Remove unnecessary default parameters
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ac2fb08aea
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@ -134,7 +134,7 @@ class DataProvider:
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combination.
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Returns empty dataframe and Epoch 0 (1970-01-01) if no dataframe was cached.
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"""
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pair_key = (pair, timeframe, CandleType.SPOT)
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pair_key = (pair, timeframe, CandleType.SPOT_)
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if pair_key in self.__cached_pairs:
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if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
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df, date = self.__cached_pairs[pair_key]
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@ -44,12 +44,7 @@ class HDF5DataHandler(IDataHandler):
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) for match in _tmp if match and len(match.groups()) > 1]
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@classmethod
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def ohlcv_get_pairs(
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cls,
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datadir: Path,
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timeframe: str,
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candle_type: CandleType
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) -> List[str]:
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def ohlcv_get_pairs(cls, datadir: Path, timeframe: str, candle_type: CandleType) -> List[str]:
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"""
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Returns a list of all pairs with ohlcv data available in this datadir
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for the specified timeframe
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@ -69,12 +64,7 @@ class HDF5DataHandler(IDataHandler):
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return [cls.rebuild_pair_from_filename(match[0]) for match in _tmp if match]
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def ohlcv_store(
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self,
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pair: str,
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timeframe: str,
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data: pd.DataFrame,
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candle_type: CandleType = CandleType.SPOT_
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) -> None:
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self, pair: str, timeframe: str, data: pd.DataFrame, candle_type: CandleType) -> None:
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"""
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Store data in hdf5 file.
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:param pair: Pair - used to generate filename
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@ -94,8 +84,7 @@ class HDF5DataHandler(IDataHandler):
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)
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def _ohlcv_load(self, pair: str, timeframe: str,
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timerange: Optional[TimeRange] = None,
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candle_type: CandleType = CandleType.SPOT_
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timerange: Optional[TimeRange], candle_type: CandleType
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) -> pd.DataFrame:
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"""
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Internal method used to load data for one pair from disk.
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@ -48,12 +48,7 @@ class IDataHandler(ABC):
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"""
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@abstractclassmethod
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def ohlcv_get_pairs(
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cls,
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datadir: Path,
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timeframe: str,
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candle_type: CandleType
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) -> List[str]:
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def ohlcv_get_pairs(cls, datadir: Path, timeframe: str, candle_type: CandleType) -> List[str]:
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"""
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Returns a list of all pairs with ohlcv data available in this datadir
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for the specified timeframe
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@ -65,12 +60,7 @@ class IDataHandler(ABC):
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@abstractmethod
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def ohlcv_store(
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self,
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pair: str,
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timeframe: str,
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data: DataFrame,
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candle_type: CandleType = CandleType.SPOT_
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) -> None:
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self, pair: str, timeframe: str, data: DataFrame, candle_type: CandleType) -> None:
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"""
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Store ohlcv data.
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:param pair: Pair - used to generate filename
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@ -81,8 +71,8 @@ class IDataHandler(ABC):
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"""
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@abstractmethod
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def _ohlcv_load(self, pair: str, timeframe: str, timerange: Optional[TimeRange] = None,
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candle_type: CandleType = CandleType.SPOT_
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def _ohlcv_load(self, pair: str, timeframe: str, timerange: Optional[TimeRange],
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candle_type: CandleType
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) -> DataFrame:
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"""
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Internal method used to load data for one pair from disk.
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@ -45,12 +45,7 @@ class JsonDataHandler(IDataHandler):
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) for match in _tmp if match and len(match.groups()) > 1]
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@classmethod
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def ohlcv_get_pairs(
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cls,
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datadir: Path,
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timeframe: str,
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candle_type: CandleType
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) -> List[str]:
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def ohlcv_get_pairs(cls, datadir: Path, timeframe: str, candle_type: CandleType) -> List[str]:
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"""
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Returns a list of all pairs with ohlcv data available in this datadir
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for the specified timeframe
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@ -70,12 +65,7 @@ class JsonDataHandler(IDataHandler):
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return [cls.rebuild_pair_from_filename(match[0]) for match in _tmp if match]
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def ohlcv_store(
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self,
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pair: str,
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timeframe: str,
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data: DataFrame,
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candle_type: CandleType = CandleType.SPOT_
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) -> None:
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self, pair: str, timeframe: str, data: DataFrame, candle_type: CandleType) -> None:
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"""
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Store data in json format "values".
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format looks as follows:
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@ -98,8 +88,7 @@ class JsonDataHandler(IDataHandler):
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compression='gzip' if self._use_zip else None)
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def _ohlcv_load(self, pair: str, timeframe: str,
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timerange: Optional[TimeRange] = None,
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candle_type: CandleType = CandleType.SPOT_
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timerange: Optional[TimeRange], candle_type: CandleType
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) -> DataFrame:
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"""
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Internal method used to load data for one pair from disk.
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@ -922,7 +922,7 @@ def test_hdf5datahandler_ohlcv_load_and_resave(
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tmpdir2 = tmpdir1 / 'futures'
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tmpdir2.mkdir()
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dh = HDF5DataHandler(testdatadir)
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ohlcv = dh._ohlcv_load(pair, timeframe, candle_type=candle_type)
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ohlcv = dh._ohlcv_load(pair, timeframe, None, candle_type=candle_type)
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assert isinstance(ohlcv, DataFrame)
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assert len(ohlcv) > 0
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