295 lines
11 KiB
Python
295 lines
11 KiB
Python
# pragma pylint: disable=missing-docstring
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import gzip
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try:
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import ujson as json
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_UJSON = True
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except ImportError:
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# see mypy/issues/1153
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import json # type: ignore
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_UJSON = False
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import logging
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import os
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from datetime import datetime
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from typing import Optional, List, Dict, Tuple, Any
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import operator
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import arrow
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from pandas import DataFrame
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from freqtrade import misc, constants, OperationalException
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from freqtrade.exchange import Exchange
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from freqtrade.arguments import TimeRange
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from freqtrade.optimize.default_hyperopt import DefaultHyperOpts # noqa: F401
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logger = logging.getLogger(__name__)
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def json_load(data):
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"""Try to load data with ujson"""
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if _UJSON:
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return json.load(data, precise_float=True)
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else:
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return json.load(data)
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def trim_tickerlist(tickerlist: List[Dict], timerange: TimeRange) -> List[Dict]:
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if not tickerlist:
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return tickerlist
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start_index = 0
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stop_index = len(tickerlist)
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if timerange.starttype == 'line':
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stop_index = timerange.startts
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if timerange.starttype == 'index':
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start_index = timerange.startts
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elif timerange.starttype == 'date':
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while (start_index < len(tickerlist) and
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tickerlist[start_index][0] < timerange.startts * 1000):
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start_index += 1
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if timerange.stoptype == 'line':
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start_index = len(tickerlist) + timerange.stopts
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if timerange.stoptype == 'index':
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stop_index = timerange.stopts
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elif timerange.stoptype == 'date':
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while (stop_index > 0 and
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tickerlist[stop_index-1][0] > timerange.stopts * 1000):
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stop_index -= 1
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if start_index > stop_index:
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raise ValueError(f'The timerange [{timerange.startts},{timerange.stopts}] is incorrect')
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return tickerlist[start_index:stop_index]
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def get_timeframe(data: Dict[str, DataFrame]) -> Tuple[arrow.Arrow, arrow.Arrow]:
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"""
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Get the maximum timeframe for the given backtest data
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:param data: dictionary with preprocessed backtesting data
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:return: tuple containing min_date, max_date
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"""
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timeframe = [
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(arrow.get(frame['date'].min()), arrow.get(frame['date'].max()))
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for frame in data.values()
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]
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return min(timeframe, key=operator.itemgetter(0))[0], \
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max(timeframe, key=operator.itemgetter(1))[1]
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def validate_backtest_data(data: Dict[str, DataFrame], min_date: datetime,
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max_date: datetime, ticker_interval_mins: int) -> bool:
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"""
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Validates preprocessed backtesting data for missing values and shows warnings about it that.
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:param data: dictionary with preprocessed backtesting data
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:param min_date: start-date of the data
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:param max_date: end-date of the data
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:param ticker_interval_mins: ticker interval in minutes
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"""
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# total difference in minutes / interval-minutes
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expected_frames = int((max_date - min_date).total_seconds() // 60 // ticker_interval_mins)
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found_missing = False
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for pair, df in data.items():
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dflen = len(df)
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if dflen < expected_frames:
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found_missing = True
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logger.warning("%s has missing frames: expected %s, got %s, that's %s missing values",
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pair, expected_frames, dflen, expected_frames - dflen)
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return found_missing
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def load_tickerdata_file(
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datadir: str, pair: str,
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ticker_interval: str,
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timerange: Optional[TimeRange] = None) -> Optional[List[Dict]]:
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"""
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Load a pair from file,
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:return dict OR empty if unsuccesful
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"""
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path = make_testdata_path(datadir)
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pair_s = pair.replace('/', '_')
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file = os.path.join(path, f'{pair_s}-{ticker_interval}.json')
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gzipfile = file + '.gz'
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# If the file does not exist we download it when None is returned.
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# If file exists, read the file, load the json
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if os.path.isfile(gzipfile):
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logger.debug('Loading ticker data from file %s', gzipfile)
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with gzip.open(gzipfile) as tickerdata:
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pairdata = json.load(tickerdata)
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elif os.path.isfile(file):
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logger.debug('Loading ticker data from file %s', file)
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with open(file) as tickerdata:
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pairdata = json.load(tickerdata)
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else:
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return None
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if timerange:
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pairdata = trim_tickerlist(pairdata, timerange)
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return pairdata
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def load_data(datadir: str,
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ticker_interval: str,
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pairs: List[str],
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refresh_pairs: Optional[bool] = False,
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exchange: Optional[Exchange] = None,
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timerange: TimeRange = TimeRange(None, None, 0, 0)) -> Dict[str, List]:
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"""
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Loads ticker history data for the given parameters
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:return: dict
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"""
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result = {}
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# If the user force the refresh of pairs
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if refresh_pairs:
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logger.info('Download data for all pairs and store them in %s', datadir)
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if not exchange:
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raise OperationalException("Exchange needs to be initialized when "
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"calling load_data with refresh_pairs=True")
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download_pairs(datadir, exchange, pairs, ticker_interval, timerange=timerange)
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for pair in pairs:
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pairdata = load_tickerdata_file(datadir, pair, ticker_interval, timerange=timerange)
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if pairdata:
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if timerange.starttype == 'date' and pairdata[0][0] > timerange.startts * 1000:
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logger.warning('Missing data at start for pair %s, data starts at %s',
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pair,
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arrow.get(pairdata[0][0] // 1000).strftime('%Y-%m-%d %H:%M:%S'))
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if timerange.stoptype == 'date' and pairdata[-1][0] < timerange.stopts * 1000:
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logger.warning('Missing data at end for pair %s, data ends at %s',
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pair,
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arrow.get(pairdata[-1][0] // 1000).strftime('%Y-%m-%d %H:%M:%S'))
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result[pair] = pairdata
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else:
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logger.warning(
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'No data for pair: "%s", Interval: %s. '
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'Use --refresh-pairs-cached to download the data',
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pair,
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ticker_interval
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)
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return result
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def make_testdata_path(datadir: str) -> str:
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"""Return the path where testdata files are stored"""
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return datadir or os.path.abspath(
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os.path.join(
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os.path.dirname(__file__), '..', 'tests', 'testdata'
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)
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)
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def download_pairs(datadir, exchange: Exchange, pairs: List[str],
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ticker_interval: str,
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timerange: TimeRange = TimeRange(None, None, 0, 0)) -> bool:
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"""For each pairs passed in parameters, download the ticker intervals"""
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for pair in pairs:
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try:
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download_backtesting_testdata(datadir,
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exchange=exchange,
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pair=pair,
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tick_interval=ticker_interval,
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timerange=timerange)
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except BaseException:
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logger.info(
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'Failed to download the pair: "%s", Interval: %s',
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pair,
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ticker_interval
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)
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return False
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return True
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def load_cached_data_for_updating(filename: str,
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tick_interval: str,
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timerange: Optional[TimeRange]) -> Tuple[
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List[Any],
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Optional[int]]:
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"""
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Load cached data and choose what part of the data should be updated
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"""
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since_ms = None
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# user sets timerange, so find the start time
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if timerange:
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if timerange.starttype == 'date':
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since_ms = timerange.startts * 1000
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elif timerange.stoptype == 'line':
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num_minutes = timerange.stopts * constants.TICKER_INTERVAL_MINUTES[tick_interval]
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since_ms = arrow.utcnow().shift(minutes=num_minutes).timestamp * 1000
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# read the cached file
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if os.path.isfile(filename):
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with open(filename, "rt") as file:
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data = json_load(file)
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# remove the last item, because we are not sure if it is correct
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# it could be fetched when the candle was incompleted
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if data:
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data.pop()
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else:
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data = []
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if data:
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if since_ms and since_ms < data[0][0]:
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# the data is requested for earlier period than the cache has
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# so fully redownload all the data
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data = []
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else:
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# a part of the data was already downloaded, so
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# download unexist data only
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since_ms = data[-1][0] + 1
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return (data, since_ms)
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def download_backtesting_testdata(datadir: str,
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exchange: Exchange,
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pair: str,
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tick_interval: str = '5m',
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timerange: Optional[TimeRange] = None) -> None:
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"""
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Download the latest ticker intervals from the exchange for the pair passed in parameters
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The data is downloaded starting from the last correct ticker interval data that
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exists in a cache. If timerange starts earlier than the data in the cache,
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the full data will be redownloaded
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Based on @Rybolov work: https://github.com/rybolov/freqtrade-data
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:param pair: pair to download
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:param tick_interval: ticker interval
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:param timerange: range of time to download
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:return: None
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"""
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path = make_testdata_path(datadir)
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filepair = pair.replace("/", "_")
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filename = os.path.join(path, f'{filepair}-{tick_interval}.json')
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logger.info(
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'Download the pair: "%s", Interval: %s',
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pair,
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tick_interval
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)
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data, since_ms = load_cached_data_for_updating(filename, tick_interval, timerange)
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logger.debug("Current Start: %s", misc.format_ms_time(data[1][0]) if data else 'None')
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logger.debug("Current End: %s", misc.format_ms_time(data[-1][0]) if data else 'None')
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# Default since_ms to 30 days if nothing is given
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new_data = exchange.get_history(pair=pair, tick_interval=tick_interval,
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since_ms=since_ms if since_ms
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else
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int(arrow.utcnow().shift(days=-30).float_timestamp) * 1000)
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data.extend(new_data)
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logger.debug("New Start: %s", misc.format_ms_time(data[0][0]))
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logger.debug("New End: %s", misc.format_ms_time(data[-1][0]))
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misc.file_dump_json(filename, data)
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