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Fix exception when few pairs with no data do not result in aborting backtest.

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Exception is triggered by backtesting 20210301-20210501 range with BAKE/USDT pair (binance). Pair data starts on 2021-04-30 12:00:00 and after adjusting for startup candles pair dataframe is empty.

Solution: Since there are other pairs with enough data - skip pairs with no data and issue a warning.

Exception:
```
Traceback (most recent call last):
  File "/home/rk/src/freqtrade/freqtrade/main.py", line 37, in main
    return_code = args['func'](args)
  File "/home/rk/src/freqtrade/freqtrade/commands/optimize_commands.py", line 53, in start_backtesting
    backtesting.start()
  File "/home/rk/src/freqtrade/freqtrade/optimize/backtesting.py", line 502, in start
    min_date, max_date = self.backtest_one_strategy(strat, data, timerange)
  File "/home/rk/src/freqtrade/freqtrade/optimize/backtesting.py", line 474, in backtest_one_strategy
    results = self.backtest(
  File "/home/rk/src/freqtrade/freqtrade/optimize/backtesting.py", line 365, in backtest
    data: Dict = self._get_ohlcv_as_lists(processed)
  File "/home/rk/src/freqtrade/freqtrade/optimize/backtesting.py", line 199, in _get_ohlcv_as_lists
    pair_data.loc[:, 'buy'] = 0  # cleanup from previous run
  File "/home/rk/src/freqtrade/venv/lib/python3.9/site-packages/pandas/core/indexing.py", line 692, in __setitem__
    iloc._setitem_with_indexer(indexer, value, self.name)
  File "/home/rk/src/freqtrade/venv/lib/python3.9/site-packages/pandas/core/indexing.py", line 1587, in _setitem_with_indexer
    raise ValueError(
ValueError: cannot set a frame with no defined index and a scalar
```
This commit is contained in:
Rokas Kupstys 2021-05-13 09:47:28 +03:00
parent 84222c89ee
commit 29fed37df3
1 changed files with 15 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

22
freqtrade/optimize/backtesting.py
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@ -9,7 +9,7 @@ from copy import deepcopy
from datetime import datetime, timedelta, timezone from datetime import datetime, timedelta, timezone
from typing import Any, Dict, List, Optional, Tuple from typing import Any, Dict, List, Optional, Tuple
from pandas import DataFrame, NaT from pandas import DataFrame
from freqtrade.configuration import TimeRange, remove_credentials, validate_config_consistency from freqtrade.configuration import TimeRange, remove_credentials, validate_config_consistency
from freqtrade.constants import DATETIME_PRINT_FORMAT from freqtrade.constants import DATETIME_PRINT_FORMAT
@ -457,13 +457,21 @@ class Backtesting:
preprocessed = self.strategy.ohlcvdata_to_dataframe(data) preprocessed = self.strategy.ohlcvdata_to_dataframe(data)
# Trim startup period from analyzed dataframe # Trim startup period from analyzed dataframe
for pair, df in preprocessed.items(): for pair in list(preprocessed):
preprocessed[pair] = trim_dataframe(df, timerange, df = preprocessed[pair]
startup_candles=self.required_startup) df = trim_dataframe(df, timerange, startup_candles=self.required_startup)
min_date, max_date = history.get_timerange(preprocessed) if len(df) > 0:
if min_date is NaT or max_date is NaT: preprocessed[pair] = df
else:
logger.warning(f'{pair} has no data left after adjusting for startup candles, '
f'skipping.')
del preprocessed[pair]
if not preprocessed:
raise OperationalException( raise OperationalException(
"No data left after adjusting for startup candles. ") "No data left after adjusting for startup candles.")
min_date, max_date = history.get_timerange(preprocessed)
logger.info(f'Backtesting with data from {min_date.strftime(DATETIME_PRINT_FORMAT)} ' logger.info(f'Backtesting with data from {min_date.strftime(DATETIME_PRINT_FORMAT)} '
f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} ' f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} '
f'({(max_date - min_date).days} days).') f'({(max_date - min_date).days} days).')