Added default type none to price argument in OHLCV methods
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@@ -219,13 +219,15 @@ class Binance(Exchange):
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raise OperationalException(e) from e
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def _get_mark_price(self, pair: str, date: datetime) -> float:
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# TODO-lev: implement
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raise OperationalException(f'_get_mark_price has not been implemented on {self.name}')
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def _get_funding_rate(self, pair: str, premium_index: float) -> Optional[float]:
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def _get_funding_rate(self, pair: str, when: datetime):
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"""
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Get's the funding_rate for a pair at a specific date and time in the past
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"""
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raise OperationalException(f'_get_mark_price has not been implemented on {self.name}')
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# TODO-lev: implement
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raise OperationalException(f"get_funding_rate has not been implemented for {self.name}")
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def _get_funding_fee(
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self,
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@@ -253,7 +255,7 @@ class Binance(Exchange):
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timeframe: str,
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since_ms: int,
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is_new_pair: bool,
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price: Optional[str]
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price: Optional[str] = None
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) -> List:
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"""
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Overwrite to introduce "fast new pair" functionality by detecting the pair's listing date
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@@ -1296,7 +1296,7 @@ class Exchange:
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pair: str,
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timeframe: str,
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since_ms: int,
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price: Optional[str]
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price: Optional[str] = None
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) -> DataFrame:
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"""
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Minimal wrapper around get_historic_ohlcv - converting the result into a dataframe
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@@ -1306,14 +1306,13 @@ class Exchange:
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:param price: "mark" if retrieving the mark price cnadles, "index" for index price candles
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:return: OHLCV DataFrame
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"""
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ticks = self.get_historic_ohlcv(pair, timeframe, since_ms=since_ms)
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ticks = self.get_historic_ohlcv(pair, timeframe, since_ms=since_ms, price=price)
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return ohlcv_to_dataframe(
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ticks,
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timeframe,
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pair=pair,
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fill_missing=True,
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drop_incomplete=self._ohlcv_partial_candle,
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price=price
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drop_incomplete=self._ohlcv_partial_candle
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)
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async def _async_get_historic_ohlcv(
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@@ -1322,7 +1321,7 @@ class Exchange:
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timeframe: str,
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since_ms: int,
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is_new_pair: bool,
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price: Optional[str]
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price: Optional[str] = None
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) -> List:
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"""
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Download historic ohlcv
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@@ -1368,7 +1367,7 @@ class Exchange:
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pair_list: ListPairsWithTimeframes, *,
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since_ms: Optional[int] = None,
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cache: bool = True,
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price: Optional[str]
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price: Optional[str] = None
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) -> Dict[Tuple[str, str], DataFrame]:
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"""
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Refresh in-memory OHLCV asynchronously and set `_klines` with the result
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