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Add support for download-data "until"
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@ -139,8 +139,9 @@ def _load_cached_data_for_updating(
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timeframe: str,
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timerange: Optional[TimeRange],
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data_handler: IDataHandler,
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candle_type: CandleType
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) -> Tuple[DataFrame, Optional[int]]:
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candle_type: CandleType,
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prepend: bool = False,
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) -> Tuple[DataFrame, Optional[int], Optional[int]]:
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"""
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Load cached data to download more data.
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If timerange is passed in, checks whether data from an before the stored data will be
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@ -150,9 +151,12 @@ def _load_cached_data_for_updating(
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Note: Only used by download_pair_history().
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"""
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start = None
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end = None
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if timerange:
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if timerange.starttype == 'date':
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start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc)
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if timerange.stoptype == 'date':
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end = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc)
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# Intentionally don't pass timerange in - since we need to load the full dataset.
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data = data_handler.ohlcv_load(pair, timeframe=timeframe,
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@ -160,14 +164,18 @@ def _load_cached_data_for_updating(
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drop_incomplete=True, warn_no_data=False,
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candle_type=candle_type)
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if not data.empty:
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if start and start < data.iloc[0]['date']:
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if not prepend and start and start < data.iloc[0]['date']:
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# Earlier data than existing data requested, redownload all
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data = DataFrame(columns=DEFAULT_DATAFRAME_COLUMNS)
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else:
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start = data.iloc[-1]['date']
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if prepend:
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end = data.iloc[0]['date']
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else:
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start = data.iloc[-1]['date']
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start_ms = int(start.timestamp() * 1000) if start else None
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return data, start_ms
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end_ms = int(end.timestamp() * 1000) if end else None
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return data, start_ms, end_ms
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def _download_pair_history(pair: str, *,
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@ -208,9 +216,12 @@ def _download_pair_history(pair: str, *,
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f'candle type: {candle_type} and store in {datadir}.'
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)
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data, since_ms = _load_cached_data_for_updating(pair, timeframe, timerange,
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data_handler=data_handler,
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candle_type=candle_type)
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data, since_ms, until_ms = _load_cached_data_for_updating(
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pair, timeframe, timerange,
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data_handler=data_handler,
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candle_type=candle_type,
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prepend=False)
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# TODO: Prepend should come from a param
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logger.debug("Current Start: %s",
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f"{data.iloc[0]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
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@ -225,6 +236,7 @@ def _download_pair_history(pair: str, *,
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days=-new_pairs_days).int_timestamp * 1000,
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is_new_pair=data.empty,
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candle_type=candle_type,
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until_ms=until_ms if until_ms else None
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)
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# TODO: Maybe move parsing to exchange class (?)
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new_dataframe = ohlcv_to_dataframe(new_data, timeframe, pair,
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@ -95,6 +95,7 @@ class Binance(Exchange):
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async def _async_get_historic_ohlcv(self, pair: str, timeframe: str,
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since_ms: int, candle_type: CandleType,
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is_new_pair: bool = False, raise_: bool = False,
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until_ms: int = None
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) -> Tuple[str, str, str, 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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@ -115,7 +116,8 @@ class Binance(Exchange):
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since_ms=since_ms,
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is_new_pair=is_new_pair,
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raise_=raise_,
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candle_type=candle_type
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candle_type=candle_type,
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until_ms=until_ms,
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)
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def funding_fee_cutoff(self, open_date: datetime):
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@ -1645,7 +1645,8 @@ class Exchange:
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def get_historic_ohlcv(self, pair: str, timeframe: str,
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since_ms: int, candle_type: CandleType,
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is_new_pair: bool = False) -> List:
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is_new_pair: bool = False,
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until_ms: int = None) -> List:
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"""
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Get candle history using asyncio and returns the list of candles.
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Handles all async work for this.
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@ -1653,13 +1654,14 @@ class Exchange:
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:param pair: Pair to download
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:param timeframe: Timeframe to get data for
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:param since_ms: Timestamp in milliseconds to get history from
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:param until_ms: Timestamp in milliseconds to get history up to
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:param candle_type: '', mark, index, premiumIndex, or funding_rate
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:return: List with candle (OHLCV) data
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"""
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pair, _, _, data = self.loop.run_until_complete(
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self._async_get_historic_ohlcv(pair=pair, timeframe=timeframe,
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since_ms=since_ms, is_new_pair=is_new_pair,
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candle_type=candle_type))
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since_ms=since_ms, until_ms=until_ms,
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is_new_pair=is_new_pair, candle_type=candle_type))
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logger.info(f"Downloaded data for {pair} with length {len(data)}.")
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return data
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@ -1680,6 +1682,7 @@ class Exchange:
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async def _async_get_historic_ohlcv(self, pair: str, timeframe: str,
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since_ms: int, candle_type: CandleType,
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is_new_pair: bool = False, raise_: bool = False,
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until_ms: int = None
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) -> Tuple[str, str, str, List]:
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"""
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Download historic ohlcv
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@ -1695,7 +1698,7 @@ class Exchange:
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)
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input_coroutines = [self._async_get_candle_history(
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pair, timeframe, candle_type, since) for since in
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range(since_ms, arrow.utcnow().int_timestamp * 1000, one_call)]
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range(since_ms, until_ms or (arrow.utcnow().int_timestamp * 1000), one_call)]
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data: List = []
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# Chunk requests into batches of 100 to avoid overwelming ccxt Throttling
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@ -223,42 +223,65 @@ def test_load_cached_data_for_updating(mocker, testdatadir) -> None:
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# timeframe starts earlier than the cached data
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# should fully update data
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timerange = TimeRange('date', None, test_data[0][0] / 1000 - 1, 0)
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data, start_ts = _load_cached_data_for_updating(
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data, start_ts, end_ts = _load_cached_data_for_updating(
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'UNITTEST/BTC', '1m', timerange, data_handler, CandleType.SPOT)
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assert data.empty
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assert start_ts == test_data[0][0] - 1000
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assert end_ts is None
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# timeframe starts earlier than the cached data - prepending
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timerange = TimeRange('date', None, test_data[0][0] / 1000 - 1, 0)
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data, start_ts, end_ts = _load_cached_data_for_updating(
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'UNITTEST/BTC', '1m', timerange, data_handler, CandleType.SPOT, True)
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assert_frame_equal(data, test_data_df.iloc[:-1])
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assert start_ts == test_data[0][0] - 1000
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assert end_ts == test_data[0][0]
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# timeframe starts in the center of the cached data
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# should return the cached data w/o the last item
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timerange = TimeRange('date', None, test_data[0][0] / 1000 + 1, 0)
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data, start_ts = _load_cached_data_for_updating(
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data, start_ts, end_ts = _load_cached_data_for_updating(
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'UNITTEST/BTC', '1m', timerange, data_handler, CandleType.SPOT)
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assert_frame_equal(data, test_data_df.iloc[:-1])
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assert test_data[-2][0] <= start_ts < test_data[-1][0]
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assert end_ts is None
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# timeframe starts after the cached data
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# should return the cached data w/o the last item
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timerange = TimeRange('date', None, test_data[-1][0] / 1000 + 100, 0)
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data, start_ts = _load_cached_data_for_updating(
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data, start_ts, end_ts = _load_cached_data_for_updating(
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'UNITTEST/BTC', '1m', timerange, data_handler, CandleType.SPOT)
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assert_frame_equal(data, test_data_df.iloc[:-1])
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assert test_data[-2][0] <= start_ts < test_data[-1][0]
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assert end_ts is None
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# no datafile exist
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# should return timestamp start time
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timerange = TimeRange('date', None, now_ts - 10000, 0)
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data, start_ts = _load_cached_data_for_updating(
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data, start_ts, end_ts = _load_cached_data_for_updating(
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'NONEXIST/BTC', '1m', timerange, data_handler, CandleType.SPOT)
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assert data.empty
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assert start_ts == (now_ts - 10000) * 1000
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assert end_ts is None
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# no datafile exist
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# should return timestamp start and end time time
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timerange = TimeRange('date', 'date', now_ts - 1000000, now_ts - 100000)
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data, start_ts, end_ts = _load_cached_data_for_updating(
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'NONEXIST/BTC', '1m', timerange, data_handler, CandleType.SPOT)
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assert data.empty
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assert start_ts == (now_ts - 1000000) * 1000
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assert end_ts == (now_ts - 100000) * 1000
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# no datafile exist, no timeframe is set
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# should return an empty array and None
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data, start_ts = _load_cached_data_for_updating(
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data, start_ts, end_ts = _load_cached_data_for_updating(
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'NONEXIST/BTC', '1m', None, data_handler, CandleType.SPOT)
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assert data.empty
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assert start_ts is None
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assert end_ts is None
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@pytest.mark.parametrize('candle_type,subdir,file_tail', [
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