Merge branch 'freqtrade:develop' into bt-metrics

This commit is contained in:
Stefano Ariestasia 2023-09-20 17:48:37 +09:00 committed by GitHub
commit a74b6df14e
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
35 changed files with 536 additions and 138 deletions

View File

@ -55,7 +55,7 @@ This configuration enables kraken, as well as rate-limiting to avoid bans from t
## Binance
!!! Warning "Server location and geo-ip restrictions"
Please be aware that binance restrict api access regarding the server country. The currents and non exhaustive countries blocked are United States, Malaysia (Singapour), Ontario (Canada). Please go to [binance terms > b. Eligibility](https://www.binance.com/en/terms) to find up to date list.
Please be aware that Binance restricts API access regarding the server country. The current and non-exhaustive countries blocked are Canada, Malaysia, Netherlands and United States. Please go to [binance terms > b. Eligibility](https://www.binance.com/en/terms) to find up to date list.
Binance supports [time_in_force](configuration.md#understand-order_time_in_force).

View File

@ -376,7 +376,7 @@ If the trading range over the last 10 days is <1% or >99%, remove the pair from
"lookback_days": 10,
"min_rate_of_change": 0.01,
"max_rate_of_change": 0.99,
"refresh_period": 1440
"refresh_period": 86400
}
]
```
@ -431,7 +431,7 @@ The below example blacklists `BNB/BTC`, uses `VolumePairList` with `20` assets,
"method": "RangeStabilityFilter",
"lookback_days": 10,
"min_rate_of_change": 0.01,
"refresh_period": 1440
"refresh_period": 86400
},
{
"method": "VolatilityFilter",

View File

@ -1,6 +1,6 @@
markdown==3.4.4
mkdocs==1.5.2
mkdocs-material==9.2.8
mkdocs-material==9.3.1
mdx_truly_sane_lists==1.3
pymdown-extensions==10.3
jinja2==3.1.2

View File

@ -510,6 +510,9 @@ Each of these methods are called right before placing an order on the exchange.
!!! Note
If your custom pricing function return None or an invalid value, price will fall back to `proposed_rate`, which is based on the regular pricing configuration.
!!! Note
Using custom_entry_price, the Trade object will be available as soon as the first entry order associated with the trade is created, for the first entry, `trade` parameter value will be `None`.
### Custom order entry and exit price example
``` python
@ -520,7 +523,7 @@ class AwesomeStrategy(IStrategy):
# ... populate_* methods
def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
def custom_entry_price(self, pair: str, trade: Optional['Trade'], current_time: datetime, proposed_rate: float,
entry_tag: Optional[str], side: str, **kwargs) -> float:
dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
@ -823,7 +826,7 @@ class DigDeeperStrategy(IStrategy):
"""
Custom trade adjustment logic, returning the stake amount that a trade should be
increased or decreased.
This means extra buy or sell orders with additional fees.
This means extra entry or exit orders with additional fees.
Only called when `position_adjustment_enable` is set to True.
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
@ -832,8 +835,9 @@ class DigDeeperStrategy(IStrategy):
:param trade: trade object.
:param current_time: datetime object, containing the current datetime
:param current_rate: Current buy rate.
:param current_profit: Current profit (as ratio), calculated based on current_rate.
:param current_rate: Current entry rate (same as current_entry_profit)
:param current_profit: Current profit (as ratio), calculated based on current_rate
(same as current_entry_profit).
:param min_stake: Minimal stake size allowed by exchange (for both entries and exits)
:param max_stake: Maximum stake allowed (either through balance, or by exchange limits).
:param current_entry_rate: Current rate using entry pricing.

View File

@ -280,7 +280,7 @@ After:
``` python hl_lines="3"
class AwesomeStrategy(IStrategy):
def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
def custom_entry_price(self, pair: str, trade: Optional[Trade], current_time: datetime, proposed_rate: float,
entry_tag: Optional[str], side: str, **kwargs) -> float:
return proposed_rate
```

View File

@ -77,7 +77,8 @@ DL_DATA_TIMEFRAMES = ['1m', '5m']
ENV_VAR_PREFIX = 'FREQTRADE__'
NON_OPEN_EXCHANGE_STATES = ('cancelled', 'canceled', 'closed', 'expired')
CANCELED_EXCHANGE_STATES = ('cancelled', 'canceled', 'expired')
NON_OPEN_EXCHANGE_STATES = CANCELED_EXCHANGE_STATES + ('closed',)
# Define decimals per coin for outputs
# Only used for outputs.

View File

@ -1420,7 +1420,7 @@ class Exchange:
except ccxt.BaseError as e:
raise OperationalException(e) from e
def __fetch_orders_emulate(self, pair: str, since_ms: int) -> List[Dict]:
def _fetch_orders_emulate(self, pair: str, since_ms: int) -> List[Dict]:
orders = []
if self.exchange_has('fetchClosedOrders'):
orders = self._api.fetch_closed_orders(pair, since=since_ms)
@ -1450,9 +1450,9 @@ class Exchange:
except ccxt.NotSupported:
# Some exchanges don't support fetchOrders
# attempt to fetch open and closed orders separately
orders = self.__fetch_orders_emulate(pair, since_ms)
orders = self._fetch_orders_emulate(pair, since_ms)
else:
orders = self.__fetch_orders_emulate(pair, since_ms)
orders = self._fetch_orders_emulate(pair, since_ms)
self._log_exchange_response('fetch_orders', orders)
orders = [self._order_contracts_to_amount(o) for o in orders]
return orders

View File

@ -1,4 +1,5 @@
import logging
from datetime import timedelta
from typing import Any, Dict, List, Optional, Tuple
import ccxt
@ -10,6 +11,7 @@ from freqtrade.exceptions import (DDosProtection, OperationalException, Retryabl
from freqtrade.exchange import Exchange, date_minus_candles
from freqtrade.exchange.common import retrier
from freqtrade.misc import safe_value_fallback2
from freqtrade.util import dt_now, dt_ts
logger = logging.getLogger(__name__)
@ -186,7 +188,7 @@ class Okx(Exchange):
def _convert_stop_order(self, pair: str, order_id: str, order: Dict) -> Dict:
if (
order['status'] == 'closed'
order.get('status', 'open') == 'closed'
and (real_order_id := order.get('info', {}).get('ordId')) is not None
):
# Once a order triggered, we fetch the regular followup order.
@ -240,3 +242,18 @@ class Okx(Exchange):
pair=pair,
params=params1,
)
def _fetch_orders_emulate(self, pair: str, since_ms: int) -> List[Dict]:
orders = []
orders = self._api.fetch_closed_orders(pair, since=since_ms)
if (since_ms < dt_ts(dt_now() - timedelta(days=6, hours=23))):
# Regular fetch_closed_orders only returns 7 days of data.
# Force usage of "archive" endpoint, which returns 3 months of data.
params = {'method': 'privateGetTradeOrdersHistoryArchive'}
orders_hist = self._api.fetch_closed_orders(pair, since=since_ms, params=params)
orders.extend(orders_hist)
orders_open = self._api.fetch_open_orders(pair, since=since_ms)
orders.extend(orders_open)
return orders

View File

@ -263,23 +263,46 @@ class FreqaiDataDrawer:
self.pair_dict[metadata["pair"]] = self.empty_pair_dict.copy()
return
def set_initial_return_values(self, pair: str, pred_df: DataFrame) -> None:
def set_initial_return_values(self, pair: str,
pred_df: DataFrame,
dataframe: DataFrame
) -> None:
"""
Set the initial return values to the historical predictions dataframe. This avoids needing
to repredict on historical candles, and also stores historical predictions despite
retrainings (so stored predictions are true predictions, not just inferencing on trained
data)
data).
We also aim to keep the date from historical predictions so that the FreqUI displays
zeros during any downtime (between FreqAI reloads).
"""
hist_df = self.historic_predictions
len_diff = len(hist_df[pair].index) - len(pred_df.index)
if len_diff < 0:
df_concat = pd.concat([pred_df.iloc[:abs(len_diff)], hist_df[pair]],
ignore_index=True, keys=hist_df[pair].keys())
new_pred = pred_df.copy()
# set new_pred values to nans (we want to signal to user that there was nothing
# historically made during downtime. The newest pred will get appeneded later in
# append_model_predictions)
new_pred.iloc[:, :] = np.nan
new_pred["date_pred"] = dataframe["date"]
hist_preds = self.historic_predictions[pair].copy()
# find the closest common date between new_pred and historic predictions
# and cut off the new_pred dataframe at that date
common_dates = pd.merge(new_pred, hist_preds, on="date_pred", how="inner")
if len(common_dates.index) > 0:
new_pred = new_pred.iloc[len(common_dates):]
else:
df_concat = hist_df[pair].tail(len(pred_df.index)).reset_index(drop=True)
logger.warning("No common dates found between new predictions and historic "
"predictions. You likely left your FreqAI instance offline "
f"for more than {len(dataframe.index)} candles.")
df_concat = pd.concat([hist_preds, new_pred], ignore_index=True, keys=hist_preds.keys())
# remove last row because we will append that later in append_model_predictions()
df_concat = df_concat.iloc[:-1]
# any missing values will get zeroed out so users can see the exact
# downtime in FreqUI
df_concat = df_concat.fillna(0)
self.model_return_values[pair] = df_concat
self.historic_predictions[pair] = df_concat
self.model_return_values[pair] = df_concat.tail(len(dataframe.index)).reset_index(drop=True)
def append_model_predictions(self, pair: str, predictions: DataFrame,
do_preds: NDArray[np.int_],

View File

@ -244,6 +244,14 @@ class FreqaiDataKitchen:
f"{self.pair}: dropped {len(unfiltered_df) - len(filtered_df)} training points"
f" due to NaNs in populated dataset {len(unfiltered_df)}."
)
if len(unfiltered_df) == 0 and not self.live:
raise OperationalException(
f"{self.pair}: all training data dropped due to NaNs. "
"You likely did not download enough training data prior "
"to your backtest timerange. Hint:\n"
"https://www.freqtrade.io/en/stable/freqai-running/"
"#downloading-data-to-cover-the-full-backtest-period"
)
if (1 - len(filtered_df) / len(unfiltered_df)) > 0.1 and self.live:
worst_indicator = str(unfiltered_df.count().idxmin())
logger.warning(

View File

@ -453,7 +453,7 @@ class IFreqaiModel(ABC):
pred_df, do_preds = self.predict(dataframe, dk)
if pair not in self.dd.historic_predictions:
self.set_initial_historic_predictions(pred_df, dk, pair, dataframe)
self.dd.set_initial_return_values(pair, pred_df)
self.dd.set_initial_return_values(pair, pred_df, dataframe)
dk.return_dataframe = self.dd.attach_return_values_to_return_dataframe(pair, dataframe)
return
@ -645,11 +645,11 @@ class IFreqaiModel(ABC):
If the user reuses an identifier on a subsequent instance,
this function will not be called. In that case, "real" predictions
will be appended to the loaded set of historic predictions.
:param df: DataFrame = the dataframe containing the training feature data
:param model: Any = A model which was `fit` using a common library such as
catboost or lightgbm
:param pred_df: DataFrame = the dataframe containing the predictions coming
out of a model
:param dk: FreqaiDataKitchen = object containing methods for data analysis
:param pair: str = current pair
:param strat_df: DataFrame = dataframe coming from strategy
"""
self.dd.historic_predictions[pair] = pred_df

View File

@ -456,31 +456,42 @@ class FreqtradeBot(LoggingMixin):
Only used balance disappeared, which would make exiting impossible.
"""
try:
orders = self.exchange.fetch_orders(trade.pair, trade.open_date_utc)
orders = self.exchange.fetch_orders(
trade.pair, trade.open_date_utc - timedelta(seconds=10))
prev_exit_reason = trade.exit_reason
prev_trade_state = trade.is_open
for order in orders:
trade_order = [o for o in trade.orders if o.order_id == order['id']]
if trade_order:
continue
logger.info(f"Found previously unknown order {order['id']} for {trade.pair}.")
order_obj = Order.parse_from_ccxt_object(order, trade.pair, order['side'])
order_obj.order_filled_date = datetime.fromtimestamp(
safe_value_fallback(order, 'lastTradeTimestamp', 'timestamp') // 1000,
tz=timezone.utc)
trade.orders.append(order_obj)
prev_exit_reason = trade.exit_reason
trade.exit_reason = ExitType.SOLD_ON_EXCHANGE.value
self.update_trade_state(trade, order['id'], order)
if trade_order:
# We knew this order, but didn't have it updated properly
order_obj = trade_order[0]
else:
logger.info(f"Found previously unknown order {order['id']} for {trade.pair}.")
order_obj = Order.parse_from_ccxt_object(order, trade.pair, order['side'])
order_obj.order_filled_date = datetime.fromtimestamp(
safe_value_fallback(order, 'lastTradeTimestamp', 'timestamp') // 1000,
tz=timezone.utc)
trade.orders.append(order_obj)
Trade.commit()
trade.exit_reason = ExitType.SOLD_ON_EXCHANGE.value
self.update_trade_state(trade, order['id'], order, send_msg=False)
logger.info(f"handled order {order['id']}")
if not trade.is_open:
# Trade was just closed
trade.close_date = order_obj.order_filled_date
Trade.commit()
break
else:
trade.exit_reason = prev_exit_reason
Trade.commit()
# Refresh trade from database
Trade.session.refresh(trade)
if not trade.is_open:
# Trade was just closed
trade.close_date = trade.date_last_filled_utc
self.order_close_notify(trade, order_obj,
order_obj.ft_order_side == 'stoploss',
send_msg=prev_trade_state != trade.is_open)
else:
trade.exit_reason = prev_exit_reason
Trade.commit()
except ExchangeError:
logger.warning("Error finding onexchange order.")
@ -927,7 +938,8 @@ class FreqtradeBot(LoggingMixin):
# Don't call custom_entry_price in order-adjust scenario
custom_entry_price = strategy_safe_wrapper(self.strategy.custom_entry_price,
default_retval=enter_limit_requested)(
pair=pair, current_time=datetime.now(timezone.utc),
pair=pair, trade=trade,
current_time=datetime.now(timezone.utc),
proposed_rate=enter_limit_requested, entry_tag=entry_tag,
side=trade_side,
)
@ -1352,18 +1364,21 @@ class FreqtradeBot(LoggingMixin):
self.handle_cancel_enter(trade, order, order_id, reason)
else:
canceled = self.handle_cancel_exit(trade, order, order_id, reason)
canceled_count = trade.get_exit_order_count()
canceled_count = trade.get_canceled_exit_order_count()
max_timeouts = self.config.get('unfilledtimeout', {}).get('exit_timeout_count', 0)
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.')
self.emergency_exit(trade, order['price'])
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. force selling {order['amount']}.")
self.emergency_exit(trade, order['price'], order['amount'])
def emergency_exit(self, trade: Trade, price: float) -> None:
def emergency_exit(
self, trade: Trade, price: float, sub_trade_amt: Optional[float] = None) -> None:
try:
self.execute_trade_exit(
trade, price,
exit_check=ExitCheckTuple(exit_type=ExitType.EMERGENCY_EXIT))
exit_check=ExitCheckTuple(exit_type=ExitType.EMERGENCY_EXIT),
sub_trade_amt=sub_trade_amt
)
except DependencyException as exception:
logger.warning(
f'Unable to emergency exit trade {trade.pair}: {exception}')
@ -1838,7 +1853,7 @@ class FreqtradeBot(LoggingMixin):
def update_trade_state(
self, trade: Trade, order_id: Optional[str],
action_order: Optional[Dict[str, Any]] = None,
action_order: Optional[Dict[str, Any]] = None, *,
stoploss_order: bool = False, send_msg: bool = True) -> bool:
"""
Checks trades with open orders and updates the amount if necessary
@ -1875,7 +1890,7 @@ class FreqtradeBot(LoggingMixin):
self.handle_order_fee(trade, order_obj, order)
trade.update_trade(order_obj)
trade.update_trade(order_obj, not send_msg)
trade = self._update_trade_after_fill(trade, order_obj)
Trade.commit()

View File

@ -11,8 +11,8 @@ from freqtrade.util.gc_setup import gc_set_threshold
# check min. python version
if sys.version_info < (3, 8): # pragma: no cover
sys.exit("Freqtrade requires Python version >= 3.8")
if sys.version_info < (3, 9): # pragma: no cover
sys.exit("Freqtrade requires Python version >= 3.9")
from freqtrade import __version__
from freqtrade.commands import Arguments

View File

@ -156,7 +156,7 @@ def round_dict(d, n):
return {k: (round(v, n) if isinstance(v, float) else v) for k, v in d.items()}
def safe_value_fallback(obj: dict, key1: str, key2: str, default_value=None):
def safe_value_fallback(obj: dict, key1: str, key2: Optional[str] = None, default_value=None):
"""
Search a value in obj, return this if it's not None.
Then search key2 in obj - return that if it's not none - then use default_value.
@ -165,7 +165,7 @@ def safe_value_fallback(obj: dict, key1: str, key2: str, default_value=None):
if key1 in obj and obj[key1] is not None:
return obj[key1]
else:
if key2 in obj and obj[key2] is not None:
if key2 and key2 in obj and obj[key2] is not None:
return obj[key2]
return default_value

View File

@ -738,7 +738,9 @@ class Backtesting:
if order_type == 'limit':
new_rate = strategy_safe_wrapper(self.strategy.custom_entry_price,
default_retval=propose_rate)(
pair=pair, current_time=current_time,
pair=pair,
trade=trade, # type: ignore[arg-type]
current_time=current_time,
proposed_rate=propose_rate, entry_tag=entry_tag,
side=direction,
) # default value is the open rate

View File

@ -13,15 +13,17 @@ from sqlalchemy import (Enum, Float, ForeignKey, Integer, ScalarResult, Select,
from sqlalchemy.orm import Mapped, lazyload, mapped_column, relationship, validates
from typing_extensions import Self
from freqtrade.constants import (CUSTOM_TAG_MAX_LENGTH, DATETIME_PRINT_FORMAT, MATH_CLOSE_PREC,
NON_OPEN_EXCHANGE_STATES, BuySell, LongShort)
from freqtrade.constants import (CANCELED_EXCHANGE_STATES, CUSTOM_TAG_MAX_LENGTH,
DATETIME_PRINT_FORMAT, MATH_CLOSE_PREC, NON_OPEN_EXCHANGE_STATES,
BuySell, LongShort)
from freqtrade.enums import ExitType, TradingMode
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.exchange import (ROUND_DOWN, ROUND_UP, amount_to_contract_precision,
price_to_precision)
from freqtrade.leverage import interest
from freqtrade.misc import safe_value_fallback
from freqtrade.persistence.base import ModelBase, SessionType
from freqtrade.util import FtPrecise, dt_now
from freqtrade.util import FtPrecise, dt_from_ts, dt_now, dt_ts
logger = logging.getLogger(__name__)
@ -176,7 +178,9 @@ class Order(ModelBase):
# (represents the funding fee since the last order)
self.funding_fee = self.trade.funding_fees
if (order.get('filled', 0.0) or 0.0) > 0 and not self.order_filled_date:
self.order_filled_date = datetime.now(timezone.utc)
self.order_filled_date = dt_from_ts(
safe_value_fallback(order, 'lastTradeTimestamp', default_value=dt_ts())
)
self.order_update_date = datetime.now(timezone.utc)
def to_ccxt_object(self, stopPriceName: str = 'stopPrice') -> Dict[str, Any]:
@ -430,13 +434,20 @@ class LocalTrade:
return self.amount
@property
def date_last_filled_utc(self) -> datetime:
def _date_last_filled_utc(self) -> Optional[datetime]:
""" Date of the last filled order"""
orders = self.select_filled_orders()
if not orders:
if orders:
return max(o.order_filled_utc for o in orders if o.order_filled_utc)
return None
@property
def date_last_filled_utc(self) -> datetime:
""" Date of the last filled order - or open_date if no orders are filled"""
dt_last_filled = self._date_last_filled_utc
if not dt_last_filled:
return self.open_date_utc
return max([self.open_date_utc,
max(o.order_filled_utc for o in orders if o.order_filled_utc)])
return max([self.open_date_utc, dt_last_filled])
@property
def open_date_utc(self):
@ -617,8 +628,9 @@ class LocalTrade:
'amount_precision': self.amount_precision,
'price_precision': self.price_precision,
'precision_mode': self.precision_mode,
'orders': orders_json,
'contract_size': self.contract_size,
'has_open_orders': self.has_open_orders,
'orders': orders_json,
}
@staticmethod
@ -716,7 +728,7 @@ class LocalTrade:
f"Trailing stoploss saved us: "
f"{float(self.stop_loss) - float(self.initial_stop_loss or 0.0):.8f}.")
def update_trade(self, order: Order) -> None:
def update_trade(self, order: Order, recalculating: bool = False) -> None:
"""
Updates this entity with amount and actual open/close rates.
:param order: order retrieved by exchange.fetch_order()
@ -758,8 +770,9 @@ class LocalTrade:
self.precision_mode, self.contract_size)
if (
isclose(order.safe_amount_after_fee, amount_tr, abs_tol=MATH_CLOSE_PREC)
or order.safe_amount_after_fee > amount_tr
or (not recalculating and order.safe_amount_after_fee > amount_tr)
):
# When recalculating a trade, only comming out to 0 can force a close
self.close(order.safe_price)
else:
self.recalc_trade_from_orders()
@ -772,7 +785,7 @@ class LocalTrade:
and marks trade as closed
"""
self.close_rate = rate
self.close_date = self.close_date or datetime.utcnow()
self.close_date = self.close_date or self._date_last_filled_utc or dt_now()
self.is_open = False
self.exit_order_status = 'closed'
self.recalc_trade_from_orders(is_closing=True)
@ -812,12 +825,13 @@ class LocalTrade:
def update_order(self, order: Dict) -> None:
Order.update_orders(self.orders, order)
def get_exit_order_count(self) -> int:
def get_canceled_exit_order_count(self) -> int:
"""
Get amount of failed exiting orders
assumes full exits.
"""
return len([o for o in self.orders if o.ft_order_side == self.exit_side])
return len([o for o in self.orders if o.ft_order_side == self.exit_side
and o.status in CANCELED_EXCHANGE_STATES])
def _calc_open_trade_value(self, amount: float, open_rate: float) -> float:
"""
@ -1776,6 +1790,10 @@ class Trade(ModelBase, LocalTrade):
is_short=data["is_short"],
trading_mode=data["trading_mode"],
funding_fees=data["funding_fees"],
amount_precision=data.get('amount_precision', None),
price_precision=data.get('price_precision', None),
precision_mode=data.get('precision_mode', None),
contract_size=data.get('contract_size', None),
)
for order in data["orders"]:

View File

@ -30,7 +30,7 @@ class RangeStabilityFilter(IPairList):
self._days = pairlistconfig.get('lookback_days', 10)
self._min_rate_of_change = pairlistconfig.get('min_rate_of_change', 0.01)
self._max_rate_of_change = pairlistconfig.get('max_rate_of_change')
self._refresh_period = pairlistconfig.get('refresh_period', 1440)
self._refresh_period = pairlistconfig.get('refresh_period', 86400)
self._def_candletype = self._config['candle_type_def']
self._pair_cache: TTLCache = TTLCache(maxsize=1000, ttl=self._refresh_period)

View File

@ -395,7 +395,8 @@ class IStrategy(ABC, HyperStrategyMixin):
"""
return self.stoploss
def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
def custom_entry_price(self, pair: str, trade: Optional[Trade],
current_time: datetime, proposed_rate: float,
entry_tag: Optional[str], side: str, **kwargs) -> float:
"""
Custom entry price logic, returning the new entry price.
@ -405,6 +406,7 @@ class IStrategy(ABC, HyperStrategyMixin):
When not implemented by a strategy, returns None, orderbook is used to set entry price
:param pair: Pair that's currently analyzed
:param trade: trade object (None for initial entries).
:param current_time: datetime object, containing the current datetime
:param proposed_rate: Rate, calculated based on pricing settings in exit_pricing.
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
@ -513,7 +515,7 @@ class IStrategy(ABC, HyperStrategyMixin):
"""
Custom trade adjustment logic, returning the stake amount that a trade should be
increased or decreased.
This means extra buy or sell orders with additional fees.
This means extra entry or exit orders with additional fees.
Only called when `position_adjustment_enable` is set to True.
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
@ -522,8 +524,9 @@ class IStrategy(ABC, HyperStrategyMixin):
:param trade: trade object.
:param current_time: datetime object, containing the current datetime
:param current_rate: Current buy rate.
:param current_profit: Current profit (as ratio), calculated based on current_rate.
:param current_rate: Current entry rate (same as current_entry_profit)
:param current_profit: Current profit (as ratio), calculated based on current_rate
(same as current_entry_profit).
:param min_stake: Minimal stake size allowed by exchange (for both entries and exits)
:param max_stake: Maximum stake allowed (either through balance, or by exchange limits).
:param current_entry_rate: Current rate using entry pricing.

View File

@ -31,7 +31,7 @@ class FreqaiExampleStrategy(IStrategy):
plot_config = {
"main_plot": {},
"subplots": {
"&-s_close": {"prediction": {"color": "blue"}},
"&-s_close": {"&-s_close": {"color": "blue"}},
"do_predict": {
"do_predict": {"color": "brown"},
},

View File

@ -13,7 +13,8 @@ def bot_loop_start(self, current_time: datetime, **kwargs) -> None:
"""
pass
def custom_entry_price(self, pair: str, current_time: 'datetime', proposed_rate: float,
def custom_entry_price(self, pair: str, trade: Optional['Trade'],
current_time: 'datetime', proposed_rate: float,
entry_tag: 'Optional[str]', side: str, **kwargs) -> float:
"""
Custom entry price logic, returning the new entry price.
@ -23,6 +24,7 @@ def custom_entry_price(self, pair: str, current_time: 'datetime', proposed_rate:
When not implemented by a strategy, returns None, orderbook is used to set entry price
:param pair: Pair that's currently analyzed
:param trade: trade object (None for initial entries).
:param current_time: datetime object, containing the current datetime
:param proposed_rate: Rate, calculated based on pricing settings in exit_pricing.
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
@ -257,7 +259,7 @@ def adjust_trade_position(self, trade: 'Trade', current_time: datetime,
"""
Custom trade adjustment logic, returning the stake amount that a trade should be
increased or decreased.
This means extra buy or sell orders with additional fees.
This means extra entry or exit orders with additional fees.
Only called when `position_adjustment_enable` is set to True.
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
@ -266,8 +268,9 @@ def adjust_trade_position(self, trade: 'Trade', current_time: datetime,
:param trade: trade object.
:param current_time: datetime object, containing the current datetime
:param current_rate: Current buy rate.
:param current_profit: Current profit (as ratio), calculated based on current_rate.
:param current_rate: Current entry rate (same as current_entry_profit)
:param current_profit: Current profit (as ratio), calculated based on current_rate
(same as current_entry_profit).
:param min_stake: Minimal stake size allowed by exchange (for both entries and exits)
:param max_stake: Maximum stake allowed (either through balance, or by exchange limits).
:param current_entry_rate: Current rate using entry pricing.
@ -276,8 +279,8 @@ def adjust_trade_position(self, trade: 'Trade', current_time: datetime,
:param current_exit_profit: Current profit using exit pricing.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: Stake amount to adjust your trade,
Positive values to increase position, Negative values to decrease position.
Return None for no action.
Positive values to increase position, Negative values to decrease position.
Return None for no action.
"""
return None

View File

@ -65,6 +65,7 @@ ignore = ["freqtrade/vendor/**"]
line-length = 100
extend-exclude = [".env", ".venv"]
target-version = "py38"
# Exclude UP036 as it's causing the "exit if < 3.9" to fail.
extend-select = [
"C90", # mccabe
# "N", # pep8-naming

View File

@ -7,7 +7,7 @@
-r docs/requirements-docs.txt
coveralls==3.3.1
ruff==0.0.287
ruff==0.0.290
mypy==1.5.1
pre-commit==3.4.0
pytest==7.4.2

View File

@ -6,7 +6,7 @@
scikit-learn==1.1.3
joblib==1.3.2
catboost==1.2.1; 'arm' not in platform_machine
lightgbm==4.0.0
xgboost==1.7.6
lightgbm==4.1.0
xgboost==2.0.0
tensorboard==2.14.0
datasieve==0.1.7

View File

@ -5,4 +5,4 @@
scipy==1.11.2
scikit-learn==1.1.3
scikit-optimize==0.9.0
filelock==3.12.3
filelock==3.12.4

View File

@ -1,4 +1,4 @@
# Include all requirements to run the bot.
-r requirements.txt
plotly==5.16.1
plotly==5.17.0

View File

@ -1,4 +1,4 @@
numpy==1.25.2
numpy==1.26.0
pandas==2.0.3
pandas-ta==0.3.14b
@ -23,14 +23,14 @@ jinja2==3.1.2
tables==3.8.0
blosc==1.11.1
joblib==1.3.2
rich==13.5.2
rich==13.5.3
pyarrow==13.0.0; platform_machine != 'armv7l'
# find first, C search in arrays
py_find_1st==1.1.5
# Load ticker files 30% faster
python-rapidjson==1.10
python-rapidjson==1.11
# Properly format api responses
orjson==3.9.7

View File

@ -24,7 +24,7 @@ from tests.conftest import (EXMS, generate_test_data_raw, get_mock_coro, get_pat
# Make sure to always keep one exchange here which is NOT subclassed!!
EXCHANGES = ['bittrex', 'binance', 'kraken', 'gate', 'kucoin', 'bybit']
EXCHANGES = ['bittrex', 'binance', 'kraken', 'gate', 'kucoin', 'bybit', 'okx']
get_entry_rate_data = [
('other', 20, 19, 10, 0.0, 20), # Full ask side
@ -1312,8 +1312,11 @@ def test_create_order(default_conf, mocker, side, ordertype, rate, marketprice,
leverage=3.0
)
assert exchange._set_leverage.call_count == 1
assert exchange.set_margin_mode.call_count == 1
if exchange_name != 'okx':
assert exchange._set_leverage.call_count == 1
assert exchange.set_margin_mode.call_count == 1
else:
assert api_mock.set_leverage.call_count == 1
assert order['amount'] == 0.01
@ -1677,7 +1680,10 @@ def test_fetch_orders(default_conf, mocker, exchange_name, limit_order):
api_mock.fetch_closed_orders = MagicMock(return_value=[limit_order['buy']])
mocker.patch(f'{EXMS}.exchange_has', return_value=True)
start_time = datetime.now(timezone.utc) - timedelta(days=5)
start_time = datetime.now(timezone.utc) - timedelta(days=20)
expected = 1
if exchange_name == 'bybit':
expected = 3
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
# Not available in dry-run
@ -1687,10 +1693,10 @@ def test_fetch_orders(default_conf, mocker, exchange_name, limit_order):
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
res = exchange.fetch_orders('mocked', start_time)
assert api_mock.fetch_orders.call_count == 1
assert api_mock.fetch_orders.call_count == expected
assert api_mock.fetch_open_orders.call_count == 0
assert api_mock.fetch_closed_orders.call_count == 0
assert len(res) == 2
assert len(res) == 2 * expected
res = exchange.fetch_orders('mocked', start_time)
@ -1704,13 +1710,17 @@ def test_fetch_orders(default_conf, mocker, exchange_name, limit_order):
if endpoint == 'fetchOpenOrders':
return True
if exchange_name == 'okx':
# Special OKX case is tested separately
return
mocker.patch(f'{EXMS}.exchange_has', has_resp)
# happy path without fetchOrders
res = exchange.fetch_orders('mocked', start_time)
exchange.fetch_orders('mocked', start_time)
assert api_mock.fetch_orders.call_count == 0
assert api_mock.fetch_open_orders.call_count == 1
assert api_mock.fetch_closed_orders.call_count == 1
assert api_mock.fetch_open_orders.call_count == expected
assert api_mock.fetch_closed_orders.call_count == expected
mocker.patch(f'{EXMS}.exchange_has', return_value=True)
@ -1723,11 +1733,11 @@ def test_fetch_orders(default_conf, mocker, exchange_name, limit_order):
api_mock.fetch_open_orders.reset_mock()
api_mock.fetch_closed_orders.reset_mock()
res = exchange.fetch_orders('mocked', start_time)
exchange.fetch_orders('mocked', start_time)
assert api_mock.fetch_orders.call_count == 1
assert api_mock.fetch_open_orders.call_count == 1
assert api_mock.fetch_closed_orders.call_count == 1
assert api_mock.fetch_orders.call_count == expected
assert api_mock.fetch_open_orders.call_count == expected
assert api_mock.fetch_closed_orders.call_count == expected
def test_fetch_trading_fees(default_conf, mocker):
@ -2044,7 +2054,7 @@ async def test__async_get_historic_ohlcv(default_conf, mocker, caplog, exchange_
)
# Required candles
candles = (end_ts - start_ts) / 300_000
exp = candles // exchange.ohlcv_candle_limit('5m', CandleType.SPOT) + 1
exp = candles // exchange.ohlcv_candle_limit('5m', candle_type, start_ts) + 1
# Depending on the exchange, this should be called between 1 and 6 times.
assert exchange._api_async.fetch_ohlcv.call_count == exp
@ -3122,25 +3132,28 @@ def test_cancel_stoploss_order(default_conf, mocker, exchange_name):
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_cancel_stoploss_order_with_result(default_conf, mocker, exchange_name):
default_conf['dry_run'] = False
mock_prefix = 'freqtrade.exchange.gate.Gate'
if exchange_name == 'okx':
mock_prefix = 'freqtrade.exchange.okx.Okx'
mocker.patch(f'{EXMS}.fetch_stoploss_order', return_value={'for': 123})
mocker.patch('freqtrade.exchange.gate.Gate.fetch_stoploss_order', return_value={'for': 123})
mocker.patch(f'{mock_prefix}.fetch_stoploss_order', return_value={'for': 123})
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
res = {'fee': {}, 'status': 'canceled', 'amount': 1234}
mocker.patch(f'{EXMS}.cancel_stoploss_order', return_value=res)
mocker.patch('freqtrade.exchange.gate.Gate.cancel_stoploss_order', return_value=res)
mocker.patch(f'{mock_prefix}.cancel_stoploss_order', return_value=res)
co = exchange.cancel_stoploss_order_with_result(order_id='_', pair='TKN/BTC', amount=555)
assert co == res
mocker.patch(f'{EXMS}.cancel_stoploss_order', return_value='canceled')
mocker.patch('freqtrade.exchange.gate.Gate.cancel_stoploss_order', return_value='canceled')
mocker.patch(f'{mock_prefix}.cancel_stoploss_order', return_value='canceled')
# Fall back to fetch_stoploss_order
co = exchange.cancel_stoploss_order_with_result(order_id='_', pair='TKN/BTC', amount=555)
assert co == {'for': 123}
exc = InvalidOrderException("")
mocker.patch(f'{EXMS}.fetch_stoploss_order', side_effect=exc)
mocker.patch('freqtrade.exchange.gate.Gate.fetch_stoploss_order', side_effect=exc)
mocker.patch(f'{mock_prefix}.fetch_stoploss_order', side_effect=exc)
co = exchange.cancel_stoploss_order_with_result(order_id='_', pair='TKN/BTC', amount=555)
assert co['amount'] == 555
assert co == {'fee': {}, 'status': 'canceled', 'amount': 555, 'info': {}}
@ -3148,7 +3161,7 @@ def test_cancel_stoploss_order_with_result(default_conf, mocker, exchange_name):
with pytest.raises(InvalidOrderException):
exc = InvalidOrderException("Did not find order")
mocker.patch(f'{EXMS}.cancel_stoploss_order', side_effect=exc)
mocker.patch('freqtrade.exchange.gate.Gate.cancel_stoploss_order', side_effect=exc)
mocker.patch(f'{mock_prefix}.cancel_stoploss_order', side_effect=exc)
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
exchange.cancel_stoploss_order_with_result(order_id='_', pair='TKN/BTC', amount=123)
@ -3223,8 +3236,14 @@ def test_fetch_stoploss_order(default_conf, mocker, exchange_name):
api_mock = MagicMock()
api_mock.fetch_order = MagicMock(return_value={'id': '123', 'symbol': 'TKN/BTC'})
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
assert exchange.fetch_stoploss_order('X', 'TKN/BTC') == {'id': '123', 'symbol': 'TKN/BTC'}
res = {'id': '123', 'symbol': 'TKN/BTC'}
if exchange_name == 'okx':
res = {'id': '123', 'symbol': 'TKN/BTC', 'type': 'stoploss'}
assert exchange.fetch_stoploss_order('X', 'TKN/BTC') == res
if exchange_name == 'okx':
# Tested separately.
return
with pytest.raises(InvalidOrderException):
api_mock.fetch_order = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
@ -3544,6 +3563,8 @@ def test_get_markets_error(default_conf, mocker):
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_ohlcv_candle_limit(default_conf, mocker, exchange_name):
if exchange_name == 'okx':
pytest.skip("Tested separately for okx")
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
timeframes = ('1m', '5m', '1h')
expected = exchange._ft_has['ohlcv_candle_limit']

View File

@ -618,3 +618,70 @@ def test__get_stop_params_okx(mocker, default_conf):
assert params['tdMode'] == 'isolated'
assert params['posSide'] == 'net'
def test_fetch_orders_okx(default_conf, mocker, limit_order):
api_mock = MagicMock()
api_mock.fetch_orders = MagicMock(return_value=[
limit_order['buy'],
limit_order['sell'],
])
api_mock.fetch_open_orders = MagicMock(return_value=[limit_order['buy']])
api_mock.fetch_closed_orders = MagicMock(return_value=[limit_order['buy']])
mocker.patch(f'{EXMS}.exchange_has', return_value=True)
start_time = datetime.now(timezone.utc) - timedelta(days=20)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id='okx')
# Not available in dry-run
assert exchange.fetch_orders('mocked', start_time) == []
assert api_mock.fetch_orders.call_count == 0
default_conf['dry_run'] = False
exchange = get_patched_exchange(mocker, default_conf, api_mock, id='okx')
def has_resp(_, endpoint):
if endpoint == 'fetchOrders':
return False
if endpoint == 'fetchClosedOrders':
return True
if endpoint == 'fetchOpenOrders':
return True
mocker.patch(f'{EXMS}.exchange_has', has_resp)
history_params = {'method': 'privateGetTradeOrdersHistoryArchive'}
# happy path without fetchOrders
exchange.fetch_orders('mocked', start_time)
assert api_mock.fetch_orders.call_count == 0
assert api_mock.fetch_open_orders.call_count == 1
assert api_mock.fetch_closed_orders.call_count == 2
assert 'params' not in api_mock.fetch_closed_orders.call_args_list[0][1]
assert api_mock.fetch_closed_orders.call_args_list[1][1]['params'] == history_params
api_mock.fetch_open_orders.reset_mock()
api_mock.fetch_closed_orders.reset_mock()
# regular closed_orders endpoint only has history for 7 days.
exchange.fetch_orders('mocked', datetime.now(timezone.utc) - timedelta(days=6))
assert api_mock.fetch_orders.call_count == 0
assert api_mock.fetch_open_orders.call_count == 1
assert api_mock.fetch_closed_orders.call_count == 1
assert 'params' not in api_mock.fetch_closed_orders.call_args_list[0][1]
mocker.patch(f'{EXMS}.exchange_has', return_value=True)
# Unhappy path - first fetch-orders call fails.
api_mock.fetch_orders = MagicMock(side_effect=ccxt.NotSupported())
api_mock.fetch_open_orders.reset_mock()
api_mock.fetch_closed_orders.reset_mock()
exchange.fetch_orders('mocked', start_time)
assert api_mock.fetch_orders.call_count == 1
assert api_mock.fetch_open_orders.call_count == 1
assert api_mock.fetch_closed_orders.call_count == 2
assert 'params' not in api_mock.fetch_closed_orders.call_args_list[0][1]
assert api_mock.fetch_closed_orders.call_args_list[1][1]['params'] == history_params

View File

@ -1,7 +1,9 @@
import shutil
from pathlib import Path
from unittest.mock import patch
import pandas as pd
import pytest
from freqtrade.configuration import TimeRange
@ -135,3 +137,111 @@ def test_get_timerange_from_backtesting_live_df_pred_not_found(mocker, freqai_co
match=r'Historic predictions not found.*'
):
freqai.dd.get_timerange_from_live_historic_predictions()
def test_set_initial_return_values(mocker, freqai_conf):
"""
Simple test of the set initial return values that ensures
we are concatening and ffilling values properly.
"""
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
exchange = get_patched_exchange(mocker, freqai_conf)
strategy.dp = DataProvider(freqai_conf, exchange)
freqai = strategy.freqai
freqai.live = False
freqai.dk = FreqaiDataKitchen(freqai_conf)
# Setup
pair = "BTC/USD"
end_x = "2023-08-31"
start_x_plus_1 = "2023-08-30"
end_x_plus_5 = "2023-09-03"
historic_data = {
'date_pred': pd.date_range(end=end_x, periods=5),
'value': range(1, 6)
}
new_data = {
'date': pd.date_range(start=start_x_plus_1, end=end_x_plus_5),
'value': range(6, 11)
}
freqai.dd.historic_predictions[pair] = pd.DataFrame(historic_data)
new_pred_df = pd.DataFrame(new_data)
dataframe = pd.DataFrame(new_data)
# Action
with patch('logging.Logger.warning') as mock_logger_warning:
freqai.dd.set_initial_return_values(pair, new_pred_df, dataframe)
# Assertions
hist_pred_df = freqai.dd.historic_predictions[pair]
model_return_df = freqai.dd.model_return_values[pair]
assert (hist_pred_df['date_pred'].iloc[-1] ==
pd.Timestamp(end_x_plus_5) - pd.Timedelta(days=1))
assert 'date_pred' in hist_pred_df.columns
assert hist_pred_df.shape[0] == 7 # Total rows: 5 from historic and 2 new zeros
# compare values in model_return_df with hist_pred_df
assert (model_return_df["value"].values ==
hist_pred_df.tail(len(dataframe))["value"].values).all()
assert model_return_df.shape[0] == len(dataframe)
# Ensure logger error is not called
mock_logger_warning.assert_not_called()
def test_set_initial_return_values_warning(mocker, freqai_conf):
"""
Simple test of set_initial_return_values that hits the warning
associated with leaving a FreqAI bot offline so long that the
exchange candles have no common date with the historic predictions
"""
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
exchange = get_patched_exchange(mocker, freqai_conf)
strategy.dp = DataProvider(freqai_conf, exchange)
freqai = strategy.freqai
freqai.live = False
freqai.dk = FreqaiDataKitchen(freqai_conf)
# Setup
pair = "BTC/USD"
end_x = "2023-08-31"
start_x_plus_1 = "2023-09-01"
end_x_plus_5 = "2023-09-05"
historic_data = {
'date_pred': pd.date_range(end=end_x, periods=5),
'value': range(1, 6)
}
new_data = {
'date': pd.date_range(start=start_x_plus_1, end=end_x_plus_5),
'value': range(6, 11)
}
freqai.dd.historic_predictions[pair] = pd.DataFrame(historic_data)
new_pred_df = pd.DataFrame(new_data)
dataframe = pd.DataFrame(new_data)
# Action
with patch('logging.Logger.warning') as mock_logger_warning:
freqai.dd.set_initial_return_values(pair, new_pred_df, dataframe)
# Assertions
hist_pred_df = freqai.dd.historic_predictions[pair]
model_return_df = freqai.dd.model_return_values[pair]
assert hist_pred_df['date_pred'].iloc[-1] == pd.Timestamp(end_x_plus_5) - pd.Timedelta(days=1)
assert 'date_pred' in hist_pred_df.columns
assert hist_pred_df.shape[0] == 9 # Total rows: 5 from historic and 4 new zeros
# compare values in model_return_df with hist_pred_df
assert (model_return_df["value"].values == hist_pred_df.tail(
len(dataframe))["value"].values).all()
assert model_return_df.shape[0] == len(dataframe)
# Ensure logger error is not called
mock_logger_warning.assert_called()

View File

@ -600,7 +600,9 @@ def test_calc_open_close_trade_price(
@pytest.mark.usefixtures("init_persistence")
def test_trade_close(fee):
def test_trade_close(fee, time_machine):
time_machine.move_to("2022-09-01 05:00:00 +00:00", tick=False)
trade = Trade(
pair='ADA/USDT',
stake_amount=60.0,
@ -609,7 +611,7 @@ def test_trade_close(fee):
is_open=True,
fee_open=fee.return_value,
fee_close=fee.return_value,
open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=10),
open_date=dt_now() - timedelta(minutes=10),
interest_rate=0.0005,
exchange='binance',
trading_mode=margin,
@ -628,6 +630,7 @@ def test_trade_close(fee):
status="closed",
order_type="limit",
side=trade.entry_side,
order_filled_date=trade.open_date,
))
trade.orders.append(Order(
ft_order_side=trade.exit_side,
@ -642,6 +645,7 @@ def test_trade_close(fee):
status="closed",
order_type="limit",
side=trade.exit_side,
order_filled_date=dt_now(),
))
assert trade.close_profit is None
assert trade.close_date is None
@ -650,14 +654,15 @@ def test_trade_close(fee):
assert trade.is_open is False
assert pytest.approx(trade.close_profit) == 0.094513715
assert trade.close_date is not None
assert trade.close_date_utc == dt_now()
new_date = datetime(2020, 2, 2, 15, 6, 1),
assert trade.close_date != new_date
new_date = dt_now() + timedelta(minutes=5)
assert trade.close_date_utc != new_date
# Close should NOT update close_date if the trade has been closed already
assert trade.is_open is False
trade.close_date = new_date
trade.close(2.2)
assert trade.close_date == new_date
assert trade.close_date_utc == new_date
@pytest.mark.usefixtures("init_persistence")
@ -1380,6 +1385,7 @@ def test_to_json(fee):
precision_mode=1,
amount_precision=8.0,
price_precision=7.0,
contract_size=1,
)
result = trade.to_json()
assert isinstance(result, dict)
@ -1445,6 +1451,7 @@ def test_to_json(fee):
'amount_precision': 8.0,
'price_precision': 7.0,
'precision_mode': 1,
'contract_size': 1,
'orders': [],
'has_open_orders': False,
}
@ -1466,6 +1473,7 @@ def test_to_json(fee):
precision_mode=2,
amount_precision=7.0,
price_precision=8.0,
contract_size=1
)
result = trade.to_json()
assert isinstance(result, dict)
@ -1531,6 +1539,7 @@ def test_to_json(fee):
'amount_precision': 7.0,
'price_precision': 8.0,
'precision_mode': 2,
'contract_size': 1,
'orders': [],
'has_open_orders': False,
}
@ -1923,11 +1932,15 @@ def test_get_best_pair_lev(fee):
@pytest.mark.usefixtures("init_persistence")
@pytest.mark.parametrize('is_short', [True, False])
def test_get_exit_order_count(fee, is_short):
def test_get_canceled_exit_order_count(fee, is_short):
create_mock_trades(fee, is_short=is_short)
trade = Trade.get_trades([Trade.pair == 'ETC/BTC']).first()
assert trade.get_exit_order_count() == 1
# No canceled order.
assert trade.get_canceled_exit_order_count() == 0
trade.orders[-1].status = 'canceled'
assert trade.get_canceled_exit_order_count() == 1
@pytest.mark.usefixtures("init_persistence")

View File

@ -66,6 +66,10 @@ def test_trade_fromjson():
"is_short": false,
"trading_mode": "spot",
"funding_fees": 0.0,
"amount_precision": 1.0,
"price_precision": 3.0,
"precision_mode": 2,
"contract_size": 1.0,
"open_order_id": null,
"orders": [
{
@ -180,6 +184,9 @@ def test_trade_fromjson():
assert isinstance(trade.open_date, datetime)
assert trade.exit_reason == 'no longer good'
assert trade.realized_profit == 2.76315361
assert trade.precision_mode == 2
assert trade.amount_precision == 1.0
assert trade.contract_size == 1.0
assert len(trade.orders) == 5
last_o = trade.orders[-1]

View File

@ -90,6 +90,7 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
'amount_precision': 8.0,
'price_precision': 8.0,
'precision_mode': 2,
'contract_size': 1,
'has_open_orders': False,
'orders': [{
'amount': 91.07468123, 'average': 1.098e-05, 'safe_price': 1.098e-05,
@ -263,7 +264,11 @@ def test_rpc_status_table(default_conf, ticker, fee, mocker) -> None:
assert isnan(fiat_profit_sum)
def test__rpc_timeunit_profit(default_conf_usdt, ticker, fee, markets, mocker) -> None:
def test__rpc_timeunit_profit(
default_conf_usdt, ticker, fee, markets, mocker, time_machine) -> None:
time_machine.move_to("2023-09-05 10:00:00 +00:00", tick=False)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
EXMS,

View File

@ -6,6 +6,8 @@ from typing import Optional
from pandas import DataFrame
from strategy_test_v3 import StrategyTestV3
from freqtrade.persistence import Trade
class StrategyTestV3CustomEntryPrice(StrategyTestV3):
"""
@ -31,7 +33,8 @@ class StrategyTestV3CustomEntryPrice(StrategyTestV3):
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
return dataframe
def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
def custom_entry_price(self, pair: str, trade: Optional[Trade], current_time: datetime,
proposed_rate: float,
entry_tag: Optional[str], side: str, **kwargs) -> float:
return self.new_entry_price

View File

@ -2991,6 +2991,8 @@ def test_manage_open_orders_exit_usercustom(
is_short, open_trade_usdt, caplog
) -> None:
default_conf_usdt["unfilledtimeout"] = {"entry": 1440, "exit": 1440, "exit_timeout_count": 1}
limit_sell_order_old['amount'] = open_trade_usdt.amount
limit_sell_order_old['remaining'] = open_trade_usdt.amount
if is_short:
limit_sell_order_old['side'] = 'buy'
@ -3052,7 +3054,7 @@ def test_manage_open_orders_exit_usercustom(
# 2nd canceled trade - Fail execute exit
caplog.clear()
mocker.patch('freqtrade.persistence.Trade.get_exit_order_count', return_value=1)
mocker.patch('freqtrade.persistence.Trade.get_canceled_exit_order_count', return_value=1)
mocker.patch('freqtrade.freqtradebot.FreqtradeBot.execute_trade_exit',
side_effect=DependencyException)
freqtrade.manage_open_orders()
@ -5658,6 +5660,7 @@ def test_handle_insufficient_funds(mocker, default_conf_usdt, fee, is_short, cap
@pytest.mark.usefixtures("init_persistence")
@pytest.mark.parametrize("is_short", [False, True])
def test_handle_onexchange_order(mocker, default_conf_usdt, limit_order, is_short, caplog):
default_conf_usdt['dry_run'] = False
freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
mock_uts = mocker.spy(freqtrade, 'update_trade_state')
@ -5669,17 +5672,17 @@ def test_handle_onexchange_order(mocker, default_conf_usdt, limit_order, is_shor
])
trade = Trade(
pair='ETH/USDT',
fee_open=0.001,
fee_close=0.001,
open_rate=entry_order['price'],
open_date=dt_now(),
stake_amount=entry_order['cost'],
amount=entry_order['amount'],
exchange="binance",
is_short=is_short,
leverage=1,
)
pair='ETH/USDT',
fee_open=0.001,
fee_close=0.001,
open_rate=entry_order['price'],
open_date=dt_now(),
stake_amount=entry_order['cost'],
amount=entry_order['amount'],
exchange="binance",
is_short=is_short,
leverage=1,
)
trade.orders.append(Order.parse_from_ccxt_object(
entry_order, 'ADA/USDT', entry_side(is_short))
@ -5687,7 +5690,8 @@ def test_handle_onexchange_order(mocker, default_conf_usdt, limit_order, is_shor
Trade.session.add(trade)
freqtrade.handle_onexchange_order(trade)
assert log_has_re(r"Found previously unknown order .*", caplog)
assert mock_uts.call_count == 1
# Update trade state is called twice, once for the known and once for the unknown order.
assert mock_uts.call_count == 2
assert mock_fo.call_count == 1
trade = Trade.session.scalars(select(Trade)).first()
@ -5697,6 +5701,77 @@ def test_handle_onexchange_order(mocker, default_conf_usdt, limit_order, is_shor
assert trade.exit_reason == ExitType.SOLD_ON_EXCHANGE.value
@pytest.mark.usefixtures("init_persistence")
@pytest.mark.parametrize("is_short", [False, True])
def test_handle_onexchange_order_exit(mocker, default_conf_usdt, limit_order, is_short, caplog):
default_conf_usdt['dry_run'] = False
freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
mock_uts = mocker.spy(freqtrade, 'update_trade_state')
entry_order = limit_order[entry_side(is_short)]
add_entry_order = deepcopy(entry_order)
add_entry_order.update({
'id': '_partial_entry_id',
'amount': add_entry_order['amount'] / 1.5,
'cost': add_entry_order['cost'] / 1.5,
'filled': add_entry_order['filled'] / 1.5,
})
exit_order_part = deepcopy(limit_order[exit_side(is_short)])
exit_order_part.update({
'id': 'some_random_partial_id',
'amount': exit_order_part['amount'] / 2,
'cost': exit_order_part['cost'] / 2,
'filled': exit_order_part['filled'] / 2,
})
exit_order = limit_order[exit_side(is_short)]
# Orders intentionally in the wrong sequence
mock_fo = mocker.patch(f'{EXMS}.fetch_orders', return_value=[
entry_order,
exit_order_part,
exit_order,
add_entry_order,
])
trade = Trade(
pair='ETH/USDT',
fee_open=0.001,
fee_close=0.001,
open_rate=entry_order['price'],
open_date=dt_now(),
stake_amount=entry_order['cost'],
amount=entry_order['amount'],
exchange="binance",
is_short=is_short,
leverage=1,
is_open=True,
)
trade.orders = [
Order.parse_from_ccxt_object(entry_order, trade.pair, entry_side(is_short)),
Order.parse_from_ccxt_object(exit_order_part, trade.pair, exit_side(is_short)),
Order.parse_from_ccxt_object(add_entry_order, trade.pair, entry_side(is_short)),
Order.parse_from_ccxt_object(exit_order, trade.pair, exit_side(is_short)),
]
trade.recalc_trade_from_orders()
Trade.session.add(trade)
Trade.commit()
freqtrade.handle_onexchange_order(trade)
# assert log_has_re(r"Found previously unknown order .*", caplog)
# Update trade state is called three times, once for every order
assert mock_uts.call_count == 4
assert mock_fo.call_count == 1
trade = Trade.session.scalars(select(Trade)).first()
assert len(trade.orders) == 4
assert trade.is_open is True
assert trade.exit_reason is None
assert trade.amount == 5.0
def test_get_valid_price(mocker, default_conf_usdt) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)

View File

@ -121,6 +121,8 @@ def test_safe_value_fallback():
assert safe_value_fallback(dict1, 'keyNo', 'keyNo') is None
assert safe_value_fallback(dict1, 'keyNo', 'keyNo', 55) == 55
assert safe_value_fallback(dict1, 'keyNo', default_value=55) == 55
assert safe_value_fallback(dict1, 'keyNo', None, default_value=55) == 55
def test_safe_value_fallback2():