201 lines
6.4 KiB
Python
Executable File
201 lines
6.4 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Script to display when the bot will buy a specific pair
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Mandatory Cli parameters:
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-p / --pair: pair to examine
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Optional Cli parameters
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-d / --datadir: path to pair backtest data
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--timerange: specify what timerange of data to use.
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-l / --live: Live, to download the latest ticker for the pair
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"""
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import logging
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import sys
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from argparse import Namespace
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from os import path
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import glob
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import json
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import re
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from typing import List, Dict
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import gzip
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from freqtrade.arguments import Arguments
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from freqtrade import misc, constants
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from pandas import DataFrame
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import dateutil.parser
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logger = logging.getLogger('freqtrade')
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def load_old_file(filename) -> (List[Dict], bool):
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if not path.isfile(filename):
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logger.warning("filename %s does not exist", filename)
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return (None, False)
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logger.debug('Loading ticker data from file %s', filename)
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pairdata = None
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if filename.endswith('.gz'):
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logger.debug('Loading ticker data from file %s', filename)
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is_zip = True
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with gzip.open(filename) as tickerdata:
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pairdata = json.load(tickerdata)
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else:
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is_zip = False
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with open(filename) as tickerdata:
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pairdata = json.load(tickerdata)
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return (pairdata, is_zip)
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def parse_old_backtest_data(ticker) -> DataFrame:
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"""
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Reads old backtest data
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Format: "O": 8.794e-05,
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"H": 8.948e-05,
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"L": 8.794e-05,
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"C": 8.88e-05,
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"V": 991.09056638,
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"T": "2017-11-26T08:50:00",
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"BV": 0.0877869
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"""
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columns = {'C': 'close', 'V': 'volume', 'O': 'open',
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'H': 'high', 'L': 'low', 'T': 'date'}
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frame = DataFrame(ticker) \
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.rename(columns=columns)
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if 'BV' in frame:
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frame.drop('BV', 1, inplace=True)
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if 'date' not in frame:
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logger.warning("Date not in frame - probably not a Ticker file")
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return None
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frame.sort_values('date', inplace=True)
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return frame
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def convert_dataframe(frame: DataFrame):
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"""Convert dataframe to new format"""
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# reorder columns:
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cols = ['date', 'open', 'high', 'low', 'close', 'volume']
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frame = frame[cols]
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# Make sure parsing/printing data is assumed to be UTC
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frame['date'] = frame['date'].apply(
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lambda d: int(dateutil.parser.parse(d+'+00:00').timestamp()) * 1000)
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frame['date'] = frame['date'].astype('int64')
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# Convert columns one by one to preserve type.
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by_column = [frame[x].values.tolist() for x in frame.columns]
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return list(list(x) for x in zip(*by_column))
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def convert_file(filename: str, filename_new: str) -> None:
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"""Converts a file from old format to ccxt format"""
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(pairdata, is_zip) = load_old_file(filename)
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if pairdata and type(pairdata) is list:
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if type(pairdata[0]) is list:
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logger.error("pairdata for %s already in new format", filename)
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return
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frame = parse_old_backtest_data(pairdata)
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# Convert frame to new format
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if frame is not None:
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frame1 = convert_dataframe(frame)
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misc.file_dump_json(filename_new, frame1, is_zip)
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def convert_main(args: Namespace) -> None:
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"""
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converts a folder given in --datadir from old to new format to support ccxt
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"""
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workdir = path.join(args.datadir, "")
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logger.info("Workdir: %s", workdir)
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for filename in glob.glob(workdir + "*.json"):
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# swap currency names
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ret = re.search(r'[A-Z_]{7,}', path.basename(filename))
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if args.norename:
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filename_new = filename
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else:
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if not ret:
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logger.warning("file %s could not be converted, could not extract currencies",
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filename)
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continue
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pair = ret.group(0)
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currencies = pair.split("_")
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if len(currencies) != 2:
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logger.warning("file %s could not be converted, could not extract currencies",
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filename)
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continue
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ret_integer = re.search(r'\d+(?=\.json)', path.basename(filename))
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ret_string = re.search(r'(\d+[mhdw])(?=\.json)', path.basename(filename))
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if ret_integer:
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minutes = int(ret_integer.group(0))
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# default to adding 'm' to end of minutes for new interval name
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interval = str(minutes) + 'm'
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# but check if there is a mapping between int and string also
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for str_interval, minutes_interval in constants.TICKER_INTERVAL_MINUTES.items():
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if minutes_interval == minutes:
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interval = str_interval
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break
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# change order on pairs if old ticker interval found
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filename_new = path.join(path.dirname(filename),
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f"{currencies[1]}_{currencies[0]}-{interval}.json")
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elif ret_string:
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interval = ret_string.group(0)
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filename_new = path.join(path.dirname(filename),
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f"{currencies[0]}_{currencies[1]}-{interval}.json")
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else:
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logger.warning("file %s could not be converted, interval not found", filename)
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continue
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logger.debug("Converting and renaming %s to %s", filename, filename_new)
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convert_file(filename, filename_new)
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def convert_parse_args(args: List[str]) -> Namespace:
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"""
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Parse args passed to the script
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:param args: Cli arguments
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:return: args: Array with all arguments
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"""
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arguments = Arguments(args, 'Convert datafiles')
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arguments.parser.add_argument(
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'-d', '--datadir',
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help='path to backtest data (default: %(default)s',
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dest='datadir',
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default=path.join('freqtrade', 'tests', 'testdata'),
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type=str,
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metavar='PATH',
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)
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arguments.parser.add_argument(
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'-n', '--norename',
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help='don''t rename files from BTC_<PAIR> to <PAIR>_BTC - '
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'Note that not renaming will overwrite source files',
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dest='norename',
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default=False,
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action='store_true'
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)
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return arguments.parse_args()
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def main(sysargv: List[str]) -> None:
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"""
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This function will initiate the bot and start the trading loop.
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:return: None
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"""
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logger.info('Starting Dataframe conversation')
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convert_main(convert_parse_args(sysargv))
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if __name__ == '__main__':
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main(sys.argv[1:])
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