Remove checks for dataprovider existance - it's available in all modes.
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@ -617,7 +617,6 @@ Please always check the mode of operation to select the correct method to get da
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### *available_pairs*
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``` python
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if self.dp:
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for pair, timeframe in self.dp.available_pairs:
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print(f"available {pair}, {timeframe}")
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```
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@ -653,7 +652,6 @@ This is where calling `self.dp.current_whitelist()` comes in handy.
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``` python
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# fetch live / historical candle (OHLCV) data for the first informative pair
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if self.dp:
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inf_pair, inf_timeframe = self.informative_pairs()[0]
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informative = self.dp.get_pair_dataframe(pair=inf_pair,
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timeframe=inf_timeframe)
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@ -671,7 +669,6 @@ It can also be used in specific callbacks to get the signal that caused the acti
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``` python
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# fetch current dataframe
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if self.dp:
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if self.dp.runmode.value in ('live', 'dry_run'):
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dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=metadata['pair'],
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timeframe=self.timeframe)
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@ -684,7 +681,6 @@ if self.dp:
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### *orderbook(pair, maximum)*
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``` python
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if self.dp:
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if self.dp.runmode.value in ('live', 'dry_run'):
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ob = self.dp.orderbook(metadata['pair'], 1)
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dataframe['best_bid'] = ob['bids'][0][0]
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@ -717,7 +713,6 @@ Therefore, using `ob['bids'][0][0]` as demonstrated above will result in using t
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### *ticker(pair)*
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``` python
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if self.dp:
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if self.dp.runmode.value in ('live', 'dry_run'):
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ticker = self.dp.ticker(metadata['pair'])
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dataframe['last_price'] = ticker['last']
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@ -617,9 +617,6 @@ class IStrategy(ABC, HyperStrategyMixin):
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)
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informative_pairs.append(pair_tf)
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else:
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if not self.dp:
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raise OperationalException('@informative decorator with unspecified asset '
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'requires DataProvider instance.')
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for pair in self.dp.current_whitelist():
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informative_pairs.append((pair, inf_data.timeframe, candle_type))
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return list(set(informative_pairs))
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@ -713,7 +710,6 @@ class IStrategy(ABC, HyperStrategyMixin):
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# Defs that only make change on new candle data.
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dataframe = self.analyze_ticker(dataframe, metadata)
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self._last_candle_seen_per_pair[pair] = dataframe.iloc[-1]['date']
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if self.dp:
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self.dp._set_cached_df(
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pair, self.timeframe, dataframe,
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candle_type=self.config.get('candle_type_def', CandleType.SPOT))
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@ -737,8 +733,6 @@ class IStrategy(ABC, HyperStrategyMixin):
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The analyzed dataframe is then accessible via `dp.get_analyzed_dataframe()`.
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:param pair: Pair to analyze.
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"""
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if not self.dp:
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raise OperationalException("DataProvider not found.")
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dataframe = self.dp.ohlcv(
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pair, self.timeframe, candle_type=self.config.get('candle_type_def', CandleType.SPOT)
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)
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