60ed4b9d1e
This argument enables usage of different backtesting directories. Useful if one wants compare backtesting performance over time.
134 lines
4.5 KiB
Python
134 lines
4.5 KiB
Python
# pragma pylint: disable=missing-docstring
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import logging
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import json
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import os
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from typing import Optional, List, Dict
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from pandas import DataFrame
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from freqtrade.exchange import get_ticker_history
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from freqtrade.optimize.hyperopt_conf import hyperopt_optimize_conf
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from freqtrade.analyze import populate_indicators, parse_ticker_dataframe
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logger = logging.getLogger(__name__)
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def load_tickerdata_file(datadir, pair, ticker_interval):
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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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file = '{abspath}/{pair}-{ticker_interval}.json'.format(
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abspath=path,
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pair=pair,
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ticker_interval=ticker_interval,
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)
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# The file does not exist we download it
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if not os.path.isfile(file):
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return None
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# Read the file, load the json
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with open(file) as tickerdata:
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pairdata = json.load(tickerdata)
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return pairdata
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def load_data(datadir: str, ticker_interval: int = 5, pairs: Optional[List[str]] = None,
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refresh_pairs: Optional[bool] = False) -> Dict[str, List]:
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"""
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Loads ticker history data for the given parameters
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:param ticker_interval: ticker interval in minutes
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:param pairs: list of pairs
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:return: dict
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"""
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result = {}
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_pairs = pairs or hyperopt_optimize_conf()['exchange']['pair_whitelist']
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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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download_pairs(datadir, _pairs)
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for pair in _pairs:
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pairdata = load_tickerdata_file(datadir, pair, ticker_interval)
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if not pairdata:
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# download the tickerdata from exchange
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download_backtesting_testdata(datadir, pair=pair, interval=ticker_interval)
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# and retry reading the pair
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pairdata = load_tickerdata_file(datadir, pair, ticker_interval)
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result[pair] = pairdata
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return result
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def preprocess(tickerdata: Dict[str, List]) -> Dict[str, DataFrame]:
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"""Creates a dataframe and populates indicators for given ticker data"""
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return {pair: populate_indicators(parse_ticker_dataframe(pair_data))
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for pair, pair_data in tickerdata.items()}
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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(os.path.join(os.path.dirname(__file__),
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'..', 'tests', 'testdata'))
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def download_pairs(datadir, pairs: List[str]) -> bool:
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"""For each pairs passed in parameters, download 1 and 5 ticker intervals"""
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for pair in pairs:
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try:
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for interval in [1, 5]:
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download_backtesting_testdata(datadir, pair=pair, interval=interval)
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except BaseException:
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logger.info('Failed to download the pair: "{pair}", Interval: {interval} min'.format(
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pair=pair,
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interval=interval,
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))
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return False
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return True
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def download_backtesting_testdata(datadir: str, pair: str, interval: int = 5) -> bool:
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"""
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Download the latest 1 and 5 ticker intervals from Bittrex for the pairs passed in parameters
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Based on @Rybolov work: https://github.com/rybolov/freqtrade-data
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:param pairs: list of pairs to download
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:return: bool
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"""
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path = make_testdata_path(datadir)
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logger.info('Download the pair: "{pair}", Interval: {interval} min'.format(
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pair=pair,
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interval=interval,
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))
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filepair = pair.replace("-", "_")
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filename = os.path.join(path, '{pair}-{interval}.json'.format(
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pair=filepair,
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interval=interval,
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))
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filename = filename.replace('USDT_BTC', 'BTC_FAKEBULL')
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if os.path.isfile(filename):
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with open(filename, "rt") as fp:
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data = json.load(fp)
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logger.debug("Current Start: {}".format(data[1]['T']))
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logger.debug("Current End: {}".format(data[-1:][0]['T']))
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else:
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data = []
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logger.debug("Current Start: None")
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logger.debug("Current End: None")
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new_data = get_ticker_history(pair=pair, tick_interval=int(interval))
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for row in new_data:
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if row not in data:
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data.append(row)
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logger.debug("New Start: {}".format(data[1]['T']))
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logger.debug("New End: {}".format(data[-1:][0]['T']))
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data = sorted(data, key=lambda data: data['T'])
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with open(filename, "wt") as fp:
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json.dump(data, fp)
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return True
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