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Merge branch 'develop' into stoploss_market

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This commit is contained in:
Matthias 2020-01-26 20:33:41 +01:00
commit 1ef148317d
31 changed files with 1263 additions and 1191 deletions
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25
freqtrade/commands/__init__.py Normal file
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@ -0,0 +1,25 @@
# flake8: noqa: F401
"""
Commands module.
Contains all start-commands, subcommands and CLI Interface creation.
Note: Be careful with file-scoped imports in these subfiles.
as they are parsed on startup, nothing containing optional modules should be loaded.
"""
from freqtrade.commands.arguments import Arguments
from freqtrade.commands.data_commands import start_download_data
from freqtrade.commands.deploy_commands import (start_create_userdir,
start_new_hyperopt,
start_new_strategy)
from freqtrade.commands.hyperopt_commands import (start_hyperopt_list,
start_hyperopt_show)
from freqtrade.commands.list_commands import (start_list_exchanges,
start_list_markets,
start_list_strategies,
start_list_timeframes)
from freqtrade.commands.optimize_commands import (start_backtesting,
start_edge, start_hyperopt)
from freqtrade.commands.pairlist_commands import start_test_pairlist
from freqtrade.commands.plot_commands import (start_plot_dataframe,
start_plot_profit)
from freqtrade.commands.trade_commands import start_trading

18
freqtrade/configuration/arguments.py → freqtrade/commands/arguments.py
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@ -7,7 +7,7 @@ from pathlib import Path
from typing import Any, Dict, List, Optional
from freqtrade import constants
from freqtrade.configuration.cli_options import AVAILABLE_CLI_OPTIONS
from freqtrade.commands.cli_options import AVAILABLE_CLI_OPTIONS
ARGS_COMMON = ["verbosity", "logfile", "version", "config", "datadir", "user_data_dir"]
@ -130,14 +130,14 @@ class Arguments:
self.parser = argparse.ArgumentParser(description='Free, open source crypto trading bot')
self._build_args(optionlist=['version'], parser=self.parser)
from freqtrade.optimize import start_backtesting, start_hyperopt, start_edge
from freqtrade.utils import (start_create_userdir, start_download_data,
start_hyperopt_list, start_hyperopt_show,
start_list_exchanges, start_list_markets,
start_list_strategies, start_new_hyperopt,
start_new_strategy, start_list_timeframes,
start_test_pairlist, start_trading)
from freqtrade.plot.plot_utils import start_plot_dataframe, start_plot_profit
from freqtrade.commands import (start_create_userdir, start_download_data,
start_hyperopt_list, start_hyperopt_show,
start_list_exchanges, start_list_markets,
start_list_strategies, start_new_hyperopt,
start_new_strategy, start_list_timeframes,
start_plot_dataframe, start_plot_profit,
start_backtesting, start_hyperopt, start_edge,
start_test_pairlist, start_trading)
subparsers = self.parser.add_subparsers(dest='command',
# Use custom message when no subhandler is added

6
freqtrade/configuration/cli_options.py → freqtrade/commands/cli_options.py
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@ -1,7 +1,7 @@
"""
Definition of cli arguments used in arguments.py
"""
import argparse
from argparse import ArgumentTypeError
from freqtrade import __version__, constants
@ -12,7 +12,7 @@ def check_int_positive(value: str) -> int:
if uint <= 0:
raise ValueError
except ValueError:
raise argparse.ArgumentTypeError(
raise ArgumentTypeError(
f"{value} is invalid for this parameter, should be a positive integer value"
)
return uint
@ -24,7 +24,7 @@ def check_int_nonzero(value: str) -> int:
if uint == 0:
raise ValueError
except ValueError:
raise argparse.ArgumentTypeError(
raise ArgumentTypeError(
f"{value} is invalid for this parameter, should be a non-zero integer value"
)
return uint

63
freqtrade/commands/data_commands.py Normal file
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@ -0,0 +1,63 @@
import logging
import sys
from typing import Any, Dict, List
import arrow
from freqtrade.configuration import TimeRange, setup_utils_configuration
from freqtrade.data.history import (convert_trades_to_ohlcv,
refresh_backtest_ohlcv_data,
refresh_backtest_trades_data)
from freqtrade.exceptions import OperationalException
from freqtrade.resolvers import ExchangeResolver
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
def start_download_data(args: Dict[str, Any]) -> None:
"""
Download data (former download_backtest_data.py script)
"""
config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
timerange = TimeRange()
if 'days' in config:
time_since = arrow.utcnow().shift(days=-config['days']).strftime("%Y%m%d")
timerange = TimeRange.parse_timerange(f'{time_since}-')
if 'pairs' not in config:
raise OperationalException(
"Downloading data requires a list of pairs. "
"Please check the documentation on how to configure this.")
logger.info(f'About to download pairs: {config["pairs"]}, '
f'intervals: {config["timeframes"]} to {config["datadir"]}')
pairs_not_available: List[str] = []
# Init exchange
exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config)
try:
if config.get('download_trades'):
pairs_not_available = refresh_backtest_trades_data(
exchange, pairs=config["pairs"], datadir=config['datadir'],
timerange=timerange, erase=config.get("erase"))
# Convert downloaded trade data to different timeframes
convert_trades_to_ohlcv(
pairs=config["pairs"], timeframes=config["timeframes"],
datadir=config['datadir'], timerange=timerange, erase=config.get("erase"))
else:
pairs_not_available = refresh_backtest_ohlcv_data(
exchange, pairs=config["pairs"], timeframes=config["timeframes"],
datadir=config['datadir'], timerange=timerange, erase=config.get("erase"))
except KeyboardInterrupt:
sys.exit("SIGINT received, aborting ...")
finally:
if pairs_not_available:
logger.info(f"Pairs [{','.join(pairs_not_available)}] not available "
f"on exchange {exchange.name}.")

112
freqtrade/commands/deploy_commands.py Normal file
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@ -0,0 +1,112 @@
import logging
import sys
from pathlib import Path
from typing import Any, Dict
from freqtrade.configuration import setup_utils_configuration
from freqtrade.configuration.directory_operations import (copy_sample_files,
create_userdata_dir)
from freqtrade.constants import USERPATH_HYPEROPTS, USERPATH_STRATEGY
from freqtrade.exceptions import OperationalException
from freqtrade.misc import render_template
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
def start_create_userdir(args: Dict[str, Any]) -> None:
"""
Create "user_data" directory to contain user data strategies, hyperopt, ...)
:param args: Cli args from Arguments()
:return: None
"""
if "user_data_dir" in args and args["user_data_dir"]:
userdir = create_userdata_dir(args["user_data_dir"], create_dir=True)
copy_sample_files(userdir, overwrite=args["reset"])
else:
logger.warning("`create-userdir` requires --userdir to be set.")
sys.exit(1)
def deploy_new_strategy(strategy_name, strategy_path: Path, subtemplate: str):
"""
Deploy new strategy from template to strategy_path
"""
indicators = render_template(templatefile=f"subtemplates/indicators_{subtemplate}.j2",)
buy_trend = render_template(templatefile=f"subtemplates/buy_trend_{subtemplate}.j2",)
sell_trend = render_template(templatefile=f"subtemplates/sell_trend_{subtemplate}.j2",)
plot_config = render_template(templatefile=f"subtemplates/plot_config_{subtemplate}.j2",)
strategy_text = render_template(templatefile='base_strategy.py.j2',
arguments={"strategy": strategy_name,
"indicators": indicators,
"buy_trend": buy_trend,
"sell_trend": sell_trend,
"plot_config": plot_config,
})
logger.info(f"Writing strategy to `{strategy_path}`.")
strategy_path.write_text(strategy_text)
def start_new_strategy(args: Dict[str, Any]) -> None:
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
if "strategy" in args and args["strategy"]:
if args["strategy"] == "DefaultStrategy":
raise OperationalException("DefaultStrategy is not allowed as name.")
new_path = config['user_data_dir'] / USERPATH_STRATEGY / (args["strategy"] + ".py")
if new_path.exists():
raise OperationalException(f"`{new_path}` already exists. "
"Please choose another Strategy Name.")
deploy_new_strategy(args['strategy'], new_path, args['template'])
else:
raise OperationalException("`new-strategy` requires --strategy to be set.")
def deploy_new_hyperopt(hyperopt_name, hyperopt_path: Path, subtemplate: str):
"""
Deploys a new hyperopt template to hyperopt_path
"""
buy_guards = render_template(
templatefile=f"subtemplates/hyperopt_buy_guards_{subtemplate}.j2",)
sell_guards = render_template(
templatefile=f"subtemplates/hyperopt_sell_guards_{subtemplate}.j2",)
buy_space = render_template(
templatefile=f"subtemplates/hyperopt_buy_space_{subtemplate}.j2",)
sell_space = render_template(
templatefile=f"subtemplates/hyperopt_sell_space_{subtemplate}.j2",)
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,
})
logger.info(f"Writing hyperopt to `{hyperopt_path}`.")
hyperopt_path.write_text(strategy_text)
def start_new_hyperopt(args: Dict[str, Any]) -> None:
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
if "hyperopt" in args and args["hyperopt"]:
if args["hyperopt"] == "DefaultHyperopt":
raise OperationalException("DefaultHyperopt is not allowed as name.")
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 Strategy Name.")
deploy_new_hyperopt(args['hyperopt'], new_path, args['template'])
else:
raise OperationalException("`new-hyperopt` requires --hyperopt to be set.")

114
freqtrade/commands/hyperopt_commands.py Normal file
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@ -0,0 +1,114 @@
import logging
from operator import itemgetter
from typing import Any, Dict, List
from colorama import init as colorama_init
from freqtrade.configuration import setup_utils_configuration
from freqtrade.exceptions import OperationalException
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
def start_hyperopt_list(args: Dict[str, Any]) -> None:
"""
List hyperopt epochs previously evaluated
"""
from freqtrade.optimize.hyperopt import Hyperopt
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
only_best = config.get('hyperopt_list_best', False)
only_profitable = config.get('hyperopt_list_profitable', False)
print_colorized = config.get('print_colorized', False)
print_json = config.get('print_json', False)
no_details = config.get('hyperopt_list_no_details', False)
no_header = False
trials_file = (config['user_data_dir'] /
'hyperopt_results' / 'hyperopt_results.pickle')
# Previous evaluations
trials = Hyperopt.load_previous_results(trials_file)
total_epochs = len(trials)
trials = _hyperopt_filter_trials(trials, only_best, only_profitable)
# TODO: fetch the interval for epochs to print from the cli option
epoch_start, epoch_stop = 0, None
if print_colorized:
colorama_init(autoreset=True)
try:
# Human-friendly indexes used here (starting from 1)
for val in trials[epoch_start:epoch_stop]:
Hyperopt.print_results_explanation(val, total_epochs, not only_best, print_colorized)
except KeyboardInterrupt:
print('User interrupted..')
if trials and not no_details:
sorted_trials = sorted(trials, key=itemgetter('loss'))
results = sorted_trials[0]
Hyperopt.print_epoch_details(results, total_epochs, print_json, no_header)
def start_hyperopt_show(args: Dict[str, Any]) -> None:
"""
Show details of a hyperopt epoch previously evaluated
"""
from freqtrade.optimize.hyperopt import Hyperopt
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
only_best = config.get('hyperopt_list_best', False)
only_profitable = config.get('hyperopt_list_profitable', False)
no_header = config.get('hyperopt_show_no_header', False)
trials_file = (config['user_data_dir'] /
'hyperopt_results' / 'hyperopt_results.pickle')
# Previous evaluations
trials = Hyperopt.load_previous_results(trials_file)
total_epochs = len(trials)
trials = _hyperopt_filter_trials(trials, only_best, only_profitable)
trials_epochs = len(trials)
n = config.get('hyperopt_show_index', -1)
if n > trials_epochs:
raise OperationalException(
f"The index of the epoch to show should be less than {trials_epochs + 1}.")
if n < -trials_epochs:
raise OperationalException(
f"The index of the epoch to show should be greater than {-trials_epochs - 1}.")
# Translate epoch index from human-readable format to pythonic
if n > 0:
n -= 1
print_json = config.get('print_json', False)
if trials:
val = trials[n]
Hyperopt.print_epoch_details(val, total_epochs, print_json, no_header,
header_str="Epoch details")
def _hyperopt_filter_trials(trials: List, only_best: bool, only_profitable: bool) -> List:
"""
Filter our items from the list of hyperopt results
"""
if only_best:
trials = [x for x in trials if x['is_best']]
if only_profitable:
trials = [x for x in trials if x['results_metrics']['profit'] > 0]
logger.info(f"{len(trials)} " +
("best " if only_best else "") +
("profitable " if only_profitable else "") +
"epochs found.")
return trials

156
freqtrade/commands/list_commands.py Normal file
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@ -0,0 +1,156 @@
import csv
import logging
import sys
from collections import OrderedDict
from pathlib import Path
from typing import Any, Dict
import rapidjson
from tabulate import tabulate
from freqtrade.configuration import setup_utils_configuration
from freqtrade.constants import USERPATH_STRATEGY
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import (available_exchanges, ccxt_exchanges,
market_is_active, symbol_is_pair)
from freqtrade.misc import plural
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
def start_list_exchanges(args: Dict[str, Any]) -> None:
"""
Print available exchanges
:param args: Cli args from Arguments()
:return: None
"""
exchanges = ccxt_exchanges() if args['list_exchanges_all'] else available_exchanges()
if args['print_one_column']:
print('\n'.join(exchanges))
else:
if args['list_exchanges_all']:
print(f"All exchanges supported by the ccxt library: {', '.join(exchanges)}")
else:
print(f"Exchanges available for Freqtrade: {', '.join(exchanges)}")
def start_list_strategies(args: Dict[str, Any]) -> None:
"""
Print Strategies available in a directory
"""
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
directory = Path(config.get('strategy_path', config['user_data_dir'] / USERPATH_STRATEGY))
strategies = StrategyResolver.search_all_objects(directory)
# Sort alphabetically
strategies = sorted(strategies, key=lambda x: x['name'])
strats_to_print = [{'name': s['name'], 'location': s['location'].name} for s in strategies]
if args['print_one_column']:
print('\n'.join([s['name'] for s in strategies]))
else:
print(tabulate(strats_to_print, headers='keys', tablefmt='pipe'))
def start_list_timeframes(args: Dict[str, Any]) -> None:
"""
Print ticker intervals (timeframes) available on Exchange
"""
config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
# Do not use ticker_interval set in the config
config['ticker_interval'] = None
# Init exchange
exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config, validate=False)
if args['print_one_column']:
print('\n'.join(exchange.timeframes))
else:
print(f"Timeframes available for the exchange `{exchange.name}`: "
f"{', '.join(exchange.timeframes)}")
def start_list_markets(args: Dict[str, Any], pairs_only: bool = False) -> None:
"""
Print pairs/markets on the exchange
:param args: Cli args from Arguments()
:param pairs_only: if True print only pairs, otherwise print all instruments (markets)
:return: None
"""
config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
# Init exchange
exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config, validate=False)
# By default only active pairs/markets are to be shown
active_only = not args.get('list_pairs_all', False)
base_currencies = args.get('base_currencies', [])
quote_currencies = args.get('quote_currencies', [])
try:
pairs = exchange.get_markets(base_currencies=base_currencies,
quote_currencies=quote_currencies,
pairs_only=pairs_only,
active_only=active_only)
# Sort the pairs/markets by symbol
pairs = OrderedDict(sorted(pairs.items()))
except Exception as e:
raise OperationalException(f"Cannot get markets. Reason: {e}") from e
else:
summary_str = ((f"Exchange {exchange.name} has {len(pairs)} ") +
("active " if active_only else "") +
(plural(len(pairs), "pair" if pairs_only else "market")) +
(f" with {', '.join(base_currencies)} as base "
f"{plural(len(base_currencies), 'currency', 'currencies')}"
if base_currencies else "") +
(" and" if base_currencies and quote_currencies else "") +
(f" with {', '.join(quote_currencies)} as quote "
f"{plural(len(quote_currencies), 'currency', 'currencies')}"
if quote_currencies else ""))
headers = ["Id", "Symbol", "Base", "Quote", "Active",
*(['Is pair'] if not pairs_only else [])]
tabular_data = []
for _, v in pairs.items():
tabular_data.append({'Id': v['id'], 'Symbol': v['symbol'],
'Base': v['base'], 'Quote': v['quote'],
'Active': market_is_active(v),
**({'Is pair': symbol_is_pair(v['symbol'])}
if not pairs_only else {})})
if (args.get('print_one_column', False) or
args.get('list_pairs_print_json', False) or
args.get('print_csv', False)):
# Print summary string in the log in case of machine-readable
# regular formats.
logger.info(f"{summary_str}.")
else:
# Print empty string separating leading logs and output in case of
# human-readable formats.
print()
if len(pairs):
if args.get('print_list', False):
# print data as a list, with human-readable summary
print(f"{summary_str}: {', '.join(pairs.keys())}.")
elif args.get('print_one_column', False):
print('\n'.join(pairs.keys()))
elif args.get('list_pairs_print_json', False):
print(rapidjson.dumps(list(pairs.keys()), default=str))
elif args.get('print_csv', False):
writer = csv.DictWriter(sys.stdout, fieldnames=headers)
writer.writeheader()
writer.writerows(tabular_data)
else:
# print data as a table, with the human-readable summary
print(f"{summary_str}:")
print(tabulate(tabular_data, headers='keys', tablefmt='pipe'))
elif not (args.get('print_one_column', False) or
args.get('list_pairs_print_json', False) or
args.get('print_csv', False)):
print(f"{summary_str}.")

102
freqtrade/commands/optimize_commands.py Normal file
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@ -0,0 +1,102 @@
import logging
from typing import Any, Dict
from freqtrade import constants
from freqtrade.configuration import setup_utils_configuration
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
def setup_optimize_configuration(args: Dict[str, Any], method: RunMode) -> Dict[str, Any]:
"""
Prepare the configuration for the Hyperopt module
:param args: Cli args from Arguments()
:return: Configuration
"""
config = setup_utils_configuration(args, method)
if method == RunMode.BACKTEST:
if config['stake_amount'] == constants.UNLIMITED_STAKE_AMOUNT:
raise DependencyException('stake amount could not be "%s" for backtesting' %
constants.UNLIMITED_STAKE_AMOUNT)
return config
def start_backtesting(args: Dict[str, Any]) -> None:
"""
Start Backtesting script
:param args: Cli args from Arguments()
:return: None
"""
# Import here to avoid loading backtesting module when it's not used
from freqtrade.optimize.backtesting import Backtesting
# Initialize configuration
config = setup_optimize_configuration(args, RunMode.BACKTEST)
logger.info('Starting freqtrade in Backtesting mode')
# Initialize backtesting object
backtesting = Backtesting(config)
backtesting.start()
def start_hyperopt(args: Dict[str, Any]) -> None:
"""
Start hyperopt script
:param args: Cli args from Arguments()
:return: None
"""
# Import here to avoid loading hyperopt module when it's not used
try:
from filelock import FileLock, Timeout
from freqtrade.optimize.hyperopt import Hyperopt
except ImportError as e:
raise OperationalException(
f"{e}. Please ensure that the hyperopt dependencies are installed.") from e
# Initialize configuration
config = setup_optimize_configuration(args, RunMode.HYPEROPT)
logger.info('Starting freqtrade in Hyperopt mode')
lock = FileLock(Hyperopt.get_lock_filename(config))
try:
with lock.acquire(timeout=1):
# Remove noisy log messages
logging.getLogger('hyperopt.tpe').setLevel(logging.WARNING)
logging.getLogger('filelock').setLevel(logging.WARNING)
# Initialize backtesting object
hyperopt = Hyperopt(config)
hyperopt.start()
except Timeout:
logger.info("Another running instance of freqtrade Hyperopt detected.")
logger.info("Simultaneous execution of multiple Hyperopt commands is not supported. "
"Hyperopt module is resource hungry. Please run your Hyperopt sequentially "
"or on separate machines.")
logger.info("Quitting now.")
# TODO: return False here in order to help freqtrade to exit
# with non-zero exit code...
# Same in Edge and Backtesting start() functions.
def start_edge(args: Dict[str, Any]) -> None:
"""
Start Edge script
:param args: Cli args from Arguments()
:return: None
"""
from freqtrade.optimize.edge_cli import EdgeCli
# Initialize configuration
config = setup_optimize_configuration(args, RunMode.EDGE)
logger.info('Starting freqtrade in Edge mode')
# Initialize Edge object
edge_cli = EdgeCli(config)
edge_cli.start()

42
freqtrade/commands/pairlist_commands.py Normal file
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@ -0,0 +1,42 @@
import logging
from typing import Any, Dict
import rapidjson
from freqtrade.configuration import setup_utils_configuration
from freqtrade.resolvers import ExchangeResolver
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
def start_test_pairlist(args: Dict[str, Any]) -> None:
"""
Test Pairlist configuration
"""
from freqtrade.pairlist.pairlistmanager import PairListManager
config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config, validate=False)
quote_currencies = args.get('quote_currencies')
if not quote_currencies:
quote_currencies = [config.get('stake_currency')]
results = {}
for curr in quote_currencies:
config['stake_currency'] = curr
# Do not use ticker_interval set in the config
pairlists = PairListManager(exchange, config)
pairlists.refresh_pairlist()
results[curr] = pairlists.whitelist
for curr, pairlist in results.items():
if not args.get('print_one_column', False):
print(f"Pairs for {curr}: ")
if args.get('print_one_column', False):
print('\n'.join(pairlist))
elif args.get('list_pairs_print_json', False):
print(rapidjson.dumps(list(pairlist), default=str))
else:
print(pairlist)

2
freqtrade/plot/plot_utils.py → freqtrade/commands/plot_commands.py
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@ -1,8 +1,8 @@
from typing import Any, Dict
from freqtrade.configuration import setup_utils_configuration
from freqtrade.exceptions import OperationalException
from freqtrade.state import RunMode
from freqtrade.utils import setup_utils_configuration
def validate_plot_args(args: Dict[str, Any]):

25
freqtrade/commands/trade_commands.py Normal file
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@ -0,0 +1,25 @@
import logging
from typing import Any, Dict
logger = logging.getLogger(__name__)
def start_trading(args: Dict[str, Any]) -> int:
"""
Main entry point for trading mode
"""
from freqtrade.worker import Worker
# Load and run worker
worker = None
try:
worker = Worker(args)
worker.run()
except KeyboardInterrupt:
logger.info('SIGINT received, aborting ...')
finally:
if worker:
logger.info("worker found ... calling exit")
worker.exit()
return 0

12
freqtrade/configuration/__init__.py
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@ -1,5 +1,7 @@
from freqtrade.configuration.arguments import Arguments # noqa: F401
from freqtrade.configuration.check_exchange import check_exchange, remove_credentials # noqa: F401
from freqtrade.configuration.timerange import TimeRange # noqa: F401
from freqtrade.configuration.configuration import Configuration # noqa: F401
from freqtrade.configuration.config_validation import validate_config_consistency # noqa: F401
# flake8: noqa: F401
from freqtrade.configuration.config_setup import setup_utils_configuration
from freqtrade.configuration.check_exchange import check_exchange, remove_credentials
from freqtrade.configuration.timerange import TimeRange
from freqtrade.configuration.configuration import Configuration
from freqtrade.configuration.config_validation import validate_config_consistency

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import logging
from typing import Any, Dict
from .config_validation import validate_config_consistency
from .configuration import Configuration
from .check_exchange import remove_credentials
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
def setup_utils_configuration(args: Dict[str, Any], method: RunMode) -> Dict[str, Any]:
"""
Prepare the configuration for utils subcommands
:param args: Cli args from Arguments()
:return: Configuration
"""
configuration = Configuration(args, method)
config = configuration.get_config()
# Ensure we do not use Exchange credentials
remove_credentials(config)
validate_config_consistency(config)
return config

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freqtrade/edge/__init__.py
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# pragma pylint: disable=W0603
""" Edge positioning package """
import logging
from typing import Any, Dict, NamedTuple
import arrow
import numpy as np
import utils_find_1st as utf1st
from pandas import DataFrame
from freqtrade import constants
from freqtrade.configuration import TimeRange
from freqtrade.data import history
from freqtrade.exceptions import OperationalException
from freqtrade.strategy.interface import SellType
logger = logging.getLogger(__name__)
class PairInfo(NamedTuple):
stoploss: float
winrate: float
risk_reward_ratio: float
required_risk_reward: float
expectancy: float
nb_trades: int
avg_trade_duration: float
class Edge:
"""
Calculates Win Rate, Risk Reward Ratio, Expectancy
against historical data for a give set of markets and a strategy
it then adjusts stoploss and position size accordingly
and force it into the strategy
Author: https://github.com/mishaker
"""
config: Dict = {}
_cached_pairs: Dict[str, Any] = {} # Keeps a list of pairs
def __init__(self, config: Dict[str, Any], exchange, strategy) -> None:
self.config = config
self.exchange = exchange
self.strategy = strategy
self.edge_config = self.config.get('edge', {})
self._cached_pairs: Dict[str, Any] = {} # Keeps a list of pairs
self._final_pairs: list = []
# checking max_open_trades. it should be -1 as with Edge
# the number of trades is determined by position size
if self.config['max_open_trades'] != float('inf'):
logger.critical('max_open_trades should be -1 in config !')
if self.config['stake_amount'] != constants.UNLIMITED_STAKE_AMOUNT:
raise OperationalException('Edge works only with unlimited stake amount')
# Deprecated capital_available_percentage. Will use tradable_balance_ratio in the future.
self._capital_percentage: float = self.edge_config.get(
'capital_available_percentage', self.config['tradable_balance_ratio'])
self._allowed_risk: float = self.edge_config.get('allowed_risk')
self._since_number_of_days: int = self.edge_config.get('calculate_since_number_of_days', 14)
self._last_updated: int = 0 # Timestamp of pairs last updated time
self._refresh_pairs = True
self._stoploss_range_min = float(self.edge_config.get('stoploss_range_min', -0.01))
self._stoploss_range_max = float(self.edge_config.get('stoploss_range_max', -0.05))
self._stoploss_range_step = float(self.edge_config.get('stoploss_range_step', -0.001))
# calculating stoploss range
self._stoploss_range = np.arange(
self._stoploss_range_min,
self._stoploss_range_max,
self._stoploss_range_step
)
self._timerange: TimeRange = TimeRange.parse_timerange("%s-" % arrow.now().shift(
days=-1 * self._since_number_of_days).format('YYYYMMDD'))
if config.get('fee'):
self.fee = config['fee']
else:
self.fee = self.exchange.get_fee(symbol=self.config['exchange']['pair_whitelist'][0])
def calculate(self) -> bool:
pairs = self.config['exchange']['pair_whitelist']
heartbeat = self.edge_config.get('process_throttle_secs')
if (self._last_updated > 0) and (
self._last_updated + heartbeat > arrow.utcnow().timestamp):
return False
data: Dict[str, Any] = {}
logger.info('Using stake_currency: %s ...', self.config['stake_currency'])
logger.info('Using local backtesting data (using whitelist in given config) ...')
if self._refresh_pairs:
history.refresh_data(
datadir=self.config['datadir'],
pairs=pairs,
exchange=self.exchange,
timeframe=self.strategy.ticker_interval,
timerange=self._timerange,
)
data = history.load_data(
datadir=self.config['datadir'],
pairs=pairs,
timeframe=self.strategy.ticker_interval,
timerange=self._timerange,
startup_candles=self.strategy.startup_candle_count,
)
if not data:
# Reinitializing cached pairs
self._cached_pairs = {}
logger.critical("No data found. Edge is stopped ...")
return False
preprocessed = self.strategy.tickerdata_to_dataframe(data)
# Print timeframe
min_date, max_date = history.get_timerange(preprocessed)
logger.info(
'Measuring data from %s up to %s (%s days) ...',
min_date.isoformat(),
max_date.isoformat(),
(max_date - min_date).days
)
headers = ['date', 'buy', 'open', 'close', 'sell', 'high', 'low']
trades: list = []
for pair, pair_data in preprocessed.items():
# Sorting dataframe by date and reset index
pair_data = pair_data.sort_values(by=['date'])
pair_data = pair_data.reset_index(drop=True)
ticker_data = self.strategy.advise_sell(
self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()
trades += self._find_trades_for_stoploss_range(ticker_data, pair, self._stoploss_range)
# If no trade found then exit
if len(trades) == 0:
logger.info("No trades found.")
return False
# Fill missing, calculable columns, profit, duration , abs etc.
trades_df = self._fill_calculable_fields(DataFrame(trades))
self._cached_pairs = self._process_expectancy(trades_df)
self._last_updated = arrow.utcnow().timestamp
return True
def stake_amount(self, pair: str, free_capital: float,
total_capital: float, capital_in_trade: float) -> float:
stoploss = self.stoploss(pair)
available_capital = (total_capital + capital_in_trade) * self._capital_percentage
allowed_capital_at_risk = available_capital * self._allowed_risk
max_position_size = abs(allowed_capital_at_risk / stoploss)
position_size = min(max_position_size, free_capital)
if pair in self._cached_pairs:
logger.info(
'winrate: %s, expectancy: %s, position size: %s, pair: %s,'
' capital in trade: %s, free capital: %s, total capital: %s,'
' stoploss: %s, available capital: %s.',
self._cached_pairs[pair].winrate,
self._cached_pairs[pair].expectancy,
position_size, pair,
capital_in_trade, free_capital, total_capital,
stoploss, available_capital
)
return round(position_size, 15)
def stoploss(self, pair: str) -> float:
if pair in self._cached_pairs:
return self._cached_pairs[pair].stoploss
else:
logger.warning('tried to access stoploss of a non-existing pair, '
'strategy stoploss is returned instead.')
return self.strategy.stoploss
def adjust(self, pairs) -> list:
"""
Filters out and sorts "pairs" according to Edge calculated pairs
"""
final = []
for pair, info in self._cached_pairs.items():
if info.expectancy > float(self.edge_config.get('minimum_expectancy', 0.2)) and \
info.winrate > float(self.edge_config.get('minimum_winrate', 0.60)) and \
pair in pairs:
final.append(pair)
if self._final_pairs != final:
self._final_pairs = final
if self._final_pairs:
logger.info(
'Minimum expectancy and minimum winrate are met only for %s,'
' so other pairs are filtered out.',
self._final_pairs
)
else:
logger.info(
'Edge removed all pairs as no pair with minimum expectancy '
'and minimum winrate was found !'
)
return self._final_pairs
def accepted_pairs(self) -> list:
"""
return a list of accepted pairs along with their winrate, expectancy and stoploss
"""
final = []
for pair, info in self._cached_pairs.items():
if info.expectancy > float(self.edge_config.get('minimum_expectancy', 0.2)) and \
info.winrate > float(self.edge_config.get('minimum_winrate', 0.60)):
final.append({
'Pair': pair,
'Winrate': info.winrate,
'Expectancy': info.expectancy,
'Stoploss': info.stoploss,
})
return final
def _fill_calculable_fields(self, result: DataFrame) -> DataFrame:
"""
The result frame contains a number of columns that are calculable
from other columns. These are left blank till all rows are added,
to be populated in single vector calls.
Columns to be populated are:
- Profit
- trade duration
- profit abs
:param result Dataframe
:return: result Dataframe
"""
# stake and fees
# stake = 0.015
# 0.05% is 0.0005
# fee = 0.001
# we set stake amount to an arbitrary amount.
# as it doesn't change the calculation.
# all returned values are relative. they are percentages.
stake = 0.015
fee = self.fee
open_fee = fee / 2
close_fee = fee / 2
result['trade_duration'] = result['close_time'] - result['open_time']
result['trade_duration'] = result['trade_duration'].map(
lambda x: int(x.total_seconds() / 60))
# Spends, Takes, Profit, Absolute Profit
# Buy Price
result['buy_vol'] = stake / result['open_rate'] # How many target are we buying
result['buy_fee'] = stake * open_fee
result['buy_spend'] = stake + result['buy_fee'] # How much we're spending
# Sell price
result['sell_sum'] = result['buy_vol'] * result['close_rate']
result['sell_fee'] = result['sell_sum'] * close_fee
result['sell_take'] = result['sell_sum'] - result['sell_fee']
# profit_percent
result['profit_percent'] = (result['sell_take'] - result['buy_spend']) / result['buy_spend']
# Absolute profit
result['profit_abs'] = result['sell_take'] - result['buy_spend']
return result
def _process_expectancy(self, results: DataFrame) -> Dict[str, Any]:
"""
This calculates WinRate, Required Risk Reward, Risk Reward and Expectancy of all pairs
The calulation will be done per pair and per strategy.
"""
# Removing pairs having less than min_trades_number
min_trades_number = self.edge_config.get('min_trade_number', 10)
results = results.groupby(['pair', 'stoploss']).filter(lambda x: len(x) > min_trades_number)
###################################
# Removing outliers (Only Pumps) from the dataset
# The method to detect outliers is to calculate standard deviation
# Then every value more than (standard deviation + 2*average) is out (pump)
#
# Removing Pumps
if self.edge_config.get('remove_pumps', False):
results = results.groupby(['pair', 'stoploss']).apply(
lambda x: x[x['profit_abs'] < 2 * x['profit_abs'].std() + x['profit_abs'].mean()])
##########################################################################
# Removing trades having a duration more than X minutes (set in config)
max_trade_duration = self.edge_config.get('max_trade_duration_minute', 1440)
results = results[results.trade_duration < max_trade_duration]
#######################################################################
if results.empty:
return {}
groupby_aggregator = {
'profit_abs': [
('nb_trades', 'count'), # number of all trades
('profit_sum', lambda x: x[x > 0].sum()), # cumulative profit of all winning trades
('loss_sum', lambda x: abs(x[x < 0].sum())), # cumulative loss of all losing trades
('nb_win_trades', lambda x: x[x > 0].count()) # number of winning trades
],
'trade_duration': [('avg_trade_duration', 'mean')]
}
# Group by (pair and stoploss) by applying above aggregator
df = results.groupby(['pair', 'stoploss'])['profit_abs', 'trade_duration'].agg(
groupby_aggregator).reset_index(col_level=1)
# Dropping level 0 as we don't need it
df.columns = df.columns.droplevel(0)
# Calculating number of losing trades, average win and average loss
df['nb_loss_trades'] = df['nb_trades'] - df['nb_win_trades']
df['average_win'] = df['profit_sum'] / df['nb_win_trades']
df['average_loss'] = df['loss_sum'] / df['nb_loss_trades']
# Win rate = number of profitable trades / number of trades
df['winrate'] = df['nb_win_trades'] / df['nb_trades']
# risk_reward_ratio = average win / average loss
df['risk_reward_ratio'] = df['average_win'] / df['average_loss']
# required_risk_reward = (1 / winrate) - 1
df['required_risk_reward'] = (1 / df['winrate']) - 1
# expectancy = (risk_reward_ratio * winrate) - (lossrate)
df['expectancy'] = (df['risk_reward_ratio'] * df['winrate']) - (1 - df['winrate'])
# sort by expectancy and stoploss
df = df.sort_values(by=['expectancy', 'stoploss'], ascending=False).groupby(
'pair').first().sort_values(by=['expectancy'], ascending=False).reset_index()
final = {}
for x in df.itertuples():
final[x.pair] = PairInfo(
x.stoploss,
x.winrate,
x.risk_reward_ratio,
x.required_risk_reward,
x.expectancy,
x.nb_trades,
x.avg_trade_duration
)
# Returning a list of pairs in order of "expectancy"
return final
def _find_trades_for_stoploss_range(self, ticker_data, pair, stoploss_range):
buy_column = ticker_data['buy'].values
sell_column = ticker_data['sell'].values
date_column = ticker_data['date'].values
ohlc_columns = ticker_data[['open', 'high', 'low', 'close']].values
result: list = []
for stoploss in stoploss_range:
result += self._detect_next_stop_or_sell_point(
buy_column, sell_column, date_column, ohlc_columns, round(stoploss, 6), pair
)
return result
def _detect_next_stop_or_sell_point(self, buy_column, sell_column, date_column,
ohlc_columns, stoploss, pair):
"""
Iterate through ohlc_columns in order to find the next trade
Next trade opens from the first buy signal noticed to
The sell or stoploss signal after it.
It then cuts OHLC, buy_column, sell_column and date_column.
Cut from (the exit trade index) + 1.
Author: https://github.com/mishaker
"""
result: list = []
start_point = 0
while True:
open_trade_index = utf1st.find_1st(buy_column, 1, utf1st.cmp_equal)
# Return empty if we don't find trade entry (i.e. buy==1) or
# we find a buy but at the end of array
if open_trade_index == -1 or open_trade_index == len(buy_column) - 1:
break
else:
# When a buy signal is seen,
# trade opens in reality on the next candle
open_trade_index += 1
stop_price_percentage = stoploss + 1
open_price = ohlc_columns[open_trade_index, 0]
stop_price = (open_price * stop_price_percentage)
# Searching for the index where stoploss is hit
stop_index = utf1st.find_1st(
ohlc_columns[open_trade_index:, 2], stop_price, utf1st.cmp_smaller)
# If we don't find it then we assume stop_index will be far in future (infinite number)
if stop_index == -1:
stop_index = float('inf')
# Searching for the index where sell is hit
sell_index = utf1st.find_1st(sell_column[open_trade_index:], 1, utf1st.cmp_equal)
# If we don't find it then we assume sell_index will be far in future (infinite number)
if sell_index == -1:
sell_index = float('inf')
# Check if we don't find any stop or sell point (in that case trade remains open)
# It is not interesting for Edge to consider it so we simply ignore the trade
# And stop iterating there is no more entry
if stop_index == sell_index == float('inf'):
break
if stop_index <= sell_index:
exit_index = open_trade_index + stop_index
exit_type = SellType.STOP_LOSS
exit_price = stop_price
elif stop_index > sell_index:
# If exit is SELL then we exit at the next candle
exit_index = open_trade_index + sell_index + 1
# Check if we have the next candle
if len(ohlc_columns) - 1 < exit_index:
break
exit_type = SellType.SELL_SIGNAL
exit_price = ohlc_columns[exit_index, 0]
trade = {'pair': pair,
'stoploss': stoploss,
'profit_percent': '',
'profit_abs': '',
'open_time': date_column[open_trade_index],
'close_time': date_column[exit_index],
'open_index': start_point + open_trade_index,
'close_index': start_point + exit_index,
'trade_duration': '',
'open_rate': round(open_price, 15),
'close_rate': round(exit_price, 15),
'exit_type': exit_type
}
result.append(trade)
# Giving a view of exit_index till the end of array
buy_column = buy_column[exit_index:]
sell_column = sell_column[exit_index:]
date_column = date_column[exit_index:]
ohlc_columns = ohlc_columns[exit_index:]
start_point += exit_index
return result
from .edge_positioning import Edge, PairInfo # noqa: F401

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# pragma pylint: disable=W0603
""" Edge positioning package """
import logging
from typing import Any, Dict, NamedTuple
import arrow
import numpy as np
import utils_find_1st as utf1st
from pandas import DataFrame
from freqtrade import constants
from freqtrade.configuration import TimeRange
from freqtrade.data import history
from freqtrade.exceptions import OperationalException
from freqtrade.strategy.interface import SellType
logger = logging.getLogger(__name__)
class PairInfo(NamedTuple):
stoploss: float
winrate: float
risk_reward_ratio: float
required_risk_reward: float
expectancy: float
nb_trades: int
avg_trade_duration: float
class Edge:
"""
Calculates Win Rate, Risk Reward Ratio, Expectancy
against historical data for a give set of markets and a strategy
it then adjusts stoploss and position size accordingly
and force it into the strategy
Author: https://github.com/mishaker
"""
config: Dict = {}
_cached_pairs: Dict[str, Any] = {} # Keeps a list of pairs
def __init__(self, config: Dict[str, Any], exchange, strategy) -> None:
self.config = config
self.exchange = exchange
self.strategy = strategy
self.edge_config = self.config.get('edge', {})
self._cached_pairs: Dict[str, Any] = {} # Keeps a list of pairs
self._final_pairs: list = []
# checking max_open_trades. it should be -1 as with Edge
# the number of trades is determined by position size
if self.config['max_open_trades'] != float('inf'):
logger.critical('max_open_trades should be -1 in config !')
if self.config['stake_amount'] != constants.UNLIMITED_STAKE_AMOUNT:
raise OperationalException('Edge works only with unlimited stake amount')
# Deprecated capital_available_percentage. Will use tradable_balance_ratio in the future.
self._capital_percentage: float = self.edge_config.get(
'capital_available_percentage', self.config['tradable_balance_ratio'])
self._allowed_risk: float = self.edge_config.get('allowed_risk')
self._since_number_of_days: int = self.edge_config.get('calculate_since_number_of_days', 14)
self._last_updated: int = 0 # Timestamp of pairs last updated time
self._refresh_pairs = True
self._stoploss_range_min = float(self.edge_config.get('stoploss_range_min', -0.01))
self._stoploss_range_max = float(self.edge_config.get('stoploss_range_max', -0.05))
self._stoploss_range_step = float(self.edge_config.get('stoploss_range_step', -0.001))
# calculating stoploss range
self._stoploss_range = np.arange(
self._stoploss_range_min,
self._stoploss_range_max,
self._stoploss_range_step
)
self._timerange: TimeRange = TimeRange.parse_timerange("%s-" % arrow.now().shift(
days=-1 * self._since_number_of_days).format('YYYYMMDD'))
if config.get('fee'):
self.fee = config['fee']
else:
self.fee = self.exchange.get_fee(symbol=self.config['exchange']['pair_whitelist'][0])
def calculate(self) -> bool:
pairs = self.config['exchange']['pair_whitelist']
heartbeat = self.edge_config.get('process_throttle_secs')
if (self._last_updated > 0) and (
self._last_updated + heartbeat > arrow.utcnow().timestamp):
return False
data: Dict[str, Any] = {}
logger.info('Using stake_currency: %s ...', self.config['stake_currency'])
logger.info('Using local backtesting data (using whitelist in given config) ...')
if self._refresh_pairs:
history.refresh_data(
datadir=self.config['datadir'],
pairs=pairs,
exchange=self.exchange,
timeframe=self.strategy.ticker_interval,
timerange=self._timerange,
)
data = history.load_data(
datadir=self.config['datadir'],
pairs=pairs,
timeframe=self.strategy.ticker_interval,
timerange=self._timerange,
startup_candles=self.strategy.startup_candle_count,
)
if not data:
# Reinitializing cached pairs
self._cached_pairs = {}
logger.critical("No data found. Edge is stopped ...")
return False
preprocessed = self.strategy.tickerdata_to_dataframe(data)
# Print timeframe
min_date, max_date = history.get_timerange(preprocessed)
logger.info(
'Measuring data from %s up to %s (%s days) ...',
min_date.isoformat(),
max_date.isoformat(),
(max_date - min_date).days
)
headers = ['date', 'buy', 'open', 'close', 'sell', 'high', 'low']
trades: list = []
for pair, pair_data in preprocessed.items():
# Sorting dataframe by date and reset index
pair_data = pair_data.sort_values(by=['date'])
pair_data = pair_data.reset_index(drop=True)
ticker_data = self.strategy.advise_sell(
self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()
trades += self._find_trades_for_stoploss_range(ticker_data, pair, self._stoploss_range)
# If no trade found then exit
if len(trades) == 0:
logger.info("No trades found.")
return False
# Fill missing, calculable columns, profit, duration , abs etc.
trades_df = self._fill_calculable_fields(DataFrame(trades))
self._cached_pairs = self._process_expectancy(trades_df)
self._last_updated = arrow.utcnow().timestamp
return True
def stake_amount(self, pair: str, free_capital: float,
total_capital: float, capital_in_trade: float) -> float:
stoploss = self.stoploss(pair)
available_capital = (total_capital + capital_in_trade) * self._capital_percentage
allowed_capital_at_risk = available_capital * self._allowed_risk
max_position_size = abs(allowed_capital_at_risk / stoploss)
position_size = min(max_position_size, free_capital)
if pair in self._cached_pairs:
logger.info(
'winrate: %s, expectancy: %s, position size: %s, pair: %s,'
' capital in trade: %s, free capital: %s, total capital: %s,'
' stoploss: %s, available capital: %s.',
self._cached_pairs[pair].winrate,
self._cached_pairs[pair].expectancy,
position_size, pair,
capital_in_trade, free_capital, total_capital,
stoploss, available_capital
)
return round(position_size, 15)
def stoploss(self, pair: str) -> float:
if pair in self._cached_pairs:
return self._cached_pairs[pair].stoploss
else:
logger.warning('tried to access stoploss of a non-existing pair, '
'strategy stoploss is returned instead.')
return self.strategy.stoploss
def adjust(self, pairs) -> list:
"""
Filters out and sorts "pairs" according to Edge calculated pairs
"""
final = []
for pair, info in self._cached_pairs.items():
if info.expectancy > float(self.edge_config.get('minimum_expectancy', 0.2)) and \
info.winrate > float(self.edge_config.get('minimum_winrate', 0.60)) and \
pair in pairs:
final.append(pair)
if self._final_pairs != final:
self._final_pairs = final
if self._final_pairs:
logger.info(
'Minimum expectancy and minimum winrate are met only for %s,'
' so other pairs are filtered out.',
self._final_pairs
)
else:
logger.info(
'Edge removed all pairs as no pair with minimum expectancy '
'and minimum winrate was found !'
)
return self._final_pairs
def accepted_pairs(self) -> list:
"""
return a list of accepted pairs along with their winrate, expectancy and stoploss
"""
final = []
for pair, info in self._cached_pairs.items():
if info.expectancy > float(self.edge_config.get('minimum_expectancy', 0.2)) and \
info.winrate > float(self.edge_config.get('minimum_winrate', 0.60)):
final.append({
'Pair': pair,
'Winrate': info.winrate,
'Expectancy': info.expectancy,
'Stoploss': info.stoploss,
})
return final
def _fill_calculable_fields(self, result: DataFrame) -> DataFrame:
"""
The result frame contains a number of columns that are calculable
from other columns. These are left blank till all rows are added,
to be populated in single vector calls.
Columns to be populated are:
- Profit
- trade duration
- profit abs
:param result Dataframe
:return: result Dataframe
"""
# stake and fees
# stake = 0.015
# 0.05% is 0.0005
# fee = 0.001
# we set stake amount to an arbitrary amount.
# as it doesn't change the calculation.
# all returned values are relative. they are percentages.
stake = 0.015
fee = self.fee
open_fee = fee / 2
close_fee = fee / 2
result['trade_duration'] = result['close_time'] - result['open_time']
result['trade_duration'] = result['trade_duration'].map(
lambda x: int(x.total_seconds() / 60))
# Spends, Takes, Profit, Absolute Profit
# Buy Price
result['buy_vol'] = stake / result['open_rate'] # How many target are we buying
result['buy_fee'] = stake * open_fee
result['buy_spend'] = stake + result['buy_fee'] # How much we're spending
# Sell price
result['sell_sum'] = result['buy_vol'] * result['close_rate']
result['sell_fee'] = result['sell_sum'] * close_fee
result['sell_take'] = result['sell_sum'] - result['sell_fee']
# profit_percent
result['profit_percent'] = (result['sell_take'] - result['buy_spend']) / result['buy_spend']
# Absolute profit
result['profit_abs'] = result['sell_take'] - result['buy_spend']
return result
def _process_expectancy(self, results: DataFrame) -> Dict[str, Any]:
"""
This calculates WinRate, Required Risk Reward, Risk Reward and Expectancy of all pairs
The calulation will be done per pair and per strategy.
"""
# Removing pairs having less than min_trades_number
min_trades_number = self.edge_config.get('min_trade_number', 10)
results = results.groupby(['pair', 'stoploss']).filter(lambda x: len(x) > min_trades_number)
###################################
# Removing outliers (Only Pumps) from the dataset
# The method to detect outliers is to calculate standard deviation
# Then every value more than (standard deviation + 2*average) is out (pump)
#
# Removing Pumps
if self.edge_config.get('remove_pumps', False):
results = results.groupby(['pair', 'stoploss']).apply(
lambda x: x[x['profit_abs'] < 2 * x['profit_abs'].std() + x['profit_abs'].mean()])
##########################################################################
# Removing trades having a duration more than X minutes (set in config)
max_trade_duration = self.edge_config.get('max_trade_duration_minute', 1440)
results = results[results.trade_duration < max_trade_duration]
#######################################################################
if results.empty:
return {}
groupby_aggregator = {
'profit_abs': [
('nb_trades', 'count'), # number of all trades
('profit_sum', lambda x: x[x > 0].sum()), # cumulative profit of all winning trades
('loss_sum', lambda x: abs(x[x < 0].sum())), # cumulative loss of all losing trades
('nb_win_trades', lambda x: x[x > 0].count()) # number of winning trades
],
'trade_duration': [('avg_trade_duration', 'mean')]
}
# Group by (pair and stoploss) by applying above aggregator
df = results.groupby(['pair', 'stoploss'])['profit_abs', 'trade_duration'].agg(
groupby_aggregator).reset_index(col_level=1)
# Dropping level 0 as we don't need it
df.columns = df.columns.droplevel(0)
# Calculating number of losing trades, average win and average loss
df['nb_loss_trades'] = df['nb_trades'] - df['nb_win_trades']
df['average_win'] = df['profit_sum'] / df['nb_win_trades']
df['average_loss'] = df['loss_sum'] / df['nb_loss_trades']
# Win rate = number of profitable trades / number of trades
df['winrate'] = df['nb_win_trades'] / df['nb_trades']
# risk_reward_ratio = average win / average loss
df['risk_reward_ratio'] = df['average_win'] / df['average_loss']
# required_risk_reward = (1 / winrate) - 1
df['required_risk_reward'] = (1 / df['winrate']) - 1
# expectancy = (risk_reward_ratio * winrate) - (lossrate)
df['expectancy'] = (df['risk_reward_ratio'] * df['winrate']) - (1 - df['winrate'])
# sort by expectancy and stoploss
df = df.sort_values(by=['expectancy', 'stoploss'], ascending=False).groupby(
'pair').first().sort_values(by=['expectancy'], ascending=False).reset_index()
final = {}
for x in df.itertuples():
final[x.pair] = PairInfo(
x.stoploss,
x.winrate,
x.risk_reward_ratio,
x.required_risk_reward,
x.expectancy,
x.nb_trades,
x.avg_trade_duration
)
# Returning a list of pairs in order of "expectancy"
return final
def _find_trades_for_stoploss_range(self, ticker_data, pair, stoploss_range):
buy_column = ticker_data['buy'].values
sell_column = ticker_data['sell'].values
date_column = ticker_data['date'].values
ohlc_columns = ticker_data[['open', 'high', 'low', 'close']].values
result: list = []
for stoploss in stoploss_range:
result += self._detect_next_stop_or_sell_point(
buy_column, sell_column, date_column, ohlc_columns, round(stoploss, 6), pair
)
return result
def _detect_next_stop_or_sell_point(self, buy_column, sell_column, date_column,
ohlc_columns, stoploss, pair):
"""
Iterate through ohlc_columns in order to find the next trade
Next trade opens from the first buy signal noticed to
The sell or stoploss signal after it.
It then cuts OHLC, buy_column, sell_column and date_column.
Cut from (the exit trade index) + 1.
Author: https://github.com/mishaker
"""
result: list = []
start_point = 0
while True:
open_trade_index = utf1st.find_1st(buy_column, 1, utf1st.cmp_equal)
# Return empty if we don't find trade entry (i.e. buy==1) or
# we find a buy but at the end of array
if open_trade_index == -1 or open_trade_index == len(buy_column) - 1:
break
else:
# When a buy signal is seen,
# trade opens in reality on the next candle
open_trade_index += 1
stop_price_percentage = stoploss + 1
open_price = ohlc_columns[open_trade_index, 0]
stop_price = (open_price * stop_price_percentage)
# Searching for the index where stoploss is hit
stop_index = utf1st.find_1st(
ohlc_columns[open_trade_index:, 2], stop_price, utf1st.cmp_smaller)
# If we don't find it then we assume stop_index will be far in future (infinite number)
if stop_index == -1:
stop_index = float('inf')
# Searching for the index where sell is hit
sell_index = utf1st.find_1st(sell_column[open_trade_index:], 1, utf1st.cmp_equal)
# If we don't find it then we assume sell_index will be far in future (infinite number)
if sell_index == -1:
sell_index = float('inf')
# Check if we don't find any stop or sell point (in that case trade remains open)
# It is not interesting for Edge to consider it so we simply ignore the trade
# And stop iterating there is no more entry
if stop_index == sell_index == float('inf'):
break
if stop_index <= sell_index:
exit_index = open_trade_index + stop_index
exit_type = SellType.STOP_LOSS
exit_price = stop_price
elif stop_index > sell_index:
# If exit is SELL then we exit at the next candle
exit_index = open_trade_index + sell_index + 1
# Check if we have the next candle
if len(ohlc_columns) - 1 < exit_index:
break
exit_type = SellType.SELL_SIGNAL
exit_price = ohlc_columns[exit_index, 0]
trade = {'pair': pair,
'stoploss': stoploss,
'profit_percent': '',
'profit_abs': '',
'open_time': date_column[open_trade_index],
'close_time': date_column[exit_index],
'open_index': start_point + open_trade_index,
'close_index': start_point + exit_index,
'trade_duration': '',
'open_rate': round(open_price, 15),
'close_rate': round(exit_price, 15),
'exit_type': exit_type
}
result.append(trade)
# Giving a view of exit_index till the end of array
buy_column = buy_column[exit_index:]
sell_column = sell_column[exit_index:]
date_column = date_column[exit_index:]
ohlc_columns = ohlc_columns[exit_index:]
start_point += exit_index
return result

2
freqtrade/main.py
View File

@ -14,7 +14,7 @@ if sys.version_info < (3, 6):
import logging
from typing import Any, List
from freqtrade.configuration import Arguments
from freqtrade.commands import Arguments
logger = logging.getLogger('freqtrade')

102
freqtrade/optimize/__init__.py
View File

@ -1,102 +0,0 @@
import logging
from typing import Any, Dict
from freqtrade import constants
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.state import RunMode
from freqtrade.utils import setup_utils_configuration
logger = logging.getLogger(__name__)
def setup_configuration(args: Dict[str, Any], method: RunMode) -> Dict[str, Any]:
"""
Prepare the configuration for the Hyperopt module
:param args: Cli args from Arguments()
:return: Configuration
"""
config = setup_utils_configuration(args, method)
if method == RunMode.BACKTEST:
if config['stake_amount'] == constants.UNLIMITED_STAKE_AMOUNT:
raise DependencyException('stake amount could not be "%s" for backtesting' %
constants.UNLIMITED_STAKE_AMOUNT)
return config
def start_backtesting(args: Dict[str, Any]) -> None:
"""
Start Backtesting script
:param args: Cli args from Arguments()
:return: None
"""
# Import here to avoid loading backtesting module when it's not used
from freqtrade.optimize.backtesting import Backtesting
# Initialize configuration
config = setup_configuration(args, RunMode.BACKTEST)
logger.info('Starting freqtrade in Backtesting mode')
# Initialize backtesting object
backtesting = Backtesting(config)
backtesting.start()
def start_hyperopt(args: Dict[str, Any]) -> None:
"""
Start hyperopt script
:param args: Cli args from Arguments()
:return: None
"""
# Import here to avoid loading hyperopt module when it's not used
try:
from filelock import FileLock, Timeout
from freqtrade.optimize.hyperopt import Hyperopt
except ImportError as e:
raise OperationalException(
f"{e}. Please ensure that the hyperopt dependencies are installed.") from e
# Initialize configuration
config = setup_configuration(args, RunMode.HYPEROPT)
logger.info('Starting freqtrade in Hyperopt mode')
lock = FileLock(Hyperopt.get_lock_filename(config))
try:
with lock.acquire(timeout=1):
# Remove noisy log messages
logging.getLogger('hyperopt.tpe').setLevel(logging.WARNING)
logging.getLogger('filelock').setLevel(logging.WARNING)
# Initialize backtesting object
hyperopt = Hyperopt(config)
hyperopt.start()
except Timeout:
logger.info("Another running instance of freqtrade Hyperopt detected.")
logger.info("Simultaneous execution of multiple Hyperopt commands is not supported. "
"Hyperopt module is resource hungry. Please run your Hyperopt sequentially "
"or on separate machines.")
logger.info("Quitting now.")
# TODO: return False here in order to help freqtrade to exit
# with non-zero exit code...
# Same in Edge and Backtesting start() functions.
def start_edge(args: Dict[str, Any]) -> None:
"""
Start Edge script
:param args: Cli args from Arguments()
:return: None
"""
from freqtrade.optimize.edge_cli import EdgeCli
# Initialize configuration
config = setup_configuration(args, RunMode.EDGE)
logger.info('Starting freqtrade in Edge mode')
# Initialize Edge object
edge_cli = EdgeCli(config)
edge_cli.start()

53
freqtrade/optimize/backtesting.py
View File

@ -279,30 +279,28 @@ class Backtesting:
return bt_res
return None
def backtest(self, args: Dict) -> DataFrame:
def backtest(self, processed: Dict, stake_amount: float,
start_date, end_date,
max_open_trades: int = 0, position_stacking: bool = False) -> DataFrame:
"""
Implements backtesting functionality
Implement backtesting functionality
NOTE: This method is used by Hyperopt at each iteration. Please keep it optimized.
Of course try to not have ugly code. By some accessor are sometime slower than functions.
Avoid, logging on this method
Avoid extensive logging in this method and functions it calls.
:param args: a dict containing:
stake_amount: btc amount to use for each trade
processed: a processed dictionary with format {pair, data}
max_open_trades: maximum number of concurrent trades (default: 0, disabled)
position_stacking: do we allow position stacking? (default: False)
:return: DataFrame
:param processed: a processed dictionary with format {pair, data}
:param stake_amount: amount to use for each trade
:param start_date: backtesting timerange start datetime
:param end_date: backtesting timerange end datetime
:param max_open_trades: maximum number of concurrent trades, <= 0 means unlimited
:param position_stacking: do we allow position stacking?
:return: DataFrame with trades (results of backtesting)
"""
# Arguments are long and noisy, so this is commented out.
# Uncomment if you need to debug the backtest() method.
# logger.debug(f"Start backtest, args: {args}")
processed = args['processed']
stake_amount = args['stake_amount']
max_open_trades = args.get('max_open_trades', 0)
position_stacking = args.get('position_stacking', False)
start_date = args['start_date']
end_date = args['end_date']
logger.debug(f"Run backtest, stake_amount: {stake_amount}, "
f"start_date: {start_date}, end_date: {end_date}, "
f"max_open_trades: {max_open_trades}, position_stacking: {position_stacking}"
)
trades = []
trade_count_lock: Dict = {}
@ -369,18 +367,21 @@ class Backtesting:
def start(self) -> None:
"""
Run a backtesting end-to-end
Run backtesting end-to-end
:return: None
"""
data: Dict[str, Any] = {}
logger.info('Using stake_currency: %s ...', self.config['stake_currency'])
logger.info('Using stake_amount: %s ...', self.config['stake_amount'])
# Use max_open_trades in backtesting, except --disable-max-market-positions is set
if self.config.get('use_max_market_positions', True):
max_open_trades = self.config['max_open_trades']
else:
logger.info('Ignoring max_open_trades (--disable-max-market-positions was used) ...')
max_open_trades = 0
position_stacking = self.config.get('position_stacking', False)
data, timerange = self.load_bt_data()
@ -403,14 +404,12 @@ class Backtesting:
)
# Execute backtest and print results
all_results[self.strategy.get_strategy_name()] = self.backtest(
{
'stake_amount': self.config.get('stake_amount'),
'processed': preprocessed,
'max_open_trades': max_open_trades,
'position_stacking': self.config.get('position_stacking', False),
'start_date': min_date,
'end_date': max_date,
}
processed=preprocessed,
stake_amount=self.config['stake_amount'],
start_date=min_date,
end_date=max_date,
max_open_trades=max_open_trades,
position_stacking=position_stacking,
)
for strategy, results in all_results.items():

14
freqtrade/optimize/hyperopt.py
View File

@ -372,14 +372,12 @@ class Hyperopt:
min_date, max_date = get_timerange(processed)
backtesting_results = self.backtesting.backtest(
{
'stake_amount': self.config['stake_amount'],
'processed': processed,
'max_open_trades': self.max_open_trades,
'position_stacking': self.position_stacking,
'start_date': min_date,
'end_date': max_date,
}
processed=processed,
stake_amount=self.config['stake_amount'],
start_date=min_date,
end_date=max_date,
max_open_trades=self.max_open_trades,
position_stacking=self.position_stacking,
)
return self._get_results_dict(backtesting_results, min_date, max_date,
params_dict, params_details)

482
freqtrade/utils.py
View File

@ -1,482 +0,0 @@
import csv
import logging
import sys
from collections import OrderedDict
from operator import itemgetter
from pathlib import Path
from typing import Any, Dict, List
import arrow
import rapidjson
from colorama import init as colorama_init
from tabulate import tabulate
from freqtrade.configuration import (Configuration, TimeRange,
remove_credentials,
validate_config_consistency)
from freqtrade.configuration.directory_operations import (copy_sample_files,
create_userdata_dir)
from freqtrade.constants import USERPATH_HYPEROPTS, USERPATH_STRATEGY
from freqtrade.data.history import (convert_trades_to_ohlcv,
refresh_backtest_ohlcv_data,
refresh_backtest_trades_data)
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import (available_exchanges, ccxt_exchanges,
market_is_active, symbol_is_pair)
from freqtrade.misc import plural, render_template
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
def setup_utils_configuration(args: Dict[str, Any], method: RunMode) -> Dict[str, Any]:
"""
Prepare the configuration for utils subcommands
:param args: Cli args from Arguments()
:return: Configuration
"""
configuration = Configuration(args, method)
config = configuration.get_config()
# Ensure we do not use Exchange credentials
remove_credentials(config)
validate_config_consistency(config)
return config
def start_trading(args: Dict[str, Any]) -> int:
"""
Main entry point for trading mode
"""
from freqtrade.worker import Worker
# Load and run worker
worker = None
try:
worker = Worker(args)
worker.run()
except KeyboardInterrupt:
logger.info('SIGINT received, aborting ...')
finally:
if worker:
logger.info("worker found ... calling exit")
worker.exit()
return 0
def start_list_exchanges(args: Dict[str, Any]) -> None:
"""
Print available exchanges
:param args: Cli args from Arguments()
:return: None
"""
exchanges = ccxt_exchanges() if args['list_exchanges_all'] else available_exchanges()
if args['print_one_column']:
print('\n'.join(exchanges))
else:
if args['list_exchanges_all']:
print(f"All exchanges supported by the ccxt library: {', '.join(exchanges)}")
else:
print(f"Exchanges available for Freqtrade: {', '.join(exchanges)}")
def start_create_userdir(args: Dict[str, Any]) -> None:
"""
Create "user_data" directory to contain user data strategies, hyperopt, ...)
:param args: Cli args from Arguments()
:return: None
"""
if "user_data_dir" in args and args["user_data_dir"]:
userdir = create_userdata_dir(args["user_data_dir"], create_dir=True)
copy_sample_files(userdir, overwrite=args["reset"])
else:
logger.warning("`create-userdir` requires --userdir to be set.")
sys.exit(1)
def deploy_new_strategy(strategy_name, strategy_path: Path, subtemplate: str):
"""
Deploy new strategy from template to strategy_path
"""
indicators = render_template(templatefile=f"subtemplates/indicators_{subtemplate}.j2",)
buy_trend = render_template(templatefile=f"subtemplates/buy_trend_{subtemplate}.j2",)
sell_trend = render_template(templatefile=f"subtemplates/sell_trend_{subtemplate}.j2",)
plot_config = render_template(templatefile=f"subtemplates/plot_config_{subtemplate}.j2",)
strategy_text = render_template(templatefile='base_strategy.py.j2',
arguments={"strategy": strategy_name,
"indicators": indicators,
"buy_trend": buy_trend,
"sell_trend": sell_trend,
"plot_config": plot_config,
})
logger.info(f"Writing strategy to `{strategy_path}`.")
strategy_path.write_text(strategy_text)
def start_new_strategy(args: Dict[str, Any]) -> None:
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
if "strategy" in args and args["strategy"]:
if args["strategy"] == "DefaultStrategy":
raise OperationalException("DefaultStrategy is not allowed as name.")
new_path = config['user_data_dir'] / USERPATH_STRATEGY / (args["strategy"] + ".py")
if new_path.exists():
raise OperationalException(f"`{new_path}` already exists. "
"Please choose another Strategy Name.")
deploy_new_strategy(args['strategy'], new_path, args['template'])
else:
raise OperationalException("`new-strategy` requires --strategy to be set.")
def deploy_new_hyperopt(hyperopt_name, hyperopt_path: Path, subtemplate: str):
"""
Deploys a new hyperopt template to hyperopt_path
"""
buy_guards = render_template(
templatefile=f"subtemplates/hyperopt_buy_guards_{subtemplate}.j2",)
sell_guards = render_template(
templatefile=f"subtemplates/hyperopt_sell_guards_{subtemplate}.j2",)
buy_space = render_template(
templatefile=f"subtemplates/hyperopt_buy_space_{subtemplate}.j2",)
sell_space = render_template(
templatefile=f"subtemplates/hyperopt_sell_space_{subtemplate}.j2",)
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,
})
logger.info(f"Writing hyperopt to `{hyperopt_path}`.")
hyperopt_path.write_text(strategy_text)
def start_new_hyperopt(args: Dict[str, Any]) -> None:
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
if "hyperopt" in args and args["hyperopt"]:
if args["hyperopt"] == "DefaultHyperopt":
raise OperationalException("DefaultHyperopt is not allowed as name.")
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 Strategy Name.")
deploy_new_hyperopt(args['hyperopt'], new_path, args['template'])
else:
raise OperationalException("`new-hyperopt` requires --hyperopt to be set.")
def start_download_data(args: Dict[str, Any]) -> None:
"""
Download data (former download_backtest_data.py script)
"""
config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
timerange = TimeRange()
if 'days' in config:
time_since = arrow.utcnow().shift(days=-config['days']).strftime("%Y%m%d")
timerange = TimeRange.parse_timerange(f'{time_since}-')
if 'pairs' not in config:
raise OperationalException(
"Downloading data requires a list of pairs. "
"Please check the documentation on how to configure this.")
logger.info(f'About to download pairs: {config["pairs"]}, '
f'intervals: {config["timeframes"]} to {config["datadir"]}')
pairs_not_available: List[str] = []
# Init exchange
exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config)
try:
if config.get('download_trades'):
pairs_not_available = refresh_backtest_trades_data(
exchange, pairs=config["pairs"], datadir=config['datadir'],
timerange=timerange, erase=config.get("erase"))
# Convert downloaded trade data to different timeframes
convert_trades_to_ohlcv(
pairs=config["pairs"], timeframes=config["timeframes"],
datadir=config['datadir'], timerange=timerange, erase=config.get("erase"))
else:
pairs_not_available = refresh_backtest_ohlcv_data(
exchange, pairs=config["pairs"], timeframes=config["timeframes"],
datadir=config['datadir'], timerange=timerange, erase=config.get("erase"))
except KeyboardInterrupt:
sys.exit("SIGINT received, aborting ...")
finally:
if pairs_not_available:
logger.info(f"Pairs [{','.join(pairs_not_available)}] not available "
f"on exchange {exchange.name}.")
def start_list_strategies(args: Dict[str, Any]) -> None:
"""
Print Strategies available in a directory
"""
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
directory = Path(config.get('strategy_path', config['user_data_dir'] / USERPATH_STRATEGY))
strategies = StrategyResolver.search_all_objects(directory)
# Sort alphabetically
strategies = sorted(strategies, key=lambda x: x['name'])
strats_to_print = [{'name': s['name'], 'location': s['location'].name} for s in strategies]
if args['print_one_column']:
print('\n'.join([s['name'] for s in strategies]))
else:
print(tabulate(strats_to_print, headers='keys', tablefmt='pipe'))
def start_list_timeframes(args: Dict[str, Any]) -> None:
"""
Print ticker intervals (timeframes) available on Exchange
"""
config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
# Do not use ticker_interval set in the config
config['ticker_interval'] = None
# Init exchange
exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config, validate=False)
if args['print_one_column']:
print('\n'.join(exchange.timeframes))
else:
print(f"Timeframes available for the exchange `{exchange.name}`: "
f"{', '.join(exchange.timeframes)}")
def start_list_markets(args: Dict[str, Any], pairs_only: bool = False) -> None:
"""
Print pairs/markets on the exchange
:param args: Cli args from Arguments()
:param pairs_only: if True print only pairs, otherwise print all instruments (markets)
:return: None
"""
config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
# Init exchange
exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config, validate=False)
# By default only active pairs/markets are to be shown
active_only = not args.get('list_pairs_all', False)
base_currencies = args.get('base_currencies', [])
quote_currencies = args.get('quote_currencies', [])
try:
pairs = exchange.get_markets(base_currencies=base_currencies,
quote_currencies=quote_currencies,
pairs_only=pairs_only,
active_only=active_only)
# Sort the pairs/markets by symbol
pairs = OrderedDict(sorted(pairs.items()))
except Exception as e:
raise OperationalException(f"Cannot get markets. Reason: {e}") from e
else:
summary_str = ((f"Exchange {exchange.name} has {len(pairs)} ") +
("active " if active_only else "") +
(plural(len(pairs), "pair" if pairs_only else "market")) +
(f" with {', '.join(base_currencies)} as base "
f"{plural(len(base_currencies), 'currency', 'currencies')}"
if base_currencies else "") +
(" and" if base_currencies and quote_currencies else "") +
(f" with {', '.join(quote_currencies)} as quote "
f"{plural(len(quote_currencies), 'currency', 'currencies')}"
if quote_currencies else ""))
headers = ["Id", "Symbol", "Base", "Quote", "Active",
*(['Is pair'] if not pairs_only else [])]
tabular_data = []
for _, v in pairs.items():
tabular_data.append({'Id': v['id'], 'Symbol': v['symbol'],
'Base': v['base'], 'Quote': v['quote'],
'Active': market_is_active(v),
**({'Is pair': symbol_is_pair(v['symbol'])}
if not pairs_only else {})})
if (args.get('print_one_column', False) or
args.get('list_pairs_print_json', False) or
args.get('print_csv', False)):
# Print summary string in the log in case of machine-readable
# regular formats.
logger.info(f"{summary_str}.")
else:
# Print empty string separating leading logs and output in case of
# human-readable formats.
print()
if len(pairs):
if args.get('print_list', False):
# print data as a list, with human-readable summary
print(f"{summary_str}: {', '.join(pairs.keys())}.")
elif args.get('print_one_column', False):
print('\n'.join(pairs.keys()))
elif args.get('list_pairs_print_json', False):
print(rapidjson.dumps(list(pairs.keys()), default=str))
elif args.get('print_csv', False):
writer = csv.DictWriter(sys.stdout, fieldnames=headers)
writer.writeheader()
writer.writerows(tabular_data)
else:
# print data as a table, with the human-readable summary
print(f"{summary_str}:")
print(tabulate(tabular_data, headers='keys', tablefmt='pipe'))
elif not (args.get('print_one_column', False) or
args.get('list_pairs_print_json', False) or
args.get('print_csv', False)):
print(f"{summary_str}.")
def start_test_pairlist(args: Dict[str, Any]) -> None:
"""
Test Pairlist configuration
"""
from freqtrade.pairlist.pairlistmanager import PairListManager
config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config, validate=False)
quote_currencies = args.get('quote_currencies')
if not quote_currencies:
quote_currencies = [config.get('stake_currency')]
results = {}
for curr in quote_currencies:
config['stake_currency'] = curr
# Do not use ticker_interval set in the config
pairlists = PairListManager(exchange, config)
pairlists.refresh_pairlist()
results[curr] = pairlists.whitelist
for curr, pairlist in results.items():
if not args.get('print_one_column', False):
print(f"Pairs for {curr}: ")
if args.get('print_one_column', False):
print('\n'.join(pairlist))
elif args.get('list_pairs_print_json', False):
print(rapidjson.dumps(list(pairlist), default=str))
else:
print(pairlist)
def start_hyperopt_list(args: Dict[str, Any]) -> None:
"""
List hyperopt epochs previously evaluated
"""
from freqtrade.optimize.hyperopt import Hyperopt
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
only_best = config.get('hyperopt_list_best', False)
only_profitable = config.get('hyperopt_list_profitable', False)
print_colorized = config.get('print_colorized', False)
print_json = config.get('print_json', False)
no_details = config.get('hyperopt_list_no_details', False)
no_header = False
trials_file = (config['user_data_dir'] /
'hyperopt_results' / 'hyperopt_results.pickle')
# Previous evaluations
trials = Hyperopt.load_previous_results(trials_file)
total_epochs = len(trials)
trials = _hyperopt_filter_trials(trials, only_best, only_profitable)
# TODO: fetch the interval for epochs to print from the cli option
epoch_start, epoch_stop = 0, None
if print_colorized:
colorama_init(autoreset=True)
try:
# Human-friendly indexes used here (starting from 1)
for val in trials[epoch_start:epoch_stop]:
Hyperopt.print_results_explanation(val, total_epochs, not only_best, print_colorized)
except KeyboardInterrupt:
print('User interrupted..')
if trials and not no_details:
sorted_trials = sorted(trials, key=itemgetter('loss'))
results = sorted_trials[0]
Hyperopt.print_epoch_details(results, total_epochs, print_json, no_header)
def start_hyperopt_show(args: Dict[str, Any]) -> None:
"""
Show details of a hyperopt epoch previously evaluated
"""
from freqtrade.optimize.hyperopt import Hyperopt
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
only_best = config.get('hyperopt_list_best', False)
only_profitable = config.get('hyperopt_list_profitable', False)
no_header = config.get('hyperopt_show_no_header', False)
trials_file = (config['user_data_dir'] /
'hyperopt_results' / 'hyperopt_results.pickle')
# Previous evaluations
trials = Hyperopt.load_previous_results(trials_file)
total_epochs = len(trials)
trials = _hyperopt_filter_trials(trials, only_best, only_profitable)
trials_epochs = len(trials)
n = config.get('hyperopt_show_index', -1)
if n > trials_epochs:
raise OperationalException(
f"The index of the epoch to show should be less than {trials_epochs + 1}.")
if n < -trials_epochs:
raise OperationalException(
f"The index of the epoch to show should be greater than {-trials_epochs - 1}.")
# Translate epoch index from human-readable format to pythonic
if n > 0:
n -= 1
print_json = config.get('print_json', False)
if trials:
val = trials[n]
Hyperopt.print_epoch_details(val, total_epochs, print_json, no_header,
header_str="Epoch details")
def _hyperopt_filter_trials(trials: List, only_best: bool, only_profitable: bool) -> List:
"""
Filter our items from the list of hyperopt results
"""
if only_best:
trials = [x for x in trials if x['is_best']]
if only_profitable:
trials = [x for x in trials if x['results_metrics']['profit'] > 0]
logger.info(f"{len(trials)} " +
("best " if only_best else "") +
("profitable " if only_profitable else "") +
"epochs found.")
return trials

0
tests/commands/__init__.py Normal file
View File

40
tests/test_utils.py → tests/commands/test_commands.py
View File

@ -4,15 +4,15 @@ from unittest.mock import MagicMock, PropertyMock
import pytest
from freqtrade.commands import (start_create_userdir, start_download_data,
start_hyperopt_list, start_hyperopt_show,
start_list_exchanges, start_list_markets,
start_list_strategies, start_list_timeframes,
start_new_hyperopt, start_new_strategy,
start_test_pairlist, start_trading)
from freqtrade.configuration import setup_utils_configuration
from freqtrade.exceptions import OperationalException
from freqtrade.state import RunMode
from freqtrade.utils import (setup_utils_configuration, start_create_userdir,
start_download_data, start_hyperopt_list,
start_hyperopt_show, start_list_exchanges,
start_list_markets, start_list_strategies,
start_list_timeframes, start_new_hyperopt,
start_new_strategy, start_test_pairlist,
start_trading)
from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
patched_configuration_load_config_file)
@ -451,8 +451,8 @@ def test_create_datadir(caplog, mocker):
# Added assert here to analyze random test-failures ...
assert len(caplog.record_tuples) == 0
cud = mocker.patch("freqtrade.utils.create_userdata_dir", MagicMock())
csf = mocker.patch("freqtrade.utils.copy_sample_files", MagicMock())
cud = mocker.patch("freqtrade.commands.deploy_commands.create_userdata_dir", MagicMock())
csf = mocker.patch("freqtrade.commands.deploy_commands.copy_sample_files", MagicMock())
args = [
"create-userdir",
"--userdir",
@ -538,7 +538,7 @@ def test_start_new_hyperopt_no_arg(mocker, caplog):
def test_download_data_keyboardInterrupt(mocker, caplog, markets):
dl_mock = mocker.patch('freqtrade.utils.refresh_backtest_ohlcv_data',
dl_mock = mocker.patch('freqtrade.commands.data_commands.refresh_backtest_ohlcv_data',
MagicMock(side_effect=KeyboardInterrupt))
patch_exchange(mocker)
mocker.patch(
@ -556,7 +556,7 @@ def test_download_data_keyboardInterrupt(mocker, caplog, markets):
def test_download_data_no_markets(mocker, caplog):
dl_mock = mocker.patch('freqtrade.utils.refresh_backtest_ohlcv_data',
dl_mock = mocker.patch('freqtrade.commands.data_commands.refresh_backtest_ohlcv_data',
MagicMock(return_value=["ETH/BTC", "XRP/BTC"]))
patch_exchange(mocker, id='binance')
mocker.patch(
@ -574,7 +574,7 @@ def test_download_data_no_markets(mocker, caplog):
def test_download_data_no_exchange(mocker, caplog):
mocker.patch('freqtrade.utils.refresh_backtest_ohlcv_data',
mocker.patch('freqtrade.commands.data_commands.refresh_backtest_ohlcv_data',
MagicMock(return_value=["ETH/BTC", "XRP/BTC"]))
patch_exchange(mocker)
mocker.patch(
@ -594,7 +594,7 @@ def test_download_data_no_pairs(mocker, caplog):
mocker.patch.object(Path, "exists", MagicMock(return_value=False))
mocker.patch('freqtrade.utils.refresh_backtest_ohlcv_data',
mocker.patch('freqtrade.commands.data_commands.refresh_backtest_ohlcv_data',
MagicMock(return_value=["ETH/BTC", "XRP/BTC"]))
patch_exchange(mocker)
mocker.patch(
@ -613,9 +613,9 @@ def test_download_data_no_pairs(mocker, caplog):
def test_download_data_trades(mocker, caplog):
dl_mock = mocker.patch('freqtrade.utils.refresh_backtest_trades_data',
dl_mock = mocker.patch('freqtrade.commands.data_commands.refresh_backtest_trades_data',
MagicMock(return_value=[]))
convert_mock = mocker.patch('freqtrade.utils.convert_trades_to_ohlcv',
convert_mock = mocker.patch('freqtrade.commands.data_commands.convert_trades_to_ohlcv',
MagicMock(return_value=[]))
patch_exchange(mocker)
mocker.patch(
@ -639,7 +639,7 @@ def test_start_list_strategies(mocker, caplog, capsys):
args = [
"list-strategies",
"--strategy-path",
str(Path(__file__).parent / "strategy"),
str(Path(__file__).parent.parent / "strategy"),
"-1"
]
pargs = get_args(args)
@ -654,7 +654,7 @@ def test_start_list_strategies(mocker, caplog, capsys):
args = [
"list-strategies",
"--strategy-path",
str(Path(__file__).parent / "strategy"),
str(Path(__file__).parent.parent / "strategy"),
]
pargs = get_args(args)
# pargs['config'] = None
@ -665,11 +665,11 @@ def test_start_list_strategies(mocker, caplog, capsys):
assert "DefaultStrategy" in captured.out
def test_start_test_pairlist(mocker, caplog, markets, tickers, default_conf, capsys):
def test_start_test_pairlist(mocker, caplog, tickers, default_conf, capsys):
patch_exchange(mocker, mock_markets=True)
mocker.patch.multiple('freqtrade.exchange.Exchange',
markets=PropertyMock(return_value=markets),
exchange_has=MagicMock(return_value=True),
get_tickers=tickers
get_tickers=tickers,
)
default_conf['pairlists'] = [

2
tests/conftest.py
View File

@ -14,7 +14,7 @@ import pytest
from telegram import Chat, Message, Update
from freqtrade import constants, persistence
from freqtrade.configuration import Arguments
from freqtrade.commands import Arguments
from freqtrade.data.converter import parse_ticker_dataframe
from freqtrade.edge import Edge, PairInfo
from freqtrade.exchange import Exchange

12
tests/optimize/test_backtest_detail.py
View File

@ -382,13 +382,11 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
data_processed = {pair: frame.copy()}
min_date, max_date = get_timerange({pair: frame})
results = backtesting.backtest(
{
'stake_amount': default_conf['stake_amount'],
'processed': data_processed,
'max_open_trades': 10,
'start_date': min_date,
'end_date': max_date,
}
processed=data_processed,
stake_amount=default_conf['stake_amount'],
start_date=min_date,
end_date=max_date,
max_open_trades=10,
)
assert len(results) == len(data.trades)

85
tests/optimize/test_backtesting.py
View File

@ -12,13 +12,13 @@ from arrow import Arrow
from freqtrade import constants
from freqtrade.configuration import TimeRange
from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_backtesting
from freqtrade.data import history
from freqtrade.data.btanalysis import evaluate_result_multi
from freqtrade.data.converter import parse_ticker_dataframe
from freqtrade.data.dataprovider import DataProvider
from freqtrade.data.history import get_timerange
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.optimize import setup_configuration, start_backtesting
from freqtrade.optimize.backtesting import Backtesting
from freqtrade.state import RunMode
from freqtrade.strategy.default_strategy import DefaultStrategy
@ -103,14 +103,12 @@ def simple_backtest(config, contour, num_results, mocker, testdatadir) -> None:
min_date, max_date = get_timerange(processed)
assert isinstance(processed, dict)
results = backtesting.backtest(
{
'stake_amount': config['stake_amount'],
'processed': processed,
'max_open_trades': 1,
'position_stacking': False,
'start_date': min_date,
'end_date': max_date,
}
processed=processed,
stake_amount=config['stake_amount'],
start_date=min_date,
end_date=max_date,
max_open_trades=1,
position_stacking=False,
)
# results :: <class 'pandas.core.frame.DataFrame'>
assert len(results) == num_results
@ -132,7 +130,7 @@ def _load_pair_as_ticks(pair, tickfreq):
# FIX: fixturize this?
def _make_backtest_conf(mocker, datadir, conf=None, pair='UNITTEST/BTC', record=None):
def _make_backtest_conf(mocker, datadir, conf=None, pair='UNITTEST/BTC'):
data = history.load_data(datadir=datadir, timeframe='1m', pairs=[pair])
data = trim_dictlist(data, -201)
patch_exchange(mocker)
@ -140,13 +138,12 @@ def _make_backtest_conf(mocker, datadir, conf=None, pair='UNITTEST/BTC', record=
processed = backtesting.strategy.tickerdata_to_dataframe(data)
min_date, max_date = get_timerange(processed)
return {
'stake_amount': conf['stake_amount'],
'processed': processed,
'max_open_trades': 10,
'position_stacking': False,
'record': record,
'stake_amount': conf['stake_amount'],
'start_date': min_date,
'end_date': max_date,
'max_open_trades': 10,
'position_stacking': False,
}
@ -180,7 +177,7 @@ def _trend_alternate(dataframe=None, metadata=None):
# Unit tests
def test_setup_configuration_without_arguments(mocker, default_conf, caplog) -> None:
def test_setup_optimize_configuration_without_arguments(mocker, default_conf, caplog) -> None:
patched_configuration_load_config_file(mocker, default_conf)
args = [
@ -189,7 +186,7 @@ def test_setup_configuration_without_arguments(mocker, default_conf, caplog) ->
'--strategy', 'DefaultStrategy',
]
config = setup_configuration(get_args(args), RunMode.BACKTEST)
config = setup_optimize_configuration(get_args(args), RunMode.BACKTEST)
assert 'max_open_trades' in config
assert 'stake_currency' in config
assert 'stake_amount' in config
@ -230,7 +227,7 @@ def test_setup_bt_configuration_with_arguments(mocker, default_conf, caplog) ->
'--fee', '0',
]
config = setup_configuration(get_args(args), RunMode.BACKTEST)
config = setup_optimize_configuration(get_args(args), RunMode.BACKTEST)
assert 'max_open_trades' in config
assert 'stake_currency' in config
assert 'stake_amount' in config
@ -263,7 +260,7 @@ def test_setup_bt_configuration_with_arguments(mocker, default_conf, caplog) ->
assert log_has('Parameter --fee detected, setting fee to: {} ...'.format(config['fee']), caplog)
def test_setup_configuration_unlimited_stake_amount(mocker, default_conf, caplog) -> None:
def test_setup_optimize_configuration_unlimited_stake_amount(mocker, default_conf, caplog) -> None:
default_conf['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
patched_configuration_load_config_file(mocker, default_conf)
@ -275,7 +272,7 @@ def test_setup_configuration_unlimited_stake_amount(mocker, default_conf, caplog
]
with pytest.raises(DependencyException, match=r'.*stake amount.*'):
setup_configuration(get_args(args), RunMode.BACKTEST)
setup_optimize_configuration(get_args(args), RunMode.BACKTEST)
def test_start(mocker, fee, default_conf, caplog) -> None:
@ -422,14 +419,12 @@ def test_backtest(default_conf, fee, mocker, testdatadir) -> None:
data_processed = backtesting.strategy.tickerdata_to_dataframe(data)
min_date, max_date = get_timerange(data_processed)
results = backtesting.backtest(
{
'stake_amount': default_conf['stake_amount'],
'processed': data_processed,
'max_open_trades': 10,
'position_stacking': False,
'start_date': min_date,
'end_date': max_date,
}
processed=data_processed,
stake_amount=default_conf['stake_amount'],
start_date=min_date,
end_date=max_date,
max_open_trades=10,
position_stacking=False,
)
assert not results.empty
assert len(results) == 2
@ -478,14 +473,12 @@ def test_backtest_1min_ticker_interval(default_conf, fee, mocker, testdatadir) -
processed = backtesting.strategy.tickerdata_to_dataframe(data)
min_date, max_date = get_timerange(processed)
results = backtesting.backtest(
{
'stake_amount': default_conf['stake_amount'],
'processed': processed,
'max_open_trades': 1,
'position_stacking': False,
'start_date': min_date,
'end_date': max_date,
}
processed=processed,
stake_amount=default_conf['stake_amount'],
start_date=min_date,
end_date=max_date,
max_open_trades=1,
position_stacking=False,
)
assert not results.empty
assert len(results) == 1
@ -525,7 +518,7 @@ def test_backtest_clash_buy_sell(mocker, default_conf, testdatadir):
backtesting = Backtesting(default_conf)
backtesting.strategy.advise_buy = fun # Override
backtesting.strategy.advise_sell = fun # Override
results = backtesting.backtest(backtest_conf)
results = backtesting.backtest(**backtest_conf)
assert results.empty
@ -540,7 +533,7 @@ def test_backtest_only_sell(mocker, default_conf, testdatadir):
backtesting = Backtesting(default_conf)
backtesting.strategy.advise_buy = fun # Override
backtesting.strategy.advise_sell = fun # Override
results = backtesting.backtest(backtest_conf)
results = backtesting.backtest(**backtest_conf)
assert results.empty
@ -553,7 +546,7 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir):
backtesting = Backtesting(default_conf)
backtesting.strategy.advise_buy = _trend_alternate # Override
backtesting.strategy.advise_sell = _trend_alternate # Override
results = backtesting.backtest(backtest_conf)
results = backtesting.backtest(**backtest_conf)
backtesting._store_backtest_result("test_.json", results)
# 200 candles in backtest data
# won't buy on first (shifted by 1)
@ -598,15 +591,15 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
data_processed = backtesting.strategy.tickerdata_to_dataframe(data)
min_date, max_date = get_timerange(data_processed)
backtest_conf = {
'stake_amount': default_conf['stake_amount'],
'processed': data_processed,
'max_open_trades': 3,
'position_stacking': False,
'stake_amount': default_conf['stake_amount'],
'start_date': min_date,
'end_date': max_date,
'max_open_trades': 3,
'position_stacking': False,
}
results = backtesting.backtest(backtest_conf)
results = backtesting.backtest(**backtest_conf)
# Make sure we have parallel trades
assert len(evaluate_result_multi(results, '5m', 2)) > 0
@ -614,14 +607,14 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
assert len(evaluate_result_multi(results, '5m', 3)) == 0
backtest_conf = {
'stake_amount': default_conf['stake_amount'],
'processed': data_processed,
'max_open_trades': 1,
'position_stacking': False,
'stake_amount': default_conf['stake_amount'],
'start_date': min_date,
'end_date': max_date,
'max_open_trades': 1,
'position_stacking': False,
}
results = backtesting.backtest(backtest_conf)
results = backtesting.backtest(**backtest_conf)
assert len(evaluate_result_multi(results, '5m', 1)) == 0

8
tests/optimize/test_edge_cli.py
View File

@ -3,14 +3,14 @@
from unittest.mock import MagicMock
from freqtrade.optimize import setup_configuration, start_edge
from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_edge
from freqtrade.optimize.edge_cli import EdgeCli
from freqtrade.state import RunMode
from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
patched_configuration_load_config_file)
def test_setup_configuration_without_arguments(mocker, default_conf, caplog) -> None:
def test_setup_optimize_configuration_without_arguments(mocker, default_conf, caplog) -> None:
patched_configuration_load_config_file(mocker, default_conf)
args = [
@ -19,7 +19,7 @@ def test_setup_configuration_without_arguments(mocker, default_conf, caplog) ->
'--strategy', 'DefaultStrategy',
]
config = setup_configuration(get_args(args), RunMode.EDGE)
config = setup_optimize_configuration(get_args(args), RunMode.EDGE)
assert config['runmode'] == RunMode.EDGE
assert 'max_open_trades' in config
@ -53,7 +53,7 @@ def test_setup_edge_configuration_with_arguments(mocker, edge_conf, caplog) -> N
'--stoplosses=-0.01,-0.10,-0.001'
]
config = setup_configuration(get_args(args), RunMode.EDGE)
config = setup_optimize_configuration(get_args(args), RunMode.EDGE)
assert 'max_open_trades' in config
assert 'stake_currency' in config
assert 'stake_amount' in config

8
tests/optimize/test_hyperopt.py
View File

@ -9,10 +9,10 @@ import pytest
from arrow import Arrow
from filelock import Timeout
from freqtrade.exceptions import OperationalException
from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_hyperopt
from freqtrade.data.converter import parse_ticker_dataframe
from freqtrade.data.history import load_tickerdata_file
from freqtrade.optimize import setup_configuration, start_hyperopt
from freqtrade.exceptions import OperationalException
from freqtrade.optimize.default_hyperopt import DefaultHyperOpt
from freqtrade.optimize.default_hyperopt_loss import DefaultHyperOptLoss
from freqtrade.optimize.hyperopt import Hyperopt
@ -77,7 +77,7 @@ def test_setup_hyperopt_configuration_without_arguments(mocker, default_conf, ca
'--hyperopt', 'DefaultHyperOpt',
]
config = setup_configuration(get_args(args), RunMode.HYPEROPT)
config = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
assert 'max_open_trades' in config
assert 'stake_currency' in config
assert 'stake_amount' in config
@ -117,7 +117,7 @@ def test_setup_hyperopt_configuration_with_arguments(mocker, default_conf, caplo
'--print-all'
]
config = setup_configuration(get_args(args), RunMode.HYPEROPT)
config = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
assert 'max_open_trades' in config
assert 'stake_currency' in config
assert 'stake_amount' in config

4
tests/test_arguments.py
View File

@ -5,8 +5,8 @@ from unittest.mock import MagicMock
import pytest
from freqtrade.configuration import Arguments
from freqtrade.configuration.cli_options import check_int_positive
from freqtrade.commands import Arguments
from freqtrade.commands.cli_options import check_int_positive
# Parse common command-line-arguments. Used for all tools

3
tests/test_configuration.py
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@ -10,7 +10,8 @@ from unittest.mock import MagicMock
import pytest
from jsonschema import ValidationError
from freqtrade.configuration import (Arguments, Configuration, check_exchange,
from freqtrade.commands import Arguments
from freqtrade.configuration import (Configuration, check_exchange,
remove_credentials,
validate_config_consistency)
from freqtrade.configuration.config_validation import validate_config_schema

6
tests/test_main.py
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@ -5,7 +5,7 @@ from unittest.mock import MagicMock, PropertyMock
import pytest
from freqtrade.configuration import Arguments
from freqtrade.commands import Arguments
from freqtrade.exceptions import OperationalException, FreqtradeException
from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.main import main
@ -26,7 +26,7 @@ def test_parse_args_backtesting(mocker) -> None:
Test that main() can start backtesting and also ensure we can pass some specific arguments
further argument parsing is done in test_arguments.py
"""
backtesting_mock = mocker.patch('freqtrade.optimize.start_backtesting', MagicMock())
backtesting_mock = mocker.patch('freqtrade.commands.start_backtesting')
backtesting_mock.__name__ = PropertyMock("start_backtesting")
# it's sys.exit(0) at the end of backtesting
with pytest.raises(SystemExit):
@ -42,7 +42,7 @@ def test_parse_args_backtesting(mocker) -> None:
def test_main_start_hyperopt(mocker) -> None:
hyperopt_mock = mocker.patch('freqtrade.optimize.start_hyperopt', MagicMock())
hyperopt_mock = mocker.patch('freqtrade.commands.start_hyperopt', MagicMock())
hyperopt_mock.__name__ = PropertyMock("start_hyperopt")
# it's sys.exit(0) at the end of hyperopt
with pytest.raises(SystemExit):

2
tests/test_plotting.py
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@ -11,7 +11,7 @@ from freqtrade.configuration import TimeRange
from freqtrade.data import history
from freqtrade.data.btanalysis import create_cum_profit, load_backtest_data
from freqtrade.exceptions import OperationalException
from freqtrade.plot.plot_utils import start_plot_dataframe, start_plot_profit
from freqtrade.commands import start_plot_dataframe, start_plot_profit
from freqtrade.plot.plotting import (add_indicators, add_profit,
create_plotconfig,
generate_candlestick_graph,