Merge branch 'develop' into feat/freqai
This commit is contained in:
commit
3273881282
@ -15,9 +15,9 @@ repos:
|
||||
additional_dependencies:
|
||||
- types-cachetools==5.2.1
|
||||
- types-filelock==3.2.7
|
||||
- types-requests==2.28.1
|
||||
- types-requests==2.28.3
|
||||
- types-tabulate==0.8.11
|
||||
- types-python-dateutil==2.8.18
|
||||
- types-python-dateutil==2.8.19
|
||||
# stages: [push]
|
||||
|
||||
- repo: https://github.com/pycqa/isort
|
||||
|
@ -50,6 +50,8 @@ This applies across all pairs, unless `only_per_pair` is set to true, which will
|
||||
|
||||
Similarly, this protection will by default look at all trades (long and short). For futures bots, setting `only_per_side` will make the bot only consider one side, and will then only lock this one side, allowing for example shorts to continue after a series of long stoplosses.
|
||||
|
||||
`required_profit` will determine the required relative profit (or loss) for stoplosses to consider. This should normally not be set and defaults to 0.0 - which means all losing stoplosses will be triggering a block.
|
||||
|
||||
The below example stops trading for all pairs for 4 candles after the last trade if the bot hit stoploss 4 times within the last 24 candles.
|
||||
|
||||
``` python
|
||||
@ -61,6 +63,7 @@ def protections(self):
|
||||
"lookback_period_candles": 24,
|
||||
"trade_limit": 4,
|
||||
"stop_duration_candles": 4,
|
||||
"required_profit": 0.0,
|
||||
"only_per_pair": False,
|
||||
"only_per_side": False
|
||||
}
|
||||
|
@ -1,5 +1,5 @@
|
||||
markdown==3.4.1
|
||||
mkdocs==1.3.0
|
||||
markdown==3.3.7
|
||||
mkdocs==1.3.1
|
||||
mkdocs-material==8.3.9
|
||||
mdx_truly_sane_lists==1.3
|
||||
pymdown-extensions==9.5
|
||||
|
@ -1264,7 +1264,7 @@ class Exchange:
|
||||
return False
|
||||
|
||||
required = ('fee', 'status', 'amount')
|
||||
return all(k in corder for k in required)
|
||||
return all(corder.get(k, None) is not None for k in required)
|
||||
|
||||
def cancel_order_with_result(self, order_id: str, pair: str, amount: float) -> Dict:
|
||||
"""
|
||||
|
@ -23,13 +23,14 @@ class StoplossGuard(IProtection):
|
||||
self._trade_limit = protection_config.get('trade_limit', 10)
|
||||
self._disable_global_stop = protection_config.get('only_per_pair', False)
|
||||
self._only_per_side = protection_config.get('only_per_side', False)
|
||||
self._profit_limit = protection_config.get('required_profit', 0.0)
|
||||
|
||||
def short_desc(self) -> str:
|
||||
"""
|
||||
Short method description - used for startup-messages
|
||||
"""
|
||||
return (f"{self.name} - Frequent Stoploss Guard, {self._trade_limit} stoplosses "
|
||||
f"within {self.lookback_period_str}.")
|
||||
f"with profit < {self._profit_limit:.2%} within {self.lookback_period_str}.")
|
||||
|
||||
def _reason(self) -> str:
|
||||
"""
|
||||
@ -49,7 +50,7 @@ class StoplossGuard(IProtection):
|
||||
trades = [trade for trade in trades1 if (str(trade.exit_reason) in (
|
||||
ExitType.TRAILING_STOP_LOSS.value, ExitType.STOP_LOSS.value,
|
||||
ExitType.STOPLOSS_ON_EXCHANGE.value)
|
||||
and trade.close_profit and trade.close_profit < 0)]
|
||||
and trade.close_profit and trade.close_profit < self._profit_limit)]
|
||||
|
||||
if self._only_per_side:
|
||||
# Long or short trades only
|
||||
|
@ -8,7 +8,7 @@
|
||||
coveralls==3.3.1
|
||||
flake8==4.0.1
|
||||
flake8-tidy-imports==4.8.0
|
||||
mypy==0.961
|
||||
mypy==0.971
|
||||
pre-commit==2.20.0
|
||||
pytest==7.1.2
|
||||
pytest-asyncio==0.19.0
|
||||
@ -25,6 +25,6 @@ nbconvert==6.5.0
|
||||
# mypy types
|
||||
types-cachetools==5.2.1
|
||||
types-filelock==3.2.7
|
||||
types-requests==2.28.1
|
||||
types-requests==2.28.3
|
||||
types-tabulate==0.8.11
|
||||
types-python-dateutil==2.8.18
|
||||
types-python-dateutil==2.8.19
|
||||
|
@ -2,7 +2,7 @@ numpy==1.23.1
|
||||
pandas==1.4.3
|
||||
pandas-ta==0.3.14b
|
||||
|
||||
ccxt==1.90.89
|
||||
ccxt==1.91.29
|
||||
# Pin cryptography for now due to rust build errors with piwheels
|
||||
cryptography==37.0.4
|
||||
aiohttp==3.8.1
|
||||
@ -28,7 +28,7 @@ py_find_1st==1.1.5
|
||||
# Load ticker files 30% faster
|
||||
python-rapidjson==1.8
|
||||
# Properly format api responses
|
||||
orjson==3.7.7
|
||||
orjson==3.7.8
|
||||
|
||||
# Notify systemd
|
||||
sdnotify==0.3.2
|
||||
|
@ -2910,6 +2910,9 @@ def test_check_order_canceled_empty(mocker, default_conf, exchange_name, order,
|
||||
({'amount': 10.0, 'fee': {}}, False),
|
||||
({'result': 'testest123'}, False),
|
||||
('hello_world', False),
|
||||
({'status': 'canceled', 'amount': None, 'fee': None}, False),
|
||||
({'status': 'canceled', 'filled': None, 'amount': None, 'fee': None}, False),
|
||||
|
||||
])
|
||||
def test_is_cancel_order_result_suitable(mocker, default_conf, exchange_name, order, result):
|
||||
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
|
||||
|
@ -424,7 +424,7 @@ def test_MaxDrawdown(mocker, default_conf, fee, caplog):
|
||||
@pytest.mark.parametrize("protectionconf,desc_expected,exception_expected", [
|
||||
({"method": "StoplossGuard", "lookback_period": 60, "trade_limit": 2, "stop_duration": 60},
|
||||
"[{'StoplossGuard': 'StoplossGuard - Frequent Stoploss Guard, "
|
||||
"2 stoplosses within 60 minutes.'}]",
|
||||
"2 stoplosses with profit < 0.00% within 60 minutes.'}]",
|
||||
None
|
||||
),
|
||||
({"method": "CooldownPeriod", "stop_duration": 60},
|
||||
@ -442,9 +442,9 @@ def test_MaxDrawdown(mocker, default_conf, fee, caplog):
|
||||
None
|
||||
),
|
||||
({"method": "StoplossGuard", "lookback_period_candles": 12, "trade_limit": 2,
|
||||
"stop_duration": 60},
|
||||
"required_profit": -0.05, "stop_duration": 60},
|
||||
"[{'StoplossGuard': 'StoplossGuard - Frequent Stoploss Guard, "
|
||||
"2 stoplosses within 12 candles.'}]",
|
||||
"2 stoplosses with profit < -5.00% within 12 candles.'}]",
|
||||
None
|
||||
),
|
||||
({"method": "CooldownPeriod", "stop_duration_candles": 5},
|
||||
|
@ -1402,7 +1402,6 @@ def test_api_strategies(botclient):
|
||||
'InformativeDecoratorTest',
|
||||
'StrategyTestV2',
|
||||
'StrategyTestV3',
|
||||
'StrategyTestV3Analysis',
|
||||
'StrategyTestV3Futures',
|
||||
'freqai_test_multimodel_strat',
|
||||
'freqai_test_strat'
|
||||
|
@ -1,175 +0,0 @@
|
||||
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
|
||||
|
||||
import talib.abstract as ta
|
||||
from pandas import DataFrame
|
||||
|
||||
import freqtrade.vendor.qtpylib.indicators as qtpylib
|
||||
from freqtrade.strategy import (BooleanParameter, DecimalParameter, IntParameter, IStrategy,
|
||||
RealParameter)
|
||||
|
||||
|
||||
class StrategyTestV3Analysis(IStrategy):
|
||||
"""
|
||||
Strategy used by tests freqtrade bot.
|
||||
Please do not modify this strategy, it's intended for internal use only.
|
||||
Please look at the SampleStrategy in the user_data/strategy directory
|
||||
or strategy repository https://github.com/freqtrade/freqtrade-strategies
|
||||
for samples and inspiration.
|
||||
"""
|
||||
INTERFACE_VERSION = 3
|
||||
|
||||
# Minimal ROI designed for the strategy
|
||||
minimal_roi = {
|
||||
"40": 0.0,
|
||||
"30": 0.01,
|
||||
"20": 0.02,
|
||||
"0": 0.04
|
||||
}
|
||||
|
||||
# Optimal stoploss designed for the strategy
|
||||
stoploss = -0.10
|
||||
|
||||
# Optimal timeframe for the strategy
|
||||
timeframe = '5m'
|
||||
|
||||
# Optional order type mapping
|
||||
order_types = {
|
||||
'entry': 'limit',
|
||||
'exit': 'limit',
|
||||
'stoploss': 'limit',
|
||||
'stoploss_on_exchange': False
|
||||
}
|
||||
|
||||
# Number of candles the strategy requires before producing valid signals
|
||||
startup_candle_count: int = 20
|
||||
|
||||
# Optional time in force for orders
|
||||
order_time_in_force = {
|
||||
'entry': 'gtc',
|
||||
'exit': 'gtc',
|
||||
}
|
||||
|
||||
buy_params = {
|
||||
'buy_rsi': 35,
|
||||
# Intentionally not specified, so "default" is tested
|
||||
# 'buy_plusdi': 0.4
|
||||
}
|
||||
|
||||
sell_params = {
|
||||
'sell_rsi': 74,
|
||||
'sell_minusdi': 0.4
|
||||
}
|
||||
|
||||
buy_rsi = IntParameter([0, 50], default=30, space='buy')
|
||||
buy_plusdi = RealParameter(low=0, high=1, default=0.5, space='buy')
|
||||
sell_rsi = IntParameter(low=50, high=100, default=70, space='sell')
|
||||
sell_minusdi = DecimalParameter(low=0, high=1, default=0.5001, decimals=3, space='sell',
|
||||
load=False)
|
||||
protection_enabled = BooleanParameter(default=True)
|
||||
protection_cooldown_lookback = IntParameter([0, 50], default=30)
|
||||
|
||||
# TODO: Can this work with protection tests? (replace HyperoptableStrategy implicitly ... )
|
||||
# @property
|
||||
# def protections(self):
|
||||
# prot = []
|
||||
# if self.protection_enabled.value:
|
||||
# prot.append({
|
||||
# "method": "CooldownPeriod",
|
||||
# "stop_duration_candles": self.protection_cooldown_lookback.value
|
||||
# })
|
||||
# return prot
|
||||
|
||||
bot_started = False
|
||||
|
||||
def bot_start(self):
|
||||
self.bot_started = True
|
||||
|
||||
def informative_pairs(self):
|
||||
|
||||
return []
|
||||
|
||||
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
|
||||
# Momentum Indicator
|
||||
# ------------------------------------
|
||||
|
||||
# ADX
|
||||
dataframe['adx'] = ta.ADX(dataframe)
|
||||
|
||||
# MACD
|
||||
macd = ta.MACD(dataframe)
|
||||
dataframe['macd'] = macd['macd']
|
||||
dataframe['macdsignal'] = macd['macdsignal']
|
||||
dataframe['macdhist'] = macd['macdhist']
|
||||
|
||||
# Minus Directional Indicator / Movement
|
||||
dataframe['minus_di'] = ta.MINUS_DI(dataframe)
|
||||
|
||||
# Plus Directional Indicator / Movement
|
||||
dataframe['plus_di'] = ta.PLUS_DI(dataframe)
|
||||
|
||||
# RSI
|
||||
dataframe['rsi'] = ta.RSI(dataframe)
|
||||
|
||||
# Stoch fast
|
||||
stoch_fast = ta.STOCHF(dataframe)
|
||||
dataframe['fastd'] = stoch_fast['fastd']
|
||||
dataframe['fastk'] = stoch_fast['fastk']
|
||||
|
||||
# Bollinger bands
|
||||
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
|
||||
dataframe['bb_lowerband'] = bollinger['lower']
|
||||
dataframe['bb_middleband'] = bollinger['mid']
|
||||
dataframe['bb_upperband'] = bollinger['upper']
|
||||
|
||||
# EMA - Exponential Moving Average
|
||||
dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
|
||||
|
||||
return dataframe
|
||||
|
||||
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
|
||||
dataframe.loc[
|
||||
(
|
||||
(dataframe['rsi'] < self.buy_rsi.value) &
|
||||
(dataframe['fastd'] < 35) &
|
||||
(dataframe['adx'] > 30) &
|
||||
(dataframe['plus_di'] > self.buy_plusdi.value)
|
||||
) |
|
||||
(
|
||||
(dataframe['adx'] > 65) &
|
||||
(dataframe['plus_di'] > self.buy_plusdi.value)
|
||||
),
|
||||
['enter_long', 'enter_tag']] = 1, 'enter_tag_long'
|
||||
|
||||
dataframe.loc[
|
||||
(
|
||||
qtpylib.crossed_below(dataframe['rsi'], self.sell_rsi.value)
|
||||
),
|
||||
['enter_short', 'enter_tag']] = 1, 'enter_tag_short'
|
||||
|
||||
return dataframe
|
||||
|
||||
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
dataframe.loc[
|
||||
(
|
||||
(
|
||||
(qtpylib.crossed_above(dataframe['rsi'], self.sell_rsi.value)) |
|
||||
(qtpylib.crossed_above(dataframe['fastd'], 70))
|
||||
) &
|
||||
(dataframe['adx'] > 10) &
|
||||
(dataframe['minus_di'] > 0)
|
||||
) |
|
||||
(
|
||||
(dataframe['adx'] > 70) &
|
||||
(dataframe['minus_di'] > self.sell_minusdi.value)
|
||||
),
|
||||
['exit_long', 'exit_tag']] = 1, 'exit_tag_long'
|
||||
|
||||
dataframe.loc[
|
||||
(
|
||||
qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value)
|
||||
),
|
||||
['exit_long', 'exit_tag']] = 1, 'exit_tag_short'
|
||||
|
||||
return dataframe
|
@ -34,7 +34,7 @@ def test_search_all_strategies_no_failed():
|
||||
directory = Path(__file__).parent / "strats"
|
||||
strategies = StrategyResolver.search_all_objects(directory, enum_failed=False)
|
||||
assert isinstance(strategies, list)
|
||||
assert len(strategies) == 9
|
||||
assert len(strategies) == 8
|
||||
assert isinstance(strategies[0], dict)
|
||||
|
||||
|
||||
@ -42,10 +42,10 @@ def test_search_all_strategies_with_failed():
|
||||
directory = Path(__file__).parent / "strats"
|
||||
strategies = StrategyResolver.search_all_objects(directory, enum_failed=True)
|
||||
assert isinstance(strategies, list)
|
||||
assert len(strategies) == 10
|
||||
assert len(strategies) == 9
|
||||
# with enum_failed=True search_all_objects() shall find 2 good strategies
|
||||
# and 1 which fails to load
|
||||
assert len([x for x in strategies if x['class'] is not None]) == 9
|
||||
assert len([x for x in strategies if x['class'] is not None]) == 8
|
||||
assert len([x for x in strategies if x['class'] is None]) == 1
|
||||
|
||||
|
||||
|
Loading…
Reference in New Issue
Block a user