Move price_jump_warn to dataloading

it's not relevant for live data, and should only run when loading data
from disk.
This commit is contained in:
Matthias 2022-10-22 08:37:30 +02:00
parent 60cb11a44d
commit 0ff7a0771d
4 changed files with 98 additions and 14 deletions

View File

@ -119,14 +119,6 @@ def ohlcv_fill_up_missing_data(dataframe: DataFrame, timeframe: str, pair: str)
else: else:
# Don't be verbose if only a small amount is missing # Don't be verbose if only a small amount is missing
logger.debug(message) logger.debug(message)
candle_price_gap = 0
if not df.empty and 'close' in df.columns:
returns = df['close'].pct_change().dropna()
if len(returns):
candle_price_gap = max(abs(returns))
if candle_price_gap > 0.3:
logger.info(f"Price jump in {pair} between two candles of {candle_price_gap:.2%} detected.")
return df return df

View File

@ -335,6 +335,20 @@ class IDataHandler(ABC):
"Use `freqtrade download-data` to download the data" "Use `freqtrade download-data` to download the data"
) )
return True return True
else:
candle_price_gap = 0
if (candle_type in (CandleType.SPOT, CandleType.FUTURES) and
not pairdf.empty
and 'close' in pairdf.columns and 'open' in pairdf.columns):
# Detect gaps between prior close and open
gaps = ((pairdf['open'] - pairdf['close'].shift(1)) / pairdf['close'].shift(1))
gaps = gaps.dropna()
if len(gaps):
candle_price_gap = max(abs(gaps))
if candle_price_gap > 0.1:
logger.info(f"Price jump in {pair} between two candles of "
f"{candle_price_gap:.2%} detected.")
return False return False
def _validate_pairdata(self, pair, pairdata: DataFrame, timeframe: str, def _validate_pairdata(self, pair, pairdata: DataFrame, timeframe: str,

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@ -80,10 +80,10 @@ def test_ohlcv_fill_up_missing_data2(caplog):
ticks = [ ticks = [
[ [
1511686200000, # 8:50:00 1511686200000, # 8:50:00
8.794e-07, # open 8.794e-05, # open
8.948e-07, # high 8.948e-05, # high
8.794e-07, # low 8.794e-05, # low
8.88e-07, # close 8.88e-05, # close
2255, # volume (in quote currency) 2255, # volume (in quote currency)
], ],
[ [
@ -118,7 +118,6 @@ def test_ohlcv_fill_up_missing_data2(caplog):
assert len(data) == 3 assert len(data) == 3
caplog.set_level(logging.DEBUG) caplog.set_level(logging.DEBUG)
data2 = ohlcv_fill_up_missing_data(data, timeframe, "UNITTEST/BTC") data2 = ohlcv_fill_up_missing_data(data, timeframe, "UNITTEST/BTC")
assert log_has_re(r"Price jump in .* between two candles .* detected\.", caplog)
assert len(data2) == 4 assert len(data2) == 4
# 3rd candle has been filled # 3rd candle has been filled
row = data2.loc[2, :] row = data2.loc[2, :]

View File

@ -15,7 +15,7 @@ from freqtrade.data.history.idatahandler import IDataHandler, get_datahandler, g
from freqtrade.data.history.jsondatahandler import JsonDataHandler, JsonGzDataHandler from freqtrade.data.history.jsondatahandler import JsonDataHandler, JsonGzDataHandler
from freqtrade.data.history.parquetdatahandler import ParquetDataHandler from freqtrade.data.history.parquetdatahandler import ParquetDataHandler
from freqtrade.enums import CandleType, TradingMode from freqtrade.enums import CandleType, TradingMode
from tests.conftest import log_has from tests.conftest import log_has, log_has_re
def test_datahandler_ohlcv_get_pairs(testdatadir): def test_datahandler_ohlcv_get_pairs(testdatadir):
@ -154,6 +154,85 @@ def test_jsondatahandler_ohlcv_load(testdatadir, caplog):
assert df.columns.equals(df1.columns) assert df.columns.equals(df1.columns)
def test_datahandler__check_empty_df(testdatadir, caplog):
dh = JsonDataHandler(testdatadir)
expected_text = r"Price jump in UNITTEST/USDT between"
df = DataFrame([
[
1511686200000, # 8:50:00
8.794, # open
8.948, # high
8.794, # low
8.88, # close
2255, # volume (in quote currency)
],
[
1511686500000, # 8:55:00
8.88,
8.942,
8.88,
8.893,
9911,
],
[
1511687100000, # 9:05:00
8.891,
8.893,
8.875,
8.877,
2251
],
[
1511687400000, # 9:10:00
8.877,
8.883,
8.895,
8.817,
123551
]
], columns=['date', 'open', 'high', 'low', 'close', 'volume'])
dh._check_empty_df(df, 'UNITTEST/USDT', '1h', CandleType.SPOT, True)
assert not log_has_re(expected_text, caplog)
df = DataFrame([
[
1511686200000, # 8:50:00
8.794, # open
8.948, # high
8.794, # low
8.88, # close
2255, # volume (in quote currency)
],
[
1511686500000, # 8:55:00
8.88,
8.942,
8.88,
8.893,
9911,
],
[
1511687100000, # 9:05:00
889.1, # Price jump by several decimals
889.3,
887.5,
887.7,
2251
],
[
1511687400000, # 9:10:00
8.877,
8.883,
8.895,
8.817,
123551
]
], columns=['date', 'open', 'high', 'low', 'close', 'volume'])
dh._check_empty_df(df, 'UNITTEST/USDT', '1h', CandleType.SPOT, True)
assert log_has_re(expected_text, caplog)
@pytest.mark.parametrize('datahandler', ['feather', 'parquet']) @pytest.mark.parametrize('datahandler', ['feather', 'parquet'])
def test_datahandler_trades_not_supported(datahandler, testdatadir, ): def test_datahandler_trades_not_supported(datahandler, testdatadir, ):
dh = get_datahandler(testdatadir, datahandler) dh = get_datahandler(testdatadir, datahandler)