p2pool/skiplists.py

   1 import operator
   2
   3 from p2pool.util import forest, math
   4
   5 class WeightsSkipList(forest.TrackerSkipList):
   6     # share_count, weights, total_weight
   7
   8     def get_delta(self, element):
   9         from p2pool.bitcoin import data as bitcoin_data
  10         if element is None:
  11             return (2**256, {}, 0, 0) # XXX
  12         share = self.tracker.shares[element]
  13         att = bitcoin_data.target_to_average_attempts(share.target)
  14         return 1, {share.new_script: att*(65535-share.donation)}, att*65535, att*share.donation
  15
  16     def combine_deltas(self, (share_count1, weights1, total_weight1, total_donation_weight1), (share_count2, weights2, total_weight2, total_donation_weight2)):
  17         return share_count1 + share_count2, math.add_dicts(weights1, weights2), total_weight1 + total_weight2, total_donation_weight1 + total_donation_weight2
  18
  19     def initial_solution(self, start, (max_shares, desired_weight)):
  20         assert desired_weight % 65535 == 0, divmod(desired_weight, 65535)
  21         return 0, {}, 0, 0
  22
  23     def apply_delta(self, (share_count1, weights1, total_weight1, total_donation_weight1), (share_count2, weights2, total_weight2, total_donation_weight2), (max_shares, desired_weight)):
  24         if total_weight1 + total_weight2 > desired_weight and share_count2 == 1:
  25             script, = weights2.iterkeys()
  26             new_weights = dict(weights1)
  27             assert (desired_weight - total_weight1) % 65535 == 0
  28             new_weights[script] = new_weights.get(script, 0) + (desired_weight - total_weight1)//65535*weights2[script]//(total_weight2//65535)
  29             return share_count1 + share_count2, new_weights, desired_weight, total_donation_weight1 + (desired_weight - total_weight1)//65535*total_donation_weight2//(total_weight2//65535)
  30         return share_count1 + share_count2, math.add_dicts(weights1, weights2), total_weight1 + total_weight2, total_donation_weight1 + total_donation_weight2
  31
  32     def judge(self, (share_count, weights, total_weight, total_donation_weight), (max_shares, desired_weight)):
  33         if share_count > max_shares or total_weight > desired_weight:
  34             return 1
  35         elif share_count == max_shares or total_weight == desired_weight:
  36             return 0
  37         else:
  38             return -1
  39
  40     def finalize(self, (share_count, weights, total_weight, total_donation_weight), (max_shares, desired_weight)):
  41         assert share_count <= max_shares and total_weight <= desired_weight
  42         assert share_count == max_shares or total_weight == desired_weight
  43         return weights, total_weight, total_donation_weight
  44
  45 class SumSkipList(forest.TrackerSkipList):
  46     def __init__(self, tracker, value_func, identity_value=0, add_func=operator.add):
  47         forest.TrackerSkipList.__init__(self, tracker)
  48         self.value_func = value_func
  49         self.identity_value = identity_value
  50         self.add_func = add_func
  51
  52
  53     def get_delta(self, element):
  54         return self.value_func(self.tracker.shares[element]), 1
  55
  56     def combine_deltas(self, (result1, count1), (result2, count2)):
  57         return self.add_func(result1, result2), count1 + count2
  58
  59
  60     def initial_solution(self, start_hash, (desired_count,)):
  61         return self.identity_value, 0
  62
  63     def apply_delta(self, (result, count), (d_result, d_count), (desired_count,)):
  64         return self.add_func(result, d_result), count + d_count
  65
  66     def judge(self, (result, count), (desired_count,)):
  67         return cmp(count, desired_count)
  68
  69     def finalize(self, (result, count), (desired_count,)):
  70         assert count == desired_count
  71         return result