lbry-sdk/torba/client/coinselection.py
2018-11-04 01:55:50 -04:00

115 lines
4.3 KiB
Python

from random import Random
from typing import List
from torba.client import basetransaction
MAXIMUM_TRIES = 100000
class CoinSelector:
def __init__(self, txos: List[basetransaction.BaseOutputEffectiveAmountEstimator],
target: int, cost_of_change: int, seed: str = None) -> None:
self.txos = txos
self.target = target
self.cost_of_change = cost_of_change
self.exact_match = False
self.tries = 0
self.available = sum(c.effective_amount for c in self.txos)
self.random = Random(seed)
if seed is not None:
self.random.seed(seed, version=1)
def select(self) -> List[basetransaction.BaseOutputEffectiveAmountEstimator]:
if not self.txos:
return []
if self.target > self.available:
return []
return (
self.branch_and_bound() or
self.closest_match() or
self.random_draw()
)
def branch_and_bound(self) -> List[basetransaction.BaseOutputEffectiveAmountEstimator]:
# see bitcoin implementation for more info:
# https://github.com/bitcoin/bitcoin/blob/master/src/wallet/coinselection.cpp
self.txos.sort(reverse=True)
current_value = 0
current_available_value = self.available
current_selection: List[bool] = []
best_waste = self.cost_of_change
best_selection: List[bool] = []
while self.tries < MAXIMUM_TRIES:
self.tries += 1
backtrack = False
if current_value + current_available_value < self.target or \
current_value > self.target + self.cost_of_change:
backtrack = True
elif current_value >= self.target:
new_waste = current_value - self.target
if new_waste <= best_waste:
best_waste = new_waste
best_selection = current_selection[:]
backtrack = True
if backtrack:
while current_selection and not current_selection[-1]:
current_selection.pop()
current_available_value += self.txos[len(current_selection)].effective_amount
if not current_selection:
break
current_selection[-1] = False
utxo = self.txos[len(current_selection) - 1]
current_value -= utxo.effective_amount
else:
utxo = self.txos[len(current_selection)]
current_available_value -= utxo.effective_amount
previous_utxo = self.txos[len(current_selection) - 1] if current_selection else None
if current_selection and not current_selection[-1] and previous_utxo and \
utxo.effective_amount == previous_utxo.effective_amount and \
utxo.fee == previous_utxo.fee:
current_selection.append(False)
else:
current_selection.append(True)
current_value += utxo.effective_amount
if best_selection:
self.exact_match = True
return [
self.txos[i] for i, include in enumerate(best_selection) if include
]
return []
def closest_match(self) -> List[basetransaction.BaseOutputEffectiveAmountEstimator]:
""" Pick one UTXOs that is larger than the target but with the smallest change. """
target = self.target + self.cost_of_change
smallest_change = None
best_match = None
for txo in self.txos:
if txo.effective_amount >= target:
change = txo.effective_amount - target
if smallest_change is None or change < smallest_change:
smallest_change, best_match = change, txo
return [best_match] if best_match else []
def random_draw(self) -> List[basetransaction.BaseOutputEffectiveAmountEstimator]:
""" Accumulate UTXOs at random until there is enough to cover the target. """
target = self.target + self.cost_of_change
self.random.shuffle(self.txos, self.random.random)
selection = []
amount = 0
for coin in self.txos:
selection.append(coin)
amount += coin.effective_amount
if amount >= target:
return selection
return []