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Merge branch 'feat/short' into pr/samgermain/5780

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Matthias 2021-11-23 19:01:07 +01:00
commit 51e54a666c
19 changed files with 50 additions and 46 deletions
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3
docs/configuration.md
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@ -204,9 +204,8 @@ There are several methods to configure how much of the stake currency the bot wi
#### Minimum trade stake
The minimum stake amount will depend on exchange and pair and is usually listed in the exchange support pages.
Assuming the minimum tradable amount for XRP/USD is 20 XRP (given by the exchange), and the price is 0.6$.
The minimum stake amount to buy this pair is, therefore, `20 * 0.6 ~= 12`.
Assuming the minimum tradable amount for XRP/USD is 20 XRP (given by the exchange), and the price is 0.6$, the minimum stake amount to buy this pair is `20 * 0.6 ~= 12`.
This exchange has also a limit on USD - where all orders must be > 10$ - which however does not apply in this case.
To guarantee safe execution, freqtrade will not allow buying with a stake-amount of 10.1$, instead, it'll make sure that there's enough space to place a stoploss below the pair (+ an offset, defined by `amount_reserve_percent`, which defaults to 5%).

2
docs/includes/pairlists.md
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@ -292,7 +292,7 @@ If the trading range over the last 10 days is <1% or >99%, remove the pair from
#### VolatilityFilter
Volatility is the degree of historical variation of a pairs over time, is is measured by the standard deviation of logarithmic daily returns. Returns are assumed to be normally distributed, although actual distribution might be different. In a normal distribution, 68% of observations fall within one standard deviation and 95% of observations fall within two standard deviations. Assuming a volatility of 0.05 means that the expected returns for 20 out of 30 days is expected to be less than 5% (one standard deviation). Volatility is a positive ratio of the expected deviation of return and can be greater than 1.00. Please refer to the wikipedia definition of [`volatility`](https://en.wikipedia.org/wiki/Volatility_(finance)).
Volatility is the degree of historical variation of a pairs over time, it is measured by the standard deviation of logarithmic daily returns. Returns are assumed to be normally distributed, although actual distribution might be different. In a normal distribution, 68% of observations fall within one standard deviation and 95% of observations fall within two standard deviations. Assuming a volatility of 0.05 means that the expected returns for 20 out of 30 days is expected to be less than 5% (one standard deviation). Volatility is a positive ratio of the expected deviation of return and can be greater than 1.00. Please refer to the wikipedia definition of [`volatility`](https://en.wikipedia.org/wiki/Volatility_(finance)).
This filter removes pairs if the average volatility over a `lookback_days` days is below `min_volatility` or above `max_volatility`. Since this is a filter that requires additional data, the results are cached for `refresh_period`.

6
freqtrade/exchange/binance.py
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@ -3,7 +3,7 @@ import json
import logging
from datetime import datetime
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
from typing import Dict, List, Optional, Tuple
import arrow
import ccxt
@ -119,10 +119,6 @@ class Binance(Exchange):
except ccxt.BaseError as e:
raise OperationalException(e) from e
def market_is_future(self, market: Dict[str, Any]) -> bool:
# TODO-lev: This should be unified in ccxt to "swap"...
return market.get('future', False) is True
@retrier
def fill_leverage_brackets(self):
"""

2
freqtrade/exchange/exchange.py
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@ -338,7 +338,7 @@ class Exchange:
return self.markets.get(pair, {}).get('base', '')
def market_is_future(self, market: Dict[str, Any]) -> bool:
return market.get('swap', False) is True
return market.get(self._ft_has["ccxt_futures_name"], False) is True
def market_is_spot(self, market: Dict[str, Any]) -> bool:
return market.get('spot', False) is True

7
freqtrade/exchange/ftx.py
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@ -20,7 +20,8 @@ class Ftx(Exchange):
_ft_has: Dict = {
"stoploss_on_exchange": True,
"ohlcv_candle_limit": 1500,
"mark_ohlcv_price": "index"
"mark_ohlcv_price": "index",
"ccxt_futures_name": "future"
}
_supported_trading_mode_collateral_pairs: List[Tuple[TradingMode, Collateral]] = [
@ -159,7 +160,3 @@ class Ftx(Exchange):
if order['type'] == 'stop':
return safe_value_fallback2(order, order, 'id_stop', 'id')
return order['id']
def market_is_future(self, market: Dict[str, Any]) -> bool:
# TODO-lev: This should be unified in ccxt to "swap"...
return market.get('future', False) is True

2
freqtrade/optimize/backtesting.py
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@ -70,7 +70,7 @@ class Backtesting:
self.all_results: Dict[str, Dict] = {}
self._exchange_name = self.config['exchange']['name']
self.exchange = ExchangeResolver.load_exchange(self._exchange_name, self.config)
self.dataprovider = DataProvider(self.config, None)
self.dataprovider = DataProvider(self.config, self.exchange)
if self.config.get('strategy_list', None):
for strat in list(self.config['strategy_list']):

1
freqtrade/rpc/api_server/api_schemas.py
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@ -144,6 +144,7 @@ class OrderTypes(BaseModel):
class ShowConfig(BaseModel):
version: str
api_version: float
dry_run: bool
trading_mode: str
short_allowed: bool

9
freqtrade/rpc/api_server/api_v1.py
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@ -26,6 +26,11 @@ from freqtrade.rpc.rpc import RPCException
logger = logging.getLogger(__name__)
# API version
# Pre-1.1, no version was provided
# Version increments should happen in "small" steps (1.1, 1.12, ...) unless big changes happen.
API_VERSION = 1.1
# Public API, requires no auth.
router_public = APIRouter()
# Private API, protected by authentication
@ -117,7 +122,9 @@ def show_config(rpc: Optional[RPC] = Depends(get_rpc_optional), config=Depends(g
state = ''
if rpc:
state = rpc._freqtrade.state
return RPC._rpc_show_config(config, state)
resp = RPC._rpc_show_config(config, state)
resp['api_version'] = API_VERSION
return resp
@router.post('/forcebuy', response_model=ForceBuyResponse, tags=['trading'])

6
freqtrade/rpc/telegram.py
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@ -274,11 +274,11 @@ class Telegram(RPCHandler):
f"*Buy Tag:* `{msg['buy_tag']}`\n"
f"*Sell Reason:* `{msg['sell_reason']}`\n"
f"*Duration:* `{msg['duration']} ({msg['duration_min']:.1f} min)`\n"
f"*Amount:* `{msg['amount']:.8f}`\n")
f"*Amount:* `{msg['amount']:.8f}`\n"
f"*Open Rate:* `{msg['open_rate']:.8f}`\n")
if msg['type'] == RPCMessageType.SELL:
message += (f"*Open Rate:* `{msg['open_rate']:.8f}`\n"
f"*Current Rate:* `{msg['current_rate']:.8f}`\n"
message += (f"*Current Rate:* `{msg['current_rate']:.8f}`\n"
f"*Close Rate:* `{msg['limit']:.8f}`")
elif msg['type'] == RPCMessageType.SELL_FILL:

11
freqtrade/strategy/informative_decorator.py
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@ -81,12 +81,11 @@ def _create_and_merge_informative_pair(strategy, dataframe: DataFrame, metadata:
# Not specifying an asset will define informative dataframe for current pair.
asset = metadata['pair']
if '/' in asset:
base, quote = asset.split('/')
else:
# When futures are supported this may need reevaluation.
# base, quote = asset, ''
raise OperationalException('Not implemented.')
market = strategy.dp.market(asset)
if market is None:
raise OperationalException(f'Market {asset} is not available.')
base = market['base']
quote = market['quote']
# 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.

2
requirements-dev.txt
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@ -20,7 +20,7 @@ time-machine==2.4.0
nbconvert==6.3.0
# mypy types
types-cachetools==4.2.4
types-cachetools==4.2.5
types-filelock==3.2.1
types-requests==2.26.0
types-tabulate==0.8.3

2
requirements-hyperopt.txt
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@ -5,7 +5,7 @@
scipy==1.7.2
scikit-learn==1.0.1
scikit-optimize==0.9.0
filelock==3.3.2
filelock==3.4.0
joblib==1.1.0
psutil==5.8.0
progressbar2==3.55.0

2
requirements-plot.txt
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@ -1,5 +1,5 @@
# Include all requirements to run the bot.
-r requirements.txt
plotly==5.3.1
plotly==5.4.0

6
requirements.txt
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@ -2,10 +2,10 @@ numpy==1.21.4
pandas==1.3.4
pandas-ta==0.3.14b
ccxt==1.61.24
ccxt==1.61.92
# Pin cryptography for now due to rust build errors with piwheels
cryptography==35.0.0
aiohttp==3.7.4.post0
cryptography==36.0.0
aiohttp==3.8.1
SQLAlchemy==1.4.27
python-telegram-bot==13.8.1
arrow==1.2.1

2
tests/exchange/test_exchange.py
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@ -3329,7 +3329,7 @@ def test_validate_trading_mode_and_collateral(
("bibox", "margin", {"has": {"fetchCurrencies": False}, "options": {"defaultType": "margin"}}),
("bibox", "futures", {"has": {"fetchCurrencies": False}, "options": {"defaultType": "swap"}}),
("bybit", "futures", {"options": {"defaultType": "linear"}}),
("ftx", "futures", {"options": {"defaultType": "swap"}}),
("ftx", "futures", {"options": {"defaultType": "future"}}),
("gateio", "futures", {"options": {"defaultType": "swap"}}),
("hitbtc", "futures", {"options": {"defaultType": "swap"}}),
("kraken", "futures", {"options": {"defaultType": "swap"}}),

2
tests/rpc/test_rpc_apiserver.py
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@ -541,6 +541,8 @@ def test_api_show_config(botclient):
assert 'ask_strategy' in response
assert 'unfilledtimeout' in response
assert 'version' in response
assert 'api_version' in response
assert 1.1 <= response['api_version'] <= 1.2
def test_api_daily(botclient, mocker, ticker, fee, markets):

1
tests/rpc/test_rpc_telegram.py
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@ -1847,6 +1847,7 @@ def test_send_msg_sell_fill_notification(default_conf, mocker) -> None:
'*Sell Reason:* `stop_loss`\n'
'*Duration:* `1 day, 2:30:00 (1590.0 min)`\n'
'*Amount:* `1333.33333333`\n'
'*Open Rate:* `0.00007500`\n'
'*Close Rate:* `0.00003201`'
)

10
tests/strategy/strats/informative_decorator_strategy.py
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@ -19,7 +19,7 @@ class InformativeDecoratorTest(IStrategy):
startup_candle_count: int = 20
def informative_pairs(self):
return [('BTC/USDT', '5m', '')]
return [('NEO/USDT', '5m', '')]
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['buy'] = 0
@ -37,8 +37,8 @@ class InformativeDecoratorTest(IStrategy):
return dataframe
# Simple informative test.
@informative('1h', 'BTC/{stake}')
def populate_indicators_btc_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
@informative('1h', 'NEO/{stake}')
def populate_indicators_neo_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['rsi'] = 14
return dataframe
@ -49,7 +49,7 @@ class InformativeDecoratorTest(IStrategy):
return dataframe
# 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:
dataframe['rsi'] = 14
return dataframe
@ -67,7 +67,7 @@ class InformativeDecoratorTest(IStrategy):
dataframe['rsi_less'] = dataframe['rsi'] < dataframe['rsi_1h']
# 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
dataframe = merge_informative_pair(dataframe, informative, self.timeframe, '5m', ffill=True)

20
tests/strategy/test_strategy_helpers.py
View File

@ -7,6 +7,7 @@ import pytest
from freqtrade.data.dataprovider import DataProvider
from freqtrade.strategy import (merge_informative_pair, stoploss_from_absolute, stoploss_from_open,
timeframe_to_minutes)
from tests.conftest import get_patched_exchange
def generate_test_data(timeframe: str, size: int, start: str = '2020-07-05'):
@ -156,9 +157,9 @@ def test_informative_decorator(mocker, default_conf):
('LTC/USDT', '5m', ''): test_data_5m,
('LTC/USDT', '30m', ''): test_data_30m,
('LTC/USDT', '1h', ''): test_data_1h,
('BTC/USDT', '30m', ''): test_data_30m,
('BTC/USDT', '5m', ''): test_data_5m,
('BTC/USDT', '1h', ''): test_data_1h,
('NEO/USDT', '30m', ''): test_data_30m,
('NEO/USDT', '5m', ''): test_data_5m,
('NEO/USDT', '1h', ''): test_data_1h,
('ETH/USDT', '1h', ''): test_data_1h,
('ETH/USDT', '30m', ''): test_data_30m,
('ETH/BTC', '1h', ''): test_data_1h,
@ -166,15 +167,16 @@ def test_informative_decorator(mocker, default_conf):
from .strats.informative_decorator_strategy import InformativeDecoratorTest
default_conf['stake_currency'] = 'USDT'
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=[
'XRP/USDT', 'LTC/USDT', 'BTC/USDT'
'XRP/USDT', 'LTC/USDT', 'NEO/USDT'
])
assert len(strategy._ft_informative) == 6 # Equal to number of decorators used
informative_pairs = [('XRP/USDT', '1h', ''), ('LTC/USDT', '1h', ''), ('XRP/USDT', '30m', ''),
('LTC/USDT', '30m', ''), ('BTC/USDT', '1h', ''), ('BTC/USDT', '30m', ''),
('BTC/USDT', '5m', ''), ('ETH/BTC', '1h', ''), ('ETH/USDT', '30m', '')]
('LTC/USDT', '30m', ''), ('NEO/USDT', '1h', ''), ('NEO/USDT', '30m', ''),
('NEO/USDT', '5m', ''), ('ETH/BTC', '1h', ''), ('ETH/USDT', '30m', '')]
for inf_pair in informative_pairs:
assert inf_pair in strategy.gather_informative_pairs()
@ -187,8 +189,8 @@ def test_informative_decorator(mocker, default_conf):
{p: data[(p, strategy.timeframe, '')] for p in ('XRP/USDT', 'LTC/USDT')})
expected_columns = [
'rsi_1h', 'rsi_30m', # Stacked informative decorators
'btc_usdt_rsi_1h', # BTC 1h informative
'rsi_BTC_USDT_btc_usdt_BTC/USDT_30m', # Column formatting
'neo_usdt_rsi_1h', # NEO 1h informative
'rsi_NEO_USDT_neo_usdt_NEO/USDT_30m', # Column formatting
'rsi_from_callable', # Custom column formatter
'eth_btc_rsi_1h', # Quote currency not matching stake currency
'rsi', 'rsi_less', # Non-informative columns