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Merge remote-tracking branch 'origin/strategy_utils' into strategy_utils

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This commit is contained in:
hippocritical
2023-03-18 20:07:34 +01:00
parent b1f88e8861 209811d23a
commit 4925d8f580
25 changed files with 2984 additions and 1206 deletions
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3984
freqtrade/exchange/binance_leverage_tiers.json
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File diff suppressed because it is too large Load Diff

25
freqtrade/exchange/exchange.py
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@@ -1087,7 +1087,7 @@ class Exchange:
f'Tried to {side} amount {amount} at rate {rate}.'
f'Message: {e}') from e
except ccxt.InvalidOrder as e:
raise ExchangeError(
raise InvalidOrderException(
f'Could not create {ordertype} {side} order on market {pair}. '
f'Tried to {side} amount {amount} at rate {rate}. '
f'Message: {e}') from e
@@ -1138,7 +1138,10 @@ class Exchange:
# Ensure rate is less than stop price
if bad_stop_price:
raise OperationalException(
'In stoploss limit order, stop price should be more than limit price')
"In stoploss limit order, stop price should be more than limit price. "
f"Stop price: {stop_price}, Limit price: {limit_rate}, "
f"Limit Price pct: {limit_price_pct}"
)
return limit_rate
def _get_stop_params(self, side: BuySell, ordertype: str, stop_price: float) -> Dict:
@@ -2755,10 +2758,10 @@ class Exchange:
raise OperationalException(
f"{self.name} does not support {self.margin_mode} {self.trading_mode}")
isolated_liq = None
liquidation_price = None
if self._config['dry_run'] or not self.exchange_has("fetchPositions"):
isolated_liq = self.dry_run_liquidation_price(
liquidation_price = self.dry_run_liquidation_price(
pair=pair,
open_rate=open_rate,
is_short=is_short,
@@ -2773,16 +2776,16 @@ class Exchange:
positions = self.fetch_positions(pair)
if len(positions) > 0:
pos = positions[0]
isolated_liq = pos['liquidationPrice']
liquidation_price = pos['liquidationPrice']
if isolated_liq is not None:
buffer_amount = abs(open_rate - isolated_liq) * self.liquidation_buffer
isolated_liq = (
isolated_liq - buffer_amount
if liquidation_price is not None:
buffer_amount = abs(open_rate - liquidation_price) * self.liquidation_buffer
liquidation_price_buffer = (
liquidation_price - buffer_amount
if is_short else
isolated_liq + buffer_amount
liquidation_price + buffer_amount
)
return isolated_liq
return max(liquidation_price_buffer, 0.0)
else:
return None

2
freqtrade/freqai/RL/Base3ActionRLEnv.py
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@@ -47,7 +47,7 @@ class Base3ActionRLEnv(BaseEnvironment):
self._update_unrealized_total_profit()
step_reward = self.calculate_reward(action)
self.total_reward += step_reward
self.tensorboard_log(self.actions._member_names_[action])
self.tensorboard_log(self.actions._member_names_[action], category="actions")
trade_type = None
if self.is_tradesignal(action):

2
freqtrade/freqai/RL/Base4ActionRLEnv.py
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@@ -48,7 +48,7 @@ class Base4ActionRLEnv(BaseEnvironment):
self._update_unrealized_total_profit()
step_reward = self.calculate_reward(action)
self.total_reward += step_reward
self.tensorboard_log(self.actions._member_names_[action])
self.tensorboard_log(self.actions._member_names_[action], category="actions")
trade_type = None
if self.is_tradesignal(action):

2
freqtrade/freqai/RL/Base5ActionRLEnv.py
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@@ -49,7 +49,7 @@ class Base5ActionRLEnv(BaseEnvironment):
self._update_unrealized_total_profit()
step_reward = self.calculate_reward(action)
self.total_reward += step_reward
self.tensorboard_log(self.actions._member_names_[action])
self.tensorboard_log(self.actions._member_names_[action], category="actions")
trade_type = None
if self.is_tradesignal(action):

22
freqtrade/freqai/RL/BaseEnvironment.py
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@@ -137,7 +137,8 @@ class BaseEnvironment(gym.Env):
self.np_random, seed = seeding.np_random(seed)
return [seed]
def tensorboard_log(self, metric: str, value: Union[int, float] = 1, inc: bool = True):
def tensorboard_log(self, metric: str, value: Optional[Union[int, float]] = None,
inc: Optional[bool] = None, category: str = "custom"):
"""
Function builds the tensorboard_metrics dictionary
to be parsed by the TensorboardCallback. This
@@ -149,17 +150,24 @@ class BaseEnvironment(gym.Env):
def calculate_reward(self, action: int) -> float:
if not self._is_valid(action):
self.tensorboard_log("is_valid")
self.tensorboard_log("invalid")
return -2
:param metric: metric to be tracked and incremented
:param value: value to increment `metric` by
:param inc: sets whether the `value` is incremented or not
:param value: `metric` value
:param inc: (deprecated) sets whether the `value` is incremented or not
:param category: `metric` category
"""
if not inc or metric not in self.tensorboard_metrics:
self.tensorboard_metrics[metric] = value
increment = True if value is None else False
value = 1 if increment else value
if category not in self.tensorboard_metrics:
self.tensorboard_metrics[category] = {}
if not increment or metric not in self.tensorboard_metrics[category]:
self.tensorboard_metrics[category][metric] = value
else:
self.tensorboard_metrics[metric] += value
self.tensorboard_metrics[category][metric] += value
def reset_tensorboard_log(self):
self.tensorboard_metrics = {}

14
freqtrade/freqai/RL/TensorboardCallback.py
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@@ -46,14 +46,12 @@ class TensorboardCallback(BaseCallback):
local_info = self.locals["infos"][0]
tensorboard_metrics = self.training_env.get_attr("tensorboard_metrics")[0]
for info in local_info:
if info not in ["episode", "terminal_observation"]:
self.logger.record(f"_info/{info}", local_info[info])
for metric in local_info:
if metric not in ["episode", "terminal_observation"]:
self.logger.record(f"info/{metric}", local_info[metric])
for info in tensorboard_metrics:
if info in [action.name for action in self.actions]:
self.logger.record(f"_actions/{info}", tensorboard_metrics[info])
else:
self.logger.record(f"_custom/{info}", tensorboard_metrics[info])
for category in tensorboard_metrics:
for metric in tensorboard_metrics[category]:
self.logger.record(f"{category}/{metric}", tensorboard_metrics[category][metric])
return True

2
freqtrade/freqai/prediction_models/ReinforcementLearner.py
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@@ -100,7 +100,7 @@ class ReinforcementLearner(BaseReinforcementLearningModel):
"""
# first, penalize if the action is not valid
if not self._is_valid(action):
self.tensorboard_log("is_valid")
self.tensorboard_log("invalid", category="actions")
return -2
pnl = self.get_unrealized_profit()

34
freqtrade/freqtradebot.py
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@@ -586,7 +586,7 @@ class FreqtradeBot(LoggingMixin):
min_entry_stake = self.exchange.get_min_pair_stake_amount(trade.pair,
current_entry_rate,
self.strategy.stoploss)
0.0)
min_exit_stake = self.exchange.get_min_pair_stake_amount(trade.pair,
current_exit_rate,
self.strategy.stoploss)
@@ -700,7 +700,8 @@ class FreqtradeBot(LoggingMixin):
pos_adjust = trade is not None
enter_limit_requested, stake_amount, leverage = self.get_valid_enter_price_and_stake(
pair, price, stake_amount, trade_side, enter_tag, trade, order_adjust, leverage_)
pair, price, stake_amount, trade_side, enter_tag, trade, order_adjust, leverage_,
pos_adjust)
if not stake_amount:
return False
@@ -860,7 +861,12 @@ class FreqtradeBot(LoggingMixin):
trade: Optional[Trade],
order_adjust: bool,
leverage_: Optional[float],
pos_adjust: bool,
) -> Tuple[float, float, float]:
"""
Validate and eventually adjust (within limits) limit, amount and leverage
:return: Tuple with (price, amount, leverage)
"""
if price:
enter_limit_requested = price
@@ -906,7 +912,9 @@ class FreqtradeBot(LoggingMixin):
# We do however also need min-stake to determine leverage, therefore this is ignored as
# edge-case for now.
min_stake_amount = self.exchange.get_min_pair_stake_amount(
pair, enter_limit_requested, self.strategy.stoploss, leverage)
pair, enter_limit_requested,
self.strategy.stoploss if not pos_adjust else 0.0,
leverage)
max_stake_amount = self.exchange.get_max_pair_stake_amount(
pair, enter_limit_requested, leverage)
@@ -1122,8 +1130,7 @@ class FreqtradeBot(LoggingMixin):
trade.stoploss_order_id = None
logger.error(f'Unable to place a stoploss order on exchange. {e}')
logger.warning('Exiting the trade forcefully')
self.execute_trade_exit(trade, stop_price, exit_check=ExitCheckTuple(
exit_type=ExitType.EMERGENCY_EXIT))
self.emergency_exit(trade, stop_price)
except ExchangeError:
trade.stoploss_order_id = None
@@ -1281,13 +1288,16 @@ class FreqtradeBot(LoggingMixin):
if canceled and max_timeouts > 0 and canceled_count >= max_timeouts:
logger.warning(f'Emergency exiting trade {trade}, as the exit order '
f'timed out {max_timeouts} times.')
try:
self.execute_trade_exit(
trade, order['price'],
exit_check=ExitCheckTuple(exit_type=ExitType.EMERGENCY_EXIT))
except DependencyException as exception:
logger.warning(
f'Unable to emergency sell trade {trade.pair}: {exception}')
self.emergency_exit(trade, order['price'])
def emergency_exit(self, trade: Trade, price: float) -> None:
try:
self.execute_trade_exit(
trade, price,
exit_check=ExitCheckTuple(exit_type=ExitType.EMERGENCY_EXIT))
except DependencyException as exception:
logger.warning(
f'Unable to emergency exit trade {trade.pair}: {exception}')
def replace_order(self, order: Dict, order_obj: Optional[Order], trade: Trade) -> None:
"""

2
freqtrade/optimize/backtesting.py
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@@ -749,7 +749,7 @@ class Backtesting:
leverage = min(max(leverage, 1.0), max_leverage)
min_stake_amount = self.exchange.get_min_pair_stake_amount(
pair, propose_rate, -0.05, leverage=leverage) or 0
pair, propose_rate, -0.05 if not pos_adjust else 0.0, leverage=leverage) or 0
max_stake_amount = self.exchange.get_max_pair_stake_amount(
pair, propose_rate, leverage=leverage)
stake_available = self.wallets.get_available_stake_amount()

5
freqtrade/persistence/trade_model.py
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@@ -1088,6 +1088,11 @@ class LocalTrade():
In live mode, converts the filter to a database query and returns all rows
In Backtest mode, uses filters on Trade.trades to get the result.
:param pair: Filter by pair
:param is_open: Filter by open/closed status
:param open_date: Filter by open_date (filters via trade.open_date > input)
:param close_date: Filter by close_date (filters via trade.close_date > input)
Will implicitly only return closed trades.
:return: unsorted List[Trade]
"""

2
freqtrade/rpc/api_server/api_schemas.py
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@@ -311,7 +311,7 @@ class LockModel(BaseModel):
lock_timestamp: int
pair: str
side: str
reason: str
reason: Optional[str]
class Locks(BaseModel):

3
freqtrade/rpc/rpc.py
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@@ -388,12 +388,13 @@ class RPC:
Trade.close_date.desc())
output = [trade.to_json() for trade in trades]
total_trades = Trade.get_trades([Trade.is_open.is_(False)]).count()
return {
"trades": output,
"trades_count": len(output),
"offset": offset,
"total_trades": Trade.get_trades([Trade.is_open.is_(False)]).count(),
"total_trades": total_trades,
}
def _rpc_stats(self) -> Dict[str, Any]: