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Use market data to get base and quote currencies in @informative() decorator.

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This commit is contained in:
Rokas Kupstys 2021-11-22 09:27:33 +02:00
parent 280a0ec17e
commit 78a00f2518
4 changed files with 22 additions and 21 deletions
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2
freqtrade/optimize/backtesting.py
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@ -67,7 +67,7 @@ class Backtesting:
self.all_results: Dict[str, Dict] = {} self.all_results: Dict[str, Dict] = {}
self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config) self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config)
self.dataprovider = DataProvider(self.config, None) self.dataprovider = DataProvider(self.config, self.exchange)
if self.config.get('strategy_list', None): if self.config.get('strategy_list', None):
for strat in list(self.config['strategy_list']): for strat in list(self.config['strategy_list']):

11
freqtrade/strategy/informative_decorator.py
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@ -80,12 +80,11 @@ def _create_and_merge_informative_pair(strategy, dataframe: DataFrame, metadata:
# Not specifying an asset will define informative dataframe for current pair. # Not specifying an asset will define informative dataframe for current pair.
asset = metadata['pair'] asset = metadata['pair']
if '/' in asset: market = strategy.dp.market(asset)
base, quote = asset.split('/') if market is None:
else: raise OperationalException(f'Market {asset} is not available.')
# When futures are supported this may need reevaluation. base = market['base']
# base, quote = asset, '' quote = market['quote']
raise OperationalException('Not implemented.')
# Default format. This optimizes for the common case: informative pairs using same stake # Default format. This optimizes for the common case: informative pairs using same stake
# currency. When quote currency matches stake currency, column name will omit base currency. # currency. When quote currency matches stake currency, column name will omit base currency.

10
tests/strategy/strats/informative_decorator_strategy.py
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@ -20,7 +20,7 @@ class InformativeDecoratorTest(IStrategy):
startup_candle_count: int = 20 startup_candle_count: int = 20
def informative_pairs(self): def informative_pairs(self):
return [('BTC/USDT', '5m')] return [('NEO/USDT', '5m')]
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['buy'] = 0 dataframe['buy'] = 0
@ -38,8 +38,8 @@ class InformativeDecoratorTest(IStrategy):
return dataframe return dataframe
# Simple informative test. # Simple informative test.
@informative('1h', 'BTC/{stake}') @informative('1h', 'NEO/{stake}')
def populate_indicators_btc_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame: def populate_indicators_neo_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['rsi'] = 14 dataframe['rsi'] = 14
return dataframe return dataframe
@ -50,7 +50,7 @@ class InformativeDecoratorTest(IStrategy):
return dataframe return dataframe
# Formatting test. # Formatting test.
@informative('30m', 'BTC/{stake}', '{column}_{BASE}_{QUOTE}_{base}_{quote}_{asset}_{timeframe}') @informative('30m', 'NEO/{stake}', '{column}_{BASE}_{QUOTE}_{base}_{quote}_{asset}_{timeframe}')
def populate_indicators_btc_1h_2(self, dataframe: DataFrame, metadata: dict) -> DataFrame: def populate_indicators_btc_1h_2(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['rsi'] = 14 dataframe['rsi'] = 14
return dataframe return dataframe
@ -68,7 +68,7 @@ class InformativeDecoratorTest(IStrategy):
dataframe['rsi_less'] = dataframe['rsi'] < dataframe['rsi_1h'] dataframe['rsi_less'] = dataframe['rsi'] < dataframe['rsi_1h']
# Mixing manual informative pairs with decorators. # Mixing manual informative pairs with decorators.
informative = self.dp.get_pair_dataframe('BTC/USDT', '5m') informative = self.dp.get_pair_dataframe('NEO/USDT', '5m')
informative['rsi'] = 14 informative['rsi'] = 14
dataframe = merge_informative_pair(dataframe, informative, self.timeframe, '5m', ffill=True) dataframe = merge_informative_pair(dataframe, informative, self.timeframe, '5m', ffill=True)

20
tests/strategy/test_strategy_helpers.py
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@ -7,6 +7,7 @@ import pytest
from freqtrade.data.dataprovider import DataProvider from freqtrade.data.dataprovider import DataProvider
from freqtrade.strategy import (merge_informative_pair, stoploss_from_absolute, stoploss_from_open, from freqtrade.strategy import (merge_informative_pair, stoploss_from_absolute, stoploss_from_open,
timeframe_to_minutes) timeframe_to_minutes)
from tests.conftest import get_patched_exchange
def generate_test_data(timeframe: str, size: int, start: str = '2020-07-05'): def generate_test_data(timeframe: str, size: int, start: str = '2020-07-05'):
@ -155,9 +156,9 @@ def test_informative_decorator(mocker, default_conf):
('LTC/USDT', '5m'): test_data_5m, ('LTC/USDT', '5m'): test_data_5m,
('LTC/USDT', '30m'): test_data_30m, ('LTC/USDT', '30m'): test_data_30m,
('LTC/USDT', '1h'): test_data_1h, ('LTC/USDT', '1h'): test_data_1h,
('BTC/USDT', '30m'): test_data_30m, ('NEO/USDT', '30m'): test_data_30m,
('BTC/USDT', '5m'): test_data_5m, ('NEO/USDT', '5m'): test_data_5m,
('BTC/USDT', '1h'): test_data_1h, ('NEO/USDT', '1h'): test_data_1h,
('ETH/USDT', '1h'): test_data_1h, ('ETH/USDT', '1h'): test_data_1h,
('ETH/USDT', '30m'): test_data_30m, ('ETH/USDT', '30m'): test_data_30m,
('ETH/BTC', '1h'): test_data_1h, ('ETH/BTC', '1h'): test_data_1h,
@ -165,15 +166,16 @@ def test_informative_decorator(mocker, default_conf):
from .strats.informative_decorator_strategy import InformativeDecoratorTest from .strats.informative_decorator_strategy import InformativeDecoratorTest
default_conf['stake_currency'] = 'USDT' default_conf['stake_currency'] = 'USDT'
strategy = InformativeDecoratorTest(config=default_conf) strategy = InformativeDecoratorTest(config=default_conf)
strategy.dp = DataProvider({}, None, None) exchange = get_patched_exchange(mocker, default_conf)
strategy.dp = DataProvider({}, exchange, None)
mocker.patch.object(strategy.dp, 'current_whitelist', return_value=[ mocker.patch.object(strategy.dp, 'current_whitelist', return_value=[
'XRP/USDT', 'LTC/USDT', 'BTC/USDT' 'XRP/USDT', 'LTC/USDT', 'NEO/USDT'
]) ])
assert len(strategy._ft_informative) == 6 # Equal to number of decorators used assert len(strategy._ft_informative) == 6 # Equal to number of decorators used
informative_pairs = [('XRP/USDT', '1h'), ('LTC/USDT', '1h'), ('XRP/USDT', '30m'), informative_pairs = [('XRP/USDT', '1h'), ('LTC/USDT', '1h'), ('XRP/USDT', '30m'),
('LTC/USDT', '30m'), ('BTC/USDT', '1h'), ('BTC/USDT', '30m'), ('LTC/USDT', '30m'), ('NEO/USDT', '1h'), ('NEO/USDT', '30m'),
('BTC/USDT', '5m'), ('ETH/BTC', '1h'), ('ETH/USDT', '30m')] ('NEO/USDT', '5m'), ('ETH/BTC', '1h'), ('ETH/USDT', '30m')]
for inf_pair in informative_pairs: for inf_pair in informative_pairs:
assert inf_pair in strategy.gather_informative_pairs() assert inf_pair in strategy.gather_informative_pairs()
@ -186,8 +188,8 @@ def test_informative_decorator(mocker, default_conf):
{p: data[(p, strategy.timeframe)] for p in ('XRP/USDT', 'LTC/USDT')}) {p: data[(p, strategy.timeframe)] for p in ('XRP/USDT', 'LTC/USDT')})
expected_columns = [ expected_columns = [
'rsi_1h', 'rsi_30m', # Stacked informative decorators 'rsi_1h', 'rsi_30m', # Stacked informative decorators
'btc_usdt_rsi_1h', # BTC 1h informative 'neo_usdt_rsi_1h', # NEO 1h informative
'rsi_BTC_USDT_btc_usdt_BTC/USDT_30m', # Column formatting 'rsi_NEO_USDT_neo_usdt_NEO/USDT_30m', # Column formatting
'rsi_from_callable', # Custom column formatter 'rsi_from_callable', # Custom column formatter
'eth_btc_rsi_1h', # Quote currency not matching stake currency 'eth_btc_rsi_1h', # Quote currency not matching stake currency
'rsi', 'rsi_less', # Non-informative columns 'rsi', 'rsi_less', # Non-informative columns