forked from LBRYCommunity/lbry-sdk
remove unused stuff
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parent
339e666f38
commit
cb09be5336
2 changed files with 24 additions and 29 deletions
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@ -236,39 +236,12 @@ class Node(object):
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yield contact
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return list(_inner())
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def printContacts(self, *args):
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print '\n\nNODE CONTACTS\n==============='
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for i in range(len(self._routingTable._buckets)):
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print "bucket %i" % i
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for contact in self._routingTable._buckets[i]._contacts:
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print " %s:%i" % (contact.address, contact.port)
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print '=================================='
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def hasContacts(self):
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for bucket in self._routingTable._buckets:
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if bucket._contacts:
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return True
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return False
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def getApproximateTotalDHTNodes(self):
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# get the deepest bucket and the number of contacts in that bucket and multiply it
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# by the number of equivalently deep buckets in the whole DHT to get a really bad
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# estimate!
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bucket = self._routingTable._buckets[self._routingTable._kbucketIndex(self.node_id)]
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num_in_bucket = len(bucket._contacts)
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factor = (2 ** constants.key_bits) / (bucket.rangeMax - bucket.rangeMin)
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return num_in_bucket * factor
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def getApproximateTotalHashes(self):
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# Divide the number of hashes we know about by k to get a really, really, really
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# bad estimate of the average number of hashes per node, then multiply by the
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# approximate number of nodes to get a horrendous estimate of the total number
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# of hashes in the DHT
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num_in_data_store = len(self._dataStore._dict)
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if num_in_data_store == 0:
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return 0
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return num_in_data_store * self.getApproximateTotalDHTNodes() / 8
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def announceHaveBlob(self, key):
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return self.iterativeAnnounceHaveBlob(key, {'port': self.peerPort, 'lbryid': self.node_id})
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@ -73,11 +73,33 @@ def connect(port=None):
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yield reactor.stop()
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def getApproximateTotalDHTNodes(node):
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from lbrynet.dht import constants
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# get the deepest bucket and the number of contacts in that bucket and multiply it
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# by the number of equivalently deep buckets in the whole DHT to get a really bad
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# estimate!
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bucket = node._routingTable._buckets[node._routingTable._kbucketIndex(node.node_id)]
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num_in_bucket = len(bucket._contacts)
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factor = (2 ** constants.key_bits) / (bucket.rangeMax - bucket.rangeMin)
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return num_in_bucket * factor
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def getApproximateTotalHashes(node):
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# Divide the number of hashes we know about by k to get a really, really, really
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# bad estimate of the average number of hashes per node, then multiply by the
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# approximate number of nodes to get a horrendous estimate of the total number
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# of hashes in the DHT
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num_in_data_store = len(node._dataStore._dict)
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if num_in_data_store == 0:
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return 0
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return num_in_data_store * getApproximateTotalDHTNodes(node) / 8
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@defer.inlineCallbacks
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def find(node):
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try:
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log.info("Approximate number of nodes in DHT: %s", str(node.getApproximateTotalDHTNodes()))
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log.info("Approximate number of blobs in DHT: %s", str(node.getApproximateTotalHashes()))
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log.info("Approximate number of nodes in DHT: %s", str(getApproximateTotalDHTNodes(node)))
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log.info("Approximate number of blobs in DHT: %s", str(getApproximateTotalHashes(node)))
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h = "578f5e82da7db97bfe0677826d452cc0c65406a8e986c9caa126af4ecdbf4913daad2f7f5d1fb0ffec17d0bf8f187f5a"
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peersFake = yield node.getPeersForBlob(h.decode("hex"))
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