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Merge branch 'freqtrade:develop' into plot_hyperopt_stats

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2
docs/requirements-docs.txt
View File

@ -1,4 +1,4 @@
mkdocs==1.2.3
mkdocs-material==8.1.7
mkdocs-material==8.1.8
mdx_truly_sane_lists==1.2
pymdown-extensions==9.1

29
docs/strategy-callbacks.md
View File

@ -362,8 +362,8 @@ class AwesomeStrategy(IStrategy):
# ... populate_* methods
def custom_entry_price(self, pair: str, current_time: datetime,
proposed_rate, **kwargs) -> float:
def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
entry_tag: Optional[str], **kwargs) -> float:
dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
timeframe=self.timeframe)
@ -413,7 +413,7 @@ It applies a tight timeout for higher priced assets, while allowing more time to
The function must return either `True` (cancel order) or `False` (keep order alive).
``` python
from datetime import datetime, timedelta, timezone
from datetime import datetime, timedelta
from freqtrade.persistence import Trade
class AwesomeStrategy(IStrategy):
@ -426,22 +426,24 @@ class AwesomeStrategy(IStrategy):
'sell': 60 * 25
}
def check_buy_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -> bool:
if trade.open_rate > 100 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=5):
def check_buy_timeout(self, pair: str, trade: 'Trade', order: dict,
current_time: datetime, **kwargs) -> bool:
if trade.open_rate > 100 and trade.open_date_utc < current_time - timedelta(minutes=5):
return True
elif trade.open_rate > 10 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=3):
elif trade.open_rate > 10 and trade.open_date_utc < current_time - timedelta(minutes=3):
return True
elif trade.open_rate < 1 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(hours=24):
elif trade.open_rate < 1 and trade.open_date_utc < current_time - timedelta(hours=24):
return True
return False
def check_sell_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -> bool:
if trade.open_rate > 100 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=5):
def check_sell_timeout(self, pair: str, trade: Trade, order: dict,
current_time: datetime, **kwargs) -> bool:
if trade.open_rate > 100 and trade.open_date_utc < current_time - timedelta(minutes=5):
return True
elif trade.open_rate > 10 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=3):
elif trade.open_rate > 10 and trade.open_date_utc < current_time - timedelta(minutes=3):
return True
elif trade.open_rate < 1 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(hours=24):
elif trade.open_rate < 1 and trade.open_date_utc < current_time - timedelta(hours=24):
return True
return False
```
@ -500,7 +502,8 @@ class AwesomeStrategy(IStrategy):
# ... populate_* methods
def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
time_in_force: str, current_time: datetime, **kwargs) -> bool:
time_in_force: str, current_time: datetime, entry_tag: Optional[str],
**kwargs) -> bool:
"""
Called right before placing a buy order.
Timing for this function is critical, so avoid doing heavy computations or
@ -618,7 +621,7 @@ class DigDeeperStrategy(IStrategy):
# This is called when placing the initial order (opening trade)
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
proposed_stake: float, min_stake: float, max_stake: float,
**kwargs) -> float:
entry_tag: Optional[str], **kwargs) -> float:
# We need to leave most of the funds for possible further DCA orders
# This also applies to fixed stakes

2
freqtrade/exchange/exchange.py
View File

@ -614,7 +614,7 @@ class Exchange:
'side': side,
'filled': 0,
'remaining': _amount,
'datetime': arrow.utcnow().isoformat(),
'datetime': arrow.utcnow().strftime('%Y-%m-%dT%H:%M:%S.%fZ'),
'timestamp': arrow.utcnow().int_timestamp * 1000,
'status': "closed" if ordertype == "market" else "open",
'fee': None,

42
freqtrade/freqtradebot.py
View File

@ -9,8 +9,6 @@ from math import isclose
from threading import Lock
from typing import Any, Dict, List, Optional, Tuple
import arrow
from freqtrade import __version__, constants
from freqtrade.configuration import validate_config_consistency
from freqtrade.data.converter import order_book_to_dataframe
@ -533,7 +531,7 @@ class FreqtradeBot(LoggingMixin):
pos_adjust = trade is not None
enter_limit_requested, stake_amount = self.get_valid_enter_price_and_stake(
pair, price, stake_amount, trade)
pair, price, stake_amount, buy_tag, trade)
if not stake_amount:
return False
@ -552,7 +550,8 @@ class FreqtradeBot(LoggingMixin):
if not pos_adjust and not strategy_safe_wrapper(
self.strategy.confirm_trade_entry, default_retval=True)(
pair=pair, order_type=order_type, amount=amount, rate=enter_limit_requested,
time_in_force=time_in_force, current_time=datetime.now(timezone.utc)):
time_in_force=time_in_force, current_time=datetime.now(timezone.utc),
entry_tag=buy_tag):
logger.info(f"User requested abortion of buying {pair}")
return False
amount = self.exchange.amount_to_precision(pair, amount)
@ -662,6 +661,7 @@ class FreqtradeBot(LoggingMixin):
def get_valid_enter_price_and_stake(
self, pair: str, price: Optional[float], stake_amount: float,
entry_tag: Optional[str],
trade: Optional[Trade]) -> Tuple[float, float]:
if price:
enter_limit_requested = price
@ -671,7 +671,7 @@ class FreqtradeBot(LoggingMixin):
custom_entry_price = strategy_safe_wrapper(self.strategy.custom_entry_price,
default_retval=proposed_enter_rate)(
pair=pair, current_time=datetime.now(timezone.utc),
proposed_rate=proposed_enter_rate)
proposed_rate=proposed_enter_rate, entry_tag=entry_tag)
enter_limit_requested = self.get_valid_price(custom_entry_price, proposed_enter_rate)
if not enter_limit_requested:
@ -684,7 +684,7 @@ class FreqtradeBot(LoggingMixin):
default_retval=stake_amount)(
pair=pair, current_time=datetime.now(timezone.utc),
current_rate=enter_limit_requested, proposed_stake=stake_amount,
min_stake=min_stake_amount, max_stake=max_stake_amount)
min_stake=min_stake_amount, max_stake=max_stake_amount, entry_tag=entry_tag)
stake_amount = self.wallets.validate_stake_amount(pair, stake_amount, min_stake_amount)
return enter_limit_requested, stake_amount
@ -959,20 +959,6 @@ class FreqtradeBot(LoggingMixin):
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_unit = self.config.get('unfilledtimeout', {}).get('unit', 'minutes')
timeout_kwargs = {timeout_unit: -timeout}
timeout_threshold = arrow.utcnow().shift(**timeout_kwargs).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 necessary
@ -993,20 +979,16 @@ class FreqtradeBot(LoggingMixin):
if (order['side'] == 'buy' and (order['status'] == 'open' or fully_cancelled) and (
fully_cancelled
or self._check_timed_out('buy', order)
or strategy_safe_wrapper(self.strategy.check_buy_timeout,
default_retval=False)(pair=trade.pair,
trade=trade,
order=order))):
or self.strategy.ft_check_timed_out(
'buy', trade, order, datetime.now(timezone.utc))
)):
self.handle_cancel_enter(trade, order, constants.CANCEL_REASON['TIMEOUT'])
elif (order['side'] == 'sell' and (order['status'] == 'open' or fully_cancelled) and (
fully_cancelled
or self._check_timed_out('sell', order)
or strategy_safe_wrapper(self.strategy.check_sell_timeout,
default_retval=False)(pair=trade.pair,
trade=trade,
order=order))):
or self.strategy.ft_check_timed_out(
'sell', trade, order, datetime.now(timezone.utc)))
):
self.handle_cancel_exit(trade, order, constants.CANCEL_REASON['TIMEOUT'])
canceled_count = trade.get_exit_order_count()
max_timeouts = self.config.get('unfilledtimeout', {}).get('exit_timeout_count', 0)

22
freqtrade/optimize/backtesting.py
View File

@ -463,11 +463,13 @@ class Backtesting:
def _enter_trade(self, pair: str, row: Tuple, stake_amount: Optional[float] = None,
trade: Optional[LocalTrade] = None) -> Optional[LocalTrade]:
current_time = row[DATE_IDX].to_pydatetime()
entry_tag = row[BUY_TAG_IDX] if len(row) >= BUY_TAG_IDX + 1 else None
# 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
pair=pair, current_time=current_time,
proposed_rate=row[OPEN_IDX], entry_tag=entry_tag) # 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])
@ -484,8 +486,9 @@ class Backtesting:
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)
pair=pair, current_time=current_time, current_rate=propose_rate,
proposed_stake=stake_amount, min_stake=min_stake_amount, max_stake=max_stake_amount,
entry_tag=entry_tag)
stake_amount = self.wallets.validate_stake_amount(pair, stake_amount, min_stake_amount)
@ -500,24 +503,24 @@ class Backtesting:
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()):
time_in_force=time_in_force, current_time=current_time,
entry_tag=entry_tag):
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(),
open_date=current_time,
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,
buy_tag=entry_tag,
exchange='backtesting',
orders=[]
)
@ -531,6 +534,9 @@ class Backtesting:
side="buy",
order_type="market",
status="closed",
order_date=current_time,
order_filled_date=current_time,
order_update_date=current_time,
price=propose_rate,
average=propose_rate,
amount=amount,

19
freqtrade/persistence/models.py
View File

@ -577,18 +577,19 @@ class LocalTrade():
total_amount = 0.0
total_stake = 0.0
for temp_order in self.orders:
if (temp_order.ft_is_open or
(temp_order.ft_order_side != 'buy') or
(temp_order.status not in NON_OPEN_EXCHANGE_STATES)):
for o in self.orders:
if (o.ft_is_open or
(o.ft_order_side != 'buy') or
(o.status not in NON_OPEN_EXCHANGE_STATES)):
continue
tmp_amount = temp_order.amount
if temp_order.filled is not None:
tmp_amount = temp_order.filled
if tmp_amount > 0.0 and temp_order.average is not None:
tmp_amount = o.amount
tmp_price = o.average or o.price
if o.filled is not None:
tmp_amount = o.filled
if tmp_amount > 0.0 and tmp_price is not None:
total_amount += tmp_amount
total_stake += temp_order.average * tmp_amount
total_stake += tmp_price * tmp_amount
if total_amount > 0:
self.open_rate = total_stake / total_amount

60
freqtrade/strategy/interface.py
View File

@ -188,7 +188,17 @@ class IStrategy(ABC, HyperStrategyMixin):
"""
return dataframe
def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
def bot_loop_start(self, **kwargs) -> None:
"""
Called at the start of the bot iteration (one loop).
Might be used to perform pair-independent tasks
(e.g. gather some remote resource for comparison)
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
"""
pass
def check_buy_timeout(self, pair: str, trade: Trade, order: dict,
current_time: datetime, **kwargs) -> bool:
"""
Check buy timeout function callback.
This method can be used to override the buy-timeout.
@ -201,12 +211,14 @@ class IStrategy(ABC, HyperStrategyMixin):
:param pair: Pair the trade is for
:param trade: trade object.
:param order: Order dictionary as returned from CCXT.
:param current_time: datetime object, containing the current datetime
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return bool: When True is returned, then the buy-order is cancelled.
"""
return False
def check_sell_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
def check_sell_timeout(self, pair: str, trade: Trade, order: dict,
current_time: datetime, **kwargs) -> bool:
"""
Check sell timeout function callback.
This method can be used to override the sell-timeout.
@ -219,22 +231,15 @@ class IStrategy(ABC, HyperStrategyMixin):
:param pair: Pair the trade is for
:param trade: trade object.
:param order: Order dictionary as returned from CCXT.
:param current_time: datetime object, containing the current datetime
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return bool: When True is returned, then the sell-order is cancelled.
"""
return False
def bot_loop_start(self, **kwargs) -> None:
"""
Called at the start of the bot iteration (one loop).
Might be used to perform pair-independent tasks
(e.g. gather some remote resource for comparison)
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
"""
pass
def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
time_in_force: str, current_time: datetime, **kwargs) -> bool:
time_in_force: str, current_time: datetime, entry_tag: Optional[str],
**kwargs) -> bool:
"""
Called right before placing a buy order.
Timing for this function is critical, so avoid doing heavy computations or
@ -250,6 +255,7 @@ class IStrategy(ABC, HyperStrategyMixin):
:param rate: Rate that's going to be used when using limit orders
:param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
:param current_time: datetime object, containing the current datetime
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return bool: When True is returned, then the buy-order is placed on the exchange.
False aborts the process
@ -307,7 +313,7 @@ class IStrategy(ABC, HyperStrategyMixin):
return self.stoploss
def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
**kwargs) -> float:
entry_tag: Optional[str], **kwargs) -> float:
"""
Custom entry price logic, returning the new entry price.
@ -318,6 +324,7 @@ class IStrategy(ABC, HyperStrategyMixin):
:param pair: Pair that's currently analyzed
:param current_time: datetime object, containing the current datetime
:param proposed_rate: Rate, calculated based on pricing settings in ask_strategy.
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: New entry price value if provided
"""
@ -369,7 +376,7 @@ class IStrategy(ABC, HyperStrategyMixin):
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
proposed_stake: float, min_stake: float, max_stake: float,
**kwargs) -> float:
entry_tag: Optional[str], **kwargs) -> float:
"""
Customize stake size for each new trade. This method is not called when edge module is
enabled.
@ -380,6 +387,7 @@ class IStrategy(ABC, HyperStrategyMixin):
:param proposed_stake: A stake amount proposed by the bot.
:param min_stake: Minimal stake size allowed by exchange.
:param max_stake: Balance available for trading.
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
:return: A stake size, which is between min_stake and max_stake.
"""
return proposed_stake
@ -390,6 +398,7 @@ class IStrategy(ABC, HyperStrategyMixin):
"""
Custom trade adjustment logic, returning the stake amount that a trade should be increased.
This means extra buy 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/
@ -852,6 +861,29 @@ class IStrategy(ABC, HyperStrategyMixin):
else:
return current_profit > roi
def ft_check_timed_out(self, side: str, trade: Trade, order: Dict,
current_time: datetime) -> bool:
"""
FT Internal method.
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_unit = self.config.get('unfilledtimeout', {}).get('unit', 'minutes')
timeout_kwargs = {timeout_unit: -timeout}
timeout_threshold = current_time + timedelta(**timeout_kwargs)
timedout = (order['status'] == 'open' and order['side'] == side
and ordertime < timeout_threshold)
if timedout:
return True
time_method = self.check_sell_timeout if order['side'] == 'sell' else self.check_buy_timeout
return strategy_safe_wrapper(time_method,
default_retval=False)(
pair=trade.pair, trade=trade, order=order,
current_time=current_time)
def advise_all_indicators(self, data: Dict[str, DataFrame]) -> Dict[str, DataFrame]:
"""
Populates indicators for given candle (OHLCV) data (for multiple pairs)

68
freqtrade/templates/subtemplates/strategy_methods_advanced.j2
View File

@ -12,9 +12,47 @@ def bot_loop_start(self, **kwargs) -> None:
"""
pass
def custom_entry_price(self, pair: str, current_time: 'datetime', proposed_rate: float,
entry_tag: 'Optional[str]', **kwargs) -> float:
"""
Custom entry price logic, returning the new entry price.
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
When not implemented by a strategy, returns None, orderbook is used to set entry price
:param pair: Pair that's currently analyzed
:param current_time: datetime object, containing the current datetime
:param proposed_rate: Rate, calculated based on pricing settings in ask_strategy.
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: New entry price value if provided
"""
return proposed_rate
def custom_exit_price(self, pair: str, trade: 'Trade',
current_time: 'datetime', proposed_rate: float,
current_profit: float, **kwargs) -> float:
"""
Custom exit price logic, returning the new exit price.
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
When not implemented by a strategy, returns None, orderbook is used to set exit price
:param pair: Pair that's currently analyzed
:param trade: trade object.
:param current_time: datetime object, containing the current datetime
:param proposed_rate: Rate, calculated based on pricing settings in ask_strategy.
:param current_profit: Current profit (as ratio), calculated based on current_rate.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: New exit price value if provided
"""
return proposed_rate
def custom_stake_amount(self, pair: str, current_time: 'datetime', current_rate: float,
proposed_stake: float, min_stake: float, max_stake: float,
**kwargs) -> float:
entry_tag: 'Optional[str]', **kwargs) -> float:
"""
Customize stake size for each new trade. This method is not called when edge module is
enabled.
@ -25,6 +63,7 @@ def custom_stake_amount(self, pair: str, current_time: 'datetime', current_rate:
:param proposed_stake: A stake amount proposed by the bot.
:param min_stake: Minimal stake size allowed by exchange.
:param max_stake: Balance available for trading.
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
:return: A stake size, which is between min_stake and max_stake.
"""
return proposed_stake
@ -78,7 +117,8 @@ def custom_sell(self, pair: str, trade: 'Trade', current_time: 'datetime', curre
return None
def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
time_in_force: str, current_time: 'datetime', **kwargs) -> bool:
time_in_force: str, current_time: 'datetime', entry_tag: 'Optional[str]',
**kwargs) -> bool:
"""
Called right before placing a buy order.
Timing for this function is critical, so avoid doing heavy computations or
@ -94,6 +134,7 @@ def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: f
:param rate: Rate that's going to be used when using limit orders
:param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
:param current_time: datetime object, containing the current datetime
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return bool: When True is returned, then the buy-order is placed on the exchange.
False aborts the process
@ -167,3 +208,26 @@ def check_sell_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -
:return bool: When True is returned, then the sell-order is cancelled.
"""
return False
def adjust_trade_position(self, trade: 'Trade', current_time: 'datetime',
current_rate: float, current_profit: float, min_stake: float,
max_stake: float, **kwargs) -> 'Optional[float]':
"""
Custom trade adjustment logic, returning the stake amount that a trade should be increased.
This means extra buy 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/
When not implemented by a strategy, returns None
: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 min_stake: Minimal stake size allowed by exchange.
:param max_stake: Balance available for trading.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: Stake amount to adjust your trade
"""
return None

6
requirements-dev.txt
View File

@ -8,7 +8,7 @@ flake8==4.0.1
flake8-tidy-imports==4.6.0
mypy==0.931
pytest==6.2.5
pytest-asyncio==0.17.1
pytest-asyncio==0.17.2
pytest-cov==3.0.0
pytest-mock==3.6.1
pytest-random-order==1.0.4
@ -21,9 +21,9 @@ nbconvert==6.4.0
# mypy types
types-cachetools==4.2.9
types-filelock==3.2.4
types-filelock==3.2.5
types-requests==2.27.7
types-tabulate==0.8.5
# Extensions to datetime library
types-python-dateutil==2.8.7
types-python-dateutil==2.8.8

4
requirements.txt
View File

@ -7,7 +7,7 @@ ccxt==1.68.20
# Pin cryptography for now due to rust build errors with piwheels
cryptography==36.0.1
aiohttp==3.8.1
SQLAlchemy==1.4.29
SQLAlchemy==1.4.31
python-telegram-bot==13.10
arrow==1.2.1
cachetools==4.2.2
@ -32,7 +32,7 @@ python-rapidjson==1.5
sdnotify==0.3.2
# API Server
fastapi==0.72.0
fastapi==0.73.0
uvicorn==0.17.0
pyjwt==2.3.0
aiofiles==0.8.0

2
tests/optimize/test_backtesting.py
View File

@ -763,6 +763,8 @@ def test_backtest_pricecontours_protections(default_conf, fee, mocker, testdatad
# While buy-signals are unrealistic, running backtesting
# over and over again should not cause different results
for [contour, numres] in tests:
# Debug output for random test failure
print(f"{contour}, {numres}")
assert len(simple_backtest(default_conf, contour, mocker, testdatadir)['results']) == numres

2
tests/strategy/test_default_strategy.py
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@ -37,7 +37,7 @@ def test_strategy_test_v2(result, fee):
assert strategy.confirm_trade_entry(pair='ETH/BTC', order_type='limit', amount=0.1,
rate=20000, time_in_force='gtc',
current_time=datetime.utcnow()) is True
current_time=datetime.utcnow(), entry_tag=None) is True
assert strategy.confirm_trade_exit(pair='ETH/BTC', trade=trade, order_type='limit', amount=0.1,
rate=20000, time_in_force='gtc', sell_reason='roi',
current_time=datetime.utcnow()) is True

3
tests/test_integration.py
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@ -243,6 +243,8 @@ def test_dca_buying(default_conf_usdt, ticker_usdt, fee, mocker) -> None:
freqtrade.process()
trade = Trade.get_trades().first()
assert len(trade.orders) == 2
for o in trade.orders:
assert o.status == "closed"
assert trade.stake_amount == 120
# Open-rate averaged between 2.0 and 2.0 * 0.995
@ -258,7 +260,6 @@ def test_dca_buying(default_conf_usdt, ticker_usdt, fee, mocker) -> None:
assert trade.orders[1].amount == 60 / ticker_usdt_modif['bid']
assert trade.amount == trade.orders[0].amount + trade.orders[1].amount
assert trade.nr_of_successful_buys == 2
# Sell

27
tests/test_persistence.py
View File

@ -1661,6 +1661,33 @@ def test_recalc_trade_from_orders_ignores_bad_orders(fee):
assert trade.fee_open_cost == 2 * o1_fee_cost
assert trade.open_trade_value == 2 * o1_trade_val
assert trade.nr_of_successful_buys == 2
# Check with 1 order
order_noavg = Order(
ft_order_side='buy',
ft_pair=trade.pair,
ft_is_open=False,
status="closed",
symbol=trade.pair,
order_type="market",
side="buy",
price=o1_rate,
average=None,
filled=o1_amount,
remaining=0,
cost=o1_amount,
order_date=trade.open_date,
order_filled_date=trade.open_date,
)
trade.orders.append(order_noavg)
trade.recalc_trade_from_orders()
# Calling recalc with single initial order should not change anything
assert trade.amount == 3 * o1_amount
assert trade.stake_amount == 3 * o1_amount
assert trade.open_rate == o1_rate
assert trade.fee_open_cost == 3 * o1_fee_cost
assert trade.open_trade_value == 3 * o1_trade_val
assert trade.nr_of_successful_buys == 3
@pytest.mark.usefixtures("init_persistence")