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Updating PR taking into account @kriofly review!

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This commit is contained in:
Jean-Baptiste LE STANG 2018-01-28 14:03:27 +01:00
parent 961118de51
commit 277f72c6eb
2 changed files with 9 additions and 7 deletions
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7
freqtrade/main.py
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@ -309,11 +309,12 @@ def min_roi_reached(trade: Trade, current_rate: float, current_time: datetime) -
def should_sell(trade: Trade, rate: float, date: datetime, buy: bool, sell: bool) -> bool:
"""
Sells the current pair if the threshold is reached and updates the trade record.
:return: True if trade has been sold, False otherwise
This function evaluate if on the condition required to trigger a sell has been reached
if the threshold is reached and updates the trade record.
:return: True if trade should be sold, False otherwise
"""
# Check if minimal roi has been reached and no longer in buy conditions (avoiding a fee)
if not buy and min_roi_reached(trade, rate, date):
if min_roi_reached(trade, rate, date):
logger.debug('Executing sell due to ROI ...')
return True

9
freqtrade/optimize/backtesting.py
View File

@ -67,7 +67,7 @@ def generate_text_table(
return tabulate(tabular_data, headers=headers, floatfmt=floatfmt)
def get_sell_trade_entry(pair, row, rows, ticker, trade_count_lock, args):
def get_sell_trade_entry(pair, row, buy_subset, ticker, trade_count_lock, args):
stake_amount = args['stake_amount']
max_open_trades = args.get('max_open_trades', 0)
trade = Trade(open_rate=row.close,
@ -84,14 +84,14 @@ def get_sell_trade_entry(pair, row, rows, ticker, trade_count_lock, args):
# Increase trade_count_lock for every iteration
trade_count_lock[row2.date] = trade_count_lock.get(row2.date, 0) + 1
buy_signal = rows[rows.date == row2.date].empty
buy_signal = buy_subset[buy_subset.date == row2.date].empty
if(should_sell(trade, row2.close, row2.date, buy_signal, row2.sell)):
return row2, (pair,
trade.calc_profit_percent(rate=row2.close),
trade.calc_profit(rate=row2.close),
row2.Index - row.Index
), row2.date
return False
return None
def backtest(args) -> DataFrame:
@ -120,7 +120,8 @@ def backtest(args) -> DataFrame:
ticker = populate_sell_trend(populate_buy_trend(pair_data))
# for each buy point
lock_pair_until = None
buy_subset = ticker[(ticker.buy == 1) & (ticker.sell == 0)][['buy', 'open', 'close', 'date', 'sell']]
headers = ['buy', 'open', 'close', 'date', 'sell']
buy_subset = ticker[(ticker.buy == 1) & (ticker.sell == 0)][headers]
for row in buy_subset.itertuples(index=True):
if realistic:
if lock_pair_until is not None and row.date <= lock_pair_until: