class Backtesting:
"""
Backtesting class, this class contains all the logic to run a backtest
To run a backtest:
backtesting = Backtesting(config)
backtesting.start()
"""
def __init__(self, config: Dict[str, Any]) -> None:
LoggingMixin.show_output = False
self.config = config
self.results: Dict[str, Any] = {}
config['dry_run'] = True
self.run_ids: Dict[str, str] = {}
self.strategylist: List[IStrategy] = []
self.all_results: Dict[str, Dict] = {}
self.exchange = ExchangeResolver.load_exchange(
self.config['exchange']['name'], self.config)
self.dataprovider = DataProvider(self.config, self.exchange)
if self.config.get('strategy_list', None):
for strat in list(self.config['strategy_list']):
stratconf = deepcopy(self.config)
stratconf['strategy'] = strat
self.strategylist.append(
StrategyResolver.load_strategy(stratconf))
validate_config_consistency(stratconf)
else:
# No strategy list specified, only one strategy
self.strategylist.append(
StrategyResolver.load_strategy(self.config))
validate_config_consistency(self.config)
if "timeframe" not in self.config:
raise OperationalException(
"Timeframe (ticker interval) needs to be set in either "
"configuration or as cli argument `--timeframe 5m`")
self.timeframe = str(self.config.get('timeframe'))
self.timeframe_min = timeframe_to_minutes(self.timeframe)
self.init_backtest_detail()
self.pairlists = PairListManager(self.exchange, self.config)
if 'VolumePairList' in self.pairlists.name_list:
raise OperationalException(
"VolumePairList not allowed for backtesting. "
"Please use StaticPairlist instead.")
if 'PerformanceFilter' in self.pairlists.name_list:
raise OperationalException(
"PerformanceFilter not allowed for backtesting.")
if len(self.strategylist
) > 1 and 'PrecisionFilter' in self.pairlists.name_list:
raise OperationalException(
"PrecisionFilter not allowed for backtesting multiple strategies."
)
self.dataprovider.add_pairlisthandler(self.pairlists)
self.pairlists.refresh_pairlist()
if len(self.pairlists.whitelist) == 0:
raise OperationalException("No pair in whitelist.")
if config.get('fee', None) is not None:
self.fee = config['fee']
else:
self.fee = self.exchange.get_fee(
symbol=self.pairlists.whitelist[0])
self.timerange = TimeRange.parse_timerange(None if self.config.get(
'timerange') is None else str(self.config.get('timerange')))
# Get maximum required startup period
self.required_startup = max(
[strat.startup_candle_count for strat in self.strategylist])
# Add maximum startup candle count to configuration for informative pairs support
self.config['startup_candle_count'] = self.required_startup
self.exchange.validate_required_startup_candles(
self.required_startup, self.timeframe)
self.init_backtest()
def __del__(self):
self.cleanup()
def cleanup(self):
LoggingMixin.show_output = True
PairLocks.use_db = True
Trade.use_db = True
def init_backtest_detail(self):
# Load detail timeframe if specified
self.timeframe_detail = str(self.config.get('timeframe_detail', ''))
if self.timeframe_detail:
self.timeframe_detail_min = timeframe_to_minutes(
self.timeframe_detail)
if self.timeframe_min <= self.timeframe_detail_min:
raise OperationalException(
"Detail timeframe must be smaller than strategy timeframe."
)
else:
self.timeframe_detail_min = 0
self.detail_data: Dict[str, DataFrame] = {}
def init_backtest(self):
self.prepare_backtest(False)
self.wallets = Wallets(self.config, self.exchange, log=False)
self.progress = BTProgress()
self.abort = False
def _set_strategy(self, strategy: IStrategy):
"""
Load strategy into backtesting
"""
self.strategy: IStrategy = strategy
strategy.dp = self.dataprovider
# Attach Wallets to Strategy baseclass
strategy.wallets = self.wallets
# Set stoploss_on_exchange to false for backtesting,
# since a "perfect" stoploss-sell is assumed anyway
# And the regular "stoploss" function would not apply to that case
self.strategy.order_types['stoploss_on_exchange'] = False
def _load_protections(self, strategy: IStrategy):
if self.config.get('enable_protections', False):
conf = self.config
if hasattr(strategy, 'protections'):
conf = deepcopy(conf)
conf['protections'] = strategy.protections
self.protections = ProtectionManager(self.config,
strategy.protections)
def load_bt_data(self) -> Tuple[Dict[str, DataFrame], TimeRange]:
"""
Loads backtest data and returns the data combined with the timerange
as tuple.
"""
self.progress.init_step(BacktestState.DATALOAD, 1)
data = history.load_data(
datadir=self.config['datadir'],
pairs=self.pairlists.whitelist,
timeframe=self.timeframe,
timerange=self.timerange,
startup_candles=self.required_startup,
fail_without_data=True,
data_format=self.config.get('dataformat_ohlcv', 'json'),
)
min_date, max_date = history.get_timerange(data)
logger.info(
f'Loading data from {min_date.strftime(DATETIME_PRINT_FORMAT)} '
f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} '
f'({(max_date - min_date).days} days).')
# Adjust startts forward if not enough data is available
self.timerange.adjust_start_if_necessary(
timeframe_to_seconds(self.timeframe), self.required_startup,
min_date)
self.progress.set_new_value(1)
return data, self.timerange
def load_bt_data_detail(self) -> None:
"""
Loads backtest detail data (smaller timeframe) if necessary.
"""
if self.timeframe_detail:
self.detail_data = history.load_data(
datadir=self.config['datadir'],
pairs=self.pairlists.whitelist,
timeframe=self.timeframe_detail,
timerange=self.timerange,
startup_candles=0,
fail_without_data=True,
data_format=self.config.get('dataformat_ohlcv', 'json'),
)
else:
self.detail_data = {}
def prepare_backtest(self, enable_protections):
"""
Backtesting setup method - called once for every call to "backtest()".
"""
PairLocks.use_db = False
PairLocks.timeframe = self.config['timeframe']
Trade.use_db = False
PairLocks.reset_locks()
Trade.reset_trades()
self.rejected_trades = 0
self.dataprovider.clear_cache()
if enable_protections:
self._load_protections(self.strategy)
def check_abort(self):
"""
Check if abort was requested, raise DependencyException if that's the case
Only applies to Interactive backtest mode (webserver mode)
"""
if self.abort:
self.abort = False
raise DependencyException("Stop requested")
def _get_ohlcv_as_lists(
self, processed: Dict[str, DataFrame]) -> Dict[str, Tuple]:
"""
Helper function to convert a processed dataframes into lists for performance reasons.
Used by backtest() - so keep this optimized for performance.
:param processed: a processed dictionary with format {pair, data}, which gets cleared to
optimize memory usage!
"""
# Every change to this headers list must evaluate further usages of the resulting tuple
# and eventually change the constants for indexes at the top
headers = [
'date', 'buy', 'open', 'close', 'sell', 'low', 'high', 'buy_tag',
'exit_tag'
]
data: Dict = {}
self.progress.init_step(BacktestState.CONVERT, len(processed))
# Create dict with data
for pair in processed.keys():
pair_data = processed[pair]
self.check_abort()
self.progress.increment()
if not pair_data.empty:
pair_data.loc[:, 'buy'] = 0 # cleanup if buy_signal is exist
pair_data.loc[:, 'sell'] = 0 # cleanup if sell_signal is exist
pair_data.loc[:,
'buy_tag'] = None # cleanup if buy_tag is exist
pair_data.loc[:,
'exit_tag'] = None # cleanup if exit_tag is exist
df_analyzed = self.strategy.advise_sell(
self.strategy.advise_buy(pair_data, {'pair': pair}), {
'pair': pair
}).copy()
# Trim startup period from analyzed dataframe
df_analyzed = processed[pair] = pair_data = trim_dataframe(
df_analyzed,
self.timerange,
startup_candles=self.required_startup)
# To avoid using data from future, we use buy/sell signals shifted
# from the previous candle
df_analyzed.loc[:, 'buy'] = df_analyzed.loc[:, 'buy'].shift(1)
df_analyzed.loc[:, 'sell'] = df_analyzed.loc[:, 'sell'].shift(1)
df_analyzed.loc[:, 'buy_tag'] = df_analyzed.loc[:,
'buy_tag'].shift(1)
df_analyzed.loc[:,
'exit_tag'] = df_analyzed.loc[:,
'exit_tag'].shift(1)
# Update dataprovider cache
self.dataprovider._set_cached_df(pair, self.timeframe, df_analyzed)
df_analyzed = df_analyzed.drop(df_analyzed.head(1).index)
# Convert from Pandas to list for performance reasons
# (Looping Pandas is slow.)
data[pair] = df_analyzed[headers].values.tolist()
return data
def _get_close_rate(self, sell_row: Tuple, trade: LocalTrade,
sell: SellCheckTuple, trade_dur: int) -> float:
"""
Get close rate for backtesting result
"""
# Special handling if high or low hit STOP_LOSS or ROI
if sell.sell_type in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
if trade.stop_loss > sell_row[HIGH_IDX]:
# our stoploss was already higher than candle high,
# possibly due to a cancelled trade exit.
# sell at open price.
return sell_row[OPEN_IDX]
# Special case: trailing triggers within same candle as trade opened. Assume most
# pessimistic price movement, which is moving just enough to arm stoploss and
# immediately going down to stop price.
if sell.sell_type == SellType.TRAILING_STOP_LOSS and trade_dur == 0:
if (not self.strategy.use_custom_stoploss
and self.strategy.trailing_stop
and self.strategy.trailing_only_offset_is_reached and
self.strategy.trailing_stop_positive_offset is not None
and self.strategy.trailing_stop_positive):
# Worst case: price reaches stop_positive_offset and dives down.
stop_rate = (
sell_row[OPEN_IDX] *
(1 + abs(self.strategy.trailing_stop_positive_offset) -
abs(self.strategy.trailing_stop_positive)))
else:
# Worst case: price ticks tiny bit above open and dives down.
stop_rate = sell_row[OPEN_IDX] * (1 -
abs(trade.stop_loss_pct))
assert stop_rate < sell_row[HIGH_IDX]
# Limit lower-end to candle low to avoid sells below the low.
# This still remains "worst case" - but "worst realistic case".
return max(sell_row[LOW_IDX], stop_rate)
# Set close_rate to stoploss
return trade.stop_loss
elif sell.sell_type == (SellType.ROI):
roi_entry, roi = self.strategy.min_roi_reached_entry(trade_dur)
if roi is not None and roi_entry is not None:
if roi == -1 and roi_entry % self.timeframe_min == 0:
# When forceselling with ROI=-1, the roi time will always be equal to trade_dur.
# If that entry is a multiple of the timeframe (so on candle open)
# - we'll use open instead of close
return sell_row[OPEN_IDX]
# - (Expected abs profit + open_rate + open_fee) / (fee_close -1)
close_rate = -(trade.open_rate * roi + trade.open_rate *
(1 + trade.fee_open)) / (trade.fee_close - 1)
if (trade_dur > 0 and trade_dur == roi_entry
and roi_entry % self.timeframe_min == 0
and sell_row[OPEN_IDX] > close_rate):
# new ROI entry came into effect.
# use Open rate if open_rate > calculated sell rate
return sell_row[OPEN_IDX]
return close_rate
else:
# This should not be reached...
return sell_row[OPEN_IDX]
else:
return sell_row[OPEN_IDX]
def _get_adjust_trade_entry_for_candle(self, trade: LocalTrade,
row: Tuple) -> LocalTrade:
current_profit = trade.calc_profit_ratio(row[OPEN_IDX])
min_stake = self.exchange.get_min_pair_stake_amount(
trade.pair, row[OPEN_IDX], -0.1)
max_stake = self.wallets.get_available_stake_amount()
stake_amount = strategy_safe_wrapper(
self.strategy.adjust_trade_position,
default_retval=None)(trade=trade,
current_time=row[DATE_IDX].to_pydatetime(),
current_rate=row[OPEN_IDX],
current_profit=current_profit,
min_stake=min_stake,
max_stake=max_stake)
# Check if we should increase our position
if stake_amount is not None and stake_amount > 0.0:
pos_trade = self._enter_trade(trade.pair, row, stake_amount, trade)
if pos_trade is not None:
return pos_trade
return trade
def _get_sell_trade_entry_for_candle(
self, trade: LocalTrade, sell_row: Tuple) -> Optional[LocalTrade]:
# Check if we need to adjust our current positions
if self.strategy.position_adjustment_enable:
trade = self._get_adjust_trade_entry_for_candle(trade, sell_row)
sell_candle_time = sell_row[DATE_IDX].to_pydatetime()
sell = self.strategy.should_sell(
trade,
sell_row[OPEN_IDX], # type: ignore
sell_candle_time,
sell_row[BUY_IDX],
sell_row[SELL_IDX],
low=sell_row[LOW_IDX],
high=sell_row[HIGH_IDX])
if sell.sell_flag:
trade.close_date = sell_candle_time
trade_dur = int(
(trade.close_date_utc - trade.open_date_utc).total_seconds() //
60)
closerate = self._get_close_rate(sell_row, trade, sell, trade_dur)
# call the custom exit price,with default value as previous closerate
current_profit = trade.calc_profit_ratio(closerate)
if sell.sell_type in (SellType.SELL_SIGNAL, SellType.CUSTOM_SELL):
# Custom exit pricing only for sell-signals
closerate = strategy_safe_wrapper(
self.strategy.custom_exit_price,
default_retval=closerate)(pair=trade.pair,
trade=trade,
current_time=sell_row[DATE_IDX],
proposed_rate=closerate,
current_profit=current_profit)
# Use the maximum between close_rate and low as we cannot sell outside of a candle.
closerate = min(max(closerate, sell_row[LOW_IDX]),
sell_row[HIGH_IDX])
# Confirm trade exit:
time_in_force = self.strategy.order_time_in_force['sell']
if not strategy_safe_wrapper(self.strategy.confirm_trade_exit,
default_retval=True)(
pair=trade.pair,
trade=trade,
order_type='limit',
amount=trade.amount,
rate=closerate,
time_in_force=time_in_force,
sell_reason=sell.sell_reason,
current_time=sell_candle_time):
return None
trade.sell_reason = sell.sell_reason
# Checks and adds an exit tag, after checking that the length of the
# sell_row has the length for an exit tag column
if (len(sell_row) > EXIT_TAG_IDX
and sell_row[EXIT_TAG_IDX] is not None
and len(sell_row[EXIT_TAG_IDX]) > 0):
trade.sell_reason = sell_row[EXIT_TAG_IDX]
trade.close(closerate, show_msg=False)
return trade
return None
def _get_sell_trade_entry(self, trade: LocalTrade,
sell_row: Tuple) -> Optional[LocalTrade]:
if self.timeframe_detail and trade.pair in self.detail_data:
sell_candle_time = sell_row[DATE_IDX].to_pydatetime()
sell_candle_end = sell_candle_time + timedelta(
minutes=self.timeframe_min)
detail_data = self.detail_data[trade.pair]
detail_data = detail_data.loc[
(detail_data['date'] >= sell_candle_time)
& (detail_data['date'] < sell_candle_end)].copy()
if len(detail_data) == 0:
# Fall back to "regular" data if no detail data was found for this candle
return self._get_sell_trade_entry_for_candle(trade, sell_row)
detail_data.loc[:, 'buy'] = sell_row[BUY_IDX]
detail_data.loc[:, 'sell'] = sell_row[SELL_IDX]
detail_data.loc[:, 'buy_tag'] = sell_row[BUY_TAG_IDX]
detail_data.loc[:, 'exit_tag'] = sell_row[EXIT_TAG_IDX]
headers = [
'date', 'buy', 'open', 'close', 'sell', 'low', 'high',
'buy_tag', 'exit_tag'
]
for det_row in detail_data[headers].values.tolist():
res = self._get_sell_trade_entry_for_candle(trade, det_row)
if res:
return res
return None
else:
return self._get_sell_trade_entry_for_candle(trade, sell_row)
def _enter_trade(
self,
pair: str,
row: Tuple,
stake_amount: Optional[float] = None,
trade: Optional[LocalTrade] = None) -> Optional[LocalTrade]:
# let's call the custom entry price, using the open price as default price
propose_rate = strategy_safe_wrapper(
self.strategy.custom_entry_price, default_retval=row[OPEN_IDX])(
pair=pair,
current_time=row[DATE_IDX].to_pydatetime(),
proposed_rate=row[OPEN_IDX]) # default value is the open rate
# Move rate to within the candle's low/high rate
propose_rate = min(max(propose_rate, row[LOW_IDX]), row[HIGH_IDX])
min_stake_amount = self.exchange.get_min_pair_stake_amount(
pair, propose_rate, -0.05) or 0
max_stake_amount = self.wallets.get_available_stake_amount()
pos_adjust = trade is not None
if not pos_adjust:
try:
stake_amount = self.wallets.get_trade_stake_amount(pair, None)
except DependencyException:
return trade
stake_amount = strategy_safe_wrapper(
self.strategy.custom_stake_amount,
default_retval=stake_amount)(
pair=pair,
current_time=row[DATE_IDX].to_pydatetime(),
current_rate=propose_rate,
proposed_stake=stake_amount,
min_stake=min_stake_amount,
max_stake=max_stake_amount)
stake_amount = self.wallets.validate_stake_amount(
pair, stake_amount, min_stake_amount)
if not stake_amount:
# In case of pos adjust, still return the original trade
# If not pos adjust, trade is None
return trade
order_type = self.strategy.order_types['buy']
time_in_force = self.strategy.order_time_in_force['sell']
# Confirm trade entry:
if not pos_adjust:
if not strategy_safe_wrapper(
self.strategy.confirm_trade_entry, default_retval=True)(
pair=pair,
order_type=order_type,
amount=stake_amount,
rate=propose_rate,
time_in_force=time_in_force,
current_time=row[DATE_IDX].to_pydatetime()):
return None
if stake_amount and (not min_stake_amount
or stake_amount > min_stake_amount):
amount = round(stake_amount / propose_rate, 8)
if trade is None:
# Enter trade
has_buy_tag = len(row) >= BUY_TAG_IDX + 1
trade = LocalTrade(
pair=pair,
open_rate=propose_rate,
open_date=row[DATE_IDX].to_pydatetime(),
stake_amount=stake_amount,
amount=amount,
fee_open=self.fee,
fee_close=self.fee,
is_open=True,
buy_tag=row[BUY_TAG_IDX] if has_buy_tag else None,
exchange='backtesting',
orders=[])
order = Order(ft_is_open=False,
ft_pair=trade.pair,
symbol=trade.pair,
ft_order_side="buy",
side="buy",
order_type="market",
status="closed",
price=propose_rate,
average=propose_rate,
amount=amount,
filled=amount,
cost=stake_amount + trade.fee_open)
trade.orders.append(order)
if pos_adjust:
trade.recalc_trade_from_orders()
return trade
def handle_left_open(self, open_trades: Dict[str, List[LocalTrade]],
data: Dict[str, List[Tuple]]) -> List[LocalTrade]:
"""
Handling of left open trades at the end of backtesting
"""
trades = []
for pair in open_trades.keys():
if len(open_trades[pair]) > 0:
for trade in open_trades[pair]:
sell_row = data[pair][-1]
trade.close_date = sell_row[DATE_IDX].to_pydatetime()
trade.sell_reason = SellType.FORCE_SELL.value
trade.close(sell_row[OPEN_IDX], show_msg=False)
LocalTrade.close_bt_trade(trade)
# Deepcopy object to have wallets update correctly
trade1 = deepcopy(trade)
trade1.is_open = True
trades.append(trade1)
return trades
def trade_slot_available(self, max_open_trades: int,
open_trade_count: int) -> bool:
# Always allow trades when max_open_trades is enabled.
if max_open_trades <= 0 or open_trade_count < max_open_trades:
return True
# Rejected trade
self.rejected_trades += 1
return False
def backtest(self,
processed: Dict,
start_date: datetime,
end_date: datetime,
max_open_trades: int = 0,
position_stacking: bool = False,
enable_protections: bool = False) -> Dict[str, Any]:
"""
Implement backtesting functionality
NOTE: This method is used by Hyperopt at each iteration. Please keep it optimized.
Of course try to not have ugly code. By some accessor are sometime slower than functions.
Avoid extensive logging in this method and functions it calls.
:param processed: a processed dictionary with format {pair, data}, which gets cleared to
optimize memory usage!
:param start_date: backtesting timerange start datetime
:param end_date: backtesting timerange end datetime
:param max_open_trades: maximum number of concurrent trades, <= 0 means unlimited
:param position_stacking: do we allow position stacking?
:param enable_protections: Should protections be enabled?
:return: DataFrame with trades (results of backtesting)
"""
trades: List[LocalTrade] = []
self.prepare_backtest(enable_protections)
# Use dict of lists with data for performance
# (looping lists is a lot faster than pandas DataFrames)
data: Dict = self._get_ohlcv_as_lists(processed)
# Indexes per pair, so some pairs are allowed to have a missing start.
indexes: Dict = defaultdict(int)
tmp = start_date + timedelta(minutes=self.timeframe_min)
open_trades: Dict[str, List[LocalTrade]] = defaultdict(list)
open_trade_count = 0
self.progress.init_step(
BacktestState.BACKTEST,
int((end_date - start_date) /
timedelta(minutes=self.timeframe_min)))
# Loop timerange and get candle for each pair at that point in time
while tmp <= end_date:
open_trade_count_start = open_trade_count
self.check_abort()
for i, pair in enumerate(data):
row_index = indexes[pair]
try:
# Row is treated as "current incomplete candle".
# Buy / sell signals are shifted by 1 to compensate for this.
row = data[pair][row_index]
except IndexError:
# missing Data for one pair at the end.
# Warnings for this are shown during data loading
continue
# Waits until the time-counter reaches the start of the data for this pair.
if row[DATE_IDX] > tmp:
continue
row_index += 1
indexes[pair] = row_index
self.dataprovider._set_dataframe_max_index(row_index)
# without positionstacking, we can only have one open trade per pair.
# max_open_trades must be respected
# don't open on the last row
if ((position_stacking or len(open_trades[pair]) == 0)
and self.trade_slot_available(max_open_trades,
open_trade_count_start)
and tmp != end_date and row[BUY_IDX] == 1
and row[SELL_IDX] != 1
and not PairLocks.is_pair_locked(pair, row[DATE_IDX])):
trade = self._enter_trade(pair, row)
if trade:
# TODO: hacky workaround to avoid opening > max_open_trades
# This emulates previous behaviour - not sure if this is correct
# Prevents buying if the trade-slot was freed in this candle
open_trade_count_start += 1
open_trade_count += 1
# logger.debug(f"{pair} - Emulate creation of new trade: {trade}.")
open_trades[pair].append(trade)
LocalTrade.add_bt_trade(trade)
for trade in list(open_trades[pair]):
# also check the buying candle for sell conditions.
trade_entry = self._get_sell_trade_entry(trade, row)
# Sell occurred
if trade_entry:
# logger.debug(f"{pair} - Backtesting sell {trade}")
open_trade_count -= 1
open_trades[pair].remove(trade)
LocalTrade.close_bt_trade(trade)
trades.append(trade_entry)
if enable_protections:
self.protections.stop_per_pair(pair, row[DATE_IDX])
self.protections.global_stop(tmp)
# Move time one configured time_interval ahead.
self.progress.increment()
tmp += timedelta(minutes=self.timeframe_min)
trades += self.handle_left_open(open_trades, data=data)
self.wallets.update()
results = trade_list_to_dataframe(trades)
return {
'results':
results,
'config':
self.strategy.config,
'locks':
PairLocks.get_all_locks(),
'rejected_signals':
self.rejected_trades,
'final_balance':
self.wallets.get_total(self.strategy.config['stake_currency']),
}
def backtest_one_strategy(self, strat: IStrategy, data: Dict[str,
DataFrame],
timerange: TimeRange):
self.progress.init_step(BacktestState.ANALYZE, 0)
logger.info("Running backtesting for Strategy %s",
strat.get_strategy_name())
backtest_start_time = datetime.now(timezone.utc)
self._set_strategy(strat)
strategy_safe_wrapper(self.strategy.bot_loop_start,
supress_error=True)()
# Use max_open_trades in backtesting, except --disable-max-market-positions is set
if self.config.get('use_max_market_positions', True):
# Must come from strategy config, as the strategy may modify this setting.
max_open_trades = self.strategy.config['max_open_trades']
else:
logger.info(
'Ignoring max_open_trades (--disable-max-market-positions was used) ...'
)
max_open_trades = 0
# need to reprocess data every time to populate signals
preprocessed = self.strategy.advise_all_indicators(data)
# Trim startup period from analyzed dataframe
preprocessed_tmp = trim_dataframes(preprocessed, timerange,
self.required_startup)
if not preprocessed_tmp:
raise OperationalException(
"No data left after adjusting for startup candles.")
# Use preprocessed_tmp for date generation (the trimmed dataframe).
# Backtesting will re-trim the dataframes after buy/sell signal generation.
min_date, max_date = history.get_timerange(preprocessed_tmp)
logger.info(
f'Backtesting with data from {min_date.strftime(DATETIME_PRINT_FORMAT)} '
f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} '
f'({(max_date - min_date).days} days).')
# Execute backtest and store results
results = self.backtest(
processed=preprocessed,
start_date=min_date,
end_date=max_date,
max_open_trades=max_open_trades,
position_stacking=self.config.get('position_stacking', False),
enable_protections=self.config.get('enable_protections', False),
)
backtest_end_time = datetime.now(timezone.utc)
results.update({
'run_id':
self.run_ids.get(strat.get_strategy_name(), ''),
'backtest_start_time':
int(backtest_start_time.timestamp()),
'backtest_end_time':
int(backtest_end_time.timestamp()),
})
self.all_results[self.strategy.get_strategy_name()] = results
return min_date, max_date
def _get_min_cached_backtest_date(self):
min_backtest_date = None
backtest_cache_age = self.config.get('backtest_cache',
constants.BACKTEST_CACHE_DEFAULT)
if self.timerange.stopts == 0 or datetime.fromtimestamp(
self.timerange.stopts,
tz=timezone.utc) > datetime.now(tz=timezone.utc):
logger.warning(
'Backtest result caching disabled due to use of open-ended timerange.'
)
elif backtest_cache_age == 'day':
min_backtest_date = datetime.now(tz=timezone.utc) - timedelta(
days=1)
elif backtest_cache_age == 'week':
min_backtest_date = datetime.now(tz=timezone.utc) - timedelta(
weeks=1)
elif backtest_cache_age == 'month':
min_backtest_date = datetime.now(tz=timezone.utc) - timedelta(
weeks=4)
return min_backtest_date
def load_prior_backtest(self):
self.run_ids = {
strategy.get_strategy_name(): get_strategy_run_id(strategy)
for strategy in self.strategylist
}
# Load previous result that will be updated incrementally.
# This can be circumvented in certain instances in combination with downloading more data
min_backtest_date = self._get_min_cached_backtest_date()
if min_backtest_date is not None:
self.results = find_existing_backtest_stats(
self.config['user_data_dir'] / 'backtest_results',
self.run_ids, min_backtest_date)
def start(self) -> None:
"""
Run backtesting end-to-end
:return: None
"""
data: Dict[str, Any] = {}
data, timerange = self.load_bt_data()
self.load_bt_data_detail()
logger.info("Dataload complete. Calculating indicators")
self.load_prior_backtest()
for strat in self.strategylist:
if self.results and strat.get_strategy_name(
) in self.results['strategy']:
# When previous result hash matches - reuse that result and skip backtesting.
logger.info(
f'Reusing result of previous backtest for {strat.get_strategy_name()}'
)
continue
min_date, max_date = self.backtest_one_strategy(
strat, data, timerange)
# Update old results with new ones.
if len(self.all_results) > 0:
results = generate_backtest_stats(data,
self.all_results,
min_date=min_date,
max_date=max_date)
if self.results:
self.results['metadata'].update(results['metadata'])
self.results['strategy'].update(results['strategy'])
self.results['strategy_comparison'].extend(
results['strategy_comparison'])
else:
self.results = results
if self.config.get('export', 'none') == 'trades':
store_backtest_stats(self.config['exportfilename'],
self.results)
# Results may be mixed up now. Sort them so they follow --strategy-list order.
if 'strategy_list' in self.config and len(self.results) > 0:
self.results['strategy_comparison'] = sorted(
self.results['strategy_comparison'],
key=lambda c: self.config['strategy_list'].index(c['key']))
self.results['strategy'] = dict(
sorted(
self.results['strategy'].items(),
key=lambda kv: self.config['strategy_list'].index(kv[0])))
if len(self.strategylist) > 0:
# Show backtest results
show_backtest_results(self.config, self.results)
class Backtesting:
"""
Backtesting class, this class contains all the logic to run a backtest
To run a backtest:
backtesting = Backtesting(config)
backtesting.start()
"""
def __init__(self, config: Dict[str, Any]) -> None:
LoggingMixin.show_output = False
self.config = config
# Reset keys for backtesting
remove_credentials(self.config)
self.strategylist: List[IStrategy] = []
self.all_results: Dict[str, Dict] = {}
self.exchange = ExchangeResolver.load_exchange(
self.config['exchange']['name'], self.config)
self.dataprovider = DataProvider(self.config, None)
if self.config.get('strategy_list', None):
for strat in list(self.config['strategy_list']):
stratconf = deepcopy(self.config)
stratconf['strategy'] = strat
self.strategylist.append(
StrategyResolver.load_strategy(stratconf))
validate_config_consistency(stratconf)
else:
# No strategy list specified, only one strategy
self.strategylist.append(
StrategyResolver.load_strategy(self.config))
validate_config_consistency(self.config)
if "timeframe" not in self.config:
raise OperationalException(
"Timeframe (ticker interval) needs to be set in either "
"configuration or as cli argument `--timeframe 5m`")
self.timeframe = str(self.config.get('timeframe'))
self.timeframe_min = timeframe_to_minutes(self.timeframe)
self.pairlists = PairListManager(self.exchange, self.config)
if 'VolumePairList' in self.pairlists.name_list:
raise OperationalException(
"VolumePairList not allowed for backtesting.")
if 'PerformanceFilter' in self.pairlists.name_list:
raise OperationalException(
"PerformanceFilter not allowed for backtesting.")
if len(self.strategylist
) > 1 and 'PrecisionFilter' in self.pairlists.name_list:
raise OperationalException(
"PrecisionFilter not allowed for backtesting multiple strategies."
)
self.dataprovider.add_pairlisthandler(self.pairlists)
self.pairlists.refresh_pairlist()
if len(self.pairlists.whitelist) == 0:
raise OperationalException("No pair in whitelist.")
if config.get('fee', None) is not None:
self.fee = config['fee']
else:
self.fee = self.exchange.get_fee(
symbol=self.pairlists.whitelist[0])
Trade.use_db = False
Trade.reset_trades()
PairLocks.timeframe = self.config['timeframe']
PairLocks.use_db = False
PairLocks.reset_locks()
self.wallets = Wallets(self.config, self.exchange, log=False)
# Get maximum required startup period
self.required_startup = max(
[strat.startup_candle_count for strat in self.strategylist])
def __del__(self):
LoggingMixin.show_output = True
PairLocks.use_db = True
Trade.use_db = True
def _set_strategy(self, strategy: IStrategy):
"""
Load strategy into backtesting
"""
self.strategy: IStrategy = strategy
strategy.dp = self.dataprovider
# Set stoploss_on_exchange to false for backtesting,
# since a "perfect" stoploss-sell is assumed anyway
# And the regular "stoploss" function would not apply to that case
self.strategy.order_types['stoploss_on_exchange'] = False
if self.config.get('enable_protections', False):
conf = self.config
if hasattr(strategy, 'protections'):
conf = deepcopy(conf)
conf['protections'] = strategy.protections
self.protections = ProtectionManager(self.config,
strategy.protections)
def load_bt_data(self) -> Tuple[Dict[str, DataFrame], TimeRange]:
"""
Loads backtest data and returns the data combined with the timerange
as tuple.
"""
timerange = TimeRange.parse_timerange(None if self.config.get(
'timerange') is None else str(self.config.get('timerange')))
data = history.load_data(
datadir=self.config['datadir'],
pairs=self.pairlists.whitelist,
timeframe=self.timeframe,
timerange=timerange,
startup_candles=self.required_startup,
fail_without_data=True,
data_format=self.config.get('dataformat_ohlcv', 'json'),
)
min_date, max_date = history.get_timerange(data)
logger.info(
f'Loading data from {min_date.strftime(DATETIME_PRINT_FORMAT)} '
f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} '
f'({(max_date - min_date).days} days).')
# Adjust startts forward if not enough data is available
timerange.adjust_start_if_necessary(
timeframe_to_seconds(self.timeframe), self.required_startup,
min_date)
return data, timerange
def prepare_backtest(self, enable_protections):
"""
Backtesting setup method - called once for every call to "backtest()".
"""
PairLocks.use_db = False
PairLocks.timeframe = self.config['timeframe']
Trade.use_db = False
PairLocks.reset_locks()
Trade.reset_trades()
self.rejected_trades = 0
self.dataprovider.clear_cache()
def _get_ohlcv_as_lists(
self, processed: Dict[str, DataFrame]) -> Dict[str, Tuple]:
"""
Helper function to convert a processed dataframes into lists for performance reasons.
Used by backtest() - so keep this optimized for performance.
"""
# Every change to this headers list must evaluate further usages of the resulting tuple
# and eventually change the constants for indexes at the top
headers = ['date', 'buy', 'open', 'close', 'sell', 'low', 'high']
data: Dict = {}
# Create dict with data
for pair, pair_data in processed.items():
if not pair_data.empty:
pair_data.loc[:, 'buy'] = 0 # cleanup if buy_signal is exist
pair_data.loc[:, 'sell'] = 0 # cleanup if sell_signal is exist
df_analyzed = self.strategy.advise_sell(
self.strategy.advise_buy(pair_data, {'pair': pair}),
{'pair': pair})[headers].copy()
# To avoid using data from future, we use buy/sell signals shifted
# from the previous candle
df_analyzed.loc[:, 'buy'] = df_analyzed.loc[:, 'buy'].shift(1)
df_analyzed.loc[:, 'sell'] = df_analyzed.loc[:, 'sell'].shift(1)
df_analyzed.drop(df_analyzed.head(1).index, inplace=True)
# Convert from Pandas to list for performance reasons
# (Looping Pandas is slow.)
data[pair] = df_analyzed.values.tolist()
return data
def _get_close_rate(self, sell_row: Tuple, trade: LocalTrade,
sell: SellCheckTuple, trade_dur: int) -> float:
"""
Get close rate for backtesting result
"""
# Special handling if high or low hit STOP_LOSS or ROI
if sell.sell_type in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
if trade.stop_loss > sell_row[HIGH_IDX]:
# our stoploss was already higher than candle high,
# possibly due to a cancelled trade exit.
# sell at open price.
return sell_row[OPEN_IDX]
# Special case: trailing triggers within same candle as trade opened. Assume most
# pessimistic price movement, which is moving just enough to arm stoploss and
# immediately going down to stop price.
if (sell.sell_type == SellType.TRAILING_STOP_LOSS
and trade_dur == 0
and self.strategy.trailing_stop_positive):
if self.strategy.trailing_only_offset_is_reached:
# Worst case: price reaches stop_positive_offset and dives down.
stop_rate = (
sell_row[OPEN_IDX] *
(1 + abs(self.strategy.trailing_stop_positive_offset) -
abs(self.strategy.trailing_stop_positive)))
else:
# Worst case: price ticks tiny bit above open and dives down.
stop_rate = sell_row[OPEN_IDX] * (
1 - abs(self.strategy.trailing_stop_positive))
assert stop_rate < sell_row[HIGH_IDX]
return stop_rate
# Set close_rate to stoploss
return trade.stop_loss
elif sell.sell_type == (SellType.ROI):
roi_entry, roi = self.strategy.min_roi_reached_entry(trade_dur)
if roi is not None and roi_entry is not None:
if roi == -1 and roi_entry % self.timeframe_min == 0:
# When forceselling with ROI=-1, the roi time will always be equal to trade_dur.
# If that entry is a multiple of the timeframe (so on candle open)
# - we'll use open instead of close
return sell_row[OPEN_IDX]
# - (Expected abs profit + open_rate + open_fee) / (fee_close -1)
close_rate = -(trade.open_rate * roi + trade.open_rate *
(1 + trade.fee_open)) / (trade.fee_close - 1)
if (trade_dur > 0 and trade_dur == roi_entry
and roi_entry % self.timeframe_min == 0
and sell_row[OPEN_IDX] > close_rate):
# new ROI entry came into effect.
# use Open rate if open_rate > calculated sell rate
return sell_row[OPEN_IDX]
# Use the maximum between close_rate and low as we
# cannot sell outside of a candle.
# Applies when a new ROI setting comes in place and the whole candle is above that.
return min(max(close_rate, sell_row[LOW_IDX]),
sell_row[HIGH_IDX])
else:
# This should not be reached...
return sell_row[OPEN_IDX]
else:
return sell_row[OPEN_IDX]
def _get_sell_trade_entry(self, trade: LocalTrade,
sell_row: Tuple) -> Optional[LocalTrade]:
sell = self.strategy.should_sell(
trade,
sell_row[OPEN_IDX], # type: ignore
sell_row[DATE_IDX].to_pydatetime(),
sell_row[BUY_IDX],
sell_row[SELL_IDX],
low=sell_row[LOW_IDX],
high=sell_row[HIGH_IDX])
if sell.sell_flag:
trade.close_date = sell_row[DATE_IDX].to_pydatetime()
trade.sell_reason = sell.sell_reason
trade_dur = int(
(trade.close_date_utc - trade.open_date_utc).total_seconds() //
60)
closerate = self._get_close_rate(sell_row, trade, sell, trade_dur)
# Confirm trade exit:
time_in_force = self.strategy.order_time_in_force['sell']
if not strategy_safe_wrapper(
self.strategy.confirm_trade_exit, default_retval=True)(
pair=trade.pair,
trade=trade,
order_type='limit',
amount=trade.amount,
rate=closerate,
time_in_force=time_in_force,
sell_reason=sell.sell_reason,
current_time=sell_row[DATE_IDX].to_pydatetime()):
return None
trade.close(closerate, show_msg=False)
return trade
return None
def _enter_trade(self, pair: str, row: List) -> Optional[LocalTrade]:
try:
stake_amount = self.wallets.get_trade_stake_amount(pair, None)
except DependencyException:
return None
min_stake_amount = self.exchange.get_min_pair_stake_amount(
pair, row[OPEN_IDX], -0.05)
order_type = self.strategy.order_types['buy']
time_in_force = self.strategy.order_time_in_force['sell']
# Confirm trade entry:
if not strategy_safe_wrapper(
self.strategy.confirm_trade_entry, default_retval=True)(
pair=pair,
order_type=order_type,
amount=stake_amount,
rate=row[OPEN_IDX],
time_in_force=time_in_force,
current_time=row[DATE_IDX].to_pydatetime()):
return None
if stake_amount and (not min_stake_amount
or stake_amount > min_stake_amount):
# Enter trade
trade = LocalTrade(
pair=pair,
open_rate=row[OPEN_IDX],
open_date=row[DATE_IDX].to_pydatetime(),
stake_amount=stake_amount,
amount=round(stake_amount / row[OPEN_IDX], 8),
fee_open=self.fee,
fee_close=self.fee,
is_open=True,
exchange='backtesting',
)
return trade
return None
def handle_left_open(self, open_trades: Dict[str, List[LocalTrade]],
data: Dict[str, List[Tuple]]) -> List[LocalTrade]:
"""
Handling of left open trades at the end of backtesting
"""
trades = []
for pair in open_trades.keys():
if len(open_trades[pair]) > 0:
for trade in open_trades[pair]:
sell_row = data[pair][-1]
trade.close_date = sell_row[DATE_IDX].to_pydatetime()
trade.sell_reason = SellType.FORCE_SELL.value
trade.close(sell_row[OPEN_IDX], show_msg=False)
LocalTrade.close_bt_trade(trade)
# Deepcopy object to have wallets update correctly
trade1 = deepcopy(trade)
trade1.is_open = True
trades.append(trade1)
return trades
def trade_slot_available(self, max_open_trades: int,
open_trade_count: int) -> bool:
# Always allow trades when max_open_trades is enabled.
if max_open_trades <= 0 or open_trade_count < max_open_trades:
return True
# Rejected trade
self.rejected_trades += 1
return False
def backtest(self,
processed: Dict,
start_date: datetime,
end_date: datetime,
max_open_trades: int = 0,
position_stacking: bool = False,
enable_protections: bool = False) -> Dict[str, Any]:
"""
Implement backtesting functionality
NOTE: This method is used by Hyperopt at each iteration. Please keep it optimized.
Of course try to not have ugly code. By some accessor are sometime slower than functions.
Avoid extensive logging in this method and functions it calls.
:param processed: a processed dictionary with format {pair, data}
:param start_date: backtesting timerange start datetime
:param end_date: backtesting timerange end datetime
:param max_open_trades: maximum number of concurrent trades, <= 0 means unlimited
:param position_stacking: do we allow position stacking?
:param enable_protections: Should protections be enabled?
:return: DataFrame with trades (results of backtesting)
"""
trades: List[LocalTrade] = []
self.prepare_backtest(enable_protections)
# Update dataprovider cache
for pair, dataframe in processed.items():
self.dataprovider._set_cached_df(pair, self.timeframe, dataframe)
# Use dict of lists with data for performance
# (looping lists is a lot faster than pandas DataFrames)
data: Dict = self._get_ohlcv_as_lists(processed)
# Indexes per pair, so some pairs are allowed to have a missing start.
indexes: Dict = defaultdict(int)
tmp = start_date + timedelta(minutes=self.timeframe_min)
open_trades: Dict[str, List[LocalTrade]] = defaultdict(list)
open_trade_count = 0
# Loop timerange and get candle for each pair at that point in time
while tmp <= end_date:
open_trade_count_start = open_trade_count
for i, pair in enumerate(data):
row_index = indexes[pair]
try:
row = data[pair][row_index]
except IndexError:
# missing Data for one pair at the end.
# Warnings for this are shown during data loading
continue
# Waits until the time-counter reaches the start of the data for this pair.
if row[DATE_IDX] > tmp:
continue
row_index += 1
self.dataprovider._set_dataframe_max_index(row_index)
indexes[pair] = row_index
# without positionstacking, we can only have one open trade per pair.
# max_open_trades must be respected
# don't open on the last row
if ((position_stacking or len(open_trades[pair]) == 0)
and self.trade_slot_available(max_open_trades,
open_trade_count_start)
and tmp != end_date and row[BUY_IDX] == 1
and row[SELL_IDX] != 1
and not PairLocks.is_pair_locked(pair, row[DATE_IDX])):
trade = self._enter_trade(pair, row)
if trade:
# TODO: hacky workaround to avoid opening > max_open_trades
# This emulates previous behaviour - not sure if this is correct
# Prevents buying if the trade-slot was freed in this candle
open_trade_count_start += 1
open_trade_count += 1
# logger.debug(f"{pair} - Emulate creation of new trade: {trade}.")
open_trades[pair].append(trade)
LocalTrade.add_bt_trade(trade)
for trade in open_trades[pair]:
# also check the buying candle for sell conditions.
trade_entry = self._get_sell_trade_entry(trade, row)
# Sell occured
if trade_entry:
# logger.debug(f"{pair} - Backtesting sell {trade}")
open_trade_count -= 1
open_trades[pair].remove(trade)
LocalTrade.close_bt_trade(trade)
trades.append(trade_entry)
if enable_protections:
self.protections.stop_per_pair(pair, row[DATE_IDX])
self.protections.global_stop(tmp)
# Move time one configured time_interval ahead.
tmp += timedelta(minutes=self.timeframe_min)
trades += self.handle_left_open(open_trades, data=data)
self.wallets.update()
results = trade_list_to_dataframe(trades)
return {
'results':
results,
'config':
self.strategy.config,
'locks':
PairLocks.get_all_locks(),
'rejected_signals':
self.rejected_trades,
'final_balance':
self.wallets.get_total(self.strategy.config['stake_currency']),
}
def backtest_one_strategy(self, strat: IStrategy, data: Dict[str, Any],
timerange: TimeRange):
logger.info("Running backtesting for Strategy %s",
strat.get_strategy_name())
backtest_start_time = datetime.now(timezone.utc)
self._set_strategy(strat)
strategy_safe_wrapper(self.strategy.bot_loop_start,
supress_error=True)()
# Use max_open_trades in backtesting, except --disable-max-market-positions is set
if self.config.get('use_max_market_positions', True):
# Must come from strategy config, as the strategy may modify this setting.
max_open_trades = self.strategy.config['max_open_trades']
else:
logger.info(
'Ignoring max_open_trades (--disable-max-market-positions was used) ...'
)
max_open_trades = 0
# need to reprocess data every time to populate signals
preprocessed = self.strategy.ohlcvdata_to_dataframe(data)
# Trim startup period from analyzed dataframe
preprocessed = trim_dataframes(preprocessed, timerange,
self.required_startup)
if not preprocessed:
raise OperationalException(
"No data left after adjusting for startup candles.")
min_date, max_date = history.get_timerange(preprocessed)
logger.info(
f'Backtesting with data from {min_date.strftime(DATETIME_PRINT_FORMAT)} '
f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} '
f'({(max_date - min_date).days} days).')
# Execute backtest and store results
results = self.backtest(
processed=preprocessed,
start_date=min_date,
end_date=max_date,
max_open_trades=max_open_trades,
position_stacking=self.config.get('position_stacking', False),
enable_protections=self.config.get('enable_protections', False),
)
backtest_end_time = datetime.now(timezone.utc)
results.update({
'backtest_start_time':
int(backtest_start_time.timestamp()),
'backtest_end_time':
int(backtest_end_time.timestamp()),
})
self.all_results[self.strategy.get_strategy_name()] = results
return min_date, max_date
def start(self) -> None:
"""
Run backtesting end-to-end
:return: None
"""
data: Dict[str, Any] = {}
data, timerange = self.load_bt_data()
logger.info("Dataload complete. Calculating indicators")
for strat in self.strategylist:
min_date, max_date = self.backtest_one_strategy(
strat, data, timerange)
if len(self.strategylist) > 0:
stats = generate_backtest_stats(data,
self.all_results,
min_date=min_date,
max_date=max_date)
if self.config.get('export', 'none') == 'trades':
store_backtest_stats(self.config['exportfilename'], stats)
# Show backtest results
show_backtest_results(self.config, stats)
class FreqtradeBot(object):
"""
Freqtrade is the main class of the bot.
This is from here the bot start its logic.
"""
def __init__(self, config: Dict[str, Any]) -> None:
"""
Init all variables and object the bot need to work
:param config: configuration dict, you can use the Configuration.get_config()
method to get the config dict.
"""
logger.info(
'Starting freqtrade %s',
__version__,
)
# Init bot states
self.state = State.STOPPED
# Init objects
self.config = config
self.strategy: IStrategy = StrategyResolver(self.config).strategy
self.rpc: RPCManager = RPCManager(self)
self.persistence = None
self.exchange = Exchange(self.config)
self.wallets = Wallets(self.exchange)
pairlistname = self.config.get('pairlist',
{}).get('method', 'StaticPairList')
self.pairlists = PairListResolver(pairlistname, self,
self.config).pairlist
# Initializing Edge only if enabled
self.edge = Edge(self.config, self.exchange, self.strategy) if \
self.config.get('edge', {}).get('enabled', False) else None
self.active_pair_whitelist: List[str] = self.config['exchange'][
'pair_whitelist']
self._init_modules()
def _init_modules(self) -> None:
"""
Initializes all modules and updates the config
:return: None
"""
# Initialize all modules
persistence.init(self.config)
# Set initial application state
initial_state = self.config.get('initial_state')
if initial_state:
self.state = State[initial_state.upper()]
else:
self.state = State.STOPPED
def cleanup(self) -> None:
"""
Cleanup pending resources on an already stopped bot
:return: None
"""
logger.info('Cleaning up modules ...')
self.rpc.cleanup()
persistence.cleanup()
def worker(self, old_state: State = None) -> State:
"""
Trading routine that must be run at each loop
:param old_state: the previous service state from the previous call
:return: current service state
"""
# Log state transition
state = self.state
if state != old_state:
self.rpc.send_msg({
'type': RPCMessageType.STATUS_NOTIFICATION,
'status': f'{state.name.lower()}'
})
logger.info('Changing state to: %s', state.name)
if state == State.RUNNING:
self.rpc.startup_messages(self.config, self.pairlists)
if state == State.STOPPED:
time.sleep(1)
elif state == State.RUNNING:
min_secs = self.config.get('internals',
{}).get('process_throttle_secs',
constants.PROCESS_THROTTLE_SECS)
self._throttle(func=self._process, min_secs=min_secs)
return state
def _throttle(self, func: Callable[..., Any], min_secs: float, *args,
**kwargs) -> Any:
"""
Throttles the given callable that it
takes at least `min_secs` to finish execution.
:param func: Any callable
:param min_secs: minimum execution time in seconds
:return: Any
"""
start = time.time()
result = func(*args, **kwargs)
end = time.time()
duration = max(min_secs - (end - start), 0.0)
logger.debug('Throttling %s for %.2f seconds', func.__name__, duration)
time.sleep(duration)
return result
def _process(self) -> bool:
"""
Queries the persistence layer for open trades and handles them,
otherwise a new trade is created.
:return: True if one or more trades has been created or closed, False otherwise
"""
state_changed = False
try:
# Refresh whitelist
self.pairlists.refresh_pairlist()
self.active_pair_whitelist = self.pairlists.whitelist
# Calculating Edge positiong
# Should be called before refresh_tickers
# Otherwise it will override cached klines in exchange
# with delta value (klines only from last refresh_pairs)
if self.edge:
self.edge.calculate()
self.active_pair_whitelist = self.edge.adjust(
self.active_pair_whitelist)
# Query trades from persistence layer
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
# Extend active-pair whitelist with pairs from open trades
# ensures that tickers are downloaded for open trades
self.active_pair_whitelist.extend([
trade.pair for trade in trades
if trade.pair not in self.active_pair_whitelist
])
# Refreshing candles
self.exchange.refresh_tickers(self.active_pair_whitelist,
self.strategy.ticker_interval)
# First process current opened trades
for trade in trades:
state_changed |= self.process_maybe_execute_sell(trade)
# Then looking for buy opportunities
if len(trades) < self.config['max_open_trades']:
state_changed = self.process_maybe_execute_buy()
if 'unfilledtimeout' in self.config:
# Check and handle any timed out open orders
self.check_handle_timedout()
Trade.session.flush()
except TemporaryError as error:
logger.warning('%s, retrying in 30 seconds...', error)
time.sleep(constants.RETRY_TIMEOUT)
except OperationalException:
tb = traceback.format_exc()
hint = 'Issue `/start` if you think it is safe to restart.'
self.rpc.send_msg({
'type':
RPCMessageType.STATUS_NOTIFICATION,
'status':
f'OperationalException:\n```\n{tb}```{hint}'
})
logger.exception('OperationalException. Stopping trader ...')
self.state = State.STOPPED
return state_changed
def get_target_bid(self, pair: str, ticker: Dict[str, float]) -> float:
"""
Calculates bid target between current ask price and last price
:param ticker: Ticker to use for getting Ask and Last Price
:return: float: Price
"""
if ticker['ask'] < ticker['last']:
ticker_rate = ticker['ask']
else:
balance = self.config['bid_strategy']['ask_last_balance']
ticker_rate = ticker['ask'] + balance * (ticker['last'] -
ticker['ask'])
used_rate = ticker_rate
config_bid_strategy = self.config.get('bid_strategy', {})
if 'use_order_book' in config_bid_strategy and\
config_bid_strategy.get('use_order_book', False):
logger.info('Getting price from order book')
order_book_top = config_bid_strategy.get('order_book_top', 1)
order_book = self.exchange.get_order_book(pair, order_book_top)
logger.debug('order_book %s', order_book)
# top 1 = index 0
order_book_rate = order_book['bids'][order_book_top - 1][0]
# if ticker has lower rate, then use ticker ( usefull if down trending )
logger.info('...top %s order book buy rate %0.8f', order_book_top,
order_book_rate)
if ticker_rate < order_book_rate:
logger.info('...using ticker rate instead %0.8f', ticker_rate)
used_rate = ticker_rate
else:
used_rate = order_book_rate
else:
logger.info('Using Last Ask / Last Price')
used_rate = ticker_rate
return used_rate
def _get_trade_stake_amount(self, pair) -> Optional[float]:
"""
Check if stake amount can be fulfilled with the available balance
for the stake currency
:return: float: Stake Amount
"""
if self.edge:
return self.edge.stake_amount(
pair, self.wallets.get_free(self.config['stake_currency']),
self.wallets.get_total(self.config['stake_currency']),
Trade.total_open_trades_stakes())
else:
stake_amount = self.config['stake_amount']
avaliable_amount = self.wallets.get_free(self.config['stake_currency'])
if stake_amount == constants.UNLIMITED_STAKE_AMOUNT:
open_trades = len(
Trade.query.filter(Trade.is_open.is_(True)).all())
if open_trades >= self.config['max_open_trades']:
logger.warning(
'Can\'t open a new trade: max number of trades is reached')
return None
return avaliable_amount / (self.config['max_open_trades'] -
open_trades)
# Check if stake_amount is fulfilled
if avaliable_amount < stake_amount:
raise DependencyException(
'Available balance(%f %s) is lower than stake amount(%f %s)' %
(avaliable_amount, self.config['stake_currency'], stake_amount,
self.config['stake_currency']))
return stake_amount
def _get_min_pair_stake_amount(self, pair: str,
price: float) -> Optional[float]:
markets = self.exchange.get_markets()
markets = [m for m in markets if m['symbol'] == pair]
if not markets:
raise ValueError(
f'Can\'t get market information for symbol {pair}')
market = markets[0]
if 'limits' not in market:
return None
min_stake_amounts = []
limits = market['limits']
if ('cost' in limits and 'min' in limits['cost']
and limits['cost']['min'] is not None):
min_stake_amounts.append(limits['cost']['min'])
if ('amount' in limits and 'min' in limits['amount']
and limits['amount']['min'] is not None):
min_stake_amounts.append(limits['amount']['min'] * price)
if not min_stake_amounts:
return None
amount_reserve_percent = 1 - 0.05 # reserve 5% + stoploss
if self.strategy.stoploss is not None:
amount_reserve_percent += self.strategy.stoploss
# it should not be more than 50%
amount_reserve_percent = max(amount_reserve_percent, 0.5)
return min(min_stake_amounts) / amount_reserve_percent
def create_trade(self) -> bool:
"""
Checks the implemented trading indicator(s) for a randomly picked pair,
if one pair triggers the buy_signal a new trade record gets created
:return: True if a trade object has been created and persisted, False otherwise
"""
interval = self.strategy.ticker_interval
whitelist = copy.deepcopy(self.active_pair_whitelist)
# Remove currently opened and latest pairs from whitelist
for trade in Trade.query.filter(Trade.is_open.is_(True)).all():
if trade.pair in whitelist:
whitelist.remove(trade.pair)
logger.debug('Ignoring %s in pair whitelist', trade.pair)
if not whitelist:
raise DependencyException('No currency pairs in whitelist')
# running get_signal on historical data fetched
for _pair in whitelist:
(buy, sell) = self.strategy.get_signal(_pair, interval,
self.exchange.klines(_pair))
if buy and not sell:
stake_amount = self._get_trade_stake_amount(_pair)
if not stake_amount:
return False
logger.info(
'Buy signal found: about create a new trade with stake_amount: %f ...',
stake_amount)
bidstrat_check_depth_of_market = self.config.get('bid_strategy', {}).\
get('check_depth_of_market', {})
if (bidstrat_check_depth_of_market.get('enabled', False)) and\
(bidstrat_check_depth_of_market.get('bids_to_ask_delta', 0) > 0):
if self._check_depth_of_market_buy(
_pair, bidstrat_check_depth_of_market):
return self.execute_buy(_pair, stake_amount)
else:
return False
return self.execute_buy(_pair, stake_amount)
return False
def _check_depth_of_market_buy(self, pair: str, conf: Dict) -> bool:
"""
Checks depth of market before executing a buy
"""
conf_bids_to_ask_delta = conf.get('bids_to_ask_delta', 0)
logger.info('checking depth of market for %s', pair)
order_book = self.exchange.get_order_book(pair, 1000)
order_book_data_frame = order_book_to_dataframe(
order_book['bids'], order_book['asks'])
order_book_bids = order_book_data_frame['b_size'].sum()
order_book_asks = order_book_data_frame['a_size'].sum()
bids_ask_delta = order_book_bids / order_book_asks
logger.info('bids: %s, asks: %s, delta: %s', order_book_bids,
order_book_asks, bids_ask_delta)
if bids_ask_delta >= conf_bids_to_ask_delta:
return True
return False
def execute_buy(self,
pair: str,
stake_amount: float,
price: Optional[float] = None) -> bool:
"""
Executes a limit buy for the given pair
:param pair: pair for which we want to create a LIMIT_BUY
:return: None
"""
pair_s = pair.replace('_', '/')
pair_url = self.exchange.get_pair_detail_url(pair)
stake_currency = self.config['stake_currency']
fiat_currency = self.config.get('fiat_display_currency', None)
time_in_force = self.strategy.order_time_in_force['buy']
if price:
buy_limit_requested = price
else:
# Calculate amount
buy_limit_requested = self.get_target_bid(
pair, self.exchange.get_ticker(pair))
min_stake_amount = self._get_min_pair_stake_amount(
pair_s, buy_limit_requested)
if min_stake_amount is not None and min_stake_amount > stake_amount:
logger.warning(
f'Can\'t open a new trade for {pair_s}: stake amount'
f' is too small ({stake_amount} < {min_stake_amount})')
return False
amount = stake_amount / buy_limit_requested
order = self.exchange.buy(pair=pair,
ordertype=self.strategy.order_types['buy'],
amount=amount,
rate=buy_limit_requested,
time_in_force=time_in_force)
order_id = order['id']
order_status = order.get('status', None)
# we assume the order is executed at the price requested
buy_limit_filled_price = buy_limit_requested
if order_status == 'expired' or order_status == 'rejected':
order_type = self.strategy.order_types['buy']
order_tif = self.strategy.order_time_in_force['buy']
# return false if the order is not filled
if float(order['filled']) == 0:
logger.warning(
'Buy %s order with time in force %s for %s is %s by %s.'
' zero amount is fulfilled.', order_tif, order_type,
pair_s, order_status, self.exchange.name)
return False
else:
# the order is partially fulfilled
# in case of IOC orders we can check immediately
# if the order is fulfilled fully or partially
logger.warning(
'Buy %s order with time in force %s for %s is %s by %s.'
' %s amount fulfilled out of %s (%s remaining which is canceled).',
order_tif, order_type, pair_s, order_status,
self.exchange.name, order['filled'], order['amount'],
order['remaining'])
stake_amount = order['cost']
amount = order['amount']
buy_limit_filled_price = order['price']
order_id = None
# in case of FOK the order may be filled immediately and fully
elif order_status == 'closed':
stake_amount = order['cost']
amount = order['amount']
buy_limit_filled_price = order['price']
order_id = None
self.rpc.send_msg({
'type': RPCMessageType.BUY_NOTIFICATION,
'exchange': self.exchange.name.capitalize(),
'pair': pair_s,
'market_url': pair_url,
'limit': buy_limit_filled_price,
'stake_amount': stake_amount,
'stake_currency': stake_currency,
'fiat_currency': fiat_currency
})
# Fee is applied twice because we make a LIMIT_BUY and LIMIT_SELL
fee = self.exchange.get_fee(symbol=pair, taker_or_maker='maker')
trade = Trade(pair=pair,
stake_amount=stake_amount,
amount=amount,
fee_open=fee,
fee_close=fee,
open_rate=buy_limit_filled_price,
open_rate_requested=buy_limit_requested,
open_date=datetime.utcnow(),
exchange=self.exchange.id,
open_order_id=order_id,
strategy=self.strategy.get_strategy_name(),
ticker_interval=constants.TICKER_INTERVAL_MINUTES[
self.config['ticker_interval']])
Trade.session.add(trade)
Trade.session.flush()
# Updating wallets
self.wallets.update()
return True
def process_maybe_execute_buy(self) -> bool:
"""
Tries to execute a buy trade in a safe way
:return: True if executed
"""
try:
# Create entity and execute trade
if self.create_trade():
return True
logger.info(
'Found no buy signals for whitelisted currencies. Trying again..'
)
return False
except DependencyException as exception:
logger.warning('Unable to create trade: %s', exception)
return False
def process_maybe_execute_sell(self, trade: Trade) -> bool:
"""
Tries to execute a sell trade
:return: True if executed
"""
try:
# Get order details for actual price per unit
if trade.open_order_id:
# Update trade with order values
logger.info('Found open order for %s', trade)
order = self.exchange.get_order(trade.open_order_id,
trade.pair)
# Try update amount (binance-fix)
try:
new_amount = self.get_real_amount(trade, order)
if order['amount'] != new_amount:
order['amount'] = new_amount
# Fee was applied, so set to 0
trade.fee_open = 0
except OperationalException as exception:
logger.warning("could not update trade amount: %s",
exception)
trade.update(order)
if self.strategy.order_types.get(
'stoploss_on_exchange') and trade.is_open:
result = self.handle_stoploss_on_exchange(trade)
if result:
self.wallets.update()
return result
if trade.is_open and trade.open_order_id is None:
# Check if we can sell our current pair
result = self.handle_trade(trade)
# Updating wallets if any trade occured
if result:
self.wallets.update()
return result
except DependencyException as exception:
logger.warning('Unable to sell trade: %s', exception)
return False
def get_real_amount(self, trade: Trade, order: Dict) -> float:
"""
Get real amount for the trade
Necessary for self.exchanges which charge fees in base currency (e.g. binance)
"""
order_amount = order['amount']
# Only run for closed orders
if trade.fee_open == 0 or order['status'] == 'open':
return order_amount
# use fee from order-dict if possible
if 'fee' in order and order['fee'] and (order['fee'].keys() >=
{'currency', 'cost'}):
if trade.pair.startswith(order['fee']['currency']):
new_amount = order_amount - order['fee']['cost']
logger.info(
"Applying fee on amount for %s (from %s to %s) from Order",
trade, order['amount'], new_amount)
return new_amount
# Fallback to Trades
trades = self.exchange.get_trades_for_order(trade.open_order_id,
trade.pair,
trade.open_date)
if len(trades) == 0:
logger.info(
"Applying fee on amount for %s failed: myTrade-Dict empty found",
trade)
return order_amount
amount = 0
fee_abs = 0
for exectrade in trades:
amount += exectrade['amount']
if "fee" in exectrade and (exectrade['fee'].keys() >=
{'currency', 'cost'}):
# only applies if fee is in quote currency!
if trade.pair.startswith(exectrade['fee']['currency']):
fee_abs += exectrade['fee']['cost']
if amount != order_amount:
logger.warning(
f"amount {amount} does not match amount {trade.amount}")
raise OperationalException("Half bought? Amounts don't match")
real_amount = amount - fee_abs
if fee_abs != 0:
logger.info(f"""Applying fee on amount for {trade} \
(from {order_amount} to {real_amount}) from Trades""")
return real_amount
def handle_trade(self, trade: Trade) -> bool:
"""
Sells the current pair if the threshold is reached and updates the trade record.
:return: True if trade has been sold, False otherwise
"""
if not trade.is_open:
raise ValueError(f'attempt to handle closed trade: {trade}')
logger.debug('Handling %s ...', trade)
sell_rate = self.exchange.get_ticker(trade.pair)['bid']
(buy, sell) = (False, False)
experimental = self.config.get('experimental', {})
if experimental.get('use_sell_signal') or experimental.get(
'ignore_roi_if_buy_signal'):
(buy,
sell) = self.strategy.get_signal(trade.pair,
self.strategy.ticker_interval,
self.exchange.klines(trade.pair))
config_ask_strategy = self.config.get('ask_strategy', {})
if config_ask_strategy.get('use_order_book', False):
logger.info('Using order book for selling...')
# logger.debug('Order book %s',orderBook)
order_book_min = config_ask_strategy.get('order_book_min', 1)
order_book_max = config_ask_strategy.get('order_book_max', 1)
order_book = self.exchange.get_order_book(trade.pair,
order_book_max)
for i in range(order_book_min, order_book_max + 1):
order_book_rate = order_book['asks'][i - 1][0]
# if orderbook has higher rate (high profit),
# use orderbook, otherwise just use bids rate
logger.info(' order book asks top %s: %0.8f', i,
order_book_rate)
if sell_rate < order_book_rate:
sell_rate = order_book_rate
if self.check_sell(trade, sell_rate, buy, sell):
return True
break
else:
logger.debug('checking sell')
if self.check_sell(trade, sell_rate, buy, sell):
return True
logger.debug('Found no sell signal for %s.', trade)
return False
def handle_stoploss_on_exchange(self, trade: Trade) -> bool:
"""
Check if trade is fulfilled in which case the stoploss
on exchange should be added immediately if stoploss on exchnage
is enabled.
"""
result = False
# If trade is open and the buy order is fulfilled but there is no stoploss,
# then we add a stoploss on exchange
if not trade.open_order_id and not trade.stoploss_order_id:
if self.edge:
stoploss = self.edge.stoploss(pair=trade.pair)
else:
stoploss = self.strategy.stoploss
stop_price = trade.open_rate * (1 + stoploss)
# limit price should be less than stop price.
# 0.98 is arbitrary here.
limit_price = stop_price * 0.98
stoploss_order_id = self.exchange.stoploss_limit(
pair=trade.pair,
amount=trade.amount,
stop_price=stop_price,
rate=limit_price)['id']
trade.stoploss_order_id = str(stoploss_order_id)
# Or the trade open and there is already a stoploss on exchange.
# so we check if it is hit ...
elif trade.stoploss_order_id:
logger.debug('Handling stoploss on exchange %s ...', trade)
order = self.exchange.get_order(trade.stoploss_order_id,
trade.pair)
if order['status'] == 'closed':
trade.sell_reason = SellType.STOPLOSS_ON_EXCHANGE.value
trade.update(order)
result = True
else:
result = False
return result
def check_sell(self, trade: Trade, sell_rate: float, buy: bool,
sell: bool) -> bool:
if self.edge:
stoploss = self.edge.stoploss(trade.pair)
should_sell = self.strategy.should_sell(trade,
sell_rate,
datetime.utcnow(),
buy,
sell,
force_stoploss=stoploss)
else:
should_sell = self.strategy.should_sell(trade, sell_rate,
datetime.utcnow(), buy,
sell)
if should_sell.sell_flag:
self.execute_sell(trade, sell_rate, should_sell.sell_type)
logger.info('executed sell, reason: %s', should_sell.sell_type)
return True
return False
def check_handle_timedout(self) -> None:
"""
Check if any orders are timed out and cancel if neccessary
:param timeoutvalue: Number of minutes until order is considered timed out
:return: None
"""
buy_timeout = self.config['unfilledtimeout']['buy']
sell_timeout = self.config['unfilledtimeout']['sell']
buy_timeoutthreashold = arrow.utcnow().shift(
minutes=-buy_timeout).datetime
sell_timeoutthreashold = arrow.utcnow().shift(
minutes=-sell_timeout).datetime
for trade in Trade.query.filter(Trade.open_order_id.isnot(None)).all():
try:
# FIXME: Somehow the query above returns results
# where the open_order_id is in fact None.
# This is probably because the record got
# updated via /forcesell in a different thread.
if not trade.open_order_id:
continue
order = self.exchange.get_order(trade.open_order_id,
trade.pair)
except (RequestException, DependencyException):
logger.info('Cannot query order for %s due to %s', trade,
traceback.format_exc())
continue
ordertime = arrow.get(order['datetime']).datetime
# Check if trade is still actually open
if float(order['remaining']) == 0.0:
self.wallets.update()
continue
# Check if trade is still actually open
if order['status'] == 'open':
if order['side'] == 'buy' and ordertime < buy_timeoutthreashold:
self.handle_timedout_limit_buy(trade, order)
self.wallets.update()
elif order[
'side'] == 'sell' and ordertime < sell_timeoutthreashold:
self.handle_timedout_limit_sell(trade, order)
self.wallets.update()
# FIX: 20180110, why is cancel.order unconditionally here, whereas
# it is conditionally called in the
# handle_timedout_limit_sell()?
def handle_timedout_limit_buy(self, trade: Trade, order: Dict) -> bool:
"""Buy timeout - cancel order
:return: True if order was fully cancelled
"""
pair_s = trade.pair.replace('_', '/')
self.exchange.cancel_order(trade.open_order_id, trade.pair)
if order['remaining'] == order['amount']:
# if trade is not partially completed, just delete the trade
Trade.session.delete(trade)
Trade.session.flush()
logger.info('Buy order timeout for %s.', trade)
self.rpc.send_msg({
'type':
RPCMessageType.STATUS_NOTIFICATION,
'status':
f'Unfilled buy order for {pair_s} cancelled due to timeout'
})
return True
# if trade is partially complete, edit the stake details for the trade
# and close the order
trade.amount = order['amount'] - order['remaining']
trade.stake_amount = trade.amount * trade.open_rate
trade.open_order_id = None
logger.info('Partial buy order timeout for %s.', trade)
self.rpc.send_msg({
'type':
RPCMessageType.STATUS_NOTIFICATION,
'status':
f'Remaining buy order for {pair_s} cancelled due to timeout'
})
return False
# FIX: 20180110, should cancel_order() be cond. or unconditionally called?
def handle_timedout_limit_sell(self, trade: Trade, order: Dict) -> bool:
"""
Sell timeout - cancel order and update trade
:return: True if order was fully cancelled
"""
pair_s = trade.pair.replace('_', '/')
if order['remaining'] == order['amount']:
# if trade is not partially completed, just cancel the trade
self.exchange.cancel_order(trade.open_order_id, trade.pair)
trade.close_rate = None
trade.close_profit = None
trade.close_date = None
trade.is_open = True
trade.open_order_id = None
self.rpc.send_msg({
'type':
RPCMessageType.STATUS_NOTIFICATION,
'status':
f'Unfilled sell order for {pair_s} cancelled due to timeout'
})
logger.info('Sell order timeout for %s.', trade)
return True
# TODO: figure out how to handle partially complete sell orders
return False
def execute_sell(self, trade: Trade, limit: float,
sell_reason: SellType) -> None:
"""
Executes a limit sell for the given trade and limit
:param trade: Trade instance
:param limit: limit rate for the sell order
:param sellreason: Reason the sell was triggered
:return: None
"""
sell_type = 'sell'
if sell_reason in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
sell_type = 'stoploss'
# if stoploss is on exchange and we are on dry_run mode,
# we consider the sell price stop price
if self.config.get('dry_run', False) and sell_type == 'stoploss' \
and self.strategy.order_types['stoploss_on_exchange']:
limit = trade.stop_loss
# First cancelling stoploss on exchange ...
if self.strategy.order_types.get(
'stoploss_on_exchange') and trade.stoploss_order_id:
self.exchange.cancel_order(trade.stoploss_order_id, trade.pair)
# Execute sell and update trade record
order_id = self.exchange.sell(
pair=str(trade.pair),
ordertype=self.strategy.order_types[sell_type],
amount=trade.amount,
rate=limit,
time_in_force=self.strategy.order_time_in_force['sell'])['id']
trade.open_order_id = order_id
trade.close_rate_requested = limit
trade.sell_reason = sell_reason.value
profit_trade = trade.calc_profit(rate=limit)
current_rate = self.exchange.get_ticker(trade.pair)['bid']
profit_percent = trade.calc_profit_percent(limit)
pair_url = self.exchange.get_pair_detail_url(trade.pair)
gain = "profit" if profit_percent > 0 else "loss"
msg = {
'type': RPCMessageType.SELL_NOTIFICATION,
'exchange': trade.exchange.capitalize(),
'pair': trade.pair,
'gain': gain,
'market_url': pair_url,
'limit': limit,
'amount': trade.amount,
'open_rate': trade.open_rate,
'current_rate': current_rate,
'profit_amount': profit_trade,
'profit_percent': profit_percent,
'sell_reason': sell_reason.value
}
# For regular case, when the configuration exists
if 'stake_currency' in self.config and 'fiat_display_currency' in self.config:
stake_currency = self.config['stake_currency']
fiat_currency = self.config['fiat_display_currency']
msg.update({
'stake_currency': stake_currency,
'fiat_currency': fiat_currency,
})
# Send the message
self.rpc.send_msg(msg)
Trade.session.flush()
class FreqtradeBot(object):
"""
Freqtrade is the main class of the bot.
This is from here the bot start its logic.
"""
def __init__(self, config: Dict[str, Any]) -> None:
"""
Init all variables and objects the bot needs to work
:param config: configuration dict, you can use Configuration.get_config()
to get the config dict.
"""
logger.info('Starting freqtrade %s', __version__)
# Init bot state
self.state = State.STOPPED
# Init objects
self.config = config
self.strategy: IStrategy = StrategyResolver(self.config).strategy
self.rpc: RPCManager = RPCManager(self)
self.exchange = ExchangeResolver(self.config['exchange']['name'], self.config).exchange
self.wallets = Wallets(self.config, self.exchange)
self.dataprovider = DataProvider(self.config, self.exchange)
# Attach Dataprovider to Strategy baseclass
IStrategy.dp = self.dataprovider
# Attach Wallets to Strategy baseclass
IStrategy.wallets = self.wallets
pairlistname = self.config.get('pairlist', {}).get('method', 'StaticPairList')
self.pairlists = PairListResolver(pairlistname, self, self.config).pairlist
# Initializing Edge only if enabled
self.edge = Edge(self.config, self.exchange, self.strategy) if \
self.config.get('edge', {}).get('enabled', False) else None
self.active_pair_whitelist: List[str] = self.config['exchange']['pair_whitelist']
persistence.init(self.config.get('db_url', None),
clean_open_orders=self.config.get('dry_run', False))
# Set initial bot state from config
initial_state = self.config.get('initial_state')
self.state = State[initial_state.upper()] if initial_state else State.STOPPED
def cleanup(self) -> None:
"""
Cleanup pending resources on an already stopped bot
:return: None
"""
logger.info('Cleaning up modules ...')
self.rpc.cleanup()
persistence.cleanup()
def startup(self) -> None:
"""
Called on startup and after reloading the bot - triggers notifications and
performs startup tasks
"""
self.rpc.startup_messages(self.config, self.pairlists)
if not self.edge:
# Adjust stoploss if it was changed
Trade.stoploss_reinitialization(self.strategy.stoploss)
def process(self) -> bool:
"""
Queries the persistence layer for open trades and handles them,
otherwise a new trade is created.
:return: True if one or more trades has been created or closed, False otherwise
"""
state_changed = False
# Check whether markets have to be reloaded
self.exchange._reload_markets()
# Refresh whitelist
self.pairlists.refresh_pairlist()
self.active_pair_whitelist = self.pairlists.whitelist
# Calculating Edge positioning
if self.edge:
self.edge.calculate()
self.active_pair_whitelist = self.edge.adjust(self.active_pair_whitelist)
# Query trades from persistence layer
trades = Trade.get_open_trades()
# Extend active-pair whitelist with pairs from open trades
# It ensures that tickers are downloaded for open trades
self._extend_whitelist_with_trades(self.active_pair_whitelist, trades)
# Refreshing candles
self.dataprovider.refresh(self._create_pair_whitelist(self.active_pair_whitelist),
self.strategy.informative_pairs())
# First process current opened trades
for trade in trades:
state_changed |= self.process_maybe_execute_sell(trade)
# Then looking for buy opportunities
if len(trades) < self.config['max_open_trades']:
state_changed = self.process_maybe_execute_buy()
if 'unfilledtimeout' in self.config:
# Check and handle any timed out open orders
self.check_handle_timedout()
Trade.session.flush()
return state_changed
def _extend_whitelist_with_trades(self, whitelist: List[str], trades: List[Any]):
"""
Extend whitelist with pairs from open trades
"""
whitelist.extend([trade.pair for trade in trades if trade.pair not in whitelist])
def _create_pair_whitelist(self, pairs: List[str]) -> List[Tuple[str, str]]:
"""
Create pair-whitelist tuple with (pair, ticker_interval)
"""
return [(pair, self.config['ticker_interval']) for pair in pairs]
def get_target_bid(self, pair: str, tick: Dict = None) -> float:
"""
Calculates bid target between current ask price and last price
:return: float: Price
"""
config_bid_strategy = self.config.get('bid_strategy', {})
if 'use_order_book' in config_bid_strategy and\
config_bid_strategy.get('use_order_book', False):
logger.info('Getting price from order book')
order_book_top = config_bid_strategy.get('order_book_top', 1)
order_book = self.exchange.get_order_book(pair, order_book_top)
logger.debug('order_book %s', order_book)
# top 1 = index 0
order_book_rate = order_book['bids'][order_book_top - 1][0]
logger.info('...top %s order book buy rate %0.8f', order_book_top, order_book_rate)
used_rate = order_book_rate
else:
if not tick:
logger.info('Using Last Ask / Last Price')
ticker = self.exchange.get_ticker(pair)
else:
ticker = tick
if ticker['ask'] < ticker['last']:
ticker_rate = ticker['ask']
else:
balance = self.config['bid_strategy']['ask_last_balance']
ticker_rate = ticker['ask'] + balance * (ticker['last'] - ticker['ask'])
used_rate = ticker_rate
return used_rate
def _get_trade_stake_amount(self, pair) -> Optional[float]:
"""
Check if stake amount can be fulfilled with the available balance
for the stake currency
:return: float: Stake Amount
"""
if self.edge:
return self.edge.stake_amount(
pair,
self.wallets.get_free(self.config['stake_currency']),
self.wallets.get_total(self.config['stake_currency']),
Trade.total_open_trades_stakes()
)
else:
stake_amount = self.config['stake_amount']
available_amount = self.wallets.get_free(self.config['stake_currency'])
if stake_amount == constants.UNLIMITED_STAKE_AMOUNT:
open_trades = len(Trade.get_open_trades())
if open_trades >= self.config['max_open_trades']:
logger.warning('Can\'t open a new trade: max number of trades is reached')
return None
return available_amount / (self.config['max_open_trades'] - open_trades)
# Check if stake_amount is fulfilled
if available_amount < stake_amount:
raise DependencyException(
f"Available balance({available_amount} {self.config['stake_currency']}) is "
f"lower than stake amount({stake_amount} {self.config['stake_currency']})"
)
return stake_amount
def _get_min_pair_stake_amount(self, pair: str, price: float) -> Optional[float]:
try:
market = self.exchange.markets[pair]
except KeyError:
raise ValueError(f"Can't get market information for symbol {pair}")
if 'limits' not in market:
return None
min_stake_amounts = []
limits = market['limits']
if ('cost' in limits and 'min' in limits['cost']
and limits['cost']['min'] is not None):
min_stake_amounts.append(limits['cost']['min'])
if ('amount' in limits and 'min' in limits['amount']
and limits['amount']['min'] is not None):
min_stake_amounts.append(limits['amount']['min'] * price)
if not min_stake_amounts:
return None
# reserve some percent defined in config (5% default) + stoploss
amount_reserve_percent = 1.0 - self.config.get('amount_reserve_percent',
constants.DEFAULT_AMOUNT_RESERVE_PERCENT)
if self.strategy.stoploss is not None:
amount_reserve_percent += self.strategy.stoploss
# it should not be more than 50%
amount_reserve_percent = max(amount_reserve_percent, 0.5)
return min(min_stake_amounts) / amount_reserve_percent
def create_trade(self) -> bool:
"""
Checks the implemented trading indicator(s) for a randomly picked pair,
if one pair triggers the buy_signal a new trade record gets created
:return: True if a trade object has been created and persisted, False otherwise
"""
interval = self.strategy.ticker_interval
whitelist = copy.deepcopy(self.active_pair_whitelist)
if not whitelist:
logger.warning("Whitelist is empty.")
return False
# Remove currently opened and latest pairs from whitelist
for trade in Trade.get_open_trades():
if trade.pair in whitelist:
whitelist.remove(trade.pair)
logger.debug('Ignoring %s in pair whitelist', trade.pair)
if not whitelist:
logger.info("No currency pair in whitelist, but checking to sell open trades.")
return False
# running get_signal on historical data fetched
for _pair in whitelist:
(buy, sell) = self.strategy.get_signal(
_pair, interval, self.dataprovider.ohlcv(_pair, self.strategy.ticker_interval))
if buy and not sell:
stake_amount = self._get_trade_stake_amount(_pair)
if not stake_amount:
return False
logger.info(f"Buy signal found: about create a new trade with stake_amount: "
f"{stake_amount} ...")
bidstrat_check_depth_of_market = self.config.get('bid_strategy', {}).\
get('check_depth_of_market', {})
if (bidstrat_check_depth_of_market.get('enabled', False)) and\
(bidstrat_check_depth_of_market.get('bids_to_ask_delta', 0) > 0):
if self._check_depth_of_market_buy(_pair, bidstrat_check_depth_of_market):
return self.execute_buy(_pair, stake_amount)
else:
return False
return self.execute_buy(_pair, stake_amount)
return False
def _check_depth_of_market_buy(self, pair: str, conf: Dict) -> bool:
"""
Checks depth of market before executing a buy
"""
conf_bids_to_ask_delta = conf.get('bids_to_ask_delta', 0)
logger.info('checking depth of market for %s', pair)
order_book = self.exchange.get_order_book(pair, 1000)
order_book_data_frame = order_book_to_dataframe(order_book['bids'], order_book['asks'])
order_book_bids = order_book_data_frame['b_size'].sum()
order_book_asks = order_book_data_frame['a_size'].sum()
bids_ask_delta = order_book_bids / order_book_asks
logger.info('bids: %s, asks: %s, delta: %s', order_book_bids,
order_book_asks, bids_ask_delta)
if bids_ask_delta >= conf_bids_to_ask_delta:
return True
return False
def execute_buy(self, pair: str, stake_amount: float, price: Optional[float] = None) -> bool:
"""
Executes a limit buy for the given pair
:param pair: pair for which we want to create a LIMIT_BUY
:return: None
"""
pair_s = pair.replace('_', '/')
stake_currency = self.config['stake_currency']
fiat_currency = self.config.get('fiat_display_currency', None)
time_in_force = self.strategy.order_time_in_force['buy']
if price:
buy_limit_requested = price
else:
# Calculate amount
buy_limit_requested = self.get_target_bid(pair)
min_stake_amount = self._get_min_pair_stake_amount(pair_s, buy_limit_requested)
if min_stake_amount is not None and min_stake_amount > stake_amount:
logger.warning(
f'Can\'t open a new trade for {pair_s}: stake amount '
f'is too small ({stake_amount} < {min_stake_amount})'
)
return False
amount = stake_amount / buy_limit_requested
order_type = self.strategy.order_types['buy']
order = self.exchange.buy(pair=pair, ordertype=order_type,
amount=amount, rate=buy_limit_requested,
time_in_force=time_in_force)
order_id = order['id']
order_status = order.get('status', None)
# we assume the order is executed at the price requested
buy_limit_filled_price = buy_limit_requested
if order_status == 'expired' or order_status == 'rejected':
order_tif = self.strategy.order_time_in_force['buy']
# return false if the order is not filled
if float(order['filled']) == 0:
logger.warning('Buy %s order with time in force %s for %s is %s by %s.'
' zero amount is fulfilled.',
order_tif, order_type, pair_s, order_status, self.exchange.name)
return False
else:
# the order is partially fulfilled
# in case of IOC orders we can check immediately
# if the order is fulfilled fully or partially
logger.warning('Buy %s order with time in force %s for %s is %s by %s.'
' %s amount fulfilled out of %s (%s remaining which is canceled).',
order_tif, order_type, pair_s, order_status, self.exchange.name,
order['filled'], order['amount'], order['remaining']
)
stake_amount = order['cost']
amount = order['amount']
buy_limit_filled_price = order['price']
order_id = None
# in case of FOK the order may be filled immediately and fully
elif order_status == 'closed':
stake_amount = order['cost']
amount = order['amount']
buy_limit_filled_price = order['price']
self.rpc.send_msg({
'type': RPCMessageType.BUY_NOTIFICATION,
'exchange': self.exchange.name.capitalize(),
'pair': pair_s,
'limit': buy_limit_filled_price,
'order_type': order_type,
'stake_amount': stake_amount,
'stake_currency': stake_currency,
'fiat_currency': fiat_currency
})
# Fee is applied twice because we make a LIMIT_BUY and LIMIT_SELL
fee = self.exchange.get_fee(symbol=pair, taker_or_maker='maker')
trade = Trade(
pair=pair,
stake_amount=stake_amount,
amount=amount,
fee_open=fee,
fee_close=fee,
open_rate=buy_limit_filled_price,
open_rate_requested=buy_limit_requested,
open_date=datetime.utcnow(),
exchange=self.exchange.id,
open_order_id=order_id,
strategy=self.strategy.get_strategy_name(),
ticker_interval=timeframe_to_minutes(self.config['ticker_interval'])
)
# Update fees if order is closed
if order_status == 'closed':
self.update_trade_state(trade, order)
Trade.session.add(trade)
Trade.session.flush()
# Updating wallets
self.wallets.update()
return True
def process_maybe_execute_buy(self) -> bool:
"""
Tries to execute a buy trade in a safe way
:return: True if executed
"""
try:
# Create entity and execute trade
if self.create_trade():
return True
logger.info('Found no buy signals for whitelisted currencies. Trying again..')
return False
except DependencyException as exception:
logger.warning('Unable to create trade: %s', exception)
return False
def process_maybe_execute_sell(self, trade: Trade) -> bool:
"""
Tries to execute a sell trade
:return: True if executed
"""
try:
self.update_trade_state(trade)
if self.strategy.order_types.get('stoploss_on_exchange') and trade.is_open:
result = self.handle_stoploss_on_exchange(trade)
if result:
self.wallets.update()
return result
if trade.is_open and trade.open_order_id is None:
# Check if we can sell our current pair
result = self.handle_trade(trade)
# Updating wallets if any trade occured
if result:
self.wallets.update()
return result
except DependencyException as exception:
logger.warning('Unable to sell trade: %s', exception)
return False
def get_real_amount(self, trade: Trade, order: Dict) -> float:
"""
Get real amount for the trade
Necessary for exchanges which charge fees in base currency (e.g. binance)
"""
order_amount = order['amount']
# Only run for closed orders
if trade.fee_open == 0 or order['status'] == 'open':
return order_amount
# use fee from order-dict if possible
if 'fee' in order and order['fee'] and (order['fee'].keys() >= {'currency', 'cost'}):
if trade.pair.startswith(order['fee']['currency']):
new_amount = order_amount - order['fee']['cost']
logger.info("Applying fee on amount for %s (from %s to %s) from Order",
trade, order['amount'], new_amount)
return new_amount
# Fallback to Trades
trades = self.exchange.get_trades_for_order(trade.open_order_id, trade.pair,
trade.open_date)
if len(trades) == 0:
logger.info("Applying fee on amount for %s failed: myTrade-Dict empty found", trade)
return order_amount
amount = 0
fee_abs = 0
for exectrade in trades:
amount += exectrade['amount']
if "fee" in exectrade and (exectrade['fee'].keys() >= {'currency', 'cost'}):
# only applies if fee is in quote currency!
if trade.pair.startswith(exectrade['fee']['currency']):
fee_abs += exectrade['fee']['cost']
if amount != order_amount:
logger.warning(f"Amount {amount} does not match amount {trade.amount}")
raise OperationalException("Half bought? Amounts don't match")
real_amount = amount - fee_abs
if fee_abs != 0:
logger.info(f"Applying fee on amount for {trade} "
f"(from {order_amount} to {real_amount}) from Trades")
return real_amount
def update_trade_state(self, trade, action_order: dict = None):
"""
Checks trades with open orders and updates the amount if necessary
"""
# Get order details for actual price per unit
if trade.open_order_id:
# Update trade with order values
logger.info('Found open order for %s', trade)
order = action_order or self.exchange.get_order(trade.open_order_id, trade.pair)
# Try update amount (binance-fix)
try:
new_amount = self.get_real_amount(trade, order)
if order['amount'] != new_amount:
order['amount'] = new_amount
# Fee was applied, so set to 0
trade.fee_open = 0
except OperationalException as exception:
logger.warning("Could not update trade amount: %s", exception)
trade.update(order)
# Updating wallets when order is closed
if not trade.is_open:
self.wallets.update()
def get_sell_rate(self, pair: str, refresh: bool) -> float:
"""
Get sell rate - either using get-ticker bid or first bid based on orderbook
The orderbook portion is only used for rpc messaging, which would otherwise fail
for BitMex (has no bid/ask in get_ticker)
or remain static in any other case since it's not updating.
:return: Bid rate
"""
config_ask_strategy = self.config.get('ask_strategy', {})
if config_ask_strategy.get('use_order_book', False):
logger.debug('Using order book to get sell rate')
order_book = self.exchange.get_order_book(pair, 1)
rate = order_book['bids'][0][0]
else:
rate = self.exchange.get_ticker(pair, refresh)['bid']
return rate
def handle_trade(self, trade: Trade) -> bool:
"""
Sells the current pair if the threshold is reached and updates the trade record.
:return: True if trade has been sold, False otherwise
"""
if not trade.is_open:
raise ValueError(f'Attempt to handle closed trade: {trade}')
logger.debug('Handling %s ...', trade)
(buy, sell) = (False, False)
experimental = self.config.get('experimental', {})
if experimental.get('use_sell_signal') or experimental.get('ignore_roi_if_buy_signal'):
(buy, sell) = self.strategy.get_signal(
trade.pair, self.strategy.ticker_interval,
self.dataprovider.ohlcv(trade.pair, self.strategy.ticker_interval))
config_ask_strategy = self.config.get('ask_strategy', {})
if config_ask_strategy.get('use_order_book', False):
logger.info('Using order book for selling...')
# logger.debug('Order book %s',orderBook)
order_book_min = config_ask_strategy.get('order_book_min', 1)
order_book_max = config_ask_strategy.get('order_book_max', 1)
order_book = self.exchange.get_order_book(trade.pair, order_book_max)
for i in range(order_book_min, order_book_max + 1):
order_book_rate = order_book['asks'][i - 1][0]
logger.info(' order book asks top %s: %0.8f', i, order_book_rate)
sell_rate = order_book_rate
if self.check_sell(trade, sell_rate, buy, sell):
return True
else:
logger.debug('checking sell')
sell_rate = self.get_sell_rate(trade.pair, True)
if self.check_sell(trade, sell_rate, buy, sell):
return True
logger.debug('Found no sell signal for %s.', trade)
return False
def handle_stoploss_on_exchange(self, trade: Trade) -> bool:
"""
Check if trade is fulfilled in which case the stoploss
on exchange should be added immediately if stoploss on exchange
is enabled.
"""
logger.debug('Handling stoploss on exchange %s ...', trade)
stoploss_order = None
try:
# First we check if there is already a stoploss on exchange
stoploss_order = self.exchange.get_order(trade.stoploss_order_id, trade.pair) \
if trade.stoploss_order_id else None
except InvalidOrderException as exception:
logger.warning('Unable to fetch stoploss order: %s', exception)
# If trade open order id does not exist: buy order is fulfilled
buy_order_fulfilled = not trade.open_order_id
# Limit price threshold: As limit price should always be below price
limit_price_pct = 0.99
# If buy order is fulfilled but there is no stoploss, we add a stoploss on exchange
if (buy_order_fulfilled and not stoploss_order):
if self.edge:
stoploss = self.edge.stoploss(pair=trade.pair)
else:
stoploss = self.strategy.stoploss
stop_price = trade.open_rate * (1 + stoploss)
# limit price should be less than stop price.
limit_price = stop_price * limit_price_pct
try:
stoploss_order_id = self.exchange.stoploss_limit(
pair=trade.pair, amount=trade.amount, stop_price=stop_price, rate=limit_price
)['id']
trade.stoploss_order_id = str(stoploss_order_id)
trade.stoploss_last_update = datetime.now()
return False
except DependencyException as exception:
logger.warning('Unable to place a stoploss order on exchange: %s', exception)
# If stoploss order is canceled for some reason we add it
if stoploss_order and stoploss_order['status'] == 'canceled':
try:
stoploss_order_id = self.exchange.stoploss_limit(
pair=trade.pair, amount=trade.amount,
stop_price=trade.stop_loss, rate=trade.stop_loss * limit_price_pct
)['id']
trade.stoploss_order_id = str(stoploss_order_id)
return False
except DependencyException as exception:
logger.warning('Stoploss order was cancelled, '
'but unable to recreate one: %s', exception)
# We check if stoploss order is fulfilled
if stoploss_order and stoploss_order['status'] == 'closed':
trade.sell_reason = SellType.STOPLOSS_ON_EXCHANGE.value
trade.update(stoploss_order)
self.notify_sell(trade)
return True
# Finally we check if stoploss on exchange should be moved up because of trailing.
if stoploss_order and self.config.get('trailing_stop', False):
# if trailing stoploss is enabled we check if stoploss value has changed
# in which case we cancel stoploss order and put another one with new
# value immediately
self.handle_trailing_stoploss_on_exchange(trade, stoploss_order)
return False
def handle_trailing_stoploss_on_exchange(self, trade: Trade, order):
"""
Check to see if stoploss on exchange should be updated
in case of trailing stoploss on exchange
:param Trade: Corresponding Trade
:param order: Current on exchange stoploss order
:return: None
"""
if trade.stop_loss > float(order['info']['stopPrice']):
# we check if the update is neccesary
update_beat = self.strategy.order_types.get('stoploss_on_exchange_interval', 60)
if (datetime.utcnow() - trade.stoploss_last_update).total_seconds() > update_beat:
# cancelling the current stoploss on exchange first
logger.info('Trailing stoploss: cancelling current stoploss on exchange (id:{%s})'
'in order to add another one ...', order['id'])
try:
self.exchange.cancel_order(order['id'], trade.pair)
except InvalidOrderException:
logger.exception(f"Could not cancel stoploss order {order['id']} "
f"for pair {trade.pair}")
try:
# creating the new one
stoploss_order_id = self.exchange.stoploss_limit(
pair=trade.pair, amount=trade.amount,
stop_price=trade.stop_loss, rate=trade.stop_loss * 0.99
)['id']
trade.stoploss_order_id = str(stoploss_order_id)
except DependencyException:
logger.exception(f"Could create trailing stoploss order "
f"for pair {trade.pair}.")
def check_sell(self, trade: Trade, sell_rate: float, buy: bool, sell: bool) -> bool:
if self.edge:
stoploss = self.edge.stoploss(trade.pair)
should_sell = self.strategy.should_sell(
trade, sell_rate, datetime.utcnow(), buy, sell, force_stoploss=stoploss)
else:
should_sell = self.strategy.should_sell(trade, sell_rate, datetime.utcnow(), buy, sell)
if should_sell.sell_flag:
self.execute_sell(trade, sell_rate, should_sell.sell_type)
logger.info('executed sell, reason: %s', should_sell.sell_type)
return True
return False
def check_handle_timedout(self) -> None:
"""
Check if any orders are timed out and cancel if neccessary
:param timeoutvalue: Number of minutes until order is considered timed out
:return: None
"""
buy_timeout = self.config['unfilledtimeout']['buy']
sell_timeout = self.config['unfilledtimeout']['sell']
buy_timeoutthreashold = arrow.utcnow().shift(minutes=-buy_timeout).datetime
sell_timeoutthreashold = arrow.utcnow().shift(minutes=-sell_timeout).datetime
for trade in Trade.query.filter(Trade.open_order_id.isnot(None)).all():
try:
# FIXME: Somehow the query above returns results
# where the open_order_id is in fact None.
# This is probably because the record got
# updated via /forcesell in a different thread.
if not trade.open_order_id:
continue
order = self.exchange.get_order(trade.open_order_id, trade.pair)
except (RequestException, DependencyException):
logger.info(
'Cannot query order for %s due to %s',
trade,
traceback.format_exc())
continue
ordertime = arrow.get(order['datetime']).datetime
# Check if trade is still actually open
if float(order['remaining']) == 0.0:
self.wallets.update()
continue
# Handle cancelled on exchange
if order['status'] == 'canceled':
if order['side'] == 'buy':
self.handle_buy_order_full_cancel(trade, "canceled on Exchange")
elif order['side'] == 'sell':
self.handle_timedout_limit_sell(trade, order)
self.wallets.update()
# Check if order is still actually open
elif order['status'] == 'open':
if order['side'] == 'buy' and ordertime < buy_timeoutthreashold:
self.handle_timedout_limit_buy(trade, order)
self.wallets.update()
elif order['side'] == 'sell' and ordertime < sell_timeoutthreashold:
self.handle_timedout_limit_sell(trade, order)
self.wallets.update()
def handle_buy_order_full_cancel(self, trade: Trade, reason: str) -> None:
"""Close trade in database and send message"""
Trade.session.delete(trade)
Trade.session.flush()
logger.info('Buy order %s for %s.', reason, trade)
self.rpc.send_msg({
'type': RPCMessageType.STATUS_NOTIFICATION,
'status': f'Unfilled buy order for {trade.pair} {reason}'
})
def handle_timedout_limit_buy(self, trade: Trade, order: Dict) -> bool:
"""Buy timeout - cancel order
:return: True if order was fully cancelled
"""
self.exchange.cancel_order(trade.open_order_id, trade.pair)
if order['remaining'] == order['amount']:
# if trade is not partially completed, just delete the trade
self.handle_buy_order_full_cancel(trade, "cancelled due to timeout")
return True
# if trade is partially complete, edit the stake details for the trade
# and close the order
trade.amount = order['amount'] - order['remaining']
trade.stake_amount = trade.amount * trade.open_rate
trade.open_order_id = None
logger.info('Partial buy order timeout for %s.', trade)
self.rpc.send_msg({
'type': RPCMessageType.STATUS_NOTIFICATION,
'status': f'Remaining buy order for {trade.pair} cancelled due to timeout'
})
return False
def handle_timedout_limit_sell(self, trade: Trade, order: Dict) -> bool:
"""
Sell timeout - cancel order and update trade
:return: True if order was fully cancelled
"""
if order['remaining'] == order['amount']:
# if trade is not partially completed, just cancel the trade
if order["status"] != "canceled":
reason = "due to timeout"
self.exchange.cancel_order(trade.open_order_id, trade.pair)
logger.info('Sell order timeout for %s.', trade)
else:
reason = "on exchange"
logger.info('Sell order canceled on exchange for %s.', trade)
trade.close_rate = None
trade.close_profit = None
trade.close_date = None
trade.is_open = True
trade.open_order_id = None
self.rpc.send_msg({
'type': RPCMessageType.STATUS_NOTIFICATION,
'status': f'Unfilled sell order for {trade.pair} cancelled {reason}'
})
return True
# TODO: figure out how to handle partially complete sell orders
return False
def execute_sell(self, trade: Trade, limit: float, sell_reason: SellType) -> None:
"""
Executes a limit sell for the given trade and limit
:param trade: Trade instance
:param limit: limit rate for the sell order
:param sellreason: Reason the sell was triggered
:return: None
"""
sell_type = 'sell'
if sell_reason in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
sell_type = 'stoploss'
# if stoploss is on exchange and we are on dry_run mode,
# we consider the sell price stop price
if self.config.get('dry_run', False) and sell_type == 'stoploss' \
and self.strategy.order_types['stoploss_on_exchange']:
limit = trade.stop_loss
# First cancelling stoploss on exchange ...
if self.strategy.order_types.get('stoploss_on_exchange') and trade.stoploss_order_id:
try:
self.exchange.cancel_order(trade.stoploss_order_id, trade.pair)
except InvalidOrderException:
logger.exception(f"Could not cancel stoploss order {trade.stoploss_order_id}")
# Execute sell and update trade record
order_id = self.exchange.sell(pair=str(trade.pair),
ordertype=self.strategy.order_types[sell_type],
amount=trade.amount, rate=limit,
time_in_force=self.strategy.order_time_in_force['sell']
)['id']
trade.open_order_id = order_id
trade.close_rate_requested = limit
trade.sell_reason = sell_reason.value
Trade.session.flush()
self.notify_sell(trade)
def notify_sell(self, trade: Trade):
"""
Sends rpc notification when a sell occured.
"""
profit_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested
profit_trade = trade.calc_profit(rate=profit_rate)
# Use cached ticker here - it was updated seconds ago.
current_rate = self.get_sell_rate(trade.pair, False)
profit_percent = trade.calc_profit_percent(profit_rate)
gain = "profit" if profit_percent > 0 else "loss"
msg = {
'type': RPCMessageType.SELL_NOTIFICATION,
'exchange': trade.exchange.capitalize(),
'pair': trade.pair,
'gain': gain,
'limit': trade.close_rate_requested,
'order_type': self.strategy.order_types['sell'],
'amount': trade.amount,
'open_rate': trade.open_rate,
'current_rate': current_rate,
'profit_amount': profit_trade,
'profit_percent': profit_percent,
'sell_reason': trade.sell_reason
}
# For regular case, when the configuration exists
if 'stake_currency' in self.config and 'fiat_display_currency' in self.config:
stake_currency = self.config['stake_currency']
fiat_currency = self.config['fiat_display_currency']
msg.update({
'stake_currency': stake_currency,
'fiat_currency': fiat_currency,
})
# Send the message
self.rpc.send_msg(msg)
class FreqtradeBot:
"""
Freqtrade is the main class of the bot.
This is from here the bot start its logic.
"""
def __init__(self, config: Dict[str, Any]) -> None:
"""
Init all variables and objects the bot needs to work
:param config: configuration dict, you can use Configuration.get_config()
to get the config dict.
"""
logger.info('Starting freqtrade %s', __version__)
# Init bot state
self.state = State.STOPPED
# Init objects
self.config = config
self._heartbeat_msg = 0
self.heartbeat_interval = self.config.get('internals', {}).get(
'heartbeat_interval', 60)
self.strategy: IStrategy = StrategyResolver.load_strategy(self.config)
# Check config consistency here since strategies can set certain options
validate_config_consistency(config)
self.exchange = ExchangeResolver.load_exchange(
self.config['exchange']['name'], self.config)
persistence.init(self.config.get('db_url', None),
clean_open_orders=self.config['dry_run'])
self.wallets = Wallets(self.config, self.exchange)
self.dataprovider = DataProvider(self.config, self.exchange)
# Attach Dataprovider to Strategy baseclass
IStrategy.dp = self.dataprovider
# Attach Wallets to Strategy baseclass
IStrategy.wallets = self.wallets
self.pairlists = PairListManager(self.exchange, self.config)
# Initializing Edge only if enabled
self.edge = Edge(self.config, self.exchange, self.strategy) if \
self.config.get('edge', {}).get('enabled', False) else None
self.active_pair_whitelist = self._refresh_whitelist()
# Set initial bot state from config
initial_state = self.config.get('initial_state')
self.state = State[
initial_state.upper()] if initial_state else State.STOPPED
# RPC runs in separate threads, can start handling external commands just after
# initialization, even before Freqtradebot has a chance to start its throttling,
# so anything in the Freqtradebot instance should be ready (initialized), including
# the initial state of the bot.
# Keep this at the end of this initialization method.
self.rpc: RPCManager = RPCManager(self)
# Protect sell-logic from forcesell and viceversa
self._sell_lock = Lock()
def notify_status(self, msg: str) -> None:
"""
Public method for users of this class (worker, etc.) to send notifications
via RPC about changes in the bot status.
"""
self.rpc.send_msg({
'type': RPCMessageType.STATUS_NOTIFICATION,
'status': msg
})
def cleanup(self) -> None:
"""
Cleanup pending resources on an already stopped bot
:return: None
"""
logger.info('Cleaning up modules ...')
self.rpc.cleanup()
persistence.cleanup()
def startup(self) -> None:
"""
Called on startup and after reloading the bot - triggers notifications and
performs startup tasks
"""
self.rpc.startup_messages(self.config, self.pairlists)
if not self.edge:
# Adjust stoploss if it was changed
Trade.stoploss_reinitialization(self.strategy.stoploss)
def process(self) -> None:
"""
Queries the persistence layer for open trades and handles them,
otherwise a new trade is created.
:return: True if one or more trades has been created or closed, False otherwise
"""
# Check whether markets have to be reloaded
self.exchange._reload_markets()
# Query trades from persistence layer
trades = Trade.get_open_trades()
self.active_pair_whitelist = self._refresh_whitelist(trades)
# Refreshing candles
self.dataprovider.refresh(
self._create_pair_whitelist(self.active_pair_whitelist),
self.strategy.informative_pairs())
# Protect from collisions with forcesell.
# Without this, freqtrade my try to recreate stoploss_on_exchange orders
# while selling is in process, since telegram messages arrive in an different thread.
with self._sell_lock:
# First process current opened trades (positions)
self.exit_positions(trades)
# Then looking for buy opportunities
if self.get_free_open_trades():
self.enter_positions()
# Check and handle any timed out open orders
self.check_handle_timedout()
Trade.session.flush()
if (self.heartbeat_interval
and (arrow.utcnow().timestamp - self._heartbeat_msg >
self.heartbeat_interval)):
logger.info(f"Bot heartbeat. PID={getpid()}")
self._heartbeat_msg = arrow.utcnow().timestamp
def _refresh_whitelist(self, trades: List[Trade] = []) -> List[str]:
"""
Refresh whitelist from pairlist or edge and extend it with trades.
"""
# Refresh whitelist
self.pairlists.refresh_pairlist()
_whitelist = self.pairlists.whitelist
# Calculating Edge positioning
if self.edge:
self.edge.calculate()
_whitelist = self.edge.adjust(_whitelist)
if trades:
# Extend active-pair whitelist with pairs from open trades
# It ensures that tickers are downloaded for open trades
_whitelist.extend([
trade.pair for trade in trades if trade.pair not in _whitelist
])
return _whitelist
def _create_pair_whitelist(self,
pairs: List[str]) -> List[Tuple[str, str]]:
"""
Create pair-whitelist tuple with (pair, ticker_interval)
"""
return [(pair, self.config['ticker_interval']) for pair in pairs]
def get_free_open_trades(self):
"""
Return the number of free open trades slots or 0 if
max number of open trades reached
"""
open_trades = len(Trade.get_open_trades())
return max(0, self.config['max_open_trades'] - open_trades)
#
# BUY / enter positions / open trades logic and methods
#
def enter_positions(self) -> int:
"""
Tries to execute buy orders for new trades (positions)
"""
trades_created = 0
whitelist = copy.deepcopy(self.active_pair_whitelist)
if not whitelist:
logger.info("Active pair whitelist is empty.")
else:
# Remove pairs for currently opened trades from the whitelist
for trade in Trade.get_open_trades():
if trade.pair in whitelist:
whitelist.remove(trade.pair)
logger.debug('Ignoring %s in pair whitelist', trade.pair)
if not whitelist:
logger.info("No currency pair in active pair whitelist, "
"but checking to sell open trades.")
else:
# Create entity and execute trade for each pair from whitelist
for pair in whitelist:
try:
trades_created += self.create_trade(pair)
except DependencyException as exception:
logger.warning('Unable to create trade for %s: %s',
pair, exception)
if not trades_created:
logger.debug(
"Found no buy signals for whitelisted currencies. "
"Trying again...")
return trades_created
def get_buy_rate(self, pair: str, tick: Dict = None) -> float:
"""
Calculates bid target between current ask price and last price
:return: float: Price
"""
config_bid_strategy = self.config.get('bid_strategy', {})
if 'use_order_book' in config_bid_strategy and\
config_bid_strategy.get('use_order_book', False):
logger.info('Getting price from order book')
order_book_top = config_bid_strategy.get('order_book_top', 1)
order_book = self.exchange.get_order_book(pair, order_book_top)
logger.debug('order_book %s', order_book)
# top 1 = index 0
order_book_rate = order_book['bids'][order_book_top - 1][0]
logger.info('...top %s order book buy rate %0.8f', order_book_top,
order_book_rate)
used_rate = order_book_rate
else:
if not tick:
logger.info('Using Last Ask / Last Price')
ticker = self.exchange.fetch_ticker(pair)
else:
ticker = tick
if ticker['ask'] < ticker['last']:
ticker_rate = ticker['ask']
else:
balance = self.config['bid_strategy']['ask_last_balance']
ticker_rate = ticker['ask'] + balance * (ticker['last'] -
ticker['ask'])
used_rate = ticker_rate
return used_rate
def get_trade_stake_amount(self, pair) -> float:
"""
Calculate stake amount for the trade
:return: float: Stake amount
:raise: DependencyException if the available stake amount is too low
"""
stake_amount: float
# Ensure wallets are uptodate.
self.wallets.update()
if self.edge:
stake_amount = self.edge.stake_amount(
pair, self.wallets.get_free(self.config['stake_currency']),
self.wallets.get_total(self.config['stake_currency']),
Trade.total_open_trades_stakes())
else:
stake_amount = self.config['stake_amount']
if stake_amount == constants.UNLIMITED_STAKE_AMOUNT:
stake_amount = self._calculate_unlimited_stake_amount()
return self._check_available_stake_amount(stake_amount)
def _get_available_stake_amount(self) -> float:
"""
Return the total currently available balance in stake currency,
respecting tradable_balance_ratio.
Calculated as
<open_trade stakes> + free amount ) * tradable_balance_ratio - <open_trade stakes>
"""
val_tied_up = Trade.total_open_trades_stakes()
# Ensure <tradable_balance_ratio>% is used from the overall balance
# Otherwise we'd risk lowering stakes with each open trade.
# (tied up + current free) * ratio) - tied up
available_amount = (
(val_tied_up + self.wallets.get_free(self.config['stake_currency'])
) * self.config['tradable_balance_ratio']) - val_tied_up
return available_amount
def _calculate_unlimited_stake_amount(self) -> float:
"""
Calculate stake amount for "unlimited" stake amount
:return: 0 if max number of trades reached, else stake_amount to use.
"""
free_open_trades = self.get_free_open_trades()
if not free_open_trades:
return 0
available_amount = self._get_available_stake_amount()
return available_amount / free_open_trades
def _check_available_stake_amount(self, stake_amount: float) -> float:
"""
Check if stake amount can be fulfilled with the available balance
for the stake currency
:return: float: Stake amount
"""
available_amount = self._get_available_stake_amount()
if self.config['amend_last_stake_amount']:
# Remaining amount needs to be at least stake_amount * last_stake_amount_min_ratio
# Otherwise the remaining amount is too low to trade.
if available_amount > (stake_amount *
self.config['last_stake_amount_min_ratio']):
stake_amount = min(stake_amount, available_amount)
else:
stake_amount = 0
if available_amount < stake_amount:
raise DependencyException(
f"Available balance ({available_amount} {self.config['stake_currency']}) is "
f"lower than stake amount ({stake_amount} {self.config['stake_currency']})"
)
return stake_amount
def _get_min_pair_stake_amount(self, pair: str,
price: float) -> Optional[float]:
try:
market = self.exchange.markets[pair]
except KeyError:
raise ValueError(f"Can't get market information for symbol {pair}")
if 'limits' not in market:
return None
min_stake_amounts = []
limits = market['limits']
if ('cost' in limits and 'min' in limits['cost']
and limits['cost']['min'] is not None):
min_stake_amounts.append(limits['cost']['min'])
if ('amount' in limits and 'min' in limits['amount']
and limits['amount']['min'] is not None):
min_stake_amounts.append(limits['amount']['min'] * price)
if not min_stake_amounts:
return None
# reserve some percent defined in config (5% default) + stoploss
amount_reserve_percent = 1.0 - self.config.get(
'amount_reserve_percent', constants.DEFAULT_AMOUNT_RESERVE_PERCENT)
if self.strategy.stoploss is not None:
amount_reserve_percent += self.strategy.stoploss
# it should not be more than 50%
amount_reserve_percent = max(amount_reserve_percent, 0.5)
# The value returned should satisfy both limits: for amount (base currency) and
# for cost (quote, stake currency), so max() is used here.
# See also #2575 at github.
return max(min_stake_amounts) / amount_reserve_percent
def create_trade(self, pair: str) -> bool:
"""
Check the implemented trading strategy for buy signals.
If the pair triggers the buy signal a new trade record gets created
and the buy-order opening the trade gets issued towards the exchange.
:return: True if a trade has been created.
"""
logger.debug(f"create_trade for pair {pair}")
if self.strategy.is_pair_locked(pair):
logger.info(f"Pair {pair} is currently locked.")
return False
# running get_signal on historical data fetched
(buy, sell) = self.strategy.get_signal(
pair, self.strategy.ticker_interval,
self.dataprovider.ohlcv(pair, self.strategy.ticker_interval))
if buy and not sell:
if not self.get_free_open_trades():
logger.debug(
"Can't open a new trade: max number of trades is reached.")
return False
stake_amount = self.get_trade_stake_amount(pair)
if not stake_amount:
logger.debug(
"Stake amount is 0, ignoring possible trade for {pair}.")
return False
logger.info(
f"Buy signal found: about create a new trade with stake_amount: "
f"{stake_amount} ...")
bid_check_dom = self.config.get('bid_strategy',
{}).get('check_depth_of_market',
{})
if ((bid_check_dom.get('enabled', False))
and (bid_check_dom.get('bids_to_ask_delta', 0) > 0)):
if self._check_depth_of_market_buy(pair, bid_check_dom):
return self.execute_buy(pair, stake_amount)
else:
return False
return self.execute_buy(pair, stake_amount)
else:
return False
def _check_depth_of_market_buy(self, pair: str, conf: Dict) -> bool:
"""
Checks depth of market before executing a buy
"""
conf_bids_to_ask_delta = conf.get('bids_to_ask_delta', 0)
logger.info('checking depth of market for %s', pair)
order_book = self.exchange.get_order_book(pair, 1000)
order_book_data_frame = order_book_to_dataframe(
order_book['bids'], order_book['asks'])
order_book_bids = order_book_data_frame['b_size'].sum()
order_book_asks = order_book_data_frame['a_size'].sum()
bids_ask_delta = order_book_bids / order_book_asks
logger.info('bids: %s, asks: %s, delta: %s', order_book_bids,
order_book_asks, bids_ask_delta)
if bids_ask_delta >= conf_bids_to_ask_delta:
return True
return False
def execute_buy(self,
pair: str,
stake_amount: float,
price: Optional[float] = None) -> bool:
"""
Executes a limit buy for the given pair
:param pair: pair for which we want to create a LIMIT_BUY
:return: None
"""
time_in_force = self.strategy.order_time_in_force['buy']
if price:
buy_limit_requested = price
else:
# Calculate price
buy_limit_requested = self.get_buy_rate(pair)
min_stake_amount = self._get_min_pair_stake_amount(
pair, buy_limit_requested)
if min_stake_amount is not None and min_stake_amount > stake_amount:
logger.warning(
f"Can't open a new trade for {pair}: stake amount "
f"is too small ({stake_amount} < {min_stake_amount})")
return False
amount = stake_amount / buy_limit_requested
order_type = self.strategy.order_types['buy']
order = self.exchange.buy(pair=pair,
ordertype=order_type,
amount=amount,
rate=buy_limit_requested,
time_in_force=time_in_force)
order_id = order['id']
order_status = order.get('status', None)
# we assume the order is executed at the price requested
buy_limit_filled_price = buy_limit_requested
if order_status == 'expired' or order_status == 'rejected':
order_tif = self.strategy.order_time_in_force['buy']
# return false if the order is not filled
if float(order['filled']) == 0:
logger.warning(
'Buy %s order with time in force %s for %s is %s by %s.'
' zero amount is fulfilled.', order_tif, order_type, pair,
order_status, self.exchange.name)
return False
else:
# the order is partially fulfilled
# in case of IOC orders we can check immediately
# if the order is fulfilled fully or partially
logger.warning(
'Buy %s order with time in force %s for %s is %s by %s.'
' %s amount fulfilled out of %s (%s remaining which is canceled).',
order_tif, order_type, pair, order_status,
self.exchange.name, order['filled'], order['amount'],
order['remaining'])
stake_amount = order['cost']
amount = order['amount']
buy_limit_filled_price = order['price']
order_id = None
# in case of FOK the order may be filled immediately and fully
elif order_status == 'closed':
stake_amount = order['cost']
amount = order['amount']
buy_limit_filled_price = order['price']
# Fee is applied twice because we make a LIMIT_BUY and LIMIT_SELL
fee = self.exchange.get_fee(symbol=pair, taker_or_maker='maker')
trade = Trade(pair=pair,
stake_amount=stake_amount,
amount=amount,
fee_open=fee,
fee_close=fee,
open_rate=buy_limit_filled_price,
open_rate_requested=buy_limit_requested,
open_date=datetime.utcnow(),
exchange=self.exchange.id,
open_order_id=order_id,
strategy=self.strategy.get_strategy_name(),
ticker_interval=timeframe_to_minutes(
self.config['ticker_interval']))
self._notify_buy(trade, order_type)
# Update fees if order is closed
if order_status == 'closed':
self.update_trade_state(trade, order)
Trade.session.add(trade)
Trade.session.flush()
# Updating wallets
self.wallets.update()
return True
def _notify_buy(self, trade: Trade, order_type: str):
"""
Sends rpc notification when a buy occured.
"""
msg = {
'type': RPCMessageType.BUY_NOTIFICATION,
'exchange': self.exchange.name.capitalize(),
'pair': trade.pair,
'limit': trade.open_rate,
'order_type': order_type,
'stake_amount': trade.stake_amount,
'stake_currency': self.config['stake_currency'],
'fiat_currency': self.config.get('fiat_display_currency', None),
}
# Send the message
self.rpc.send_msg(msg)
#
# SELL / exit positions / close trades logic and methods
#
def exit_positions(self, trades: List[Any]) -> int:
"""
Tries to execute sell orders for open trades (positions)
"""
trades_closed = 0
for trade in trades:
try:
self.update_trade_state(trade)
if (self.strategy.order_types.get('stoploss_on_exchange')
and self.handle_stoploss_on_exchange(trade)):
trades_closed += 1
continue
# Check if we can sell our current pair
if trade.open_order_id is None and self.handle_trade(trade):
trades_closed += 1
except DependencyException as exception:
logger.warning('Unable to sell trade: %s', exception)
# Updating wallets if any trade occured
if trades_closed:
self.wallets.update()
return trades_closed
def get_sell_rate(self, pair: str, refresh: bool) -> float:
"""
Get sell rate - either using get-ticker bid or first bid based on orderbook
The orderbook portion is only used for rpc messaging, which would otherwise fail
for BitMex (has no bid/ask in fetch_ticker)
or remain static in any other case since it's not updating.
:return: Bid rate
"""
config_ask_strategy = self.config.get('ask_strategy', {})
if config_ask_strategy.get('use_order_book', False):
logger.debug('Using order book to get sell rate')
order_book = self.exchange.get_order_book(pair, 1)
rate = order_book['bids'][0][0]
else:
rate = self.exchange.fetch_ticker(pair, refresh)['bid']
return rate
def handle_trade(self, trade: Trade) -> bool:
"""
Sells the current pair if the threshold is reached and updates the trade record.
:return: True if trade has been sold, False otherwise
"""
if not trade.is_open:
raise DependencyException(
f'Attempt to handle closed trade: {trade}')
logger.debug('Handling %s ...', trade)
(buy, sell) = (False, False)
config_ask_strategy = self.config.get('ask_strategy', {})
if (config_ask_strategy.get('use_sell_signal', True)
or config_ask_strategy.get('ignore_roi_if_buy_signal')):
(buy, sell) = self.strategy.get_signal(
trade.pair, self.strategy.ticker_interval,
self.dataprovider.ohlcv(trade.pair,
self.strategy.ticker_interval))
if config_ask_strategy.get('use_order_book', False):
logger.info('Using order book for selling...')
# logger.debug('Order book %s',orderBook)
order_book_min = config_ask_strategy.get('order_book_min', 1)
order_book_max = config_ask_strategy.get('order_book_max', 1)
order_book = self.exchange.get_order_book(trade.pair,
order_book_max)
for i in range(order_book_min, order_book_max + 1):
order_book_rate = order_book['asks'][i - 1][0]
logger.info(' order book asks top %s: %0.8f', i,
order_book_rate)
sell_rate = order_book_rate
if self._check_and_execute_sell(trade, sell_rate, buy, sell):
return True
else:
logger.debug('checking sell')
sell_rate = self.get_sell_rate(trade.pair, True)
if self._check_and_execute_sell(trade, sell_rate, buy, sell):
return True
logger.debug('Found no sell signal for %s.', trade)
return False
def create_stoploss_order(self, trade: Trade, stop_price: float,
rate: float) -> bool:
"""
Abstracts creating stoploss orders from the logic.
Handles errors and updates the trade database object.
Force-sells the pair (using EmergencySell reason) in case of Problems creating the order.
:return: True if the order succeeded, and False in case of problems.
"""
# Limit price threshold: As limit price should always be below stop-price
LIMIT_PRICE_PCT = self.strategy.order_types.get(
'stoploss_on_exchange_limit_ratio', 0.99)
try:
stoploss_order = self.exchange.stoploss_limit(
pair=trade.pair,
amount=trade.amount,
stop_price=stop_price,
rate=rate * LIMIT_PRICE_PCT)
trade.stoploss_order_id = str(stoploss_order['id'])
return True
except InvalidOrderException as e:
trade.stoploss_order_id = None
logger.error(f'Unable to place a stoploss order on exchange. {e}')
logger.warning('Selling the trade forcefully')
self.execute_sell(trade,
trade.stop_loss,
sell_reason=SellType.EMERGENCY_SELL)
except DependencyException:
trade.stoploss_order_id = None
logger.exception('Unable to place a stoploss order on exchange.')
return False
def handle_stoploss_on_exchange(self, trade: Trade) -> bool:
"""
Check if trade is fulfilled in which case the stoploss
on exchange should be added immediately if stoploss on exchange
is enabled.
"""
logger.debug('Handling stoploss on exchange %s ...', trade)
stoploss_order = None
try:
# First we check if there is already a stoploss on exchange
stoploss_order = self.exchange.get_order(trade.stoploss_order_id, trade.pair) \
if trade.stoploss_order_id else None
except InvalidOrderException as exception:
logger.warning('Unable to fetch stoploss order: %s', exception)
# If buy order is fulfilled but there is no stoploss, we add a stoploss on exchange
if (not trade.open_order_id and not stoploss_order):
stoploss = self.edge.stoploss(
pair=trade.pair) if self.edge else self.strategy.stoploss
stop_price = trade.open_rate * (1 + stoploss)
if self.create_stoploss_order(trade=trade,
stop_price=stop_price,
rate=stop_price):
trade.stoploss_last_update = datetime.now()
return False
# If stoploss order is canceled for some reason we add it
if stoploss_order and stoploss_order['status'] == 'canceled':
if self.create_stoploss_order(trade=trade,
stop_price=trade.stop_loss,
rate=trade.stop_loss):
return False
else:
trade.stoploss_order_id = None
logger.warning(
'Stoploss order was cancelled, but unable to recreate one.'
)
# We check if stoploss order is fulfilled
if stoploss_order and stoploss_order['status'] == 'closed':
trade.sell_reason = SellType.STOPLOSS_ON_EXCHANGE.value
trade.update(stoploss_order)
# Lock pair for one candle to prevent immediate rebuys
self.strategy.lock_pair(
trade.pair,
timeframe_to_next_date(self.config['ticker_interval']))
self._notify_sell(trade, "stoploss")
return True
# Finally we check if stoploss on exchange should be moved up because of trailing.
if stoploss_order and self.config.get('trailing_stop', False):
# if trailing stoploss is enabled we check if stoploss value has changed
# in which case we cancel stoploss order and put another one with new
# value immediately
self.handle_trailing_stoploss_on_exchange(trade, stoploss_order)
return False
def handle_trailing_stoploss_on_exchange(self, trade: Trade, order):
"""
Check to see if stoploss on exchange should be updated
in case of trailing stoploss on exchange
:param Trade: Corresponding Trade
:param order: Current on exchange stoploss order
:return: None
"""
if trade.stop_loss > float(order['info']['stopPrice']):
# we check if the update is neccesary
update_beat = self.strategy.order_types.get(
'stoploss_on_exchange_interval', 60)
if (datetime.utcnow() -
trade.stoploss_last_update).total_seconds() >= update_beat:
# cancelling the current stoploss on exchange first
logger.info(
'Trailing stoploss: cancelling current stoploss on exchange (id:{%s})'
'in order to add another one ...', order['id'])
try:
self.exchange.cancel_order(order['id'], trade.pair)
except InvalidOrderException:
logger.exception(
f"Could not cancel stoploss order {order['id']} "
f"for pair {trade.pair}")
# Create new stoploss order
if self.create_stoploss_order(trade=trade,
stop_price=trade.stop_loss,
rate=trade.stop_loss):
return False
else:
logger.warning(f"Could not create trailing stoploss order "
f"for pair {trade.pair}.")
def _check_and_execute_sell(self, trade: Trade, sell_rate: float,
buy: bool, sell: bool) -> bool:
"""
Check and execute sell
"""
should_sell = self.strategy.should_sell(
trade,
sell_rate,
datetime.utcnow(),
buy,
sell,
force_stoploss=self.edge.stoploss(trade.pair) if self.edge else 0)
if should_sell.sell_flag:
self.execute_sell(trade, sell_rate, should_sell.sell_type)
logger.info('executed sell, reason: %s', should_sell.sell_type)
return True
return False
def _check_timed_out(self, side: str, order: dict) -> bool:
"""
Check if timeout is active, and if the order is still open and timed out
"""
timeout = self.config.get('unfilledtimeout', {}).get(side)
ordertime = arrow.get(order['datetime']).datetime
if timeout is not None:
timeout_threshold = arrow.utcnow().shift(minutes=-timeout).datetime
return (order['status'] == 'open' and order['side'] == side
and ordertime < timeout_threshold)
return False
def check_handle_timedout(self) -> None:
"""
Check if any orders are timed out and cancel if neccessary
:param timeoutvalue: Number of minutes until order is considered timed out
:return: None
"""
for trade in Trade.get_open_order_trades():
try:
if not trade.open_order_id:
continue
order = self.exchange.get_order(trade.open_order_id,
trade.pair)
except (RequestException, DependencyException,
InvalidOrderException):
logger.info('Cannot query order for %s due to %s', trade,
traceback.format_exc())
continue
# Check if trade is still actually open
if float(order.get('remaining', 0.0)) == 0.0:
self.wallets.update()
continue
if ((order['side'] == 'buy' and order['status'] == 'canceled')
or (self._check_timed_out('buy', order))):
self.handle_timedout_limit_buy(trade, order)
self.wallets.update()
elif ((order['side'] == 'sell' and order['status'] == 'canceled')
or (self._check_timed_out('sell', order))):
self.handle_timedout_limit_sell(trade, order)
self.wallets.update()
def handle_buy_order_full_cancel(self, trade: Trade, reason: str) -> None:
"""Close trade in database and send message"""
Trade.session.delete(trade)
Trade.session.flush()
logger.info('Buy order %s for %s.', reason, trade)
self.rpc.send_msg({
'type':
RPCMessageType.STATUS_NOTIFICATION,
'status':
f'Unfilled buy order for {trade.pair} {reason}'
})
def handle_timedout_limit_buy(self, trade: Trade, order: Dict) -> bool:
"""
Buy timeout - cancel order
:return: True if order was fully cancelled
"""
reason = "cancelled due to timeout"
if order['status'] != 'canceled':
corder = self.exchange.cancel_order(trade.open_order_id,
trade.pair)
else:
# Order was cancelled already, so we can reuse the existing dict
corder = order
reason = "canceled on Exchange"
if corder.get('remaining', order['remaining']) == order['amount']:
# if trade is not partially completed, just delete the trade
self.handle_buy_order_full_cancel(trade, reason)
return True
# if trade is partially complete, edit the stake details for the trade
# and close the order
# cancel_order may not contain the full order dict, so we need to fallback
# to the order dict aquired before cancelling.
# we need to fall back to the values from order if corder does not contain these keys.
trade.amount = order['amount'] - corder.get('remaining',
order['remaining'])
trade.stake_amount = trade.amount * trade.open_rate
# verify if fees were taken from amount to avoid problems during selling
try:
new_amount = self.get_real_amount(
trade, corder if 'fee' in corder else order, trade.amount)
if not isclose(order['amount'],
new_amount,
abs_tol=constants.MATH_CLOSE_PREC):
trade.amount = new_amount
# Fee was applied, so set to 0
trade.fee_open = 0
trade.recalc_open_trade_price()
except DependencyException as e:
logger.warning("Could not update trade amount: %s", e)
trade.open_order_id = None
logger.info('Partial buy order timeout for %s.', trade)
self.rpc.send_msg({
'type':
RPCMessageType.STATUS_NOTIFICATION,
'status':
f'Remaining buy order for {trade.pair} cancelled due to timeout'
})
return False
def handle_timedout_limit_sell(self, trade: Trade, order: Dict) -> bool:
"""
Sell timeout - cancel order and update trade
:return: True if order was fully cancelled
"""
if order['remaining'] == order['amount']:
# if trade is not partially completed, just cancel the trade
if order["status"] != "canceled":
reason = "due to timeout"
self.exchange.cancel_order(trade.open_order_id, trade.pair)
logger.info('Sell order timeout for %s.', trade)
else:
reason = "on exchange"
logger.info('Sell order canceled on exchange for %s.', trade)
trade.close_rate = None
trade.close_profit = None
trade.close_date = None
trade.is_open = True
trade.open_order_id = None
self.rpc.send_msg({
'type':
RPCMessageType.STATUS_NOTIFICATION,
'status':
f'Unfilled sell order for {trade.pair} cancelled {reason}'
})
return True
# TODO: figure out how to handle partially complete sell orders
return False
def _safe_sell_amount(self, pair: str, amount: float) -> float:
"""
Get sellable amount.
Should be trade.amount - but will fall back to the available amount if necessary.
This should cover cases where get_real_amount() was not able to update the amount
for whatever reason.
:param pair: Pair we're trying to sell
:param amount: amount we expect to be available
:return: amount to sell
:raise: DependencyException: if available balance is not within 2% of the available amount.
"""
# Update wallets to ensure amounts tied up in a stoploss is now free!
self.wallets.update()
wallet_amount = self.wallets.get_free(pair.split('/')[0])
logger.debug(
f"{pair} - Wallet: {wallet_amount} - Trade-amount: {amount}")
if wallet_amount >= amount:
return amount
elif wallet_amount > amount * 0.98:
logger.info(f"{pair} - Falling back to wallet-amount.")
return wallet_amount
else:
raise DependencyException(
f"Not enough amount to sell. Trade-amount: {amount}, Wallet: {wallet_amount}"
)
def execute_sell(self, trade: Trade, limit: float,
sell_reason: SellType) -> None:
"""
Executes a limit sell for the given trade and limit
:param trade: Trade instance
:param limit: limit rate for the sell order
:param sellreason: Reason the sell was triggered
:return: None
"""
sell_type = 'sell'
if sell_reason in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
sell_type = 'stoploss'
# if stoploss is on exchange and we are on dry_run mode,
# we consider the sell price stop price
if self.config['dry_run'] and sell_type == 'stoploss' \
and self.strategy.order_types['stoploss_on_exchange']:
limit = trade.stop_loss
# First cancelling stoploss on exchange ...
if self.strategy.order_types.get(
'stoploss_on_exchange') and trade.stoploss_order_id:
try:
self.exchange.cancel_order(trade.stoploss_order_id, trade.pair)
except InvalidOrderException:
logger.exception(
f"Could not cancel stoploss order {trade.stoploss_order_id}"
)
order_type = self.strategy.order_types[sell_type]
if sell_reason == SellType.EMERGENCY_SELL:
# Emergencysells (default to market!)
order_type = self.strategy.order_types.get("emergencysell",
"market")
amount = self._safe_sell_amount(trade.pair, trade.amount)
# Execute sell and update trade record
order = self.exchange.sell(
pair=str(trade.pair),
ordertype=order_type,
amount=amount,
rate=limit,
time_in_force=self.strategy.order_time_in_force['sell'])
trade.open_order_id = order['id']
trade.close_rate_requested = limit
trade.sell_reason = sell_reason.value
# In case of market sell orders the order can be closed immediately
if order.get('status', 'unknown') == 'closed':
trade.update(order)
Trade.session.flush()
# Lock pair for one candle to prevent immediate rebuys
self.strategy.lock_pair(
trade.pair, timeframe_to_next_date(self.config['ticker_interval']))
self._notify_sell(trade, order_type)
def _notify_sell(self, trade: Trade, order_type: str):
"""
Sends rpc notification when a sell occured.
"""
profit_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested
profit_trade = trade.calc_profit(rate=profit_rate)
# Use cached ticker here - it was updated seconds ago.
current_rate = self.get_sell_rate(trade.pair, False)
profit_percent = trade.calc_profit_ratio(profit_rate)
gain = "profit" if profit_percent > 0 else "loss"
msg = {
'type': RPCMessageType.SELL_NOTIFICATION,
'exchange': trade.exchange.capitalize(),
'pair': trade.pair,
'gain': gain,
'limit': trade.close_rate_requested,
'order_type': order_type,
'amount': trade.amount,
'open_rate': trade.open_rate,
'current_rate': current_rate,
'profit_amount': profit_trade,
'profit_percent': profit_percent,
'sell_reason': trade.sell_reason,
'open_date': trade.open_date,
'close_date': trade.close_date or datetime.utcnow(),
'stake_currency': self.config['stake_currency'],
}
if 'fiat_display_currency' in self.config:
msg.update({
'fiat_currency': self.config['fiat_display_currency'],
})
# Send the message
self.rpc.send_msg(msg)
#
# Common update trade state methods
#
def update_trade_state(self, trade, action_order: dict = None):
"""
Checks trades with open orders and updates the amount if necessary
"""
# Get order details for actual price per unit
if trade.open_order_id:
# Update trade with order values
logger.info('Found open order for %s', trade)
try:
order = action_order or self.exchange.get_order(
trade.open_order_id, trade.pair)
except InvalidOrderException as exception:
logger.warning('Unable to fetch order %s: %s',
trade.open_order_id, exception)
return
# Try update amount (binance-fix)
try:
new_amount = self.get_real_amount(trade, order)
if not isclose(order['amount'],
new_amount,
abs_tol=constants.MATH_CLOSE_PREC):
order['amount'] = new_amount
# Fee was applied, so set to 0
trade.fee_open = 0
trade.recalc_open_trade_price()
except DependencyException as exception:
logger.warning("Could not update trade amount: %s", exception)
trade.update(order)
# Updating wallets when order is closed
if not trade.is_open:
self.wallets.update()
def get_real_amount(self,
trade: Trade,
order: Dict,
order_amount: float = None) -> float:
"""
Get real amount for the trade
Necessary for exchanges which charge fees in base currency (e.g. binance)
"""
if order_amount is None:
order_amount = order['amount']
# Only run for closed orders
if trade.fee_open == 0 or order['status'] == 'open':
return order_amount
# use fee from order-dict if possible
if ('fee' in order and order['fee'] is not None
and (order['fee'].keys() >= {'currency', 'cost'})):
if (order['fee']['currency'] is not None
and order['fee']['cost'] is not None
and trade.pair.startswith(order['fee']['currency'])):
new_amount = order_amount - order['fee']['cost']
logger.info(
"Applying fee on amount for %s (from %s to %s) from Order",
trade, order['amount'], new_amount)
return new_amount
# Fallback to Trades
trades = self.exchange.get_trades_for_order(trade.open_order_id,
trade.pair,
trade.open_date)
if len(trades) == 0:
logger.info(
"Applying fee on amount for %s failed: myTrade-Dict empty found",
trade)
return order_amount
amount = 0
fee_abs = 0
for exectrade in trades:
amount += exectrade['amount']
if ("fee" in exectrade and exectrade['fee'] is not None
and (exectrade['fee'].keys() >= {'currency', 'cost'})):
# only applies if fee is in quote currency!
if (exectrade['fee']['currency'] is not None
and exectrade['fee']['cost'] is not None and
trade.pair.startswith(exectrade['fee']['currency'])):
fee_abs += exectrade['fee']['cost']
if not isclose(amount, order_amount,
abs_tol=constants.MATH_CLOSE_PREC):
logger.warning(
f"Amount {amount} does not match amount {trade.amount}")
raise DependencyException("Half bought? Amounts don't match")
real_amount = amount - fee_abs
if fee_abs != 0:
logger.info(f"Applying fee on amount for {trade} "
f"(from {order_amount} to {real_amount}) from Trades")
return real_amount