Merge branch 'freqtrade:develop' into patch-1

freqtrade/data/dataprovider.py

@@ -9,7 +9,7 @@ from collections import deque
 from datetime import datetime, timezone
 from typing import Any, Dict, List, Optional, Tuple
 
-from pandas import DataFrame, to_timedelta
+from pandas import DataFrame, Timedelta, Timestamp, to_timedelta
 
 from freqtrade.configuration import TimeRange
 from freqtrade.constants import (FULL_DATAFRAME_THRESHOLD, Config, ListPairsWithTimeframes,
@@ -206,9 +206,11 @@ class DataProvider:
         existing_df, _ = self.__producer_pairs_df[producer_name][pair_key]
 
         # CHECK FOR MISSING CANDLES
-        timeframe_delta = to_timedelta(timeframe)  # Convert the timeframe to a timedelta for pandas
+        # Convert the timeframe to a timedelta for pandas
-        local_last = existing_df.iloc[-1]['date']  # We want the last date from our copy
+        timeframe_delta: Timedelta = to_timedelta(timeframe)
-        incoming_first = dataframe.iloc[0]['date']  # We want the first date from the incoming
+        local_last: Timestamp = existing_df.iloc[-1]['date']  # We want the last date from our copy
+        # We want the first date from the incoming
+        incoming_first: Timestamp = dataframe.iloc[0]['date']
 
         # Remove existing candles that are newer than the incoming first candle
         existing_df1 = existing_df[existing_df['date'] < incoming_first]
@@ -221,7 +223,7 @@ class DataProvider:
         # we missed some candles between our data and the incoming
         # so return False and candle_difference.
         if candle_difference > 1:
-            return (False, candle_difference)
+            return (False, int(candle_difference))
         if existing_df1.empty:
             appended_df = dataframe
         else:

freqtrade/data/history/idatahandler.py

@@ -308,7 +308,7 @@ class IDataHandler(ABC):
             timerange=timerange_startup,
             candle_type=candle_type
         )
-        if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data, True):
+        if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data):
             return pairdf
         else:
             enddate = pairdf.iloc[-1]['date']
@@ -316,7 +316,7 @@ class IDataHandler(ABC):
             if timerange_startup:
                 self._validate_pairdata(pair, pairdf, timeframe, candle_type, timerange_startup)
                 pairdf = trim_dataframe(pairdf, timerange_startup)
-                if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data):
+                if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data, True):
                     return pairdf
 
             # incomplete candles should only be dropped if we didn't trim the end beforehand.

freqtrade/optimize/hyperopt_loss/hyperopt_loss_sharpe_daily.py

@@ -44,7 +44,7 @@ class SharpeHyperOptLossDaily(IHyperOptLoss):
 
         sum_daily = (
             results.resample(resample_freq, on='close_date').agg(
-                {"profit_ratio_after_slippage": sum}).reindex(t_index).fillna(0)
+                {"profit_ratio_after_slippage": 'sum'}).reindex(t_index).fillna(0)
         )
 
         total_profit = sum_daily["profit_ratio_after_slippage"] - risk_free_rate

freqtrade/optimize/hyperopt_loss/hyperopt_loss_sortino_daily.py

@@ -46,7 +46,7 @@ class SortinoHyperOptLossDaily(IHyperOptLoss):
 
         sum_daily = (
             results.resample(resample_freq, on='close_date').agg(
-                {"profit_ratio_after_slippage": sum}).reindex(t_index).fillna(0)
+                {"profit_ratio_after_slippage": 'sum'}).reindex(t_index).fillna(0)
         )
 
         total_profit = sum_daily["profit_ratio_after_slippage"] - minimum_acceptable_return

freqtrade/rpc/api_server/api_ws.py

@@ -90,7 +90,7 @@ async def _process_consumer_request(
 
     elif type == RPCRequestType.ANALYZED_DF:
         # Limit the amount of candles per dataframe to 'limit' or 1500
-        limit = min(data.get('limit', 1500), 1500) if data else None
+        limit = int(min(data.get('limit', 1500), 1500)) if data else None
         pair = data.get('pair', None) if data else None
 
         # For every pair in the generator, send a separate message

tests/data/test_dataprovider.py

@@ -437,6 +437,7 @@ def test_dp__add_external_df(default_conf_usdt):
     # Add the same dataframe again - dataframe size shall not change.
     res = dp._add_external_df('ETH/USDT', df, last_analyzed, timeframe, CandleType.SPOT)
     assert res[0] is True
+    assert isinstance(res[1], int)
     assert res[1] == 0
     df, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
     assert len(df) == 24
@@ -446,6 +447,7 @@ def test_dp__add_external_df(default_conf_usdt):
 
     res = dp._add_external_df('ETH/USDT', df2, last_analyzed, timeframe, CandleType.SPOT)
     assert res[0] is True
+    assert isinstance(res[1], int)
     assert res[1] == 0
     df, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
     assert len(df) == 48
@@ -455,6 +457,7 @@ def test_dp__add_external_df(default_conf_usdt):
 
     res = dp._add_external_df('ETH/USDT', df3, last_analyzed, timeframe, CandleType.SPOT)
     assert res[0] is True
+    assert isinstance(res[1], int)
     assert res[1] == 0
     df, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
     # New length = 48 + 12 (since we have a 12 hour offset).
@@ -478,6 +481,7 @@ def test_dp__add_external_df(default_conf_usdt):
     res = dp._add_external_df('ETH/USDT', df4, last_analyzed, timeframe, CandleType.SPOT)
     assert res[0] is False
     # 36 hours - from 2022-01-03 12:00:00+00:00 to 2022-01-05 00:00:00+00:00
+    assert isinstance(res[1], int)
     assert res[1] == 36
     df, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
     # New length = 61 + 1
@@ -488,4 +492,5 @@ def test_dp__add_external_df(default_conf_usdt):
     res = dp._add_external_df('ETH/USDT', df4, last_analyzed, timeframe, CandleType.SPOT)
     assert res[0] is False
     # 36 hours - from 2022-01-03 12:00:00+00:00 to 2022-01-05 00:00:00+00:00
+    assert isinstance(res[1], int)
     assert res[1] == 0