update
This commit is contained in:
0815Cracky
315
TwitchChannelPointsMiner/classes/entities/Bet.py
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315
TwitchChannelPointsMiner/classes/entities/Bet.py
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import copy
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from enum import Enum, auto
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from random import uniform
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from millify import millify
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#from TwitchChannelPointsMiner.utils import char_decision_as_index, float_round
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from TwitchChannelPointsMiner.utils import float_round
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class Strategy(Enum):
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MOST_VOTED = auto()
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HIGH_ODDS = auto()
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PERCENTAGE = auto()
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SMART_MONEY = auto()
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SMART = auto()
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def __str__(self):
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return self.name
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class Condition(Enum):
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GT = auto()
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LT = auto()
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GTE = auto()
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LTE = auto()
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def __str__(self):
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return self.name
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class OutcomeKeys(object):
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# Real key on Bet dict ['']
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PERCENTAGE_USERS = "percentage_users"
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ODDS_PERCENTAGE = "odds_percentage"
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ODDS = "odds"
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TOP_POINTS = "top_points"
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# Real key on Bet dict [''] - Sum()
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TOTAL_USERS = "total_users"
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TOTAL_POINTS = "total_points"
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# This key does not exist
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DECISION_USERS = "decision_users"
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DECISION_POINTS = "decision_points"
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class DelayMode(Enum):
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FROM_START = auto()
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FROM_END = auto()
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PERCENTAGE = auto()
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def __str__(self):
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return self.name
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class FilterCondition(object):
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__slots__ = [
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"by",
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"where",
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"value",
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]
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def __init__(self, by=None, where=None, value=None, decision=None):
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self.by = by
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self.where = where
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self.value = value
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def __repr__(self):
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return f"FilterCondition(by={self.by.upper()}, where={self.where}, value={self.value})"
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class BetSettings(object):
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__slots__ = [
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"strategy",
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"percentage",
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"percentage_gap",
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"max_points",
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"minimum_points",
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"stealth_mode",
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"filter_condition",
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"delay",
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"delay_mode",
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]
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def __init__(
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self,
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strategy: Strategy = None,
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percentage: int = None,
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percentage_gap: int = None,
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max_points: int = None,
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minimum_points: int = None,
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stealth_mode: bool = None,
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filter_condition: FilterCondition = None,
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delay: float = None,
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delay_mode: DelayMode = None,
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):
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self.strategy = strategy
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self.percentage = percentage
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self.percentage_gap = percentage_gap
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self.max_points = max_points
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self.minimum_points = minimum_points
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self.stealth_mode = stealth_mode
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self.filter_condition = filter_condition
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self.delay = delay
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self.delay_mode = delay_mode
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def default(self):
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self.strategy = self.strategy if self.strategy is not None else Strategy.SMART
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self.percentage = self.percentage if self.percentage is not None else 5
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self.percentage_gap = (
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self.percentage_gap if self.percentage_gap is not None else 20
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)
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self.max_points = self.max_points if self.max_points is not None else 50000
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self.minimum_points = (
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self.minimum_points if self.minimum_points is not None else 0
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)
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self.stealth_mode = (
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self.stealth_mode if self.stealth_mode is not None else False
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)
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self.delay = self.delay if self.delay is not None else 6
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self.delay_mode = (
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self.delay_mode if self.delay_mode is not None else DelayMode.FROM_END
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)
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def __repr__(self):
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return f"BetSettings(strategy={self.strategy}, percentage={self.percentage}, percentage_gap={self.percentage_gap}, max_points={self.max_points}, minimum_points={self.minimum_points}, stealth_mode={self.stealth_mode})"
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class Bet(object):
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__slots__ = ["outcomes", "decision", "total_users", "total_points", "settings"]
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def __init__(self, outcomes: list, settings: BetSettings):
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self.outcomes = outcomes
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self.__clear_outcomes()
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self.decision: dict = {}
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self.total_users = 0
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self.total_points = 0
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self.settings = settings
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def update_outcomes(self, outcomes):
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for index in range(0, len(self.outcomes)):
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self.outcomes[index][OutcomeKeys.TOTAL_USERS] = int(
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outcomes[index][OutcomeKeys.TOTAL_USERS]
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)
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self.outcomes[index][OutcomeKeys.TOTAL_POINTS] = int(
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outcomes[index][OutcomeKeys.TOTAL_POINTS]
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)
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if outcomes[index]["top_predictors"] != []:
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# Sort by points placed by other users
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outcomes[index]["top_predictors"] = sorted(
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outcomes[index]["top_predictors"],
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key=lambda x: x["points"],
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reverse=True,
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)
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# Get the first elements (most placed)
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top_points = outcomes[index]["top_predictors"][0]["points"]
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self.outcomes[index][OutcomeKeys.TOP_POINTS] = top_points
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# Inefficient, but otherwise outcomekeys are represented wrong
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self.total_points = 0
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self.total_users = 0
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for index in range(0, len(self.outcomes)):
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self.total_users += self.outcomes[index][OutcomeKeys.TOTAL_USERS]
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self.total_points += self.outcomes[index][OutcomeKeys.TOTAL_POINTS]
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if (
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self.total_users > 0
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and self.total_points > 0
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):
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for index in range(0, len(self.outcomes)):
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self.outcomes[index][OutcomeKeys.PERCENTAGE_USERS] = float_round(
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(100 * self.outcomes[index][OutcomeKeys.TOTAL_USERS]) / self.total_users
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)
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self.outcomes[index][OutcomeKeys.ODDS] = float_round(
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#self.total_points / max(self.outcomes[index][OutcomeKeys.TOTAL_POINTS], 1)
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0
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if self.outcomes[index][OutcomeKeys.TOTAL_POINTS] == 0
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else self.total_points / self.outcomes[index][OutcomeKeys.TOTAL_POINTS]
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)
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self.outcomes[index][OutcomeKeys.ODDS_PERCENTAGE] = float_round(
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#100 / max(self.outcomes[index][OutcomeKeys.ODDS], 1)
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0
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if self.outcomes[index][OutcomeKeys.ODDS] == 0
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else 100 / self.outcomes[index][OutcomeKeys.ODDS]
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)
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self.__clear_outcomes()
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def __repr__(self):
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return f"Bet(total_users={millify(self.total_users)}, total_points={millify(self.total_points)}), decision={self.decision})\n\t\tOutcome A({self.get_outcome(0)})\n\t\tOutcome B({self.get_outcome(1)})"
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def get_decision(self, parsed=False):
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#decision = self.outcomes[0 if self.decision["choice"] == "A" else 1]
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decision = self.outcomes[self.decision["choice"]]
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return decision if parsed is False else Bet.__parse_outcome(decision)
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@staticmethod
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def __parse_outcome(outcome):
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return f"{outcome['title']} ({outcome['color']}), Points: {millify(outcome[OutcomeKeys.TOTAL_POINTS])}, Users: {millify(outcome[OutcomeKeys.TOTAL_USERS])} ({outcome[OutcomeKeys.PERCENTAGE_USERS]}%), Odds: {outcome[OutcomeKeys.ODDS]} ({outcome[OutcomeKeys.ODDS_PERCENTAGE]}%)"
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def get_outcome(self, index):
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return Bet.__parse_outcome(self.outcomes[index])
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def __clear_outcomes(self):
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for index in range(0, len(self.outcomes)):
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keys = copy.deepcopy(list(self.outcomes[index].keys()))
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for key in keys:
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if key not in [
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OutcomeKeys.TOTAL_USERS,
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OutcomeKeys.TOTAL_POINTS,
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OutcomeKeys.TOP_POINTS,
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OutcomeKeys.PERCENTAGE_USERS,
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OutcomeKeys.ODDS,
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OutcomeKeys.ODDS_PERCENTAGE,
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"title",
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"color",
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"id",
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]:
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del self.outcomes[index][key]
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for key in [
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OutcomeKeys.PERCENTAGE_USERS,
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OutcomeKeys.ODDS,
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OutcomeKeys.ODDS_PERCENTAGE,
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OutcomeKeys.TOP_POINTS,
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]:
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if key not in self.outcomes[index]:
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self.outcomes[index][key] = 0
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'''def __return_choice(self, key) -> str:
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return "A" if self.outcomes[0][key] > self.outcomes[1][key] else "B"'''
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def __return_choice(self, key) -> int:
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largest=0
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for index in range(0, len(self.outcomes)):
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if self.outcomes[index][key] > self.outcomes[largest][key]:
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largest = index
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return largest
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def skip(self) -> bool:
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if self.settings.filter_condition is not None:
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# key == by , condition == where
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key = self.settings.filter_condition.by
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condition = self.settings.filter_condition.where
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value = self.settings.filter_condition.value
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fixed_key = (
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key
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if key not in [OutcomeKeys.DECISION_USERS, OutcomeKeys.DECISION_POINTS]
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else key.replace("decision", "total")
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)
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if key in [OutcomeKeys.TOTAL_USERS, OutcomeKeys.TOTAL_POINTS]:
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compared_value = (
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self.outcomes[0][fixed_key] + self.outcomes[1][fixed_key]
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)
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else:
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#outcome_index = char_decision_as_index(self.decision["choice"])
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outcome_index = self.decision["choice"]
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compared_value = self.outcomes[outcome_index][fixed_key]
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# Check if condition is satisfied
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if condition == Condition.GT:
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if compared_value > value:
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return False, compared_value
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elif condition == Condition.LT:
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if compared_value < value:
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return False, compared_value
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elif condition == Condition.GTE:
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if compared_value >= value:
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return False, compared_value
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elif condition == Condition.LTE:
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if compared_value <= value:
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return False, compared_value
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return True, compared_value # Else skip the bet
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else:
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return False, 0 # Default don't skip the bet
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def calculate(self, balance: int) -> dict:
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self.decision = {"choice": None, "amount": 0, "id": None}
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if self.settings.strategy == Strategy.MOST_VOTED:
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self.decision["choice"] = self.__return_choice(OutcomeKeys.TOTAL_USERS)
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elif self.settings.strategy == Strategy.HIGH_ODDS:
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self.decision["choice"] = self.__return_choice(OutcomeKeys.ODDS)
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elif self.settings.strategy == Strategy.PERCENTAGE:
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self.decision["choice"] = self.__return_choice(OutcomeKeys.ODDS_PERCENTAGE)
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elif self.settings.strategy == Strategy.SMART_MONEY:
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self.decision["choice"] = self.__return_choice(OutcomeKeys.TOP_POINTS)
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elif self.settings.strategy == Strategy.SMART:
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difference = abs(
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self.outcomes[0][OutcomeKeys.PERCENTAGE_USERS]
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- self.outcomes[1][OutcomeKeys.PERCENTAGE_USERS]
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)
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self.decision["choice"] = (
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self.__return_choice(OutcomeKeys.ODDS)
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if difference < self.settings.percentage_gap
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else self.__return_choice(OutcomeKeys.TOTAL_USERS)
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)
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if self.decision["choice"] is not None:
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#index = char_decision_as_index(self.decision["choice"])
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index = self.decision["choice"]
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self.decision["id"] = self.outcomes[index]["id"]
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self.decision["amount"] = min(
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int(balance * (self.settings.percentage / 100)),
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self.settings.max_points,
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)
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if (
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self.settings.stealth_mode is True
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and self.decision["amount"]
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>= self.outcomes[index][OutcomeKeys.TOP_POINTS]
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):
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reduce_amount = uniform(1, 5)
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self.decision["amount"] = (
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self.outcomes[index][OutcomeKeys.TOP_POINTS] - reduce_amount
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)
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self.decision["amount"] = int(self.decision["amount"])
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return self.decision
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