# each node's routing table must contain only known good nodes. A good node is
# a node has responded to one of our queries within the last 15 minutes. A node
# is also good if it has ever responded to one of our queries and has sent us a
# query within the last 15 minutes. After 15 minutes of inactivity, a node becomes
# questionable. Nodes become bad when they fail to respond to multiple queries
# in a row. Nodes that we know are good are given priority over nodes with unknown status.
#
# When there are bad or questionable nodes in the bucket, the least recent is selected for
# potential replacement (BEP 0005). When all nodes in the bucket are fresh, the head (least recent)
# contact is selected as described in section 2.2 of the kademlia paper. In both cases the new contact
# is ignored if the pinged node replies.
not_good_contacts = self.buckets[bucket_index].get_bad_or_unknown_peers()
not_recently_replied = []
for my_peer in not_good_contacts:
last_replied = self._peer_manager.get_last_replied(my_peer.address, my_peer.udp_port)
if not last_replied or last_replied + 60 < self._loop.time():
not_recently_replied.append(my_peer)
if not_recently_replied:
to_replace = not_recently_replied[0]
else:
to_replace = self.buckets[bucket_index].peers[0]
last_replied = self._peer_manager.get_last_replied(to_replace.address, to_replace.udp_port)
if last_replied and last_replied + 60 > self._loop.time():
return False
log.debug("pinging %s:%s", to_replace.address, to_replace.udp_port)
try:
await probe(to_replace)
return False
except (asyncio.TimeoutError, RemoteException):
log.debug("Replacing dead contact in bucket %i: %s:%i with %s:%i ", bucket_index,
to_replace.address, to_replace.udp_port, peer.address, peer.udp_port)
if to_replace in self.buckets[bucket_index]:
self.buckets[bucket_index].remove_peer(to_replace)
return await self.add_peer(peer, probe)