Merge branch 'develop' of https://github.com/Bovhasselt/Tradingbotv1.1 into develop

This commit is contained in:
Bo van Hasselt 2021-02-23 15:26:10 +01:00
commit 535e7a41f2
7 changed files with 451 additions and 78 deletions

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@ -12,7 +12,7 @@ from freqtrade.commands.data_commands import (start_convert_data, start_download
start_list_data)
from freqtrade.commands.deploy_commands import (start_create_userdir, start_install_ui,
start_new_hyperopt, start_new_strategy)
from freqtrade.commands.automation_commands import start_build_hyperopt
from freqtrade.commands.automation_commands import (start_build_hyperopt, start_custom_hyperopt, start_extract_strategy)
from freqtrade.commands.hyperopt_commands import start_hyperopt_list, start_hyperopt_show
from freqtrade.commands.list_commands import (start_list_exchanges, start_list_hyperopts,
start_list_markets, start_list_strategies,

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@ -55,8 +55,13 @@ ARGS_BUILD_STRATEGY = ["user_data_dir", "strategy", "template"]
ARGS_BUILD_HYPEROPT = ["user_data_dir", "hyperopt", "template"]
# Automation
ARGS_BUILD_CUSTOM_HYPEROPT = ["buy_indicators", "sell_indicators", "hyperopt"]
ARGS_EXTRACT_STRATEGY = ["strategy", "extract_name"]
ARGS_BUILD_BUILD_HYPEROPT = ["strategy", "hyperopt"]
ARGS_CONVERT_DATA = ["pairs", "format_from", "format_to", "erase"]
ARGS_CONVERT_DATA_OHLCV = ARGS_CONVERT_DATA + ["timeframes"]
@ -175,7 +180,7 @@ class Arguments:
start_list_data, start_list_exchanges, start_list_hyperopts,
start_list_markets, start_list_strategies,
start_list_timeframes, start_new_config, start_new_hyperopt,
start_build_hyperopt,
start_build_hyperopt, start_custom_hyperopt, start_extract_strategy,
start_new_strategy, start_plot_dataframe, start_plot_profit,
start_show_trades, start_test_pairlist, start_trading)
@ -210,12 +215,24 @@ class Arguments:
build_hyperopt_cmd.set_defaults(func=start_new_hyperopt)
self._build_args(optionlist=ARGS_BUILD_HYPEROPT, parser=build_hyperopt_cmd)
# add build-hyperopt subcommand
build_custom_hyperopt_cmd = subparsers.add_parser('build-hyperopt',
# add custom-hyperopt subcommand
build_custom_hyperopt_cmd = subparsers.add_parser('custom-hyperopt',
help="Build a custom hyperopt")
build_custom_hyperopt_cmd.set_defaults(func=start_build_hyperopt)
build_custom_hyperopt_cmd.set_defaults(func=start_custom_hyperopt)
self._build_args(optionlist=ARGS_BUILD_CUSTOM_HYPEROPT, parser=build_custom_hyperopt_cmd)
# add extract-strategy subcommand
extract_strategy_cmd = subparsers.add_parser('extract-strategy',
help="Extract data dictionaries for custom-hyperopt from strategy")
extract_strategy_cmd.set_defaults(func=start_extract_strategy)
self._build_args(optionlist=ARGS_EXTRACT_STRATEGY, parser=extract_strategy_cmd)
# add build-hyperopt subcommand
build_extracted_hyperopt_cmd = subparsers.add_parser('build-hyperopt',
help="Create a hyperopt for a strategy")
build_extracted_hyperopt_cmd.set_defaults(func=start_build_hyperopt)
self._build_args(optionlist=ARGS_BUILD_BUILD_HYPEROPT, parser=build_extracted_hyperopt_cmd)
# add new-strategy subcommand
build_strategy_cmd = subparsers.add_parser('new-strategy',
help="Create new strategy")

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@ -1,9 +1,10 @@
import ast
import logging
from pathlib import Path
from typing import Any, Dict
from typing import Any, Dict, List
from freqtrade.constants import USERPATH_HYPEROPTS
from freqtrade.constants import (USERPATH_HYPEROPTS,
USERPATH_STRATEGIES)
from freqtrade.exceptions import OperationalException
from freqtrade.state import RunMode
from freqtrade.configuration import setup_utils_configuration
@ -11,20 +12,139 @@ from freqtrade.misc import render_template
logger = logging.getLogger(__name__)
'''
TODO
-make the code below more dynamic with a large list of indicators and aims
-buy_space integer values variation based on aim(later deep learning)
-add --mode , see notes
-when making the strategy reading tool, make sure that the populate indicators gets copied to here
'''
POSSIBLE_GUARDS = ["rsi", "mfi", "fastd"]
POSSIBLE_TRIGGERS = ["bb_lowerband", "bb_upperband"]
POSSIBLE_VALUES = {"above": ">", "below": "<"}
# ---------------------------------------------------extract-strategy------------------------------------------------------
def get_indicator_info(file: List, indicators: Dict) -> None:
"""
Get all necessary information to build a custom hyperopt space using
the file and a dictionary filled with the indicators and their corropsonding line numbers.
"""
info_list = []
for indicator in indicators:
indicator_info = []
# find the corrosponding aim
for position, line in enumerate(file):
if position == indicators[indicator]:
# use split twice to remove the context around the indicator
back_of_line = line.split(f"(dataframe['{indicator}'] ", 1)[1]
aim = back_of_line.split()[0]
# add the indicator and aim to the info
indicator_info.append(indicator)
indicator_info.append(aim)
# check if first character after aim is a d in which case the indicator is a trigger
if back_of_line.split()[1][0] == "d":
indicator_info.append("trigger")
# add the second indicator of the guard to the info list
back_of_line = back_of_line.split("dataframe['")[1]
second_indicator = back_of_line.split("'])")[0]
indicator_info.append(second_indicator)
# elif indicator[0:3] == "CDL":
# indicator_info.append("guard")
# else it is a regular guard
else:
indicator_info.append("guard")
value = back_of_line.split()[1]
value = value[:-1]
value = float(value)
indicator_info.append(value)
info_list.append(indicator_info)
return info_list
def build_hyperopt_buyelements(buy_indicators: Dict[str, str]):
def extract_lists(strategypath: Path) -> None:
"""
Get the indicators, their aims and the stoploss and format them into lists
"""
# store the file in a list for reference
stored_file = []
with open(strategypath) as file:
for line in file:
stored_file.append(line)
# find the start and end of buy trend
for position, line in enumerate(stored_file):
if "populate_buy_trend(" in line:
start_buy_number = position
elif "populate_sell_trend(" in line:
end_buy_number = position
# list the numbers between the start and end of buy trend
buy_lines = []
for i in range(start_buy_number, end_buy_number):
buy_lines.append(i)
# populate the indicators dictionaries with indicators attached to the line they are on
buyindicators = {}
sellindicators = {}
for position, line in enumerate(stored_file):
# check the lines in buy trend for indicator and add them
if position in buy_lines and "(dataframe['" in line:
# use split twice to remove the context around the indicator
back_of_line = line.split("(dataframe['", 1)[1]
buyindicator = back_of_line.split("'] ", 1)[0]
buyindicators[buyindicator] = position
# check the lines in sell trend for indicator and add them
elif position > end_buy_number and "(dataframe['" in line:
# use split twice to remove the context around the indicator
back_of_line = line.split("(dataframe['", 1)[1]
sellindicator = back_of_line.split("'] ", 1)[0]
sellindicators[sellindicator] = position
# build the final lists
buy_info_list = get_indicator_info(stored_file, buyindicators)
sell_info_list = get_indicator_info(stored_file, sellindicators)
# put the final lists into a tuple
final_lists = (buy_info_list, sell_info_list)
return final_lists
def start_extract_strategy(args: Dict) -> None:
"""
Check if the right subcommands where passed and start extracting the strategy data
"""
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
# check if all required options are filled in
if not 'strategy' in args or not args['strategy']:
raise OperationalException("`extract-strategy` requires --strategy to be set.")
else:
# if the name is not specified use (strategy)_extract
if not 'extract_name' in args or not args['extract_name']:
args['extract_name'] = args['strategy'] + "_extract"
new_path = config['user_data_dir'] / USERPATH_STRATEGIES / (args['extract_name'] + '.txt')
if new_path.exists():
raise OperationalException(f"`{new_path}` already exists. "
"Please choose another name.")
# the path of the chosen strategy
strategy_path = config['user_data_dir'] / USERPATH_STRATEGIES / (args['strategy'] + '.py')
# extract the buy and sell indicators as dicts
extracted_lists = str(extract_lists(strategy_path))
# save the dicts in a file
logger.info(f"Writing custom hyperopt to `{new_path}`.")
new_path.write_text(extracted_lists)
# --------------------------------------------------custom-hyperopt------------------------------------------------------
def custom_hyperopt_buyelements(buy_indicators: List):
"""
Build the arguments with the placefillers for the buygenerator
"""
@ -32,39 +152,44 @@ def build_hyperopt_buyelements(buy_indicators: Dict[str, str]):
buy_triggers = ""
buy_space = ""
for indicator in buy_indicators:
# Error handling
if not indicator in POSSIBLE_GUARDS and not indicator in POSSIBLE_TRIGGERS:
raise OperationalException(
f"`{indicator}` is not part of the available indicators. The current options are {POSSIBLE_GUARDS + POSSIBLE_TRIGGERS}.")
elif not buy_indicators[indicator] in POSSIBLE_VALUES:
raise OperationalException(
f"`{buy_indicators[indicator]}` is not part of the available indicator options. The current options are {POSSIBLE_VALUES}.")
for indicator_info in buy_indicators:
indicator = indicator_info[0]
aim = indicator_info[1]
usage = indicator_info[2]
# If the indicator is a guard
elif indicator in POSSIBLE_GUARDS:
# get the symbol corrosponding to the value
aim = POSSIBLE_VALUES[buy_indicators[indicator]]
if usage == "guard":
value = indicator_info[3]
if value >= -1.0 and value <= 1.0:
lower_bound = value - 0.3
upper_bound = value + 0.3
else:
lower_bound = value - 30.0
upper_bound = value + 30.0
# add the guard to its argument
buy_guards += f"if '{indicator}-enabled' in params and params['{indicator}-enabled']: conditions.append(dataframe['{indicator}'] {aim} params['{indicator}-value'])"
buy_guards += f"if params.get('{indicator}-enabled'):\n conditions.append(dataframe['{indicator}'] {aim} params['{indicator}-value'])\n"
# add the space to its argument
buy_space += f"Integer(10, 90, name='{indicator}-value'), Categorical([True, False], name='{indicator}-enabled'),"
# If the indicator is a trigger
elif indicator in POSSIBLE_TRIGGERS:
# get the symbol corrosponding to the value
aim = POSSIBLE_VALUES[buy_indicators[indicator]]
buy_space += f"Integer({lower_bound}, {upper_bound}, name='{indicator}-value'),\nCategorical([True, False], name='{indicator}-enabled'),\n"
# If the indicator is a trigger
elif usage == "trigger":
secondindicator = indicator_info[3]
# add the trigger to its argument
buy_triggers += f"if params['trigger'] == '{indicator}': conditions.append(dataframe['{indicator}'] {aim} dataframe['close'])"
buy_triggers += f"if params['trigger'] == '{indicator}':\n conditions.append(dataframe['{indicator}'] {aim} dataframe['{secondindicator}'])\n"
# Final line of indicator space makes all triggers
buy_space += "Categorical(["
# adding all triggers to the list
for indicator in buy_indicators:
if indicator in POSSIBLE_TRIGGERS:
for indicator_info in buy_indicators:
indicator = indicator_info[0]
usage = indicator_info[2]
if usage == "trigger":
buy_space += f"'{indicator}', "
# Deleting the last ", "
@ -74,7 +199,7 @@ def build_hyperopt_buyelements(buy_indicators: Dict[str, str]):
return {"buy_guards": buy_guards, "buy_triggers": buy_triggers, "buy_space": buy_space}
def build_hyperopt_sellelements(sell_indicators: Dict[str, str]):
def custom_hyperopt_sellelements(sell_indicators: Dict[str, str]):
"""
Build the arguments with the placefillers for the sellgenerator
"""
@ -82,44 +207,50 @@ def build_hyperopt_sellelements(sell_indicators: Dict[str, str]):
sell_triggers = ""
sell_space = ""
for indicator in sell_indicators:
# Error handling
if not indicator in POSSIBLE_GUARDS and not indicator in POSSIBLE_TRIGGERS:
raise OperationalException(
f"`{indicator}` is not part of the available indicators. The current options are {POSSIBLE_GUARDS + POSSIBLE_TRIGGERS}.")
elif not sell_indicators[indicator] in POSSIBLE_VALUES:
raise OperationalException(
f"`{sell_indicators[indicator]}` is not part of the available indicator options. The current options are {POSSIBLE_VALUES}.")
# If indicator is a guard
elif indicator in POSSIBLE_GUARDS:
# get the symbol corrosponding to the value
aim = POSSIBLE_VALUES[sell_indicators[indicator]]
for indicator_info in sell_indicators:
indicator = indicator_info[0]
aim = indicator_info[1]
usage = indicator_info[2]
# If the indicator is a guard
if usage == "guard":
value = indicator_info[3]
if value >= -1 and value <= 1:
lower_bound = value - 0.3
upper_bound = value + 0.3
else:
lower_bound = value - 30
upper_bound = value + 30
# add the guard to its argument
sell_guards += f"if '{indicator}-enabled' in params and params['sell-{indicator}-enabled']: conditions.append(dataframe['{indicator}'] {aim} params['sell-{indicator}-value'])"
sell_guards += f"if params.get('sell-{indicator}-enabled'):\n conditions.append(dataframe['{indicator}'] {aim} params['sell-{indicator}-value'])\n"
# add the space to its argument
sell_space += f"Integer(10, 90, name='sell-{indicator}-value'), Categorical([True, False], name='sell-{indicator}-enabled'),"
sell_space += f"Integer({lower_bound}, {upper_bound}, name='sell-{indicator}-value'),\nCategorical([True, False], name='sell-{indicator}-enabled'),\n"
# If the indicator is a trigger
elif indicator in POSSIBLE_TRIGGERS:
# get the symbol corrosponding to the value
aim = POSSIBLE_VALUES[sell_indicators[indicator]]
elif usage == "trigger":
secondindicator = indicator_info[3]
# add the trigger to its argument
sell_triggers += f"if params['sell-trigger'] == 'sell-{indicator}': conditions.append(dataframe['{indicator}'] {aim} dataframe['close'])"
sell_triggers += f"if params['sell-trigger'] == 'sell-{indicator}':\n conditions.append(dataframe['{indicator}'] {aim} dataframe['{secondindicator}'])\n"
# Final line of indicator space makes all triggers
sell_space += "Categorical(["
# Adding all triggers to the list
for indicator in sell_indicators:
if indicator in POSSIBLE_TRIGGERS:
# adding all triggers to the list
for indicator_info in sell_indicators:
indicator = indicator_info[0]
usage = indicator_info[2]
if usage == "trigger":
sell_space += f"'sell-{indicator}', "
# Deleting the last ", "
sell_space = sell_space[:-2]
sell_space += "], name='trigger')"
sell_space += "], name='sell-trigger')"
return {"sell_guards": sell_guards, "sell_triggers": sell_triggers, "sell_space": sell_space}
@ -130,11 +261,11 @@ def deploy_custom_hyperopt(hyperopt_name: str, hyperopt_path: Path, buy_indicato
"""
# Build the arguments for the buy and sell generators
buy_args = build_hyperopt_buyelements(buy_indicators)
sell_args = build_hyperopt_sellelements(sell_indicators)
buy_args = custom_hyperopt_buyelements(buy_indicators)
sell_args = custom_hyperopt_sellelements(sell_indicators)
# Build the final template
strategy_text = render_template(templatefile='base_hyperopt.py.j2',
strategy_text = render_template(templatefile='base_custom_hyperopt.py.j2',
arguments={"hyperopt": hyperopt_name,
"buy_guards": buy_args["buy_guards"],
"buy_triggers": buy_args["buy_triggers"],
@ -148,19 +279,18 @@ def deploy_custom_hyperopt(hyperopt_name: str, hyperopt_path: Path, buy_indicato
hyperopt_path.write_text(strategy_text)
def start_build_hyperopt(args: Dict[str, Any]) -> None:
def start_custom_hyperopt(args: Dict[str, Any]) -> None:
"""
Check if the right subcommands where passed and start building the hyperopt
"""
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
# check what the name of the hyperopt should
if not 'hyperopt' in args or not args['hyperopt']:
raise OperationalException("`build-hyperopt` requires --hyperopt to be set.")
raise OperationalException("`custom-hyperopt` requires --hyperopt to be set.")
elif not 'buy_indicators' in args or not args['buy_indicators']:
raise OperationalException("`build-hyperopt` requires --buy-indicators to be set.")
raise OperationalException("`custom-hyperopt` requires --buy-indicators to be set.")
elif not 'sell_indicators' in args or not args['sell_indicators']:
raise OperationalException("`build-hyperopt` requires --sell-indicators to be set.")
raise OperationalException("`custom-hyperopt` requires --sell-indicators to be set.")
else:
if args['hyperopt'] == 'DefaultHyperopt':
raise OperationalException("DefaultHyperopt is not allowed as name.")
@ -175,3 +305,40 @@ def start_build_hyperopt(args: Dict[str, Any]) -> None:
deploy_custom_hyperopt(args['hyperopt'], new_path,
buy_indicators, sell_indicators)
# --------------------------------------------------build-hyperopt------------------------------------------------------
def start_build_hyperopt(args: Dict[str, Any]) -> None:
"""
Check if the right subcommands where passed and start building the hyperopt
"""
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
# strategy and hyperopt need to be defined
if not 'strategy' in args or not args['strategy']:
raise OperationalException("`build-hyperopt` requires --strategy to be set.")
if not 'hyperopt' in args or not args['hyperopt']:
args['hyperopt'] = args['strategy'] + "opt"
else:
if args['hyperopt'] == 'DefaultHyperopt':
raise OperationalException("DefaultHyperopt is not allowed as name.")
# the path of the chosen strategy
strategy_path = config['user_data_dir'] / USERPATH_STRATEGIES / (args['strategy'] + '.py')
# the path where the hyperopt should be written
new_path = config['user_data_dir'] / USERPATH_HYPEROPTS / (args['hyperopt'] + '.py')
if new_path.exists():
raise OperationalException(f"`{new_path}` already exists. "
"Please choose another Hyperopt Name.")
# extract the buy and sell indicators as dicts
extracted_lists = extract_lists(strategy_path)
buy_indicators = extracted_lists[0]
sell_indicators = extracted_lists[1]
# use the dicts to write the hyperopt
deploy_custom_hyperopt(args['hyperopt'], new_path,
buy_indicators, sell_indicators)

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@ -279,14 +279,21 @@ AVAILABLE_CLI_OPTIONS = {
"buy_indicators": Arg(
'-b', '--buy-indicators',
help='Specify the buy indicators the hyperopt should build. '
'Example: --buy-indicators `{"rsi":"above","bb_lowerband":"below"}`',
metavar='DICT',
'Example: --buy-indicators `[["rsi","<","trigger",30.0],["bb_lowerband",">","guard","close"]]`'
'Check the documentation for specific requirements for the lists.',
metavar='LIST',
),
"sell_indicators": Arg(
'-s', '--sell-indicators',
help='Specify the sell indicators the hyperopt should build. '
'Example: --sell-indicators `{"rsi":"above","bb_lowerband":"below"}`',
metavar='DICT',
'Example: --sell-indicators [["rsi",">","trigger",70.0],["bb_lowerband","<","guard","close"]]'
'Check the documentation for specific requirements for the lists.',
metavar='LIST',
),
"extract_name": Arg(
'--extract-name',
help='Specify the name of the file to which the data should be extracted. ',
metavar='FILENAME',
),
# List exchanges
"print_one_column": Arg(

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@ -0,0 +1,164 @@
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# --- Do not remove these libs ---
from functools import reduce
from typing import Any, Callable, Dict, List
import numpy as np # noqa
import pandas as pd # noqa
from pandas import DataFrame
from skopt.space import Categorical, Dimension, Integer, Real # noqa
from freqtrade.optimize.hyperopt_interface import IHyperOpt
# --------------------------------
# Add your lib to import here
import talib.abstract as ta # noqa
import freqtrade.vendor.qtpylib.indicators as qtpylib
class {{ hyperopt }}(IHyperOpt):
"""
This is a Hyperopt template to get you started.
More information in the documentation: https://www.freqtrade.io/en/latest/hyperopt/
You should:
- Add any lib you need to build your hyperopt.
You must keep:
- The prototypes for the methods: populate_indicators, indicator_space, buy_strategy_generator.
The methods roi_space, generate_roi_table and stoploss_space are not required
and are provided by default.
However, you may override them if you need 'roi' and 'stoploss' spaces that
differ from the defaults offered by Freqtrade.
Sample implementation of these methods will be copied to `user_data/hyperopts` when
creating the user-data directory using `freqtrade create-userdir --userdir user_data`,
or is available online under the following URL:
https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py.
"""
@staticmethod
def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
"""
Define the buy strategy parameters to be used by Hyperopt.
"""
def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Buy strategy Hyperopt will build and use.
"""
conditions = []
# GUARDS AND TRENDS
{{ buy_guards | indent(12) }}
# TRIGGERS
if 'trigger' in params:
{{ buy_triggers | indent(16) }}
# Check that the candle had volume
conditions.append(dataframe['volume'] > 0)
if conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
'buy'] = 1
return dataframe
return populate_buy_trend
@staticmethod
def indicator_space() -> List[Dimension]:
"""
Define your Hyperopt space for searching buy strategy parameters.
"""
return [
{{ buy_space | indent(12) }}
]
@staticmethod
def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
"""
Define the sell strategy parameters to be used by Hyperopt.
"""
def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Sell strategy Hyperopt will build and use.
"""
conditions = []
# GUARDS AND TRENDS
{{ sell_guards | indent(12) }}
# TRIGGERS
if 'sell-trigger' in params:
{{ sell_triggers | indent(16) }}
# Check that the candle had volume
conditions.append(dataframe['volume'] > 0)
if conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
'sell'] = 1
return dataframe
return populate_sell_trend
@staticmethod
def sell_indicator_space() -> List[Dimension]:
"""
Define your Hyperopt space for searching sell strategy parameters.
"""
return [
{{ sell_space | indent(12) }}
]
@ staticmethod
def generate_roi_table(params: Dict) -> Dict[int, float]:
"""
Generate the ROI table that will be used by Hyperopt
This implementation generates the default legacy Freqtrade ROI tables.
Change it if you need different number of steps in the generated
ROI tables or other structure of the ROI tables.
Please keep it aligned with parameters in the 'roi' optimization
hyperspace defined by the roi_space method.
"""
roi_table = {}
roi_table[0] = params['roi_p1'] + params['roi_p2'] + params['roi_p3']
roi_table[params['roi_t3']] = params['roi_p1'] + params['roi_p2']
roi_table[params['roi_t3'] + params['roi_t2']] = params['roi_p1']
roi_table[params['roi_t3'] + params['roi_t2'] + params['roi_t1']] = 0
return roi_table
@ staticmethod
def roi_space() -> List[Dimension]:
"""
Values to search for each ROI steps
Override it if you need some different ranges for the parameters in the
'roi' optimization hyperspace.
Please keep it aligned with the implementation of the
generate_roi_table method.
"""
return [
Integer(10, 120, name='roi_t1'),
Integer(10, 60, name='roi_t2'),
Integer(10, 40, name='roi_t3'),
Real(0.01, 0.04, name='roi_p1'),
Real(0.01, 0.07, name='roi_p2'),
Real(0.01, 0.20, name='roi_p3'),
]
@ staticmethod
def stoploss_space() -> List[Dimension]:
"""
Stoploss Value to search
Override it if you need some different range for the parameter in the
'stoploss' optimization hyperspace.
"""
return [
Real(-0.35, -0.02, name='stoploss'),
]

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@ -55,7 +55,16 @@ class {{ hyperopt }}(IHyperOpt):
# TRIGGERS
if 'trigger' in params:
{{ buy_triggers | indent(16) }}
if params['trigger'] == 'bb_lower':
conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
if params['trigger'] == 'macd_cross_signal':
conditions.append(qtpylib.crossed_above(
dataframe['macd'], dataframe['macdsignal']
))
if params['trigger'] == 'sar_reversal':
conditions.append(qtpylib.crossed_above(
dataframe['close'], dataframe['sar']
))
# Check that the candle had volume
conditions.append(dataframe['volume'] > 0)
@ -94,7 +103,16 @@ class {{ hyperopt }}(IHyperOpt):
# TRIGGERS
if 'sell-trigger' in params:
{{ sell_triggers | indent(16) }}
if params['sell-trigger'] == 'sell-bb_upper':
conditions.append(dataframe['close'] > dataframe['bb_upperband'])
if params['sell-trigger'] == 'sell-macd_cross_signal':
conditions.append(qtpylib.crossed_above(
dataframe['macdsignal'], dataframe['macd']
))
if params['sell-trigger'] == 'sell-sar_reversal':
conditions.append(qtpylib.crossed_above(
dataframe['sar'], dataframe['close']
))
# Check that the candle had volume
conditions.append(dataframe['volume'] > 0)