Move price_jump_warn to dataloading
it's not relevant for live data, and should only run when loading data from disk.
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@ -119,14 +119,6 @@ def ohlcv_fill_up_missing_data(dataframe: DataFrame, timeframe: str, pair: str)
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else:
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# Don't be verbose if only a small amount is missing
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logger.debug(message)
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candle_price_gap = 0
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if not df.empty and 'close' in df.columns:
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returns = df['close'].pct_change().dropna()
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if len(returns):
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candle_price_gap = max(abs(returns))
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if candle_price_gap > 0.3:
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logger.info(f"Price jump in {pair} between two candles of {candle_price_gap:.2%} detected.")
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return df
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@ -335,6 +335,20 @@ class IDataHandler(ABC):
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"Use `freqtrade download-data` to download the data"
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)
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return True
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else:
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candle_price_gap = 0
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if (candle_type in (CandleType.SPOT, CandleType.FUTURES) and
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not pairdf.empty
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and 'close' in pairdf.columns and 'open' in pairdf.columns):
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# Detect gaps between prior close and open
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gaps = ((pairdf['open'] - pairdf['close'].shift(1)) / pairdf['close'].shift(1))
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gaps = gaps.dropna()
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if len(gaps):
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candle_price_gap = max(abs(gaps))
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if candle_price_gap > 0.1:
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logger.info(f"Price jump in {pair} between two candles of "
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f"{candle_price_gap:.2%} detected.")
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return False
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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):
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ticks = [
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[
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1511686200000, # 8:50:00
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8.794e-07, # open
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8.948e-07, # high
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8.794e-07, # low
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8.88e-07, # close
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8.794e-05, # open
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8.948e-05, # high
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8.794e-05, # low
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8.88e-05, # close
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2255, # volume (in quote currency)
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],
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[
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@ -118,7 +118,6 @@ def test_ohlcv_fill_up_missing_data2(caplog):
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assert len(data) == 3
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caplog.set_level(logging.DEBUG)
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data2 = ohlcv_fill_up_missing_data(data, timeframe, "UNITTEST/BTC")
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assert log_has_re(r"Price jump in .* between two candles .* detected\.", caplog)
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assert len(data2) == 4
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# 3rd candle has been filled
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row = data2.loc[2, :]
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@ -15,7 +15,7 @@ from freqtrade.data.history.idatahandler import IDataHandler, get_datahandler, g
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from freqtrade.data.history.jsondatahandler import JsonDataHandler, JsonGzDataHandler
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from freqtrade.data.history.parquetdatahandler import ParquetDataHandler
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from freqtrade.enums import CandleType, TradingMode
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from tests.conftest import log_has
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from tests.conftest import log_has, log_has_re
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def test_datahandler_ohlcv_get_pairs(testdatadir):
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@ -154,6 +154,85 @@ def test_jsondatahandler_ohlcv_load(testdatadir, caplog):
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assert df.columns.equals(df1.columns)
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def test_datahandler__check_empty_df(testdatadir, caplog):
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dh = JsonDataHandler(testdatadir)
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expected_text = r"Price jump in UNITTEST/USDT between"
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df = DataFrame([
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[
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1511686200000, # 8:50:00
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8.794, # open
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8.948, # high
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8.794, # low
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8.88, # close
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2255, # volume (in quote currency)
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],
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[
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1511686500000, # 8:55:00
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8.88,
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8.942,
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8.88,
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8.893,
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9911,
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],
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[
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1511687100000, # 9:05:00
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8.891,
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8.893,
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8.875,
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8.877,
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2251
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],
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[
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1511687400000, # 9:10:00
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8.877,
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8.883,
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8.895,
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8.817,
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123551
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]
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], columns=['date', 'open', 'high', 'low', 'close', 'volume'])
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dh._check_empty_df(df, 'UNITTEST/USDT', '1h', CandleType.SPOT, True)
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assert not log_has_re(expected_text, caplog)
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df = DataFrame([
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[
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1511686200000, # 8:50:00
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8.794, # open
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8.948, # high
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8.794, # low
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8.88, # close
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2255, # volume (in quote currency)
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],
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[
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1511686500000, # 8:55:00
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8.88,
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8.942,
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8.88,
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8.893,
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9911,
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],
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[
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1511687100000, # 9:05:00
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889.1, # Price jump by several decimals
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889.3,
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887.5,
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887.7,
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2251
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],
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[
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1511687400000, # 9:10:00
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8.877,
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8.883,
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8.895,
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8.817,
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123551
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]
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], columns=['date', 'open', 'high', 'low', 'close', 'volume'])
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dh._check_empty_df(df, 'UNITTEST/USDT', '1h', CandleType.SPOT, True)
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assert log_has_re(expected_text, caplog)
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@pytest.mark.parametrize('datahandler', ['feather', 'parquet'])
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def test_datahandler_trades_not_supported(datahandler, testdatadir, ):
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dh = get_datahandler(testdatadir, datahandler)
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