fix: add dynamic timeframe_floor freq

fixes problems where funding-rates may be on the 1st second of the hour
(observed on gate from time to time)

freqtrade/data/converter/converter.py

@@ -39,7 +39,11 @@ def ohlcv_to_dataframe(
     df = DataFrame(ohlcv, columns=cols)
 
     # Floor date to seconds to account for exchange imprecisions
-    df["date"] = to_datetime(df["date"], unit="ms", utc=True).dt.floor("s")
+    from freqtrade.exchange import timeframe_to_floor_freq
+
+    resample_interval = timeframe_to_floor_freq(timeframe)
+
+    df["date"] = to_datetime(df["date"], unit="ms", utc=True).dt.floor(resample_interval)
 
     # Some exchanges return int values for Volume and even for OHLC.
     # Convert them since TA-LIB indicators used in the strategy assume floats

freqtrade/exchange/__init__.py

@@ -30,6 +30,7 @@ from freqtrade.exchange.exchange_utils import (
     validate_exchange,
 )
 from freqtrade.exchange.exchange_utils_timeframe import (
+    timeframe_to_floor_freq,
     timeframe_to_minutes,
     timeframe_to_msecs,
     timeframe_to_next_date,

freqtrade/exchange/exchange_utils_timeframe.py

@@ -29,6 +29,21 @@ def timeframe_to_msecs(timeframe: str) -> int:
     return ccxt.Exchange.parse_timeframe(timeframe) * 1000
 
 
+def timeframe_to_floor_freq(timeframe: str) -> str:
+    """
+    Translates the timeframe interval value written in the human readable
+    form ('1m', '5m', '1h', '1d', '1w', etc.) to the desired floor frequency used by pandas
+        ("1m", "5m", "1h", "1d", "1w", etc.).
+        Will use minute for most higher timeframes.
+    """
+    timeframe_seconds = timeframe_to_seconds(timeframe)
+    timeframe_minutes = timeframe_seconds // 60
+    if timeframe_minutes <= 1:
+        return "1s"
+    else:
+        return "1min"
+
+
 def timeframe_to_resample_freq(timeframe: str) -> str:
     """
     Translates the timeframe interval value written in the human readable