""" This module contains the class to persist trades into SQLite """ import logging from datetime import datetime from decimal import Decimal from typing import Any, Dict, List, Optional import arrow from sqlalchemy import (Boolean, Column, DateTime, Float, Integer, String, create_engine, desc, func, inspect) from sqlalchemy.exc import NoSuchModuleError from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import Query from sqlalchemy.orm.scoping import scoped_session from sqlalchemy.orm.session import sessionmaker from sqlalchemy.pool import StaticPool from freqtrade.exceptions import OperationalException logger = logging.getLogger(__name__) _DECL_BASE: Any = declarative_base() _SQL_DOCS_URL = 'http://docs.sqlalchemy.org/en/latest/core/engines.html#database-urls' def init(db_url: str, clean_open_orders: bool = False) -> None: """ Initializes this module with the given config, registers all known command handlers and starts polling for message updates :param db_url: Database to use :param clean_open_orders: Remove open orders from the database. Useful for dry-run or if all orders have been reset on the exchange. :return: None """ kwargs = {} # Take care of thread ownership if in-memory db if db_url == 'sqlite://': kwargs.update({ 'connect_args': {'check_same_thread': False}, 'poolclass': StaticPool, 'echo': False, }) try: engine = create_engine(db_url, **kwargs) except NoSuchModuleError: raise OperationalException(f"Given value for db_url: '{db_url}' " f"is no valid database URL! (See {_SQL_DOCS_URL})") # https://docs.sqlalchemy.org/en/13/orm/contextual.html#thread-local-scope # Scoped sessions proxy requests to the appropriate thread-local session. # We should use the scoped_session object - not a seperately initialized version Trade.session = scoped_session(sessionmaker(bind=engine, autoflush=True, autocommit=True)) Trade.query = Trade.session.query_property() _DECL_BASE.metadata.create_all(engine) check_migrate(engine) # Clean dry_run DB if the db is not in-memory if clean_open_orders and db_url != 'sqlite://': clean_dry_run_db() def has_column(columns: List, searchname: str) -> bool: return len(list(filter(lambda x: x["name"] == searchname, columns))) == 1 def get_column_def(columns: List, column: str, default: str) -> str: return default if not has_column(columns, column) else column def check_migrate(engine) -> None: """ Checks if migration is necessary and migrates if necessary """ inspector = inspect(engine) cols = inspector.get_columns('trades') tabs = inspector.get_table_names() table_back_name = 'trades_bak' for i, table_back_name in enumerate(tabs): table_back_name = f'trades_bak{i}' logger.debug(f'trying {table_back_name}') # Check for latest column if not has_column(cols, 'open_trade_price'): logger.info(f'Running database migration - backup available as {table_back_name}') fee_open = get_column_def(cols, 'fee_open', 'fee') fee_close = get_column_def(cols, 'fee_close', 'fee') open_rate_requested = get_column_def(cols, 'open_rate_requested', 'null') close_rate_requested = get_column_def(cols, 'close_rate_requested', 'null') stop_loss = get_column_def(cols, 'stop_loss', '0.0') stop_loss_pct = get_column_def(cols, 'stop_loss_pct', 'null') initial_stop_loss = get_column_def(cols, 'initial_stop_loss', '0.0') initial_stop_loss_pct = get_column_def(cols, 'initial_stop_loss_pct', 'null') stoploss_order_id = get_column_def(cols, 'stoploss_order_id', 'null') stoploss_last_update = get_column_def(cols, 'stoploss_last_update', 'null') max_rate = get_column_def(cols, 'max_rate', '0.0') min_rate = get_column_def(cols, 'min_rate', 'null') sell_reason = get_column_def(cols, 'sell_reason', 'null') strategy = get_column_def(cols, 'strategy', 'null') ticker_interval = get_column_def(cols, 'ticker_interval', 'null') open_trade_price = get_column_def(cols, 'open_trade_price', f'amount * open_rate * (1 + {fee_open})') # Schema migration necessary engine.execute(f"alter table trades rename to {table_back_name}") # drop indexes on backup table for index in inspector.get_indexes(table_back_name): engine.execute(f"drop index {index['name']}") # let SQLAlchemy create the schema as required _DECL_BASE.metadata.create_all(engine) # Copy data back - following the correct schema engine.execute(f"""insert into trades (id, exchange, pair, is_open, fee_open, fee_close, open_rate, open_rate_requested, close_rate, close_rate_requested, close_profit, stake_amount, amount, open_date, close_date, open_order_id, stop_loss, stop_loss_pct, initial_stop_loss, initial_stop_loss_pct, stoploss_order_id, stoploss_last_update, max_rate, min_rate, sell_reason, strategy, ticker_interval, open_trade_price ) select id, lower(exchange), case when instr(pair, '_') != 0 then substr(pair, instr(pair, '_') + 1) || '/' || substr(pair, 1, instr(pair, '_') - 1) else pair end pair, is_open, {fee_open} fee_open, {fee_close} fee_close, open_rate, {open_rate_requested} open_rate_requested, close_rate, {close_rate_requested} close_rate_requested, close_profit, stake_amount, amount, open_date, close_date, open_order_id, {stop_loss} stop_loss, {stop_loss_pct} stop_loss_pct, {initial_stop_loss} initial_stop_loss, {initial_stop_loss_pct} initial_stop_loss_pct, {stoploss_order_id} stoploss_order_id, {stoploss_last_update} stoploss_last_update, {max_rate} max_rate, {min_rate} min_rate, {sell_reason} sell_reason, {strategy} strategy, {ticker_interval} ticker_interval, {open_trade_price} open_trade_price from {table_back_name} """) # Reread columns - the above recreated the table! inspector = inspect(engine) cols = inspector.get_columns('trades') def cleanup() -> None: """ Flushes all pending operations to disk. :return: None """ Trade.session.flush() def clean_dry_run_db() -> None: """ Remove open_order_id from a Dry_run DB :return: None """ for trade in Trade.query.filter(Trade.open_order_id.isnot(None)).all(): # Check we are updating only a dry_run order not a prod one if 'dry_run' in trade.open_order_id: trade.open_order_id = None class Trade(_DECL_BASE): """ Class used to define a trade structure """ __tablename__ = 'trades' id = Column(Integer, primary_key=True) exchange = Column(String, nullable=False) pair = Column(String, nullable=False, index=True) is_open = Column(Boolean, nullable=False, default=True, index=True) fee_open = Column(Float, nullable=False, default=0.0) fee_close = Column(Float, nullable=False, default=0.0) open_rate = Column(Float) open_rate_requested = Column(Float) # open_trade_price - calcuated via _calc_open_trade_price open_trade_price = Column(Float) close_rate = Column(Float) close_rate_requested = Column(Float) close_profit = Column(Float) stake_amount = Column(Float, nullable=False) amount = Column(Float) open_date = Column(DateTime, nullable=False, default=datetime.utcnow) close_date = Column(DateTime) open_order_id = Column(String) # absolute value of the stop loss stop_loss = Column(Float, nullable=True, default=0.0) # percentage value of the stop loss stop_loss_pct = Column(Float, nullable=True) # absolute value of the initial stop loss initial_stop_loss = Column(Float, nullable=True, default=0.0) # percentage value of the initial stop loss initial_stop_loss_pct = Column(Float, nullable=True) # stoploss order id which is on exchange stoploss_order_id = Column(String, nullable=True, index=True) # last update time of the stoploss order on exchange stoploss_last_update = Column(DateTime, nullable=True) # absolute value of the highest reached price max_rate = Column(Float, nullable=True, default=0.0) # Lowest price reached min_rate = Column(Float, nullable=True) sell_reason = Column(String, nullable=True) strategy = Column(String, nullable=True) ticker_interval = Column(Integer, nullable=True) def __init__(self, **kwargs): super().__init__(**kwargs) self.recalc_open_trade_price() def __repr__(self): open_since = self.open_date.strftime('%Y-%m-%d %H:%M:%S') if self.is_open else 'closed' return (f'Trade(id={self.id}, pair={self.pair}, amount={self.amount:.8f}, ' f'open_rate={self.open_rate:.8f}, open_since={open_since})') def to_json(self) -> Dict[str, Any]: return { 'trade_id': self.id, 'pair': self.pair, 'open_date_hum': arrow.get(self.open_date).humanize(), 'open_date': self.open_date.strftime("%Y-%m-%d %H:%M:%S"), 'close_date_hum': (arrow.get(self.close_date).humanize() if self.close_date else None), 'close_date': (self.close_date.strftime("%Y-%m-%d %H:%M:%S") if self.close_date else None), 'open_rate': self.open_rate, 'close_rate': self.close_rate, 'amount': round(self.amount, 8), 'stake_amount': round(self.stake_amount, 8), 'stop_loss': self.stop_loss, 'stop_loss_pct': (self.stop_loss_pct * 100) if self.stop_loss_pct else None, 'initial_stop_loss': self.initial_stop_loss, 'initial_stop_loss_pct': (self.initial_stop_loss_pct * 100 if self.initial_stop_loss_pct else None), } def adjust_min_max_rates(self, current_price: float) -> None: """ Adjust the max_rate and min_rate. """ self.max_rate = max(current_price, self.max_rate or self.open_rate) self.min_rate = min(current_price, self.min_rate or self.open_rate) def adjust_stop_loss(self, current_price: float, stoploss: float, initial: bool = False) -> None: """ This adjusts the stop loss to it's most recently observed setting :param current_price: Current rate the asset is traded :param stoploss: Stoploss as factor (sample -0.05 -> -5% below current price). :param initial: Called to initiate stop_loss. Skips everything if self.stop_loss is already set. """ if initial and not (self.stop_loss is None or self.stop_loss == 0): # Don't modify if called with initial and nothing to do return new_loss = float(current_price * (1 - abs(stoploss))) # no stop loss assigned yet if not self.stop_loss: logger.debug(f"{self.pair} - Assigning new stoploss...") self.stop_loss = new_loss self.stop_loss_pct = -1 * abs(stoploss) self.initial_stop_loss = new_loss self.initial_stop_loss_pct = -1 * abs(stoploss) self.stoploss_last_update = datetime.utcnow() # evaluate if the stop loss needs to be updated else: if new_loss > self.stop_loss: # stop losses only walk up, never down! logger.debug(f"{self.pair} - Adjusting stoploss...") self.stop_loss = new_loss self.stop_loss_pct = -1 * abs(stoploss) self.stoploss_last_update = datetime.utcnow() else: logger.debug(f"{self.pair} - Keeping current stoploss...") logger.debug( f"{self.pair} - Stoploss adjusted. current_price={current_price:.8f}, " f"open_rate={self.open_rate:.8f}, max_rate={self.max_rate:.8f}, " f"initial_stop_loss={self.initial_stop_loss:.8f}, " f"stop_loss={self.stop_loss:.8f}. " f"Trailing stoploss saved us: " f"{float(self.stop_loss) - float(self.initial_stop_loss):.8f}.") def update(self, order: Dict) -> None: """ Updates this entity with amount and actual open/close rates. :param order: order retrieved by exchange.get_order() :return: None """ order_type = order['type'] # Ignore open and cancelled orders if order['status'] == 'open' or order['price'] is None: return logger.info('Updating trade (id=%s) ...', self.id) if order_type in ('market', 'limit') and order['side'] == 'buy': # Update open rate and actual amount self.open_rate = Decimal(order['price']) self.amount = Decimal(order['amount']) self.recalc_open_trade_price() logger.info('%s_BUY has been fulfilled for %s.', order_type.upper(), self) self.open_order_id = None elif order_type in ('market', 'limit') and order['side'] == 'sell': self.close(order['price']) logger.info('%s_SELL has been fulfilled for %s.', order_type.upper(), self) elif order_type == 'stop_loss_limit': self.stoploss_order_id = None self.close_rate_requested = self.stop_loss logger.info('STOP_LOSS_LIMIT is hit for %s.', self) self.close(order['average']) else: raise ValueError(f'Unknown order type: {order_type}') cleanup() def close(self, rate: float) -> None: """ Sets close_rate to the given rate, calculates total profit and marks trade as closed """ self.close_rate = Decimal(rate) self.close_profit = self.calc_profit_ratio() self.close_date = datetime.utcnow() self.is_open = False self.open_order_id = None logger.info( 'Marking %s as closed as the trade is fulfilled and found no open orders for it.', self ) def _calc_open_trade_price(self) -> float: """ Calculate the open_rate including open_fee. :return: Price in of the open trade incl. Fees """ buy_trade = Decimal(self.amount) * Decimal(self.open_rate) fees = buy_trade * Decimal(self.fee_open) return float(buy_trade + fees) def recalc_open_trade_price(self) -> None: """ Recalculate open_trade_price. Must be called whenever open_rate or fee_open is changed. """ self.open_trade_price = self._calc_open_trade_price() def calc_close_trade_price(self, rate: Optional[float] = None, fee: Optional[float] = None) -> float: """ Calculate the close_rate including fee :param fee: fee to use on the close rate (optional). If rate is not set self.fee will be used :param rate: rate to compare with (optional). If rate is not set self.close_rate will be used :return: Price in BTC of the open trade """ if rate is None and not self.close_rate: return 0.0 sell_trade = Decimal(self.amount) * Decimal(rate or self.close_rate) fees = sell_trade * Decimal(fee or self.fee_close) return float(sell_trade - fees) def calc_profit(self, rate: Optional[float] = None, fee: Optional[float] = None) -> float: """ Calculate the absolute profit in stake currency between Close and Open trade :param fee: fee to use on the close rate (optional). If rate is not set self.fee will be used :param rate: close rate to compare with (optional). If rate is not set self.close_rate will be used :return: profit in stake currency as float """ close_trade_price = self.calc_close_trade_price( rate=(rate or self.close_rate), fee=(fee or self.fee_close) ) profit = close_trade_price - self.open_trade_price return float(f"{profit:.8f}") def calc_profit_ratio(self, rate: Optional[float] = None, fee: Optional[float] = None) -> float: """ Calculates the profit as ratio (including fee). :param rate: rate to compare with (optional). If rate is not set self.close_rate will be used :param fee: fee to use on the close rate (optional). :return: profit ratio as float """ close_trade_price = self.calc_close_trade_price( rate=(rate or self.close_rate), fee=(fee or self.fee_close) ) profit_percent = (close_trade_price / self.open_trade_price) - 1 return float(f"{profit_percent:.8f}") @staticmethod def get_trades(trade_filter=None) -> Query: """ Helper function to query Trades using filters. :param trade_filter: Optional filter to apply to trades Can be either a Filter object, or a List of filters e.g. `(trade_filter=[Trade.id == trade_id, Trade.is_open.is_(True),])` e.g. `(trade_filter=Trade.id == trade_id)` :return: unsorted query object """ if trade_filter is not None: if not isinstance(trade_filter, list): trade_filter = [trade_filter] return Trade.query.filter(*trade_filter) else: return Trade.query @staticmethod def get_open_trades() -> List[Any]: """ Query trades from persistence layer """ return Trade.get_trades(Trade.is_open.is_(True)).all() @staticmethod def get_open_order_trades(): """ Returns all open trades """ return Trade.get_trades(Trade.open_order_id.isnot(None)).all() @staticmethod def total_open_trades_stakes() -> float: """ Calculates total invested amount in open trades in stake currency """ total_open_stake_amount = Trade.session.query(func.sum(Trade.stake_amount))\ .filter(Trade.is_open.is_(True))\ .scalar() return total_open_stake_amount or 0 @staticmethod def get_overall_performance() -> List[Dict[str, Any]]: """ Returns List of dicts containing all Trades, including profit and trade count """ pair_rates = Trade.session.query( Trade.pair, func.sum(Trade.close_profit).label('profit_sum'), func.count(Trade.pair).label('count') ).filter(Trade.is_open.is_(False))\ .group_by(Trade.pair) \ .order_by(desc('profit_sum')) \ .all() return [ { 'pair': pair, 'profit': rate, 'count': count } for pair, rate, count in pair_rates ] @staticmethod def get_best_pair(): """ Get best pair with closed trade. """ best_pair = Trade.session.query( Trade.pair, func.sum(Trade.close_profit).label('profit_sum') ).filter(Trade.is_open.is_(False)) \ .group_by(Trade.pair) \ .order_by(desc('profit_sum')).first() return best_pair @staticmethod def stoploss_reinitialization(desired_stoploss): """ Adjust initial Stoploss to desired stoploss for all open trades. """ for trade in Trade.get_open_trades(): logger.info("Found open trade: %s", trade) # skip case if trailing-stop changed the stoploss already. if (trade.stop_loss == trade.initial_stop_loss and trade.initial_stop_loss_pct != desired_stoploss): # Stoploss value got changed logger.info(f"Stoploss for {trade} needs adjustment...") # Force reset of stoploss trade.stop_loss = None trade.adjust_stop_loss(trade.open_rate, desired_stoploss) logger.info(f"New stoploss: {trade.stop_loss}.")