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generalized the build-hyperopt command for all indicators possible for the strategies

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This commit is contained in:
Bo van Hasselt 2021-02-20 02:59:18 +01:00
parent 970b0028c1
commit a215dc5212
2 changed files with 96 additions and 89 deletions
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163
freqtrade/commands/automation_commands.py
View File

@ -1,13 +1,11 @@
import ast
import logging
from os import EX_USAGE
from pathlib import Path
from typing import Any, Dict
from typing import Any, Dict, List
from freqtrade.constants import (USERPATH_HYPEROPTS,
USERPATH_STRATEGIES,
POSSIBLE_GUARDS,
POSSIBLE_TRIGGERS,
POSSIBLE_AIMS)
USERPATH_STRATEGIES)
from freqtrade.exceptions import OperationalException
from freqtrade.state import RunMode
from freqtrade.configuration import setup_utils_configuration
@ -24,10 +22,11 @@ logger = logging.getLogger(__name__)
'''
def extract_dicts(strategypath: Path):
def extract_lists(strategypath: Path):
"""
Get the indicators, their aims and the stoploss and format them into dictionaries
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:
@ -49,13 +48,13 @@ def extract_dicts(strategypath: Path):
# 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
@ -63,35 +62,70 @@ def extract_dicts(strategypath: Path):
# 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 buy dictionary
buy_dict = {}
# build the final buy list
buy_list = []
for indicator in buyindicators:
indicator_info = []
# find the corrosponding aim
for position, line in enumerate(stored_file):
if position == buyindicators[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]
buy_dict[indicator] = aim
# build the final sell dictionary
sell_dict = {}
# 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)
# else it is a guard
else:
indicator_info.append("guard")
buy_list.append(indicator_info)
# build the final sell list
sell_list = []
for indicator in sellindicators:
# find the corrosponding aim
indicator_info = []
# find the corrosponding aim and whether a guard or trigger
for position, line in enumerate(stored_file):
if position == sellindicators[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]
sell_dict[indicator] = aim
# put the final dicts into a tuple
final_dicts = (buy_dict, sell_dict)
# add the indicator and aim to the info
indicator_info.append(indicator)
indicator_info.append(aim)
return final_dicts
# 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)
# else it is a guard
else:
indicator_info.append("guard")
sell_list.append(indicator_info)
# put the final lists into a tuple
final_lists = (buy_list, sell_list)
return final_lists
def start_extract_strategy(args: Dict[str, Any]) -> None:
@ -116,11 +150,11 @@ def start_extract_strategy(args: Dict[str, Any]) -> None:
strategy_path = config['user_data_dir'] / USERPATH_STRATEGIES / (args['strategy'] + '.py')
# extract the buy and sell indicators as dicts
extracted_dicts = str(extract_dicts(strategy_path))
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_dicts)
new_path.write_text(extracted_lists)
# --------------------------------------------------custom-hyperopt------------------------------------------------------
@ -135,7 +169,7 @@ def start_extract_strategy(args: Dict[str, Any]) -> None:
'''
def custom_hyperopt_buyelements(buy_indicators: Dict[str, str]):
def custom_hyperopt_buyelements(buy_indicators: List):
"""
Build the arguments with the placefillers for the buygenerator
"""
@ -143,39 +177,35 @@ def custom_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_AIMS:
raise OperationalException(
f"`{buy_indicators[indicator]}` is not part of the available indicator options. The current options are {POSSIBLE_AIMS}.")
# If the indicator is a guard
elif indicator in POSSIBLE_GUARDS:
# get the symbol corrosponding to the value
aim = buy_indicators[indicator]
for indicator_info in buy_indicators:
indicator = indicator_info[0]
aim = indicator_info[1]
usage = indicator_info[2]
# If the indicator is a guard
if usage == "guard":
# add the guard to its argument
buy_guards += f"if '{indicator}-enabled' in params and params['{indicator}-enabled']:\n conditions.append(dataframe['{indicator}'] {aim} params['{indicator}-value'])\n"
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'),\nCategorical([True, False], name='{indicator}-enabled'),\n"
# If the indicator is a trigger
elif indicator in POSSIBLE_TRIGGERS:
# get the symbol corrosponding to the value
aim = buy_indicators[indicator]
# 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}':\n conditions.append(dataframe['{indicator}'] {aim} dataframe['close'])\n"
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 ", "
@ -192,45 +222,42 @@ def custom_hyperopt_sellelements(sell_indicators: Dict[str, str]):
sell_guards = ""
sell_triggers = ""
sell_space = ""
print(sell_indicators)
for indicator_info in sell_indicators:
indicator = indicator_info[0]
aim = indicator_info[1]
usage = indicator_info[2]
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_AIMS:
raise OperationalException(
f"`{sell_indicators[indicator]}` is not part of the available indicator options. The current options are {POSSIBLE_AIMS}.")
# If indicator is a guard
elif indicator in POSSIBLE_GUARDS:
# get the symbol corrosponding to the value
aim = sell_indicators[indicator]
# If the indicator is a guard
if usage == "guard":
# add the guard to its argument
sell_guards += f"if '{indicator}-enabled' in params and params['sell-{indicator}-enabled']:\n conditions.append(dataframe['{indicator}'] {aim} params['sell-{indicator}-value'])\n"
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'),\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 = 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}':\n conditions.append(dataframe['{indicator}'] {aim} dataframe['close'])\n"
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}
@ -319,10 +346,10 @@ def start_build_hyperopt(args: Dict[str, Any]) -> None:
"Please choose another Hyperopt Name.")
# extract the buy and sell indicators as dicts
extracted_dicts = extract_dicts(strategy_path)
buy_indicators = extracted_dicts[0]
sell_indicators = extracted_dicts[1]
extracted_lists = extract_lists(strategy_path)
print(extracted_lists)
buy_indicators = extracted_lists[0]
sell_indicators = extracted_lists[1]
# use the dicts to write the hyperopt
deploy_custom_hyperopt(args['hyperopt'], new_path,

20
freqtrade/constants.py
View File

@ -383,23 +383,3 @@ ListPairsWithTimeframes = List[PairWithTimeframe]
# Type for trades list
TradeList = List[List]
#Build-hyperopt options
POSSIBLE_GUARDS = [
"rsi",
"mfi",
"fastd",
"slowk",
"CDLHAMMER",
"fisher_rsi"
]
POSSIBLE_TRIGGERS = [
"sar",
"bb_lowerband",
"bb_upperband"
]
POSSIBLE_AIMS = [
">",
"<",
"=="
]