# pragma pylint: disable=missing-docstring import gzip import json import logging import os import arrow from typing import Optional, List, Dict, Tuple from freqtrade import misc, constants from freqtrade.exchange import get_ticker_history from user_data.hyperopt_conf import hyperopt_optimize_conf logger = logging.getLogger(__name__) def trim_tickerlist(tickerlist: List[Dict], timerange: Tuple[Tuple, int, int]) -> List[Dict]: if not tickerlist: return tickerlist stype, start, stop = timerange start_index = 0 stop_index = len(tickerlist) if stype[0] == 'line': stop_index = start if stype[0] == 'index': start_index = start elif stype[0] == 'date': while start_index < len(tickerlist) and tickerlist[start_index][0] < start * 1000: start_index += 1 if stype[1] == 'line': start_index = len(tickerlist) + stop if stype[1] == 'index': stop_index = stop elif stype[1] == 'date': while stop_index > 0 and tickerlist[stop_index-1][0] > stop * 1000: stop_index -= 1 if start_index > stop_index: raise ValueError(f'The timerange [{start},{stop}] is incorrect') return tickerlist[start_index:stop_index] def load_tickerdata_file( datadir: str, pair: str, ticker_interval: str, timerange: Optional[Tuple[Tuple, int, int]] = None) -> Optional[List[Dict]]: """ Load a pair from file, :return dict OR empty if unsuccesful """ path = make_testdata_path(datadir) pair_file_string = pair.replace('/', '_') file = os.path.join(path, '{pair}-{ticker_interval}.json'.format( pair=pair_file_string, ticker_interval=ticker_interval, )) gzipfile = file + '.gz' # If the file does not exist we download it when None is returned. # If file exists, read the file, load the json if os.path.isfile(gzipfile): logger.debug('Loading ticker data from file %s', gzipfile) with gzip.open(gzipfile) as tickerdata: pairdata = json.load(tickerdata) elif os.path.isfile(file): logger.debug('Loading ticker data from file %s', file) with open(file) as tickerdata: pairdata = json.load(tickerdata) else: return None if timerange: pairdata = trim_tickerlist(pairdata, timerange) return pairdata def load_data(datadir: str, ticker_interval: str, pairs: Optional[List[str]] = None, refresh_pairs: Optional[bool] = False, timerange: Optional[Tuple[Tuple, int, int]] = None) -> Dict[str, List]: """ Loads ticker history data for the given parameters :return: dict """ result = {} _pairs = pairs or hyperopt_optimize_conf()['exchange']['pair_whitelist'] # If the user force the refresh of pairs if refresh_pairs: logger.info('Download data for all pairs and store them in %s', datadir) download_pairs(datadir, _pairs, ticker_interval, timerange=timerange) for pair in _pairs: pairdata = load_tickerdata_file(datadir, pair, ticker_interval, timerange=timerange) if pairdata: result[pair] = pairdata else: logger.warn('No data for pair %s, use --update-pairs-cached to download the data', pair) return result def make_testdata_path(datadir: str) -> str: """Return the path where testdata files are stored""" return datadir or os.path.abspath( os.path.join( os.path.dirname(__file__), '..', 'tests', 'testdata' ) ) def download_pairs(datadir, pairs: List[str], ticker_interval: str, timerange: Optional[Tuple[Tuple, int, int]] = None) -> bool: """For each pairs passed in parameters, download the ticker intervals""" for pair in pairs: try: download_backtesting_testdata(datadir, pair=pair, tick_interval=ticker_interval, timerange=timerange) except BaseException: logger.info( 'Failed to download the pair: "%s", Interval: %s', pair, ticker_interval ) return False return True def load_cached_data_for_updating(filename: str, tick_interval: str, timerange: Optional[Tuple[Tuple, int, int]]) -> Tuple[list, int]: """ Load cached data and choose what part of the data should be updated """ since_ms = None # user sets timerange, so find the start time if timerange: if timerange[0][0] == 'date': since_ms = timerange[1] * 1000 elif timerange[0][1] == 'line': num_minutes = timerange[2] * constants.TICKER_INTERVAL_MINUTES[tick_interval] since_ms = arrow.utcnow().shift(minutes=num_minutes).timestamp * 1000 # read the cached file if os.path.isfile(filename): with open(filename, "rt") as file: data = json.load(file) # remove the last item, because we are not sure if it is correct # it could be fetched when the candle was incompleted if data: data.pop() else: data = [] if data: if since_ms and since_ms < data[0][0]: # the data is requested for earlier period than the cache has # so fully redownload all the data data = [] else: # a part of the data was already downloaded, so # download unexist data only since_ms = data[-1][0] + 1 return (data, since_ms) def download_backtesting_testdata(datadir: str, pair: str, tick_interval: str = '5m', timerange: Optional[Tuple[Tuple, int, int]] = None) -> None: """ Download the latest ticker intervals from the exchange for the pairs passed in parameters The data is downloaded starting from the last correct ticker interval data that esists in a cache. If timerange starts earlier than the data in the cache, the full data will be redownloaded Based on @Rybolov work: https://github.com/rybolov/freqtrade-data :param pairs: list of pairs to download :param tick_interval: ticker interval :param timerange: range of time to download :return: None """ path = make_testdata_path(datadir) filepair = pair.replace("/", "_") filename = os.path.join(path, f'{filepair}-{tick_interval}.json') logger.info( 'Download the pair: "%s", Interval: %s', pair, tick_interval ) data, since_ms = load_cached_data_for_updating(filename, tick_interval, timerange) logger.debug("Current Start: %s", misc.format_ms_time(data[1][0]) if data else 'None') logger.debug("Current End: %s", misc.format_ms_time(data[-1][0]) if data else 'None') new_data = get_ticker_history(pair=pair, tick_interval=tick_interval, since_ms=since_ms) data.extend(new_data) logger.debug("New Start: %s", misc.format_ms_time(data[0][0])) logger.debug("New End: %s", misc.format_ms_time(data[-1][0])) misc.file_dump_json(filename, data)