[pull] develop from freqtrade:develop

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
@@ -59,14 +63,14 @@ def ohlcv_to_dataframe(
 
 
 def clean_ohlcv_dataframe(
-    data: DataFrame, timeframe: str, pair: str, *, fill_missing: bool, drop_incomplete: bool
+    dataframe: DataFrame, timeframe: str, pair: str, *, fill_missing: bool, drop_incomplete: bool
 ) -> DataFrame:
     """
     Cleanse a OHLCV dataframe by
       * Grouping it by date (removes duplicate tics)
       * dropping last candles if requested
       * Filling up missing data (if requested)
-    :param data: DataFrame containing candle (OHLCV) data.
+    :param dataframe: DataFrame containing candle (OHLCV) data.
     :param timeframe: timeframe (e.g. 5m). Used to fill up eventual missing data
     :param pair: Pair this data is for (used to warn if fillup was necessary)
     :param fill_missing: fill up missing candles with 0 candles
@@ -75,7 +79,7 @@ def clean_ohlcv_dataframe(
     :return: DataFrame
     """
     # group by index and aggregate results to eliminate duplicate ticks
-    data = data.groupby(by="date", as_index=False, sort=True).agg(
+    dataframe = dataframe.groupby(by="date", as_index=False, sort=True).agg(
         {
             "open": "first",
             "high": "max",
@@ -86,13 +90,13 @@ def clean_ohlcv_dataframe(
     )
     # eliminate partial candle
     if drop_incomplete:
-        data.drop(data.tail(1).index, inplace=True)
+        dataframe.drop(dataframe.tail(1).index, inplace=True)
         logger.debug("Dropping last candle")
 
     if fill_missing:
-        return ohlcv_fill_up_missing_data(data, timeframe, pair)
+        return ohlcv_fill_up_missing_data(dataframe, timeframe, pair)
     else:
-        return data
+        return dataframe
 
 
 def ohlcv_fill_up_missing_data(dataframe: DataFrame, timeframe: str, pair: str) -> DataFrame:

freqtrade/exchange/__init__.py

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