prototype of custom hyperopt tool finished

This commit is contained in:
Bo van Hasselt 2021-02-11 00:38:47 +01:00
parent 1eaff121bc
commit 18e6cd9c9b
5 changed files with 147 additions and 56 deletions

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@ -13,7 +13,6 @@ from freqtrade.commands.data_commands import (start_convert_data, start_download
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.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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@ -212,7 +212,7 @@ class Arguments:
# add build-hyperopt subcommand
build_custom_hyperopt_cmd = subparsers.add_parser('build-hyperopt',
help="Build a custom hyperopt")
help="Build a custom hyperopt")
build_custom_hyperopt_cmd.set_defaults(func=start_build_hyperopt)
self._build_args(optionlist=ARGS_BUILD_CUSTOM_HYPEROPT, parser=build_custom_hyperopt_cmd)

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@ -1,3 +1,4 @@
import ast
import logging
from pathlib import Path
from typing import Any, Dict
@ -6,40 +7,141 @@ from freqtrade.constants import USERPATH_HYPEROPTS
from freqtrade.exceptions import OperationalException
from freqtrade.state import RunMode
from freqtrade.configuration import setup_utils_configuration
from freqtrade.misc import render_template, render_template_with_fallback
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
'''
def deploy_custom_hyperopt(hyperopt_name: str, hyperopt_path: Path, buy_indicators: str, sell_indicators: str) -> None:
POSSIBLE_GUARDS = ["rsi", "mfi", "fastd"]
POSSIBLE_TRIGGERS = ["bb_lowerband", "bb_upperband"]
POSSIBLE_VALUES = {"above": ">", "below": "<"}
def build_hyperopt_buyelements(buy_indicators: Dict[str, str]):
"""
Build the arguments with the placefillers for the buygenerator
"""
buy_guards = ""
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}.")
# If the indicator is a guard
elif indicator in POSSIBLE_GUARDS:
# get the symbol corrosponding to the value
aim = POSSIBLE_VALUES[buy_indicators[indicator]]
# 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'])"
# 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]]
# add the trigger to its argument
buy_triggers += f"if params['trigger'] == '{indicator}': conditions.append(dataframe['{indicator}'] {aim} dataframe['close'])"
# 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:
buy_space += f"'{indicator}', "
# Deleting the last ", "
buy_space = buy_space[:-2]
buy_space += "], name='trigger')"
return {"buy_guards": buy_guards, "buy_triggers": buy_triggers, "buy_space": buy_space}
def build_hyperopt_sellelements(sell_indicators: Dict[str, str]):
"""
Build the arguments with the placefillers for the sellgenerator
"""
sell_guards = ""
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]]
# 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'])"
# add the space to its argument
sell_space += f"Integer(10, 90, name='sell-{indicator}-value'), Categorical([True, False], name='sell-{indicator}-enabled'),"
# If the indicator is a trigger
elif indicator in POSSIBLE_TRIGGERS:
# get the symbol corrosponding to the value
aim = POSSIBLE_VALUES[sell_indicators[indicator]]
# add the trigger to its argument
sell_triggers += f"if params['sell-trigger'] == 'sell-{indicator}': conditions.append(dataframe['{indicator}'] {aim} dataframe['close'])"
# 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:
sell_space += f"'sell-{indicator}', "
# Deleting the last ", "
sell_space = sell_space[:-2]
sell_space += "], name='trigger')"
return {"sell_guards": sell_guards, "sell_triggers": sell_triggers, "sell_space": sell_space}
def deploy_custom_hyperopt(hyperopt_name: str, hyperopt_path: Path, buy_indicators: Dict[str, str], sell_indicators: Dict[str, str]) -> None:
"""
Deploys a custom hyperopt template to hyperopt_path
TODO make the code below more dynamic with a large list of indicators instead of a few templates
"""
fallback = 'full'
buy_guards = render_template_with_fallback(
templatefile=f"subtemplates/hyperopt_buy_guards_{subtemplate}.j2",
templatefallbackfile=f"subtemplates/hyperopt_buy_guards_{fallback}.j2",
)
sell_guards = render_template_with_fallback(
templatefile=f"subtemplates/hyperopt_sell_guards_{subtemplate}.j2",
templatefallbackfile=f"subtemplates/hyperopt_sell_guards_{fallback}.j2",
)
buy_space = render_template_with_fallback(
templatefile=f"subtemplates/hyperopt_buy_space_{subtemplate}.j2",
templatefallbackfile=f"subtemplates/hyperopt_buy_space_{fallback}.j2",
)
sell_space = render_template_with_fallback(
templatefile=f"subtemplates/hyperopt_sell_space_{subtemplate}.j2",
templatefallbackfile=f"subtemplates/hyperopt_sell_space_{fallback}.j2",
)
# Build the arguments for the buy and sell generators
buy_args = build_hyperopt_buyelements(buy_indicators)
sell_args = build_hyperopt_sellelements(sell_indicators)
# Build the final template
strategy_text = render_template(templatefile='base_hyperopt.py.j2',
arguments={"hyperopt": hyperopt_name,
"buy_guards": buy_guards,
"sell_guards": sell_guards,
"buy_space": buy_space,
"sell_space": sell_space,
"buy_guards": buy_args["buy_guards"],
"buy_triggers": buy_args["buy_triggers"],
"buy_space": buy_args["buy_space"],
"sell_guards": sell_args["sell_guards"],
"sell_triggers": sell_args["sell_triggers"],
"sell_space": sell_args["sell_space"],
})
logger.info(f"Writing custom hyperopt to `{hyperopt_path}`.")
@ -67,5 +169,9 @@ def start_build_hyperopt(args: Dict[str, Any]) -> None:
if new_path.exists():
raise OperationalException(f"`{new_path}` already exists. "
"Please choose another Hyperopt Name.")
buy_indicators = ast.literal_eval(args['buy_indicators'])
sell_indicators = ast.literal_eval(args['sell_indicators'])
deploy_custom_hyperopt(args['hyperopt'], new_path,
args['buy_indicators'], args['sell_indicators'])
buy_indicators, sell_indicators)

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@ -275,6 +275,19 @@ AVAILABLE_CLI_OPTIONS = {
'Example: `--hyperopt-filename=hyperopt_results_2020-09-27_16-20-48.pickle`',
metavar='FILENAME',
),
# Automation
"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',
),
"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',
),
# List exchanges
"print_one_column": Arg(
'-1', '--one-column',
@ -439,15 +452,6 @@ AVAILABLE_CLI_OPTIONS = {
help='Specify the list of trade ids.',
nargs='+',
),
# automation
"buy_indicators": Arg(
'-b', '--buy-indicators',
help='Specify the buy indicators the hyperopt should build.'
),
"sell_indicators": Arg(
'-s', '--sell-indicators',
help='Specify the buy indicators the hyperopt should build.'
),
# hyperopt-list, hyperopt-show
"hyperopt_list_profitable": Arg(
'--profitable',

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@ -55,16 +55,7 @@ class {{ hyperopt }}(IHyperOpt):
# TRIGGERS
if 'trigger' in params:
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']
))
{{ buy_triggers | indent(16) }}
# Check that the candle had volume
conditions.append(dataframe['volume'] > 0)
@ -103,16 +94,7 @@ class {{ hyperopt }}(IHyperOpt):
# TRIGGERS
if 'sell-trigger' in params:
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']
))
{{ sell_triggers | indent(16) }}
# Check that the candle had volume
conditions.append(dataframe['volume'] > 0)