# pragma pylint: disable=missing-docstring
import gzip
import json
import logging
import os
from typing import Optional, List, Dict, Tuple, Any
import arrow
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.warning(
'No data for pair: "%s", Interval: %s. '
'Use --refresh-pairs-cached to download the data',
pair,
ticker_interval
)
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[Any],
Optional[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)