Merge branch 'develop' into feat/cancel_order

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
-        local_last = existing_df.iloc[-1]['date']  # We want the last date from our copy
-        incoming_first = dataframe.iloc[0]['date']  # We want the first date from the incoming
+        # Convert the timeframe to a timedelta for pandas
+        timeframe_delta: Timedelta = to_timedelta(timeframe)
+        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/exchange/bybit.py

@@ -34,6 +34,7 @@ class Bybit(Exchange):
         "ohlcv_candle_limit": 200,
         "ohlcv_has_history": True,
         "mark_ohlcv_timeframe": "4h",
+        "funding_fee_timeframe": "8h",
         "stoploss_on_exchange": True,
         "stoploss_order_types": {"limit": "limit", "market": "market"},
     }

freqtrade/exchange/kucoin.py

@@ -36,3 +36,34 @@ class Kucoin(Exchange):
             'stop': 'loss'
             })
         return params
+
+    def create_order(
+            self,
+            *,
+            pair: str,
+            ordertype: str,
+            side: BuySell,
+            amount: float,
+            rate: float,
+            leverage: float,
+            reduceOnly: bool = False,
+            time_in_force: str = 'GTC',
+            ) -> Dict:
+
+        res = super().create_order(
+            pair=pair,
+            ordertype=ordertype,
+            side=side,
+            amount=amount,
+            rate=rate,
+            leverage=leverage,
+            reduceOnly=reduceOnly,
+            time_in_force=time_in_force,
+        )
+        # Kucoin returns only the order-id.
+        # ccxt returns status = 'closed' at the moment - which is information ccxt invented.
+        # Since we rely on status heavily, we must set it to 'open' here.
+        # ref: https://github.com/ccxt/ccxt/pull/16674, (https://github.com/ccxt/ccxt/pull/16553)
+        res['type'] = ordertype
+        res['status'] = 'open'
+        return res

freqtrade/freqtradebot.py

@@ -750,13 +750,15 @@ class FreqtradeBot(LoggingMixin):
                                self.exchange.name, order['filled'], order['amount'],
                                order['remaining']
                                )
-                amount = safe_value_fallback(order, 'filled', 'amount')
-                enter_limit_filled_price = safe_value_fallback(order, 'average', 'price')
+                amount = safe_value_fallback(order, 'filled', 'amount', amount)
+                enter_limit_filled_price = safe_value_fallback(
+                    order, 'average', 'price', enter_limit_filled_price)
 
         # in case of FOK the order may be filled immediately and fully
         elif order_status == 'closed':
-            amount = safe_value_fallback(order, 'filled', 'amount')
-            enter_limit_filled_price = safe_value_fallback(order, 'average', 'price')
+            amount = safe_value_fallback(order, 'filled', 'amount', amount)
+            enter_limit_filled_price = safe_value_fallback(
+                order, 'average', 'price', enter_limit_requested)
 
         # Fee is applied twice because we make a LIMIT_BUY and LIMIT_SELL
         fee = self.exchange.get_fee(symbol=pair, taker_or_maker='maker')

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/persistence/trade_model.py

@@ -172,7 +172,7 @@ class Order(_DECL_BASE):
 
     def to_json(self, entry_side: str, minified: bool = False) -> Dict[str, Any]:
         resp = {
-            'amount': self.amount,
+            'amount': self.safe_amount,
             'safe_price': self.safe_price,
             'ft_order_side': self.ft_order_side,
             'order_filled_timestamp': int(self.order_filled_date.replace(

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