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Merge branch 'develop' into agefilter-max-days-listed

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This commit is contained in:
Kevin Julian
2021-07-06 19:47:18 +07:00
committed by GitHub
parent 502c69dce3 dec523eef0
commit 0f3d34eaf4
35 changed files with 788 additions and 233 deletions
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5
freqtrade/commands/arguments.py
View File

@@ -29,7 +29,7 @@ ARGS_HYPEROPT = ARGS_COMMON_OPTIMIZE + ["hyperopt", "hyperopt_path",
"epochs", "spaces", "print_all",
"print_colorized", "print_json", "hyperopt_jobs",
"hyperopt_random_state", "hyperopt_min_trades",
"hyperopt_loss"]
"hyperopt_loss", "disableparamexport"]
ARGS_EDGE = ARGS_COMMON_OPTIMIZE + ["stoploss_range"]
@@ -85,7 +85,8 @@ ARGS_HYPEROPT_LIST = ["hyperopt_list_best", "hyperopt_list_profitable",
"hyperoptexportfilename", "export_csv"]
ARGS_HYPEROPT_SHOW = ["hyperopt_list_best", "hyperopt_list_profitable", "hyperopt_show_index",
"print_json", "hyperoptexportfilename", "hyperopt_show_no_header"]
"print_json", "hyperoptexportfilename", "hyperopt_show_no_header",
"disableparamexport"]
NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list-timeframes",
"list-markets", "list-pairs", "list-strategies", "list-data",

5
freqtrade/commands/cli_options.py
View File

@@ -178,6 +178,11 @@ AVAILABLE_CLI_OPTIONS = {
'Example: `--export-filename=user_data/backtest_results/backtest_today.json`',
metavar='PATH',
),
"disableparamexport": Arg(
'--disable-param-export',
help="Disable automatic hyperopt parameter export.",
action='store_true',
),
"fee": Arg(
'--fee',
help='Specify fee ratio. Will be applied twice (on trade entry and exit).',

5
freqtrade/commands/hyperopt_commands.py
View File

@@ -129,9 +129,12 @@ def start_hyperopt_show(args: Dict[str, Any]) -> None:
metrics = val['results_metrics']
if 'strategy_name' in metrics:
show_backtest_result(metrics['strategy_name'], metrics,
strategy_name = metrics['strategy_name']
show_backtest_result(strategy_name, metrics,
metrics['stake_currency'])
HyperoptTools.try_export_params(config, strategy_name, val)
HyperoptTools.show_epoch_details(val, total_epochs, print_json, no_header,
header_str="Epoch details")

2
freqtrade/configuration/configuration.py
View File

@@ -260,6 +260,8 @@ class Configuration:
self._args_to_config(config, argname='export',
logstring='Parameter --export detected: {} ...')
self._args_to_config(config, argname='disableparamexport',
logstring='Parameter --disableparamexport detected: {} ...')
# Edge section:
if 'stoploss_range' in self.args and self.args["stoploss_range"]:
txt_range = eval(self.args["stoploss_range"])

2
freqtrade/constants.py
View File

@@ -40,6 +40,7 @@ DEFAULT_DATAFRAME_COLUMNS = ['date', 'open', 'high', 'low', 'close', 'volume']
DEFAULT_TRADES_COLUMNS = ['timestamp', 'id', 'type', 'side', 'price', 'amount', 'cost']
LAST_BT_RESULT_FN = '.last_result.json'
FTHYPT_FILEVERSION = 'fthypt_fileversion'
USERPATH_HYPEROPTS = 'hyperopts'
USERPATH_STRATEGIES = 'strategies'
@@ -312,6 +313,7 @@ CONF_SCHEMA = {
},
'db_url': {'type': 'string'},
'export': {'type': 'string', 'enum': EXPORT_OPTIONS, 'default': 'trades'},
'disableparamexport': {'type': 'boolean'},
'initial_state': {'type': 'string', 'enum': ['running', 'stopped']},
'forcebuy_enable': {'type': 'boolean'},
'disable_dataframe_checks': {'type': 'boolean'},

6
freqtrade/data/history/history_utils.py
View File

@@ -194,8 +194,8 @@ def _download_pair_history(datadir: Path,
new_data = exchange.get_historic_ohlcv(pair=pair,
timeframe=timeframe,
since_ms=since_ms if since_ms else
int(arrow.utcnow().shift(
days=-new_pairs_days).float_timestamp) * 1000
arrow.utcnow().shift(
days=-new_pairs_days).int_timestamp * 1000
)
# TODO: Maybe move parsing to exchange class (?)
new_dataframe = ohlcv_to_dataframe(new_data, timeframe, pair,
@@ -272,7 +272,7 @@ def _download_trades_history(exchange: Exchange,
if timerange.stoptype == 'date':
until = timerange.stopts * 1000
else:
since = int(arrow.utcnow().shift(days=-new_pairs_days).float_timestamp) * 1000
since = arrow.utcnow().shift(days=-new_pairs_days).int_timestamp * 1000
trades = data_handler.trades_load(pair)

2
freqtrade/exchange/exchange.py
View File

@@ -578,7 +578,7 @@ class Exchange:
'side': side,
'remaining': _amount,
'datetime': arrow.utcnow().isoformat(),
'timestamp': int(arrow.utcnow().int_timestamp * 1000),
'timestamp': arrow.utcnow().int_timestamp * 1000,
'status': "closed" if ordertype == "market" else "open",
'fee': None,
'info': {}

49
freqtrade/optimize/hyperopt.py
View File

@@ -12,7 +12,6 @@ from math import ceil
from pathlib import Path
from typing import Any, Dict, List, Optional
import numpy as np
import progressbar
import rapidjson
from colorama import Fore, Style
@@ -20,16 +19,16 @@ from colorama import init as colorama_init
from joblib import Parallel, cpu_count, delayed, dump, load, wrap_non_picklable_objects
from pandas import DataFrame
from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN
from freqtrade.constants import DATETIME_PRINT_FORMAT, FTHYPT_FILEVERSION, LAST_BT_RESULT_FN
from freqtrade.data.converter import trim_dataframes
from freqtrade.data.history import get_timerange
from freqtrade.misc import file_dump_json, plural
from freqtrade.misc import deep_merge_dicts, file_dump_json, plural
from freqtrade.optimize.backtesting import Backtesting
# Import IHyperOpt and IHyperOptLoss to allow unpickling classes from these modules
from freqtrade.optimize.hyperopt_auto import HyperOptAuto
from freqtrade.optimize.hyperopt_interface import IHyperOpt # noqa: F401
from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss # noqa: F401
from freqtrade.optimize.hyperopt_tools import HyperoptTools
from freqtrade.optimize.hyperopt_tools import HyperoptTools, hyperopt_serializer
from freqtrade.optimize.optimize_reports import generate_strategy_stats
from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver, HyperOptResolver
@@ -78,8 +77,11 @@ class Hyperopt:
if not self.config.get('hyperopt'):
self.custom_hyperopt = HyperOptAuto(self.config)
self.auto_hyperopt = True
else:
self.custom_hyperopt = HyperOptResolver.load_hyperopt(self.config)
self.auto_hyperopt = False
self.backtesting._set_strategy(self.backtesting.strategylist[0])
self.custom_hyperopt.strategy = self.backtesting.strategy
@@ -163,13 +165,9 @@ class Hyperopt:
While not a valid json object - this allows appending easily.
:param epoch: result dictionary for this epoch.
"""
def default_parser(x):
if isinstance(x, np.integer):
return int(x)
return str(x)
epoch[FTHYPT_FILEVERSION] = 2
with self.results_file.open('a') as f:
rapidjson.dump(epoch, f, default=default_parser,
rapidjson.dump(epoch, f, default=hyperopt_serializer,
number_mode=rapidjson.NM_NATIVE | rapidjson.NM_NAN)
f.write("\n")
@@ -201,6 +199,25 @@ class Hyperopt:
return result
def _get_no_optimize_details(self) -> Dict[str, Any]:
"""
Get non-optimized parameters
"""
result: Dict[str, Any] = {}
strategy = self.backtesting.strategy
if not HyperoptTools.has_space(self.config, 'roi'):
result['roi'] = {str(k): v for k, v in strategy.minimal_roi.items()}
if not HyperoptTools.has_space(self.config, 'stoploss'):
result['stoploss'] = {'stoploss': strategy.stoploss}
if not HyperoptTools.has_space(self.config, 'trailing'):
result['trailing'] = {
'trailing_stop': strategy.trailing_stop,
'trailing_stop_positive': strategy.trailing_stop_positive,
'trailing_stop_positive_offset': strategy.trailing_stop_positive_offset,
'trailing_only_offset_is_reached': strategy.trailing_only_offset_is_reached,
}
return result
def print_results(self, results) -> None:
"""
Log results if it is better than any previous evaluation
@@ -310,7 +327,8 @@ class Hyperopt:
results_explanation = HyperoptTools.format_results_explanation_string(
strat_stats, self.config['stake_currency'])
not_optimized = self.backtesting.strategy.get_params_dict()
not_optimized = self.backtesting.strategy.get_no_optimize_params()
not_optimized = deep_merge_dicts(not_optimized, self._get_no_optimize_details())
trade_count = strat_stats['total_trades']
total_profit = strat_stats['profit_total']
@@ -324,7 +342,8 @@ class Hyperopt:
loss = self.calculate_loss(results=backtesting_results['results'],
trade_count=trade_count,
min_date=min_date, max_date=max_date,
config=self.config, processed=processed)
config=self.config, processed=processed,
backtest_stats=strat_stats)
return {
'loss': loss,
'params_dict': params_dict,
@@ -469,6 +488,12 @@ class Hyperopt:
f"saved to '{self.results_file}'.")
if self.current_best_epoch:
if self.auto_hyperopt:
HyperoptTools.try_export_params(
self.config,
self.backtesting.strategy.get_strategy_name(),
self.current_best_epoch)
HyperoptTools.show_epoch_details(self.current_best_epoch, self.total_epochs,
self.print_json)
else:

3
freqtrade/optimize/hyperopt_loss_interface.py
View File

@@ -5,7 +5,7 @@ This module defines the interface for the loss-function for hyperopt
from abc import ABC, abstractmethod
from datetime import datetime
from typing import Dict
from typing import Any, Dict
from pandas import DataFrame
@@ -22,6 +22,7 @@ class IHyperOptLoss(ABC):
def hyperopt_loss_function(results: DataFrame, trade_count: int,
min_date: datetime, max_date: datetime,
config: Dict, processed: Dict[str, DataFrame],
backtest_stats: Dict[str, Any],
*args, **kwargs) -> float:
"""
Objective function, returns smaller number for better results

104
freqtrade/optimize/hyperopt_tools.py
View File

@@ -1,23 +1,82 @@
import io
import logging
from copy import deepcopy
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Dict, List
from typing import Any, Dict, List, Optional
import numpy as np
import rapidjson
import tabulate
from colorama import Fore, Style
from pandas import isna, json_normalize
from freqtrade.constants import FTHYPT_FILEVERSION, USERPATH_STRATEGIES
from freqtrade.exceptions import OperationalException
from freqtrade.misc import round_coin_value, round_dict
from freqtrade.misc import deep_merge_dicts, round_coin_value, round_dict, safe_value_fallback2
logger = logging.getLogger(__name__)
NON_OPT_PARAM_APPENDIX = " # value loaded from strategy"
def hyperopt_serializer(x):
if isinstance(x, np.integer):
return int(x)
if isinstance(x, np.bool_):
return bool(x)
return str(x)
class HyperoptTools():
@staticmethod
def get_strategy_filename(config: Dict, strategy_name: str) -> Optional[Path]:
"""
Get Strategy-location (filename) from strategy_name
"""
from freqtrade.resolvers.strategy_resolver import StrategyResolver
directory = Path(config.get('strategy_path', config['user_data_dir'] / USERPATH_STRATEGIES))
strategy_objs = StrategyResolver.search_all_objects(directory, False)
strategies = [s for s in strategy_objs if s['name'] == strategy_name]
if strategies:
strategy = strategies[0]
return Path(strategy['location'])
return None
@staticmethod
def export_params(params, strategy_name: str, filename: Path):
"""
Generate files
"""
final_params = deepcopy(params['params_not_optimized'])
final_params = deep_merge_dicts(params['params_details'], final_params)
final_params = {
'strategy_name': strategy_name,
'params': final_params,
'ft_stratparam_v': 1,
'export_time': datetime.now(timezone.utc),
}
logger.info(f"Dumping parameters to {filename}")
rapidjson.dump(final_params, filename.open('w'), indent=2,
default=hyperopt_serializer,
number_mode=rapidjson.NM_NATIVE | rapidjson.NM_NAN
)
@staticmethod
def try_export_params(config: Dict[str, Any], strategy_name: str, params: Dict):
if params.get(FTHYPT_FILEVERSION, 1) >= 2 and not config.get('disableparamexport', False):
# Export parameters ...
fn = HyperoptTools.get_strategy_filename(config, strategy_name)
if fn:
HyperoptTools.export_params(params, strategy_name, fn.with_suffix('.json'))
else:
logger.warn("Strategy not found, not exporting parameter file.")
@staticmethod
def has_space(config: Dict[str, Any], space: str) -> bool:
"""
@@ -99,9 +158,9 @@ class HyperoptTools():
non_optimized)
HyperoptTools._params_pretty_print(params, 'sell', "Sell hyperspace params:",
non_optimized)
HyperoptTools._params_pretty_print(params, 'roi', "ROI table:")
HyperoptTools._params_pretty_print(params, 'stoploss', "Stoploss:")
HyperoptTools._params_pretty_print(params, 'trailing', "Trailing stop:")
HyperoptTools._params_pretty_print(params, 'roi', "ROI table:", non_optimized)
HyperoptTools._params_pretty_print(params, 'stoploss', "Stoploss:", non_optimized)
HyperoptTools._params_pretty_print(params, 'trailing', "Trailing stop:", non_optimized)
@staticmethod
def _params_update_for_json(result_dict, params, non_optimized, space: str) -> None:
@@ -127,23 +186,34 @@ class HyperoptTools():
def _params_pretty_print(params, space: str, header: str, non_optimized={}) -> None:
if space in params or space in non_optimized:
space_params = HyperoptTools._space_params(params, space, 5)
no_params = HyperoptTools._space_params(non_optimized, space, 5)
appendix = ''
if not space_params and not no_params:
# No parameters - don't print
return
if not space_params:
# Not optimized parameters - append string
appendix = NON_OPT_PARAM_APPENDIX
result = f"\n# {header}\n"
if space == 'stoploss':
result += f"stoploss = {space_params.get('stoploss')}"
elif space == 'roi':
if space == "stoploss":
stoploss = safe_value_fallback2(space_params, no_params, space, space)
result += (f"stoploss = {stoploss}{appendix}")
elif space == "roi":
result = result[:-1] + f'{appendix}\n'
minimal_roi_result = rapidjson.dumps({
str(k): v for k, v in space_params.items()
str(k): v for k, v in (space_params or no_params).items()
}, default=str, indent=4, number_mode=rapidjson.NM_NATIVE)
result += f"minimal_roi = {minimal_roi_result}"
elif space == 'trailing':
for k, v in space_params.items():
result += f'{k} = {v}\n'
elif space == "trailing":
for k, v in (space_params or no_params).items():
result += f"{k} = {v}{appendix}\n"
else:
no_params = HyperoptTools._space_params(non_optimized, space, 5)
# Buy / sell parameters
result += f"{space}_params = {HyperoptTools._pprint(space_params, no_params)}"
result += f"{space}_params = {HyperoptTools._pprint_dict(space_params, no_params)}"
result = result.replace("\n", "\n ")
print(result)
@@ -157,7 +227,7 @@ class HyperoptTools():
return {}
@staticmethod
def _pprint(params, non_optimized, indent: int = 4):
def _pprint_dict(params, non_optimized, indent: int = 4):
"""
Pretty-print hyperopt results (based on 2 dicts - with add. comment)
"""
@@ -169,7 +239,7 @@ class HyperoptTools():
result += " " * indent + f'"{k}": '
result += f'"{param}",' if isinstance(param, str) else f'{param},'
if k in non_optimized:
result += " # value loaded from strategy"
result += NON_OPT_PARAM_APPENDIX
result += "\n"
result += '}'
return result

15
freqtrade/optimize/optimize_reports.py
View File

@@ -229,8 +229,6 @@ def generate_trading_stats(results: DataFrame) -> Dict[str, Any]:
winning_trades = results.loc[results['profit_ratio'] > 0]
draw_trades = results.loc[results['profit_ratio'] == 0]
losing_trades = results.loc[results['profit_ratio'] < 0]
zero_duration_trades = len(results.loc[(results['trade_duration'] == 0) &
(results['sell_reason'] == 'trailing_stop_loss')])
holding_avg = (timedelta(minutes=round(results['trade_duration'].mean()))
if not results.empty else timedelta())
@@ -249,7 +247,6 @@ def generate_trading_stats(results: DataFrame) -> Dict[str, Any]:
'winner_holding_avg_s': winner_holding_avg.total_seconds(),
'loser_holding_avg': loser_holding_avg,
'loser_holding_avg_s': loser_holding_avg.total_seconds(),
'zero_duration_trades': zero_duration_trades,
}
@@ -264,6 +261,7 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
'winning_days': 0,
'draw_days': 0,
'losing_days': 0,
'daily_profit_list': [],
}
daily_profit_rel = results.resample('1d', on='close_date')['profit_ratio'].sum()
daily_profit = results.resample('1d', on='close_date')['profit_abs'].sum().round(10)
@@ -274,6 +272,7 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
winning_days = sum(daily_profit > 0)
draw_days = sum(daily_profit == 0)
losing_days = sum(daily_profit < 0)
daily_profit_list = daily_profit.tolist()
return {
'backtest_best_day': best_rel,
@@ -283,6 +282,7 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
'winning_days': winning_days,
'draw_days': draw_days,
'losing_days': losing_days,
'daily_profit': daily_profit_list,
}
@@ -542,14 +542,6 @@ def text_table_add_metrics(strat_results: Dict) -> str:
# Newly added fields should be ignored if they are missing in strat_results. hyperopt-show
# command stores these results and newer version of freqtrade must be able to handle old
# results with missing new fields.
zero_duration_trades = '--'
if 'zero_duration_trades' in strat_results:
zero_duration_trades_per = \
100.0 / strat_results['total_trades'] * strat_results['zero_duration_trades']
zero_duration_trades = f'{zero_duration_trades_per:.2f}% ' \
f'({strat_results["zero_duration_trades"]})'
metrics = [
('Backtesting from', strat_results['backtest_start']),
('Backtesting to', strat_results['backtest_end']),
@@ -585,7 +577,6 @@ def text_table_add_metrics(strat_results: Dict) -> str:
f"{strat_results['draw_days']} / {strat_results['losing_days']}"),
('Avg. Duration Winners', f"{strat_results['winner_holding_avg']}"),
('Avg. Duration Loser', f"{strat_results['loser_holding_avg']}"),
('Zero Duration Trades', zero_duration_trades),
('Rejected Buy signals', strat_results.get('rejected_signals', 'N/A')),
('', ''), # Empty line to improve readability

2
freqtrade/plugins/pairlist/AgeFilter.py
View File

@@ -105,7 +105,7 @@ class AgeFilter(IPairList):
len(daily_candles) <= self._max_days_listed:
# We have fetched at least the minimum required number of daily candles
# Add to cache, store the time we last checked this symbol
self._symbolsChecked[pair] = int(arrow.utcnow().float_timestamp) * 1000
self._symbolsChecked[pair] = arrow.utcnow().int_timestamp * 1000
return True
else:
self.log_once((

8
freqtrade/plugins/pairlist/VolatilityFilter.py
View File

@@ -69,10 +69,10 @@ class VolatilityFilter(IPairList):
"""
needed_pairs = [(p, '1d') for p in pairlist if p not in self._pair_cache]
since_ms = int(arrow.utcnow()
.floor('day')
.shift(days=-self._days - 1)
.float_timestamp) * 1000
since_ms = (arrow.utcnow()
.floor('day')
.shift(days=-self._days - 1)
.int_timestamp) * 1000
# Get all candles
candles = {}
if needed_pairs:

8
freqtrade/plugins/pairlist/rangestabilityfilter.py
View File

@@ -62,10 +62,10 @@ class RangeStabilityFilter(IPairList):
"""
needed_pairs = [(p, '1d') for p in pairlist if p not in self._pair_cache]
since_ms = int(arrow.utcnow()
.floor('day')
.shift(days=-self._days - 1)
.float_timestamp) * 1000
since_ms = (arrow.utcnow()
.floor('day')
.shift(days=-self._days - 1)
.int_timestamp) * 1000
# Get all candles
candles = {}
if needed_pairs:

15
freqtrade/resolvers/strategy_resolver.py
View File

@@ -53,6 +53,21 @@ class StrategyResolver(IResolver):
)
strategy.timeframe = strategy.ticker_interval
if strategy._ft_params_from_file:
# Set parameters from Hyperopt results file
params = strategy._ft_params_from_file
strategy.minimal_roi = params.get('roi', strategy.minimal_roi)
strategy.stoploss = params.get('stoploss', {}).get('stoploss', strategy.stoploss)
trailing = params.get('trailing', {})
strategy.trailing_stop = trailing.get('trailing_stop', strategy.trailing_stop)
strategy.trailing_stop_positive = trailing.get('trailing_stop_positive',
strategy.trailing_stop_positive)
strategy.trailing_stop_positive_offset = trailing.get(
'trailing_stop_positive_offset', strategy.trailing_stop_positive_offset)
strategy.trailing_only_offset_is_reached = trailing.get(
'trailing_only_offset_is_reached', strategy.trailing_only_offset_is_reached)
# Set attributes
# Check if we need to override configuration
# (Attribute name, default, subkey)

11
freqtrade/rpc/api_server/web_ui.py
View File

@@ -18,6 +18,17 @@ async def fallback():
return FileResponse(str(Path(__file__).parent / 'ui/fallback_file.html'))
@router_ui.get('/ui_version', include_in_schema=False)
async def ui_version():
from freqtrade.commands.deploy_commands import read_ui_version
uibase = Path(__file__).parent / 'ui/installed/'
version = read_ui_version(uibase)
return {
"version": version if version else "not_installed",
}
@router_ui.get('/{rest_of_path:path}', include_in_schema=False)
async def index_html(rest_of_path: str):
"""

19
freqtrade/rpc/telegram.py
View File

@@ -24,7 +24,7 @@ from freqtrade.__init__ import __version__
from freqtrade.constants import DUST_PER_COIN
from freqtrade.enums import RPCMessageType
from freqtrade.exceptions import OperationalException
from freqtrade.misc import chunks, round_coin_value
from freqtrade.misc import chunks, plural, round_coin_value
from freqtrade.rpc import RPC, RPCException, RPCHandler
@@ -598,6 +598,9 @@ class Telegram(RPCHandler):
"Starting capital: "
f"`{self._config['dry_run_wallet']}` {self._config['stake_currency']}.\n"
)
total_dust_balance = 0
total_dust_currencies = 0
curr_output = ''
for curr in result['currencies']:
if curr['est_stake'] > balance_dust_level:
curr_output = (
@@ -607,9 +610,9 @@ class Telegram(RPCHandler):
f"\t`Pending: {curr['used']:.8f}`\n"
f"\t`Est. {curr['stake']}: "
f"{round_coin_value(curr['est_stake'], curr['stake'], False)}`\n")
else:
curr_output = (f"*{curr['currency']}:* not showing <{balance_dust_level} "
f"{curr['stake']} amount \n")
elif curr['est_stake'] <= balance_dust_level:
total_dust_balance += curr['est_stake']
total_dust_currencies += 1
# Handle overflowing message length
if len(output + curr_output) >= MAX_TELEGRAM_MESSAGE_LENGTH:
@@ -618,6 +621,14 @@ class Telegram(RPCHandler):
else:
output += curr_output
if total_dust_balance > 0:
output += (
f"*{total_dust_currencies} Other "
f"{plural(total_dust_currencies, 'Currency', 'Currencies')} "
f"(< {balance_dust_level} {result['stake']}):*\n"
f"\t`Est. {result['stake']}: "
f"{round_coin_value(total_dust_balance, result['stake'], False)}`\n")
output += ("\n*Estimated Value*:\n"
f"\t`{result['stake']}: {result['total']: .8f}`\n"
f"\t`{result['symbol']}: "

64
freqtrade/strategy/hyper.py
View File

@@ -5,8 +5,10 @@ This module defines a base class for auto-hyperoptable strategies.
import logging
from abc import ABC, abstractmethod
from contextlib import suppress
from pathlib import Path
from typing import Any, Dict, Iterator, List, Optional, Sequence, Tuple, Union
from freqtrade.misc import deep_merge_dicts, json_load
from freqtrade.optimize.hyperopt_tools import HyperoptTools
@@ -205,6 +207,21 @@ class DecimalParameter(NumericParameter):
return SKDecimal(low=self.low, high=self.high, decimals=self._decimals, name=name,
**self._space_params)
@property
def range(self):
"""
Get each value in this space as list.
Returns a List from low to high (inclusive) in Hyperopt mode.
Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
calculating 100ds of indicators.
"""
if self.in_space and self.optimize:
low = int(self.low * pow(10, self._decimals))
high = int(self.high * pow(10, self._decimals)) + 1
return [round(n * pow(0.1, self._decimals), self._decimals) for n in range(low, high)]
else:
return [self.value]
class CategoricalParameter(BaseParameter):
default: Any
@@ -239,6 +256,19 @@ class CategoricalParameter(BaseParameter):
"""
return Categorical(self.opt_range, name=name, **self._space_params)
@property
def range(self):
"""
Get each value in this space as list.
Returns a List of categories in Hyperopt mode.
Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
calculating 100ds of indicators.
"""
if self.in_space and self.optimize:
return self.opt_range
else:
return [self.value]
class HyperStrategyMixin(object):
"""
@@ -305,10 +335,36 @@ class HyperStrategyMixin(object):
"""
Load Hyperoptable parameters
"""
self._load_params(getattr(self, 'buy_params', None), 'buy', hyperopt)
self._load_params(getattr(self, 'sell_params', None), 'sell', hyperopt)
params = self.load_params_from_file()
params = params.get('params', {})
self._ft_params_from_file = params
buy_params = deep_merge_dicts(params.get('buy', {}), getattr(self, 'buy_params', None))
sell_params = deep_merge_dicts(params.get('sell', {}), getattr(self, 'sell_params', None))
def _load_params(self, params: dict, space: str, hyperopt: bool = False) -> None:
self._load_params(buy_params, 'buy', hyperopt)
self._load_params(sell_params, 'sell', hyperopt)
def load_params_from_file(self) -> Dict:
filename_str = getattr(self, '__file__', '')
if not filename_str:
return {}
filename = Path(filename_str).with_suffix('.json')
if filename.is_file():
logger.info(f"Loading parameters from file {filename}")
try:
params = json_load(filename.open('r'))
if params.get('strategy_name') != self.__class__.__name__:
raise OperationalException('Invalid parameter file provided.')
return params
except ValueError:
logger.warning("Invalid parameter file format.")
return {}
logger.info("Found no parameter file.")
return {}
def _load_params(self, params: Dict, space: str, hyperopt: bool = False) -> None:
"""
Set optimizable parameter values.
:param params: Dictionary with new parameter values.
@@ -335,7 +391,7 @@ class HyperStrategyMixin(object):
else:
logger.info(f'Strategy Parameter(default): {attr_name} = {attr.value}')
def get_params_dict(self):
def get_no_optimize_params(self):
"""
Returns list of Parameters that are not part of the current optimize job
"""

1
freqtrade/strategy/interface.py
View File

@@ -62,6 +62,7 @@ class IStrategy(ABC, HyperStrategyMixin):
_populate_fun_len: int = 0
_buy_fun_len: int = 0
_sell_fun_len: int = 0
_ft_params_from_file: Dict = {}
# associated minimal roi
minimal_roi: Dict

43
freqtrade/templates/strategy_analysis_example.ipynb
View File

@@ -188,6 +188,47 @@
"trades.groupby(\"pair\")[\"sell_reason\"].value_counts()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plotting daily profit / equity line"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Plotting equity line (starting with 0 on day 1 and adding daily profit for each backtested day)\n",
"\n",
"from freqtrade.configuration import Configuration\n",
"from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats\n",
"import plotly.express as px\n",
"import pandas as pd\n",
"\n",
"# strategy = 'SampleStrategy'\n",
"# config = Configuration.from_files([\"user_data/config.json\"])\n",
"# backtest_dir = config[\"user_data_dir\"] / \"backtest_results\"\n",
"\n",
"stats = load_backtest_stats(backtest_dir)\n",
"strategy_stats = stats['strategy'][strategy]\n",
"\n",
"equity = 0\n",
"equity_daily = []\n",
"for dp in strategy_stats['daily_profit']:\n",
" equity_daily.append(equity)\n",
" equity += float(dp)\n",
"\n",
"dates = pd.date_range(strategy_stats['backtest_start'], strategy_stats['backtest_end'])\n",
"\n",
"df = pd.DataFrame({'dates': dates,'equity_daily': equity_daily})\n",
"\n",
"fig = px.line(df, x=\"dates\", y=\"equity_daily\")\n",
"fig.show()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
@@ -329,7 +370,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.4"
"version": "3.8.5"
},
"mimetype": "text/x-python",
"name": "python",