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Revert "Merge branch 'plot_hyperopt_stats' into opt-ask-force-new-points"

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This reverts commit 4eb9cc6e8b, reversing
changes made to a3b401a762.
This commit is contained in:
Italo
2022-03-30 09:39:07 +01:00
parent 4eb9cc6e8b
commit 9f171193ef
15 changed files with 169 additions and 184 deletions
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30
tests/conftest.py
View File

@@ -1019,8 +1019,8 @@ def limit_buy_order_open():
'type': 'limit',
'side': 'buy',
'symbol': 'mocked',
'timestamp': arrow.utcnow().int_timestamp * 1000,
'datetime': arrow.utcnow().isoformat(),
'timestamp': arrow.utcnow().int_timestamp,
'price': 0.00001099,
'amount': 90.99181073,
'filled': 0.0,
@@ -1046,7 +1046,6 @@ def market_buy_order():
'type': 'market',
'side': 'buy',
'symbol': 'mocked',
'timestamp': arrow.utcnow().int_timestamp * 1000,
'datetime': arrow.utcnow().isoformat(),
'price': 0.00004099,
'amount': 91.99181073,
@@ -1063,7 +1062,6 @@ def market_sell_order():
'type': 'market',
'side': 'sell',
'symbol': 'mocked',
'timestamp': arrow.utcnow().int_timestamp * 1000,
'datetime': arrow.utcnow().isoformat(),
'price': 0.00004173,
'amount': 91.99181073,
@@ -1080,8 +1078,7 @@ def limit_buy_order_old():
'type': 'limit',
'side': 'buy',
'symbol': 'mocked',
'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp * 1000,
'datetime': str(arrow.utcnow().shift(minutes=-601).datetime),
'price': 0.00001099,
'amount': 90.99181073,
'filled': 0.0,
@@ -1097,7 +1094,6 @@ def limit_sell_order_old():
'type': 'limit',
'side': 'sell',
'symbol': 'ETH/BTC',
'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp * 1000,
'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
'price': 0.00001099,
'amount': 90.99181073,
@@ -1114,7 +1110,6 @@ def limit_buy_order_old_partial():
'type': 'limit',
'side': 'buy',
'symbol': 'ETH/BTC',
'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp * 1000,
'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
'price': 0.00001099,
'amount': 90.99181073,
@@ -1144,7 +1139,7 @@ def limit_buy_order_canceled_empty(request):
'info': {},
'id': '1234512345',
'clientOrderId': None,
'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp * 1000,
'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp,
'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
'lastTradeTimestamp': None,
'symbol': 'LTC/USDT',
@@ -1165,7 +1160,7 @@ def limit_buy_order_canceled_empty(request):
'info': {},
'id': 'AZNPFF-4AC4N-7MKTAT',
'clientOrderId': None,
'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp * 1000,
'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp,
'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
'lastTradeTimestamp': None,
'status': 'canceled',
@@ -1186,7 +1181,7 @@ def limit_buy_order_canceled_empty(request):
'info': {},
'id': '1234512345',
'clientOrderId': 'alb1234123',
'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp * 1000,
'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp,
'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
'lastTradeTimestamp': None,
'symbol': 'LTC/USDT',
@@ -1207,7 +1202,7 @@ def limit_buy_order_canceled_empty(request):
'info': {},
'id': '1234512345',
'clientOrderId': 'alb1234123',
'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp * 1000,
'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp,
'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
'lastTradeTimestamp': None,
'symbol': 'LTC/USDT',
@@ -1233,7 +1228,7 @@ def limit_sell_order_open():
'side': 'sell',
'symbol': 'mocked',
'datetime': arrow.utcnow().isoformat(),
'timestamp': arrow.utcnow().int_timestamp * 1000,
'timestamp': arrow.utcnow().int_timestamp,
'price': 0.00001173,
'amount': 90.99181073,
'filled': 0.0,
@@ -1399,7 +1394,7 @@ def tickers():
'BLK/BTC': {
'symbol': 'BLK/BTC',
'timestamp': 1522014806072,
'datetime': '2018-03-25T21:53:26.072Z',
'datetime': '2018-03-25T21:53:26.720Z',
'high': 0.007745,
'low': 0.007512,
'bid': 0.007729,
@@ -1895,8 +1890,7 @@ def buy_order_fee():
'type': 'limit',
'side': 'buy',
'symbol': 'mocked',
'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp * 1000,
'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
'datetime': str(arrow.utcnow().shift(minutes=-601).datetime),
'price': 0.245441,
'amount': 8.0,
'cost': 1.963528,
@@ -2205,7 +2199,7 @@ def limit_buy_order_usdt_open():
'side': 'buy',
'symbol': 'mocked',
'datetime': arrow.utcnow().isoformat(),
'timestamp': arrow.utcnow().int_timestamp * 1000,
'timestamp': arrow.utcnow().int_timestamp,
'price': 2.00,
'amount': 30.0,
'filled': 0.0,
@@ -2232,7 +2226,7 @@ def limit_sell_order_usdt_open():
'side': 'sell',
'symbol': 'mocked',
'datetime': arrow.utcnow().isoformat(),
'timestamp': arrow.utcnow().int_timestamp * 1000,
'timestamp': arrow.utcnow().int_timestamp,
'price': 2.20,
'amount': 30.0,
'filled': 0.0,
@@ -2257,7 +2251,6 @@ def market_buy_order_usdt():
'type': 'market',
'side': 'buy',
'symbol': 'mocked',
'timestamp': arrow.utcnow().int_timestamp * 1000,
'datetime': arrow.utcnow().isoformat(),
'price': 2.00,
'amount': 30.0,
@@ -2314,7 +2307,6 @@ def market_sell_order_usdt():
'type': 'market',
'side': 'sell',
'symbol': 'mocked',
'timestamp': arrow.utcnow().int_timestamp * 1000,
'datetime': arrow.utcnow().isoformat(),
'price': 2.20,
'amount': 30.0,

2
tests/exchange/test_exchange.py
View File

@@ -1098,7 +1098,7 @@ def test_create_order(default_conf, mocker, side, ordertype, rate, marketprice,
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
order = exchange.create_order(
pair='ETH/BTC', ordertype=ordertype, side=side, amount=1, rate=rate)
pair='ETH/BTC', ordertype=ordertype, side=side, amount=1, rate=200)
assert 'id' in order
assert 'info' in order

88
tests/strategy/strats/hyperoptable_strategy.py
View File

@@ -1,13 +1,14 @@
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
import talib.abstract as ta
from pandas import DataFrame
from strategy_test_v2 import StrategyTestV2
import freqtrade.vendor.qtpylib.indicators as qtpylib
from freqtrade.strategy import BooleanParameter, DecimalParameter, IntParameter, RealParameter
from freqtrade.strategy import (BooleanParameter, DecimalParameter, IntParameter, IStrategy,
RealParameter)
class HyperoptableStrategy(StrategyTestV2):
class HyperoptableStrategy(IStrategy):
"""
Default Strategy provided by freqtrade bot.
Please do not modify this strategy, it's intended for internal use only.
@@ -15,6 +16,38 @@ class HyperoptableStrategy(StrategyTestV2):
or strategy repository https://github.com/freqtrade/freqtrade-strategies
for samples and inspiration.
"""
INTERFACE_VERSION = 2
# 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 ticker interval for the strategy
timeframe = '5m'
# Optional order type mapping
order_types = {
'buy': 'limit',
'sell': '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 = {
'buy': 'gtc',
'sell': 'gtc',
}
buy_params = {
'buy_rsi': 35,
@@ -58,6 +91,55 @@ class HyperoptableStrategy(StrategyTestV2):
"""
return []
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
Performance Note: For the best performance be frugal on the number of indicators
you are using. Let uncomment only the indicator you are using in your strategies
or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
:param dataframe: Dataframe with data from the exchange
:param metadata: Additional information, like the currently traded pair
:return: a Dataframe with all mandatory indicators for the strategies
"""
# 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_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe

2
tests/strategy/strats/strategy_test_v2.py
View File

@@ -7,7 +7,7 @@ from pandas import DataFrame
import freqtrade.vendor.qtpylib.indicators as qtpylib
from freqtrade.persistence import Trade
from freqtrade.strategy import IStrategy
from freqtrade.strategy.interface import IStrategy
class StrategyTestV2(IStrategy):