Fix dataprovider in hyperopt.

freqtrade/data/dataprovider.py

@@ -45,40 +45,6 @@ class DataProvider:
         """
         self._pairlists = pairlists
 
-    def refresh(self,
-                pairlist: ListPairsWithTimeframes,
-                helping_pairs: ListPairsWithTimeframes = None) -> None:
-        """
-        Refresh data, called with each cycle
-        """
-        if helping_pairs:
-            self._exchange.refresh_latest_ohlcv(pairlist + helping_pairs)
-        else:
-            self._exchange.refresh_latest_ohlcv(pairlist)
-
-    @property
-    def available_pairs(self) -> ListPairsWithTimeframes:
-        """
-        Return a list of tuples containing (pair, timeframe) for which data is currently cached.
-        Should be whitelist + open trades.
-        """
-        return list(self._exchange._klines.keys())
-
-    def ohlcv(self, pair: str, timeframe: str = None, copy: bool = True) -> DataFrame:
-        """
-        Get candle (OHLCV) data for the given pair as DataFrame
-        Please use the `available_pairs` method to verify which pairs are currently cached.
-        :param pair: pair to get the data for
-        :param timeframe: Timeframe to get data for
-        :param copy: copy dataframe before returning if True.
-                     Use False only for read-only operations (where the dataframe is not modified)
-        """
-        if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
-            return self._exchange.klines((pair, timeframe or self._config['timeframe']),
-                                         copy=copy)
-        else:
-            return DataFrame()
-
     def historic_ohlcv(self, pair: str, timeframe: str = None) -> DataFrame:
         """
         Get stored historical candle (OHLCV) data
@@ -123,35 +89,6 @@ class DataProvider:
 
             return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc))
 
-    def market(self, pair: str) -> Optional[Dict[str, Any]]:
-        """
-        Return market data for the pair
-        :param pair: Pair to get the data for
-        :return: Market data dict from ccxt or None if market info is not available for the pair
-        """
-        return self._exchange.markets.get(pair)
-
-    def ticker(self, pair: str):
-        """
-        Return last ticker data from exchange
-        :param pair: Pair to get the data for
-        :return: Ticker dict from exchange or empty dict if ticker is not available for the pair
-        """
-        try:
-            return self._exchange.fetch_ticker(pair)
-        except ExchangeError:
-            return {}
-
-    def orderbook(self, pair: str, maximum: int) -> Dict[str, List]:
-        """
-        Fetch latest l2 orderbook data
-        Warning: Does a network request - so use with common sense.
-        :param pair: pair to get the data for
-        :param maximum: Maximum number of orderbook entries to query
-        :return: dict including bids/asks with a total of `maximum` entries.
-        """
-        return self._exchange.fetch_l2_order_book(pair, maximum)
-
     @property
     def runmode(self) -> RunMode:
         """
@@ -175,4 +112,82 @@ class DataProvider:
             raise OperationalException("Dataprovider was not initialized with a pairlist provider.")
 
     def clear_cache(self):
+        """
+        Clear pair dataframe cache.
+        """
         self.__cached_pairs = {}
+
+    # Exchange functions
+
+    def refresh(self,
+                pairlist: ListPairsWithTimeframes,
+                helping_pairs: ListPairsWithTimeframes = None) -> None:
+        """
+        Refresh data, called with each cycle
+        """
+        if self._exchange is None:
+            raise OperationalException('Exchange is not available to DataProvider.')
+        if helping_pairs:
+            self._exchange.refresh_latest_ohlcv(pairlist + helping_pairs)
+        else:
+            self._exchange.refresh_latest_ohlcv(pairlist)
+
+    @property
+    def available_pairs(self) -> ListPairsWithTimeframes:
+        """
+        Return a list of tuples containing (pair, timeframe) for which data is currently cached.
+        Should be whitelist + open trades.
+        """
+        if self._exchange is None:
+            raise OperationalException('Exchange is not available to DataProvider.')
+        return list(self._exchange._klines.keys())
+
+    def ohlcv(self, pair: str, timeframe: str = None, copy: bool = True) -> DataFrame:
+        """
+        Get candle (OHLCV) data for the given pair as DataFrame
+        Please use the `available_pairs` method to verify which pairs are currently cached.
+        :param pair: pair to get the data for
+        :param timeframe: Timeframe to get data for
+        :param copy: copy dataframe before returning if True.
+                     Use False only for read-only operations (where the dataframe is not modified)
+        """
+        if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
+            return self._exchange.klines((pair, timeframe or self._config['timeframe']),
+                                         copy=copy)
+        else:
+            return DataFrame()
+
+    def market(self, pair: str) -> Optional[Dict[str, Any]]:
+        """
+        Return market data for the pair
+        :param pair: Pair to get the data for
+        :return: Market data dict from ccxt or None if market info is not available for the pair
+        """
+        if self._exchange is None:
+            raise OperationalException('Exchange is not available to DataProvider.')
+        return self._exchange.markets.get(pair)
+
+    def ticker(self, pair: str):
+        """
+        Return last ticker data from exchange
+        :param pair: Pair to get the data for
+        :return: Ticker dict from exchange or empty dict if ticker is not available for the pair
+        """
+        if self._exchange is None:
+            raise OperationalException('Exchange is not available to DataProvider.')
+        try:
+            return self._exchange.fetch_ticker(pair)
+        except ExchangeError:
+            return {}
+
+    def orderbook(self, pair: str, maximum: int) -> Dict[str, List]:
+        """
+        Fetch latest l2 orderbook data
+        Warning: Does a network request - so use with common sense.
+        :param pair: pair to get the data for
+        :param maximum: Maximum number of orderbook entries to query
+        :return: dict including bids/asks with a total of `maximum` entries.
+        """
+        if self._exchange is None:
+            raise OperationalException('Exchange is not available to DataProvider.')
+        return self._exchange.fetch_l2_order_book(pair, maximum)

freqtrade/optimize/backtesting.py

@@ -63,9 +63,7 @@ class Backtesting:
         self.all_results: Dict[str, Dict] = {}
 
         self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config)
-
         self.dataprovider = DataProvider(self.config, self.exchange)
-        IStrategy.dp = self.dataprovider
 
         if self.config.get('strategy_list', None):
             for strat in list(self.config['strategy_list']):
@@ -132,6 +130,7 @@ class Backtesting:
         Load strategy into backtesting
         """
         self.strategy: IStrategy = strategy
+        strategy.dp = self.dataprovider
         # Set stoploss_on_exchange to false for backtesting,
         # since a "perfect" stoploss-sell is assumed anyway
         # And the regular "stoploss" function would not apply to that case
@@ -353,7 +352,6 @@ class Backtesting:
         # Update dataprovider cache
         for pair, dataframe in processed.items():
             self.dataprovider._set_cached_df(pair, self.timeframe, dataframe)
-        self.strategy.dp = self.dataprovider
 
         # Use dict of lists with data for performance
         # (looping lists is a lot faster than pandas DataFrames)