import asyncio import random import logging import typing import itertools from lbry.dht import constants from lbry.dht.protocol.distance import Distance if typing.TYPE_CHECKING: from lbry.dht.peer import KademliaPeer, PeerManager log = logging.getLogger(__name__) class KBucket: """ Description - later """ def __init__(self, peer_manager: 'PeerManager', range_min: int, range_max: int, node_id: bytes): """ @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.last_accessed = 0 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) 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 range(len(self.peers)): p = self.peers[i] if p.node_id == peer.node_id: self.peers.remove(p) self.peers.append(peer) return True if len(self.peers) < constants.K: self.peers.append(peer) return True else: return False # raise BucketFull("No space in bucket to insert contact") def get_peer(self, node_id: bytes) -> 'KademliaPeer': for peer in self.peers: if peer.node_id == node_id: return peer raise IndexError(node_id) 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) 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. """ def __init__(self, loop: asyncio.AbstractEventLoop, peer_manager: 'PeerManager', parent_node_id: bytes, split_buckets_under_index: int = constants.SPLIT_BUCKETS_UNDER_INDEX): 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 ) ] 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': """ @raise IndexError: No contact with the specified contact ID is known by this node """ 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]: bucket_index = start_index refresh_ids = [] now = int(self._loop.time()) for bucket in self.buckets[start_index:]: if force or now - bucket.last_accessed >= constants.REFRESH_INTERVAL: to_search = self.midpoint_id_in_bucket_range(bucket_index) refresh_ids.append(to_search) bucket_index += 1 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) except ValueError: return def touch_kbucket(self, key: bytes) -> None: self.touch_kbucket_by_index(self.kbucket_index(key)) def touch_kbucket_by_index(self, bucket_index: int): self.buckets[bucket_index].last_accessed = int(self._loop.time()) 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) def join_buckets(self): if len(self.buckets) == 1: return to_pop = [i for i, bucket in enumerate(self.buckets) if not len(bucket)] 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) return self.join_buckets() def contact_in_routing_table(self, address_tuple: typing.Tuple[str, int]) -> bool: for bucket in self.buckets: for contact in bucket.get_peers(sort_distance_to=False): if address_tuple[0] == contact.address and address_tuple[1] == contact.udp_port: return True return False def buckets_with_contacts(self) -> int: count = 0 for bucket in self.buckets: if len(bucket): count += 1 return count