Use Datetime_format from constants
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@@ -228,9 +228,9 @@ def _download_pair_history(pair: str, *,
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)
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logger.debug("Current Start: %s",
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f"{data.iloc[0]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
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f"{data.iloc[0]['date']:DATETIME_PRINT_FORMAT}" if not data.empty else 'None')
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logger.debug("Current End: %s",
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f"{data.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
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f"{data.iloc[-1]['date']:DATETIME_PRINT_FORMAT}" if not data.empty else 'None')
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# Default since_ms to 30 days if nothing is given
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new_data = exchange.get_historic_ohlcv(pair=pair,
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@@ -254,9 +254,9 @@ def _download_pair_history(pair: str, *,
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fill_missing=False, drop_incomplete=False)
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logger.debug("New Start: %s",
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f"{data.iloc[0]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
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f"{data.iloc[0]['date']:DATETIME_PRINT_FORMAT}" if not data.empty else 'None')
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logger.debug("New End: %s",
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f"{data.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
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f"{data.iloc[-1]['date']:DATETIME_PRINT_FORMAT}" if not data.empty else 'None')
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data_handler.ohlcv_store(pair, timeframe, data=data, candle_type=candle_type)
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return True
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@@ -14,6 +14,7 @@ from numpy.typing import NDArray
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from pandas import DataFrame
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from freqtrade.configuration import TimeRange
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from freqtrade.constants import DATETIME_PRINT_FORMAT
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from freqtrade.enums import RunMode
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from freqtrade.exceptions import OperationalException
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from freqtrade.exchange import timeframe_to_seconds
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@@ -232,10 +233,10 @@ class IFreqaiModel(ABC):
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trained_timestamp = tr_train
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tr_train_startts_str = datetime.fromtimestamp(
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tr_train.startts,
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tz=timezone.utc).strftime("%Y-%m-%d %H:%M:%S")
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tz=timezone.utc).strftime(DATETIME_PRINT_FORMAT)
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tr_train_stopts_str = datetime.fromtimestamp(
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tr_train.stopts,
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tz=timezone.utc).strftime("%Y-%m-%d %H:%M:%S")
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tz=timezone.utc).strftime(DATETIME_PRINT_FORMAT)
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logger.info(
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f"Training {metadata['pair']}, {self.pair_it}/{self.total_pairs} pairs"
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f" from {tr_train_startts_str} to {tr_train_stopts_str}, {train_it}/{total_trains} "
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