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Merge pull request #4454 from freqtrade/backtest_compound_speed

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Backtest compound, wallet, ...
This commit is contained in:
Matthias
2021-03-10 10:07:40 +01:00
committed by GitHub
parent 60f6b998d3 4b550dab17
commit 0db5c9746f
38 changed files with 715 additions and 315 deletions
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6
freqtrade/commands/arguments.py
View File

@@ -14,18 +14,18 @@ ARGS_COMMON = ["verbosity", "logfile", "version", "config", "datadir", "user_dat
ARGS_STRATEGY = ["strategy", "strategy_path"]
ARGS_TRADE = ["db_url", "sd_notify", "dry_run"]
ARGS_TRADE = ["db_url", "sd_notify", "dry_run", "dry_run_wallet", ]
ARGS_COMMON_OPTIMIZE = ["timeframe", "timerange", "dataformat_ohlcv",
"max_open_trades", "stake_amount", "fee"]
ARGS_BACKTEST = ARGS_COMMON_OPTIMIZE + ["position_stacking", "use_max_market_positions",
"enable_protections",
"enable_protections", "dry_run_wallet",
"strategy_list", "export", "exportfilename"]
ARGS_HYPEROPT = ARGS_COMMON_OPTIMIZE + ["hyperopt", "hyperopt_path",
"position_stacking", "use_max_market_positions",
"enable_protections",
"enable_protections", "dry_run_wallet",
"epochs", "spaces", "print_all",
"print_colorized", "print_json", "hyperopt_jobs",
"hyperopt_random_state", "hyperopt_min_trades",

6
freqtrade/commands/cli_options.py
View File

@@ -110,6 +110,11 @@ AVAILABLE_CLI_OPTIONS = {
help='Enforce dry-run for trading (removes Exchange secrets and simulates trades).',
action='store_true',
),
"dry_run_wallet": Arg(
'--dry-run-wallet', '--starting-balance',
help='Starting balance, used for backtesting / hyperopt and dry-runs.',
type=float,
),
# Optimize common
"timeframe": Arg(
'-i', '--timeframe', '--ticker-interval',
@@ -128,7 +133,6 @@ AVAILABLE_CLI_OPTIONS = {
"stake_amount": Arg(
'--stake-amount',
help='Override the value of the `stake_amount` configuration setting.',
type=float,
),
# Backtesting
"position_stacking": Arg(

15
freqtrade/commands/optimize_commands.py
View File

@@ -3,7 +3,8 @@ from typing import Any, Dict
from freqtrade import constants
from freqtrade.configuration import setup_utils_configuration
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.exceptions import OperationalException
from freqtrade.misc import round_coin_value
from freqtrade.state import RunMode
@@ -22,11 +23,13 @@ def setup_optimize_configuration(args: Dict[str, Any], method: RunMode) -> Dict[
RunMode.BACKTEST: 'backtesting',
RunMode.HYPEROPT: 'hyperoptimization',
}
if (method in no_unlimited_runmodes.keys() and
config['stake_amount'] == constants.UNLIMITED_STAKE_AMOUNT):
raise DependencyException(
f'The value of `stake_amount` cannot be set as "{constants.UNLIMITED_STAKE_AMOUNT}" '
f'for {no_unlimited_runmodes[method]}')
if method in no_unlimited_runmodes.keys():
if (config['stake_amount'] != constants.UNLIMITED_STAKE_AMOUNT
and config['stake_amount'] > config['dry_run_wallet']):
wallet = round_coin_value(config['dry_run_wallet'], config['stake_currency'])
stake = round_coin_value(config['stake_amount'], config['stake_currency'])
raise OperationalException(f"Starting balance ({wallet}) "
f"is smaller than stake_amount {stake}.")
return config

17
freqtrade/configuration/configuration.py
View File

@@ -214,9 +214,6 @@ class Configuration:
self._args_to_config(
config, argname='enable_protections',
logstring='Parameter --enable-protections detected, enabling Protections. ...')
# Setting max_open_trades to infinite if -1
if config.get('max_open_trades') == -1:
config['max_open_trades'] = float('inf')
if 'use_max_market_positions' in self.args and not self.args["use_max_market_positions"]:
config.update({'use_max_market_positions': False})
@@ -228,11 +225,23 @@ class Configuration:
'overriding max_open_trades to: %s ...', config.get('max_open_trades'))
elif config['runmode'] in NON_UTIL_MODES:
logger.info('Using max_open_trades: %s ...', config.get('max_open_trades'))
# Setting max_open_trades to infinite if -1
if config.get('max_open_trades') == -1:
config['max_open_trades'] = float('inf')
if self.args.get('stake_amount', None):
# Convert explicitly to float to support CLI argument for both unlimited and value
try:
self.args['stake_amount'] = float(self.args['stake_amount'])
except ValueError:
pass
self._args_to_config(config, argname='stake_amount',
logstring='Parameter --stake-amount detected, '
'overriding stake_amount to: {} ...')
self._args_to_config(config, argname='dry_run_wallet',
logstring='Parameter --dry-run-wallet detected, '
'overriding dry_run_wallet to: {} ...')
self._args_to_config(config, argname='fee',
logstring='Parameter --fee detected, '
'setting fee to: {} ...')

21
freqtrade/data/btanalysis.py
View File

@@ -10,7 +10,7 @@ import pandas as pd
from freqtrade.constants import LAST_BT_RESULT_FN
from freqtrade.misc import json_load
from freqtrade.persistence import Trade, init_db
from freqtrade.persistence import LocalTrade, Trade, init_db
logger = logging.getLogger(__name__)
@@ -224,7 +224,7 @@ def evaluate_result_multi(results: pd.DataFrame, timeframe: str,
return df_final[df_final['open_trades'] > max_open_trades]
def trade_list_to_dataframe(trades: List[Trade]) -> pd.DataFrame:
def trade_list_to_dataframe(trades: List[LocalTrade]) -> pd.DataFrame:
"""
Convert list of Trade objects to pandas Dataframe
:param trades: List of trade objects
@@ -360,13 +360,14 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str,
def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date',
value_col: str = 'profit_ratio'
) -> Tuple[float, pd.Timestamp, pd.Timestamp]:
) -> Tuple[float, pd.Timestamp, pd.Timestamp, float, float]:
"""
Calculate max drawdown and the corresponding close dates
:param trades: DataFrame containing trades (requires columns close_date and profit_ratio)
:param date_col: Column in DataFrame to use for dates (defaults to 'close_date')
:param value_col: Column in DataFrame to use for values (defaults to 'profit_ratio')
:return: Tuple (float, highdate, lowdate) with absolute max drawdown, high and low time
:return: Tuple (float, highdate, lowdate, highvalue, lowvalue) with absolute max drawdown,
high and low time and high and low value.
:raise: ValueError if trade-dataframe was found empty.
"""
if len(trades) == 0:
@@ -382,13 +383,17 @@ def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date'
raise ValueError("No losing trade, therefore no drawdown.")
high_date = profit_results.loc[max_drawdown_df.iloc[:idxmin]['high_value'].idxmax(), date_col]
low_date = profit_results.loc[idxmin, date_col]
return abs(min(max_drawdown_df['drawdown'])), high_date, low_date
high_val = max_drawdown_df.loc[max_drawdown_df.iloc[:idxmin]
['high_value'].idxmax(), 'cumulative']
low_val = max_drawdown_df.loc[idxmin, 'cumulative']
return abs(min(max_drawdown_df['drawdown'])), high_date, low_date, high_val, low_val
def calculate_csum(trades: pd.DataFrame) -> Tuple[float, float]:
def calculate_csum(trades: pd.DataFrame, starting_balance: float = 0) -> Tuple[float, float]:
"""
Calculate min/max cumsum of trades, to show if the wallet/stake amount ratio is sane
:param trades: DataFrame containing trades (requires columns close_date and profit_percent)
:param starting_balance: Add starting balance to results, to show the wallets high / low points
:return: Tuple (float, float) with cumsum of profit_abs
:raise: ValueError if trade-dataframe was found empty.
"""
@@ -397,7 +402,7 @@ def calculate_csum(trades: pd.DataFrame) -> Tuple[float, float]:
csum_df = pd.DataFrame()
csum_df['sum'] = trades['profit_abs'].cumsum()
csum_min = csum_df['sum'].min()
csum_max = csum_df['sum'].max()
csum_min = csum_df['sum'].min() + starting_balance
csum_max = csum_df['sum'].max() + starting_balance
return csum_min, csum_max

3
freqtrade/exchange/exchange.py
View File

@@ -147,6 +147,9 @@ class Exchange:
"""
Destructor - clean up async stuff
"""
self.close()
def close(self):
logger.debug("Exchange object destroyed, closing async loop")
if self._api_async and inspect.iscoroutinefunction(self._api_async.close):
asyncio.get_event_loop().run_until_complete(self._api_async.close())

2
freqtrade/freqtradebot.py
View File

@@ -937,7 +937,7 @@ class FreqtradeBot(LoggingMixin):
Check and execute sell
"""
should_sell = self.strategy.should_sell(
trade, sell_rate, datetime.utcnow(), buy, sell,
trade, sell_rate, datetime.now(timezone.utc), buy, sell,
force_stoploss=self.edge.stoploss(trade.pair) if self.edge else 0
)

113
freqtrade/optimize/backtesting.py
View File

@@ -17,17 +17,18 @@ from freqtrade.data import history
from freqtrade.data.btanalysis import trade_list_to_dataframe
from freqtrade.data.converter import trim_dataframe
from freqtrade.data.dataprovider import DataProvider
from freqtrade.exceptions import OperationalException
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
from freqtrade.mixins import LoggingMixin
from freqtrade.optimize.optimize_reports import (generate_backtest_stats, show_backtest_results,
store_backtest_stats)
from freqtrade.persistence import PairLocks, Trade
from freqtrade.persistence import LocalTrade, PairLocks, Trade
from freqtrade.plugins.pairlistmanager import PairListManager
from freqtrade.plugins.protectionmanager import ProtectionManager
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
from freqtrade.strategy.interface import IStrategy, SellCheckTuple, SellType
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
from freqtrade.wallets import Wallets
logger = logging.getLogger(__name__)
@@ -114,6 +115,8 @@ class Backtesting:
if self.config.get('enable_protections', False):
self.protections = ProtectionManager(self.config)
self.wallets = Wallets(self.config, self.exchange, log=False)
# Get maximum required startup period
self.required_startup = max([strat.startup_candle_count for strat in self.strategylist])
# Load one (first) strategy
@@ -124,7 +127,7 @@ class Backtesting:
PairLocks.use_db = True
Trade.use_db = True
def _set_strategy(self, strategy):
def _set_strategy(self, strategy: IStrategy):
"""
Load strategy into backtesting
"""
@@ -171,10 +174,8 @@ class Backtesting:
PairLocks.use_db = False
PairLocks.timeframe = self.config['timeframe']
Trade.use_db = False
if enable_protections:
# Reset persisted data - used for protections only
PairLocks.reset_locks()
Trade.reset_trades()
PairLocks.reset_locks()
Trade.reset_trades()
def _get_ohlcv_as_lists(self, processed: Dict[str, DataFrame]) -> Dict[str, Tuple]:
"""
@@ -203,10 +204,10 @@ class Backtesting:
# Convert from Pandas to list for performance reasons
# (Looping Pandas is slow.)
data[pair] = [x for x in df_analyzed.itertuples(index=False, name=None)]
data[pair] = df_analyzed.values.tolist()
return data
def _get_close_rate(self, sell_row: Tuple, trade: Trade, sell: SellCheckTuple,
def _get_close_rate(self, sell_row: Tuple, trade: LocalTrade, sell: SellCheckTuple,
trade_dur: int) -> float:
"""
Get close rate for backtesting result
@@ -246,24 +247,48 @@ class Backtesting:
else:
return sell_row[OPEN_IDX]
def _get_sell_trade_entry(self, trade: Trade, sell_row: Tuple) -> Optional[Trade]:
def _get_sell_trade_entry(self, trade: LocalTrade, sell_row: Tuple) -> Optional[LocalTrade]:
sell = self.strategy.should_sell(trade, sell_row[OPEN_IDX], sell_row[DATE_IDX],
sell_row[BUY_IDX], sell_row[SELL_IDX],
sell = self.strategy.should_sell(trade, sell_row[OPEN_IDX], # type: ignore
sell_row[DATE_IDX], sell_row[BUY_IDX], sell_row[SELL_IDX],
low=sell_row[LOW_IDX], high=sell_row[HIGH_IDX])
if sell.sell_flag:
trade_dur = int((sell_row[DATE_IDX] - trade.open_date).total_seconds() // 60)
closerate = self._get_close_rate(sell_row, trade, sell, trade_dur)
trade.close_date = sell_row[DATE_IDX]
trade.sell_reason = sell.sell_type
trade.sell_reason = sell.sell_type.value
trade_dur = int((trade.close_date_utc - trade.open_date_utc).total_seconds() // 60)
closerate = self._get_close_rate(sell_row, trade, sell, trade_dur)
trade.close(closerate, show_msg=False)
return trade
return None
def handle_left_open(self, open_trades: Dict[str, List[Trade]],
data: Dict[str, List[Tuple]]) -> List[Trade]:
def _enter_trade(self, pair: str, row: List, max_open_trades: int,
open_trade_count: int) -> Optional[LocalTrade]:
try:
stake_amount = self.wallets.get_trade_stake_amount(
pair, max_open_trades - open_trade_count, None)
except DependencyException:
return None
min_stake_amount = self.exchange.get_min_pair_stake_amount(pair, row[OPEN_IDX], -0.05)
if stake_amount and (not min_stake_amount or stake_amount > min_stake_amount):
# Enter trade
trade = LocalTrade(
pair=pair,
open_rate=row[OPEN_IDX],
open_date=row[DATE_IDX],
stake_amount=stake_amount,
amount=round(stake_amount / row[OPEN_IDX], 8),
fee_open=self.fee,
fee_close=self.fee,
is_open=True,
exchange='backtesting',
)
return trade
return None
def handle_left_open(self, open_trades: Dict[str, List[LocalTrade]],
data: Dict[str, List[Tuple]]) -> List[LocalTrade]:
"""
Handling of left open trades at the end of backtesting
"""
@@ -274,13 +299,15 @@ class Backtesting:
sell_row = data[pair][-1]
trade.close_date = sell_row[DATE_IDX]
trade.sell_reason = SellType.FORCE_SELL
trade.sell_reason = SellType.FORCE_SELL.value
trade.close(sell_row[OPEN_IDX], show_msg=False)
trade.is_open = True
trades.append(trade)
# Deepcopy object to have wallets update correctly
trade1 = deepcopy(trade)
trade1.is_open = True
trades.append(trade1)
return trades
def backtest(self, processed: Dict, stake_amount: float,
def backtest(self, processed: Dict,
start_date: datetime, end_date: datetime,
max_open_trades: int = 0, position_stacking: bool = False,
enable_protections: bool = False) -> DataFrame:
@@ -292,7 +319,6 @@ class Backtesting:
Avoid extensive logging in this method and functions it calls.
: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
@@ -300,11 +326,7 @@ class Backtesting:
:param enable_protections: Should protections be enabled?
:return: DataFrame with trades (results of backtesting)
"""
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: List[Trade] = []
trades: List[LocalTrade] = []
self.prepare_backtest(enable_protections)
# Use dict of lists with data for performance
@@ -315,7 +337,7 @@ class Backtesting:
indexes: Dict = {}
tmp = start_date + timedelta(minutes=self.timeframe_min)
open_trades: Dict[str, List] = defaultdict(list)
open_trades: Dict[str, List[LocalTrade]] = defaultdict(list)
open_trade_count = 0
# Loop timerange and get candle for each pair at that point in time
@@ -346,28 +368,18 @@ class Backtesting:
and tmp != end_date
and row[BUY_IDX] == 1 and row[SELL_IDX] != 1
and not PairLocks.is_pair_locked(pair, row[DATE_IDX])):
# Enter trade
trade = Trade(
pair=pair,
open_rate=row[OPEN_IDX],
open_date=row[DATE_IDX],
stake_amount=stake_amount,
amount=round(stake_amount / row[OPEN_IDX], 8),
fee_open=self.fee,
fee_close=self.fee,
is_open=True,
)
# TODO: hacky workaround to avoid opening > max_open_trades
# This emulates previous behaviour - not sure if this is correct
# Prevents buying if the trade-slot was freed in this candle
open_trade_count_start += 1
open_trade_count += 1
# logger.debug(f"{pair} - Backtesting emulates creation of new trade: {trade}.")
open_trades[pair].append(trade)
Trade.trades.append(trade)
trade = self._enter_trade(pair, row, max_open_trades, open_trade_count_start)
if trade:
# TODO: hacky workaround to avoid opening > max_open_trades
# This emulates previous behaviour - not sure if this is correct
# Prevents buying if the trade-slot was freed in this candle
open_trade_count_start += 1
open_trade_count += 1
# logger.debug(f"{pair} - Emulate creation of new trade: {trade}.")
open_trades[pair].append(trade)
LocalTrade.trades.append(trade)
for trade in open_trades[pair]:
# since indexes has been incremented before, we need to go one step back to
# also check the buying candle for sell conditions.
trade_entry = self._get_sell_trade_entry(trade, row)
# Sell occured
@@ -384,6 +396,7 @@ class Backtesting:
tmp += timedelta(minutes=self.timeframe_min)
trades += self.handle_left_open(open_trades, data=data)
self.wallets.update()
return trade_list_to_dataframe(trades)
@@ -417,7 +430,6 @@ class Backtesting:
# Execute backtest and store results
results = self.backtest(
processed=preprocessed,
stake_amount=self.config['stake_amount'],
start_date=min_date.datetime,
end_date=max_date.datetime,
max_open_trades=max_open_trades,
@@ -428,7 +440,8 @@ class Backtesting:
self.all_results[self.strategy.get_strategy_name()] = {
'results': results,
'config': self.strategy.config,
'locks': PairLocks.locks,
'locks': PairLocks.get_all_locks(),
'final_balance': self.wallets.get_total(self.strategy.config['stake_currency']),
'backtest_start_time': int(backtest_start_time.timestamp()),
'backtest_end_time': int(backtest_end_time.timestamp()),
}

6
freqtrade/optimize/hyperopt.py
View File

@@ -541,7 +541,6 @@ class Hyperopt:
backtesting_results = self.backtesting.backtest(
processed=processed,
stake_amount=self.config['stake_amount'],
start_date=min_date.datetime,
end_date=max_date.datetime,
max_open_trades=self.max_open_trades,
@@ -665,7 +664,10 @@ class Hyperopt:
dump(preprocessed, self.data_pickle_file)
# We don't need exchange instance anymore while running hyperopt
self.backtesting.exchange = None # type: ignore
self.backtesting.exchange.close()
self.backtesting.exchange._api = None # type: ignore
self.backtesting.exchange._api_async = None # type: ignore
# self.backtesting.exchange = None # type: ignore
self.backtesting.pairlists = None # type: ignore
self.backtesting.strategy.dp = None # type: ignore
IStrategy.dp = None # type: ignore

105
freqtrade/optimize/optimize_reports.py
View File

@@ -8,7 +8,7 @@ from numpy import int64
from pandas import DataFrame
from tabulate import tabulate
from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN
from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN, UNLIMITED_STAKE_AMOUNT
from freqtrade.data.btanalysis import (calculate_csum, calculate_market_change,
calculate_max_drawdown)
from freqtrade.misc import decimals_per_coin, file_dump_json, round_coin_value
@@ -56,12 +56,13 @@ def _get_line_header(first_column: str, stake_currency: str) -> List[str]:
'Wins', 'Draws', 'Losses']
def _generate_result_line(result: DataFrame, max_open_trades: int, first_column: str) -> Dict:
def _generate_result_line(result: DataFrame, starting_balance: int, first_column: str) -> Dict:
"""
Generate one result dict, with "first_column" as key.
"""
profit_sum = result['profit_ratio'].sum()
profit_total = profit_sum / max_open_trades
# (end-capital - starting capital) / starting capital
profit_total = result['profit_abs'].sum() / starting_balance
return {
'key': first_column,
@@ -88,13 +89,13 @@ def _generate_result_line(result: DataFrame, max_open_trades: int, first_column:
}
def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, max_open_trades: int,
def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, starting_balance: int,
results: DataFrame, skip_nan: bool = False) -> List[Dict]:
"""
Generates and returns a list for the given backtest data and the results dataframe
:param data: Dict of <pair: dataframe> containing data that was used during backtesting.
:param stake_currency: stake-currency - used to correctly name headers
:param max_open_trades: Maximum allowed open trades
:param starting_balance: Starting balance
:param results: Dataframe containing the backtest results
:param skip_nan: Print "left open" open trades
:return: List of Dicts containing the metrics per pair
@@ -107,10 +108,10 @@ def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, max_open_t
if skip_nan and result['profit_abs'].isnull().all():
continue
tabular_data.append(_generate_result_line(result, max_open_trades, pair))
tabular_data.append(_generate_result_line(result, starting_balance, pair))
# Append Total
tabular_data.append(_generate_result_line(results, max_open_trades, 'TOTAL'))
tabular_data.append(_generate_result_line(results, starting_balance, 'TOTAL'))
return tabular_data
@@ -132,7 +133,7 @@ def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List
tabular_data.append(
{
'sell_reason': reason.value,
'sell_reason': reason,
'trades': count,
'wins': len(result[result['profit_abs'] > 0]),
'draws': len(result[result['profit_abs'] == 0]),
@@ -159,7 +160,7 @@ def generate_strategy_metrics(all_results: Dict) -> List[Dict]:
tabular_data = []
for strategy, results in all_results.items():
tabular_data.append(_generate_result_line(
results['results'], results['config']['max_open_trades'], strategy)
results['results'], results['config']['dry_run_wallet'], strategy)
)
return tabular_data
@@ -195,13 +196,18 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
return {
'backtest_best_day': 0,
'backtest_worst_day': 0,
'backtest_best_day_abs': 0,
'backtest_worst_day_abs': 0,
'winning_days': 0,
'draw_days': 0,
'losing_days': 0,
'winner_holding_avg': timedelta(),
'loser_holding_avg': timedelta(),
}
daily_profit = results.resample('1d', on='close_date')['profit_ratio'].sum()
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)
worst_rel = min(daily_profit_rel)
best_rel = max(daily_profit_rel)
worst = min(daily_profit)
best = max(daily_profit)
winning_days = sum(daily_profit > 0)
@@ -212,8 +218,10 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
losing_trades = results.loc[results['profit_ratio'] < 0]
return {
'backtest_best_day': best,
'backtest_worst_day': worst,
'backtest_best_day': best_rel,
'backtest_worst_day': worst_rel,
'backtest_best_day_abs': best,
'backtest_worst_day_abs': worst,
'winning_days': winning_days,
'draw_days': draw_days,
'losing_days': losing_days,
@@ -246,15 +254,16 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
continue
config = content['config']
max_open_trades = min(config['max_open_trades'], len(btdata.keys()))
starting_balance = config['dry_run_wallet']
stake_currency = config['stake_currency']
pair_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
max_open_trades=max_open_trades,
starting_balance=starting_balance,
results=results, skip_nan=False)
sell_reason_stats = generate_sell_reason_stats(max_open_trades=max_open_trades,
results=results)
left_open_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
max_open_trades=max_open_trades,
starting_balance=starting_balance,
results=results.loc[results['is_open']],
skip_nan=True)
daily_stats = generate_daily_stats(results)
@@ -275,8 +284,10 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
'sell_reason_summary': sell_reason_stats,
'left_open_trades': left_open_results,
'total_trades': len(results),
'total_volume': float(results['stake_amount'].sum()),
'avg_stake_amount': results['stake_amount'].mean() if len(results) > 0 else 0,
'profit_mean': results['profit_ratio'].mean() if len(results) > 0 else 0,
'profit_total': results['profit_ratio'].sum() / max_open_trades,
'profit_total': results['profit_abs'].sum() / starting_balance,
'profit_total_abs': results['profit_abs'].sum(),
'backtest_start': min_date.datetime,
'backtest_start_ts': min_date.int_timestamp * 1000,
@@ -292,6 +303,10 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
'pairlist': list(btdata.keys()),
'stake_amount': config['stake_amount'],
'stake_currency': config['stake_currency'],
'stake_currency_decimals': decimals_per_coin(config['stake_currency']),
'starting_balance': starting_balance,
'dry_run_wallet': starting_balance,
'final_balance': content['final_balance'],
'max_open_trades': max_open_trades,
'max_open_trades_setting': (config['max_open_trades']
if config['max_open_trades'] != float('inf') else -1),
@@ -316,17 +331,23 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
result['strategy'][strategy] = strat_stats
try:
max_drawdown, drawdown_start, drawdown_end = calculate_max_drawdown(
max_drawdown, _, _, _, _ = calculate_max_drawdown(
results, value_col='profit_ratio')
drawdown_abs, drawdown_start, drawdown_end, high_val, low_val = calculate_max_drawdown(
results, value_col='profit_abs')
strat_stats.update({
'max_drawdown': max_drawdown,
'max_drawdown_abs': drawdown_abs,
'drawdown_start': drawdown_start,
'drawdown_start_ts': drawdown_start.timestamp() * 1000,
'drawdown_end': drawdown_end,
'drawdown_end_ts': drawdown_end.timestamp() * 1000,
'max_drawdown_low': low_val,
'max_drawdown_high': high_val,
})
csum_min, csum_max = calculate_csum(results)
csum_min, csum_max = calculate_csum(results, starting_balance)
strat_stats.update({
'csum_min': csum_min,
'csum_max': csum_max
@@ -335,6 +356,9 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
except ValueError:
strat_stats.update({
'max_drawdown': 0.0,
'max_drawdown_abs': 0.0,
'max_drawdown_low': 0.0,
'max_drawdown_high': 0.0,
'drawdown_start': datetime(1970, 1, 1, tzinfo=timezone.utc),
'drawdown_start_ts': 0,
'drawdown_end': datetime(1970, 1, 1, tzinfo=timezone.utc),
@@ -431,8 +455,19 @@ def text_table_add_metrics(strat_results: Dict) -> str:
('Max open trades', strat_results['max_open_trades']),
('', ''), # Empty line to improve readability
('Total trades', strat_results['total_trades']),
('Total Profit %', f"{round(strat_results['profit_total'] * 100, 2)}%"),
('Starting balance', round_coin_value(strat_results['starting_balance'],
strat_results['stake_currency'])),
('Final balance', round_coin_value(strat_results['final_balance'],
strat_results['stake_currency'])),
('Absolute profit ', round_coin_value(strat_results['profit_total_abs'],
strat_results['stake_currency'])),
('Total profit %', f"{round(strat_results['profit_total'] * 100, 2)}%"),
('Trades per day', strat_results['trades_per_day']),
('Avg. stake amount', round_coin_value(strat_results['avg_stake_amount'],
strat_results['stake_currency'])),
('Total trade volume', round_coin_value(strat_results['total_volume'],
strat_results['stake_currency'])),
('', ''), # Empty line to improve readability
('Best Pair', f"{strat_results['best_pair']['key']} "
f"{round(strat_results['best_pair']['profit_sum_pct'], 2)}%"),
@@ -442,20 +477,28 @@ def text_table_add_metrics(strat_results: Dict) -> str:
('Worst trade', f"{worst_trade['pair']} "
f"{round(worst_trade['profit_ratio'] * 100, 2)}%"),
('Best day', f"{round(strat_results['backtest_best_day'] * 100, 2)}%"),
('Worst day', f"{round(strat_results['backtest_worst_day'] * 100, 2)}%"),
('Best day', round_coin_value(strat_results['backtest_best_day_abs'],
strat_results['stake_currency'])),
('Worst day', round_coin_value(strat_results['backtest_worst_day_abs'],
strat_results['stake_currency'])),
('Days win/draw/lose', f"{strat_results['winning_days']} / "
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']}"),
('', ''), # Empty line to improve readability
('Abs Profit Min', round_coin_value(strat_results['csum_min'],
strat_results['stake_currency'])),
('Abs Profit Max', round_coin_value(strat_results['csum_max'],
strat_results['stake_currency'])),
('Min balance', round_coin_value(strat_results['csum_min'],
strat_results['stake_currency'])),
('Max balance', round_coin_value(strat_results['csum_max'],
strat_results['stake_currency'])),
('Max Drawdown', f"{round(strat_results['max_drawdown'] * 100, 2)}%"),
('Drawdown', f"{round(strat_results['max_drawdown'] * 100, 2)}%"),
('Drawdown', round_coin_value(strat_results['max_drawdown_abs'],
strat_results['stake_currency'])),
('Drawdown high', round_coin_value(strat_results['max_drawdown_high'],
strat_results['stake_currency'])),
('Drawdown low', round_coin_value(strat_results['max_drawdown_low'],
strat_results['stake_currency'])),
('Drawdown Start', strat_results['drawdown_start'].strftime(DATETIME_PRINT_FORMAT)),
('Drawdown End', strat_results['drawdown_end'].strftime(DATETIME_PRINT_FORMAT)),
('Market change', f"{round(strat_results['market_change'] * 100, 2)}%"),
@@ -463,7 +506,17 @@ def text_table_add_metrics(strat_results: Dict) -> str:
return tabulate(metrics, headers=["Metric", "Value"], tablefmt="orgtbl")
else:
return ''
start_balance = round_coin_value(strat_results['starting_balance'],
strat_results['stake_currency'])
stake_amount = round_coin_value(
strat_results['stake_amount'], strat_results['stake_currency']
) if strat_results['stake_amount'] != UNLIMITED_STAKE_AMOUNT else 'unlimited'
message = ("No trades made. "
f"Your starting balance was {start_balance}, "
f"and your stake was {stake_amount}."
)
return message
def show_backtest_results(config: Dict, backtest_stats: Dict):

3
freqtrade/persistence/__init__.py
View File

@@ -1,4 +1,5 @@
# flake8: noqa: F401
from freqtrade.persistence.models import Order, Trade, clean_dry_run_db, cleanup_db, init_db
from freqtrade.persistence.models import (LocalTrade, Order, Trade, clean_dry_run_db, cleanup_db,
init_db)
from freqtrade.persistence.pairlock_middleware import PairLocks

2
freqtrade/persistence/migrations.py
View File

@@ -141,7 +141,7 @@ def check_migrate(engine, decl_base, previous_tables) -> None:
inspector = inspect(engine)
cols = inspector.get_columns('trades')
if 'orders' not in previous_tables:
if 'orders' not in previous_tables and 'trades' in previous_tables:
logger.info('Moving open orders to Orders table.')
migrate_open_orders_to_trades(engine)
else:

267
freqtrade/persistence/models.py
View File

@@ -199,67 +199,67 @@ class Order(_DECL_BASE):
return Order.query.filter(Order.ft_is_open.is_(True)).all()
class Trade(_DECL_BASE):
class LocalTrade():
"""
Trade database model.
Also handles updating and querying trades
Used in backtesting - must be aligned to Trade model!
"""
__tablename__ = 'trades'
use_db: bool = True
use_db: bool = False
# Trades container for backtesting
trades: List['Trade'] = []
trades: List['LocalTrade'] = []
id = Column(Integer, primary_key=True)
id: int = 0
orders = relationship("Order", order_by="Order.id", cascade="all, delete-orphan")
orders: List[Order] = []
exchange = Column(String, nullable=False)
pair = Column(String, nullable=False, index=True)
is_open = Column(Boolean, nullable=False, default=True, index=True)
fee_open = Column(Float, nullable=False, default=0.0)
fee_open_cost = Column(Float, nullable=True)
fee_open_currency = Column(String, nullable=True)
fee_close = Column(Float, nullable=False, default=0.0)
fee_close_cost = Column(Float, nullable=True)
fee_close_currency = Column(String, nullable=True)
open_rate = Column(Float)
open_rate_requested = Column(Float)
exchange: str = ''
pair: str = ''
is_open: bool = True
fee_open: float = 0.0
fee_open_cost: Optional[float] = None
fee_open_currency: str = ''
fee_close: float = 0.0
fee_close_cost: Optional[float] = None
fee_close_currency: str = ''
open_rate: float = 0.0
open_rate_requested: Optional[float] = None
# open_trade_value - calculated via _calc_open_trade_value
open_trade_value = Column(Float)
close_rate = Column(Float)
close_rate_requested = Column(Float)
close_profit = Column(Float)
close_profit_abs = Column(Float)
stake_amount = Column(Float, nullable=False)
amount = Column(Float)
amount_requested = Column(Float)
open_date = Column(DateTime, nullable=False, default=datetime.utcnow)
close_date = Column(DateTime)
open_order_id = Column(String)
open_trade_value: float = 0.0
close_rate: Optional[float] = None
close_rate_requested: Optional[float] = None
close_profit: Optional[float] = None
close_profit_abs: Optional[float] = None
stake_amount: float = 0.0
amount: float = 0.0
amount_requested: Optional[float] = None
open_date: datetime
close_date: Optional[datetime] = None
open_order_id: Optional[str] = None
# absolute value of the stop loss
stop_loss = Column(Float, nullable=True, default=0.0)
stop_loss: float = 0.0
# percentage value of the stop loss
stop_loss_pct = Column(Float, nullable=True)
stop_loss_pct: float = 0.0
# absolute value of the initial stop loss
initial_stop_loss = Column(Float, nullable=True, default=0.0)
initial_stop_loss: float = 0.0
# percentage value of the initial stop loss
initial_stop_loss_pct = Column(Float, nullable=True)
initial_stop_loss_pct: float = 0.0
# stoploss order id which is on exchange
stoploss_order_id = Column(String, nullable=True, index=True)
stoploss_order_id: Optional[str] = None
# last update time of the stoploss order on exchange
stoploss_last_update = Column(DateTime, nullable=True)
stoploss_last_update: Optional[datetime] = None
# absolute value of the highest reached price
max_rate = Column(Float, nullable=True, default=0.0)
max_rate: float = 0.0
# Lowest price reached
min_rate = Column(Float, nullable=True)
sell_reason = Column(String, nullable=True)
sell_order_status = Column(String, nullable=True)
strategy = Column(String, nullable=True)
timeframe = Column(Integer, nullable=True)
min_rate: float = 0.0
sell_reason: str = ''
sell_order_status: str = ''
strategy: str = ''
timeframe: Optional[int] = None
def __init__(self, **kwargs):
super().__init__(**kwargs)
for key in kwargs:
setattr(self, key, kwargs[key])
self.recalc_open_trade_value()
def __repr__(self):
@@ -268,6 +268,14 @@ class Trade(_DECL_BASE):
return (f'Trade(id={self.id}, pair={self.pair}, amount={self.amount:.8f}, '
f'open_rate={self.open_rate:.8f}, open_since={open_since})')
@property
def open_date_utc(self):
return self.open_date.replace(tzinfo=timezone.utc)
@property
def close_date_utc(self):
return self.close_date.replace(tzinfo=timezone.utc)
def to_json(self) -> Dict[str, Any]:
return {
'trade_id': self.id,
@@ -306,9 +314,9 @@ class Trade(_DECL_BASE):
'close_profit_pct': round(self.close_profit * 100, 2) if self.close_profit else None,
'close_profit_abs': self.close_profit_abs, # Deprecated
'trade_duration_s': (int((self.close_date - self.open_date).total_seconds())
'trade_duration_s': (int((self.close_date_utc - self.open_date_utc).total_seconds())
if self.close_date else None),
'trade_duration': (int((self.close_date - self.open_date).total_seconds() // 60)
'trade_duration': (int((self.close_date_utc - self.open_date_utc).total_seconds() // 60)
if self.close_date else None),
'profit_ratio': self.close_profit,
@@ -341,8 +349,7 @@ class Trade(_DECL_BASE):
"""
Resets all trades. Only active for backtesting mode.
"""
if not Trade.use_db:
Trade.trades = []
LocalTrade.trades = []
def adjust_min_max_rates(self, current_price: float) -> None:
"""
@@ -410,8 +417,8 @@ class Trade(_DECL_BASE):
if order_type in ('market', 'limit') and order['side'] == 'buy':
# Update open rate and actual amount
self.open_rate = Decimal(safe_value_fallback(order, 'average', 'price'))
self.amount = Decimal(safe_value_fallback(order, 'filled', 'amount'))
self.open_rate = float(safe_value_fallback(order, 'average', 'price'))
self.amount = float(safe_value_fallback(order, 'filled', 'amount'))
self.recalc_open_trade_value()
if self.is_open:
logger.info(f'{order_type.upper()}_BUY has been fulfilled for {self}.')
@@ -435,7 +442,7 @@ class Trade(_DECL_BASE):
Sets close_rate to the given rate, calculates total profit
and marks trade as closed
"""
self.close_rate = Decimal(rate)
self.close_rate = rate
self.close_profit = self.calc_profit_ratio()
self.close_profit_abs = self.calc_profit()
self.close_date = self.close_date or datetime.utcnow()
@@ -480,14 +487,6 @@ class Trade(_DECL_BASE):
def update_order(self, order: Dict) -> None:
Order.update_orders(self.orders, order)
def delete(self) -> None:
for order in self.orders:
Order.session.delete(order)
Trade.session.delete(self)
Trade.session.flush()
def _calc_open_trade_value(self) -> float:
"""
Calculate the open_rate including open_fee.
@@ -517,7 +516,7 @@ class Trade(_DECL_BASE):
if rate is None and not self.close_rate:
return 0.0
sell_trade = Decimal(self.amount) * Decimal(rate or self.close_rate)
sell_trade = Decimal(self.amount) * Decimal(rate or self.close_rate) # type: ignore
fees = sell_trade * Decimal(fee or self.fee_close)
return float(sell_trade - fees)
@@ -589,7 +588,7 @@ class Trade(_DECL_BASE):
@staticmethod
def get_trades_proxy(*, pair: str = None, is_open: bool = None,
open_date: datetime = None, close_date: datetime = None,
) -> List['Trade']:
) -> List['LocalTrade']:
"""
Helper function to query Trades.
Returns a List of trades, filtered on the parameters given.
@@ -598,30 +597,19 @@ class Trade(_DECL_BASE):
:return: unsorted List[Trade]
"""
if Trade.use_db:
trade_filter = []
if pair:
trade_filter.append(Trade.pair == pair)
if open_date:
trade_filter.append(Trade.open_date > open_date)
if close_date:
trade_filter.append(Trade.close_date > close_date)
if is_open is not None:
trade_filter.append(Trade.is_open.is_(is_open))
return Trade.get_trades(trade_filter).all()
else:
# Offline mode - without database
sel_trades = [trade for trade in Trade.trades]
if pair:
sel_trades = [trade for trade in sel_trades if trade.pair == pair]
if open_date:
sel_trades = [trade for trade in sel_trades if trade.open_date > open_date]
if close_date:
sel_trades = [trade for trade in sel_trades if trade.close_date
and trade.close_date > close_date]
if is_open is not None:
sel_trades = [trade for trade in sel_trades if trade.is_open == is_open]
return sel_trades
# Offline mode - without database
sel_trades = [trade for trade in LocalTrade.trades]
if pair:
sel_trades = [trade for trade in sel_trades if trade.pair == pair]
if open_date:
sel_trades = [trade for trade in sel_trades if trade.open_date > open_date]
if close_date:
sel_trades = [trade for trade in sel_trades if trade.close_date
and trade.close_date > close_date]
if is_open is not None:
sel_trades = [trade for trade in sel_trades if trade.is_open == is_open]
return sel_trades
@staticmethod
def get_open_trades() -> List[Any]:
@@ -663,9 +651,12 @@ class Trade(_DECL_BASE):
Calculates total invested amount in open trades
in stake currency
"""
total_open_stake_amount = Trade.session.query(func.sum(Trade.stake_amount))\
.filter(Trade.is_open.is_(True))\
.scalar()
if Trade.use_db:
total_open_stake_amount = Trade.session.query(
func.sum(Trade.stake_amount)).filter(Trade.is_open.is_(True)).scalar()
else:
total_open_stake_amount = sum(
t.stake_amount for t in Trade.get_trades_proxy(is_open=True))
return total_open_stake_amount or 0
@staticmethod
@@ -723,6 +714,108 @@ class Trade(_DECL_BASE):
logger.info(f"New stoploss: {trade.stop_loss}.")
class Trade(_DECL_BASE, LocalTrade):
"""
Trade database model.
Also handles updating and querying trades
Note: Fields must be aligned with LocalTrade class
"""
__tablename__ = 'trades'
use_db: bool = True
id = Column(Integer, primary_key=True)
orders = relationship("Order", order_by="Order.id", cascade="all, delete-orphan")
exchange = Column(String, nullable=False)
pair = Column(String, nullable=False, index=True)
is_open = Column(Boolean, nullable=False, default=True, index=True)
fee_open = Column(Float, nullable=False, default=0.0)
fee_open_cost = Column(Float, nullable=True)
fee_open_currency = Column(String, nullable=True)
fee_close = Column(Float, nullable=False, default=0.0)
fee_close_cost = Column(Float, nullable=True)
fee_close_currency = Column(String, nullable=True)
open_rate = Column(Float)
open_rate_requested = Column(Float)
# open_trade_value - calculated via _calc_open_trade_value
open_trade_value = Column(Float)
close_rate = Column(Float)
close_rate_requested = Column(Float)
close_profit = Column(Float)
close_profit_abs = Column(Float)
stake_amount = Column(Float, nullable=False)
amount = Column(Float)
amount_requested = Column(Float)
open_date = Column(DateTime, nullable=False, default=datetime.utcnow)
close_date = Column(DateTime)
open_order_id = Column(String)
# absolute value of the stop loss
stop_loss = Column(Float, nullable=True, default=0.0)
# percentage value of the stop loss
stop_loss_pct = Column(Float, nullable=True)
# absolute value of the initial stop loss
initial_stop_loss = Column(Float, nullable=True, default=0.0)
# percentage value of the initial stop loss
initial_stop_loss_pct = Column(Float, nullable=True)
# stoploss order id which is on exchange
stoploss_order_id = Column(String, nullable=True, index=True)
# last update time of the stoploss order on exchange
stoploss_last_update = Column(DateTime, nullable=True)
# absolute value of the highest reached price
max_rate = Column(Float, nullable=True, default=0.0)
# Lowest price reached
min_rate = Column(Float, nullable=True)
sell_reason = Column(String, nullable=True)
sell_order_status = Column(String, nullable=True)
strategy = Column(String, nullable=True)
timeframe = Column(Integer, nullable=True)
def __init__(self, **kwargs):
super().__init__(**kwargs)
self.recalc_open_trade_value()
def delete(self) -> None:
for order in self.orders:
Order.session.delete(order)
Trade.session.delete(self)
Trade.session.flush()
@staticmethod
def get_trades_proxy(*, pair: str = None, is_open: bool = None,
open_date: datetime = None, close_date: datetime = None,
) -> List['LocalTrade']:
"""
Helper function to query Trades.
Returns a List of trades, filtered on the parameters given.
In live mode, converts the filter to a database query and returns all rows
In Backtest mode, uses filters on Trade.trades to get the result.
:return: unsorted List[Trade]
"""
if Trade.use_db:
trade_filter = []
if pair:
trade_filter.append(Trade.pair == pair)
if open_date:
trade_filter.append(Trade.open_date > open_date)
if close_date:
trade_filter.append(Trade.close_date > close_date)
if is_open is not None:
trade_filter.append(Trade.is_open.is_(is_open))
return Trade.get_trades(trade_filter).all()
else:
return LocalTrade.get_trades_proxy(
pair=pair, is_open=is_open,
open_date=open_date,
close_date=close_date
)
class PairLock(_DECL_BASE):
"""
Pair Locks database model.

8
freqtrade/persistence/pairlock_middleware.py
View File

@@ -123,3 +123,11 @@ class PairLocks():
now = datetime.now(timezone.utc)
return len(PairLocks.get_pair_locks(pair, now)) > 0 or PairLocks.is_global_lock(now)
@staticmethod
def get_all_locks() -> List[PairLock]:
if PairLocks.use_db:
return PairLock.query.all()
else:
return PairLocks.locks

2
freqtrade/plot/plotting.py
View File

@@ -145,7 +145,7 @@ def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame,
Add scatter points indicating max drawdown
"""
try:
max_drawdown, highdate, lowdate = calculate_max_drawdown(trades)
max_drawdown, highdate, lowdate, _, _ = calculate_max_drawdown(trades)
drawdown = go.Scatter(
x=[highdate, lowdate],

3
freqtrade/plugins/protections/cooldown_period.py
View File

@@ -44,7 +44,8 @@ class CooldownPeriod(IProtection):
trades = Trade.get_trades_proxy(pair=pair, is_open=False, close_date=look_back_until)
if trades:
# Get latest trade
trade = sorted(trades, key=lambda t: t.close_date)[-1]
# Ignore type error as we know we only get closed trades.
trade = sorted(trades, key=lambda t: t.close_date)[-1] # type: ignore
self.log_once(f"Cooldown for {pair} for {self.stop_duration_str}.", logger.info)
until = self.calculate_lock_end([trade], self._stop_duration)

6
freqtrade/plugins/protections/iprotection.py
View File

@@ -7,7 +7,7 @@ from typing import Any, Dict, List, Optional, Tuple
from freqtrade.exchange import timeframe_to_minutes
from freqtrade.misc import plural
from freqtrade.mixins import LoggingMixin
from freqtrade.persistence import Trade
from freqtrade.persistence import LocalTrade
logger = logging.getLogger(__name__)
@@ -93,11 +93,11 @@ class IProtection(LoggingMixin, ABC):
"""
@staticmethod
def calculate_lock_end(trades: List[Trade], stop_minutes: int) -> datetime:
def calculate_lock_end(trades: List[LocalTrade], stop_minutes: int) -> datetime:
"""
Get lock end time
"""
max_date: datetime = max([trade.close_date for trade in trades])
max_date: datetime = max([trade.close_date for trade in trades if trade.close_date])
# comming from Database, tzinfo is not set.
if max_date.tzinfo is None:
max_date = max_date.replace(tzinfo=timezone.utc)

2
freqtrade/plugins/protections/low_profit_pairs.py
View File

@@ -53,7 +53,7 @@ class LowProfitPairs(IProtection):
# Not enough trades in the relevant period
return False, None, None
profit = sum(trade.close_profit for trade in trades)
profit = sum(trade.close_profit for trade in trades if trade.close_profit)
if profit < self._required_profit:
self.log_once(
f"Trading for {pair} stopped due to {profit:.2f} < {self._required_profit} "

2
freqtrade/plugins/protections/max_drawdown_protection.py
View File

@@ -55,7 +55,7 @@ class MaxDrawdown(IProtection):
# Drawdown is always positive
try:
drawdown, _, _ = calculate_max_drawdown(trades_df, value_col='close_profit')
drawdown, _, _, _, _ = calculate_max_drawdown(trades_df, value_col='close_profit')
except ValueError:
return False, None, None

2
freqtrade/plugins/protections/stoploss_guard.py
View File

@@ -56,7 +56,7 @@ class StoplossGuard(IProtection):
trades = [trade for trade in trades1 if (str(trade.sell_reason) in (
SellType.TRAILING_STOP_LOSS.value, SellType.STOP_LOSS.value,
SellType.STOPLOSS_ON_EXCHANGE.value)
and trade.close_profit < 0)]
and trade.close_profit and trade.close_profit < 0)]
if len(trades) < self._trade_limit:
return False, None, None

2
freqtrade/strategy/interface.py
View File

@@ -649,7 +649,7 @@ class IStrategy(ABC):
:return: True if bot should sell at current rate
"""
# Check if time matches and current rate is above threshold
trade_dur = int((current_time.timestamp() - trade.open_date.timestamp()) // 60)
trade_dur = int((current_time.timestamp() - trade.open_date_utc.timestamp()) // 60)
_, roi = self.min_roi_reached_entry(trade_dur)
if roi is None:
return False

20
freqtrade/wallets.py
View File

@@ -11,6 +11,7 @@ from freqtrade.constants import UNLIMITED_STAKE_AMOUNT
from freqtrade.exceptions import DependencyException
from freqtrade.exchange import Exchange
from freqtrade.persistence import Trade
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
@@ -26,8 +27,9 @@ class Wallet(NamedTuple):
class Wallets:
def __init__(self, config: dict, exchange: Exchange) -> None:
def __init__(self, config: dict, exchange: Exchange, log: bool = True) -> None:
self._config = config
self._log = log
self._exchange = exchange
self._wallets: Dict[str, Wallet] = {}
self.start_cap = config['dry_run_wallet']
@@ -64,9 +66,9 @@ class Wallets:
"""
# Recreate _wallets to reset closed trade balances
_wallets = {}
closed_trades = Trade.get_trades(Trade.is_open.is_(False)).all()
open_trades = Trade.get_trades(Trade.is_open.is_(True)).all()
tot_profit = sum([trade.calc_profit() for trade in closed_trades])
closed_trades = Trade.get_trades_proxy(is_open=False)
open_trades = Trade.get_trades_proxy(is_open=True)
tot_profit = sum([trade.close_profit_abs for trade in closed_trades])
tot_in_trades = sum([trade.stake_amount for trade in open_trades])
current_stake = self.start_cap + tot_profit - tot_in_trades
@@ -111,11 +113,12 @@ class Wallets:
:param require_update: Allow skipping an update if balances were recently refreshed
"""
if (require_update or (self._last_wallet_refresh + 3600 < arrow.utcnow().int_timestamp)):
if self._config['dry_run']:
self._update_dry()
else:
if (not self._config['dry_run'] or self._config.get('runmode') == RunMode.LIVE):
self._update_live()
logger.info('Wallets synced.')
else:
self._update_dry()
if self._log:
logger.info('Wallets synced.')
self._last_wallet_refresh = arrow.utcnow().int_timestamp
def get_all_balances(self) -> Dict[str, Any]:
@@ -154,6 +157,7 @@ class Wallets:
Check if stake amount can be fulfilled with the available balance
for the stake currency
:return: float: Stake amount
:raise: DependencyException if balance is lower than stake-amount
"""
available_amount = self._get_available_stake_amount()