stable/freqtrade/data/history.py

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"""
Handle historic data (ohlcv).
includes:
* load data for a pair (or a list of pairs) from disk
* download data from exchange and store to disk
"""
import gzip
import logging
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from pathlib import Path
from typing import Optional, List, Dict, Tuple, Any
import arrow
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from pandas import DataFrame
import ujson
from freqtrade import misc, constants, OperationalException
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from freqtrade.data.converter import parse_ticker_dataframe
from freqtrade.exchange import Exchange
from freqtrade.arguments import TimeRange
logger = logging.getLogger(__name__)
def json_load(data):
"""
load data with ujson
Use this to have a consistent experience,
otherwise "precise_float" needs to be passed to all load operations
"""
return ujson.load(data, precise_float=True)
def trim_tickerlist(tickerlist: List[Dict], timerange: TimeRange) -> List[Dict]:
"""
Trim tickerlist based on given timerange
"""
if not tickerlist:
return tickerlist
start_index = 0
stop_index = len(tickerlist)
if timerange.starttype == 'line':
stop_index = timerange.startts
if timerange.starttype == 'index':
start_index = timerange.startts
elif timerange.starttype == 'date':
while (start_index < len(tickerlist) and
tickerlist[start_index][0] < timerange.startts * 1000):
start_index += 1
if timerange.stoptype == 'line':
start_index = len(tickerlist) + timerange.stopts
if timerange.stoptype == 'index':
stop_index = timerange.stopts
elif timerange.stoptype == 'date':
while (stop_index > 0 and
tickerlist[stop_index-1][0] > timerange.stopts * 1000):
stop_index -= 1
if start_index > stop_index:
raise ValueError(f'The timerange [{timerange.startts},{timerange.stopts}] is incorrect')
return tickerlist[start_index:stop_index]
def load_tickerdata_file(
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datadir: Optional[Path], pair: str,
ticker_interval: str,
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timerange: Optional[TimeRange] = None) -> Optional[list]:
"""
Load a pair from file, either .json.gz or .json
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:return tickerlist or None if unsuccesful
"""
path = make_testdata_path(datadir)
pair_s = pair.replace('/', '_')
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file = path.joinpath(f'{pair_s}-{ticker_interval}.json')
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gzipfile = file.with_suffix(file.suffix + '.gz')
# Try gzip file first, otherwise regular json file.
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if gzipfile.is_file():
logger.debug('Loading ticker data from file %s', gzipfile)
with gzip.open(gzipfile) as tickerdata:
pairdata = json_load(tickerdata)
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elif file.is_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_pair_history(pair: str,
ticker_interval: str,
datadir: Optional[Path],
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timerange: TimeRange = TimeRange(None, None, 0, 0),
refresh_pairs: bool = False,
exchange: Optional[Exchange] = None,
) -> DataFrame:
"""
Loads cached ticker history for the given pair.
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:return: DataFrame with ohlcv data
"""
pairdata = load_tickerdata_file(datadir, pair, ticker_interval, timerange=timerange)
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# If the user force the refresh of pairs
if refresh_pairs:
if not exchange:
raise OperationalException("Exchange needs to be initialized when "
"calling load_data with refresh_pairs=True")
logger.info('Download data for all pairs and store them in %s', datadir)
download_pair_history(datadir=datadir,
exchange=exchange,
pair=pair,
tick_interval=ticker_interval,
timerange=timerange)
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if pairdata:
if timerange.starttype == 'date' and pairdata[0][0] > timerange.startts * 1000:
logger.warning('Missing data at start for pair %s, data starts at %s',
pair, arrow.get(pairdata[0][0] // 1000).strftime('%Y-%m-%d %H:%M:%S'))
if timerange.stoptype == 'date' and pairdata[-1][0] < timerange.stopts * 1000:
logger.warning('Missing data at end for pair %s, data ends at %s',
pair,
arrow.get(pairdata[-1][0] // 1000).strftime('%Y-%m-%d %H:%M:%S'))
return parse_ticker_dataframe(pairdata)
else:
logger.warning('No data for pair: "%s", Interval: %s. '
'Use --refresh-pairs-cached to download the data',
pair, ticker_interval)
return None
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def load_data(datadir: Optional[Path],
ticker_interval: str,
pairs: List[str],
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refresh_pairs: bool = False,
exchange: Optional[Exchange] = None,
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timerange: TimeRange = TimeRange(None, None, 0, 0)) -> Dict[str, DataFrame]:
"""
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Loads ticker history data for a list of pairs the given parameters
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:return: dict(<pair>:<tickerlist>)
"""
result = {}
for pair in pairs:
hist = load_pair_history(pair=pair, ticker_interval=ticker_interval,
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datadir=datadir, timerange=timerange,
refresh_pairs=refresh_pairs,
exchange=exchange)
if hist is not None:
result[pair] = hist
return result
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def make_testdata_path(datadir: Optional[Path]) -> Path:
"""Return the path where testdata files are stored"""
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return datadir or (Path(__file__).parent.parent / "tests" / "testdata").resolve()
def load_cached_data_for_updating(filename: Path, tick_interval: str,
timerange: Optional[TimeRange]) -> 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.starttype == 'date':
since_ms = timerange.startts * 1000
elif timerange.stoptype == 'line':
num_minutes = timerange.stopts * constants.TICKER_INTERVAL_MINUTES[tick_interval]
since_ms = arrow.utcnow().shift(minutes=num_minutes).timestamp * 1000
# read the cached file
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if filename.is_file():
with open(filename, "rt") as file:
data = json_load(file)
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# remove the last item, could be incomplete candle
if data:
data.pop()
else:
data = []
if data:
if since_ms and since_ms < data[0][0]:
# Earlier data than existing data requested, redownload all
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_pair_history(datadir: Optional[Path],
exchange: Exchange,
pair: str,
tick_interval: str = '5m',
timerange: Optional[TimeRange] = None) -> bool:
"""
Download the latest ticker intervals from the exchange for the pair passed in parameters
The data is downloaded starting from the last correct ticker interval data that
exists 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 pair: pair to download
:param tick_interval: ticker interval
:param timerange: range of time to download
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:return: bool with success state
"""
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try:
path = make_testdata_path(datadir)
filepair = pair.replace("/", "_")
filename = path.joinpath(f'{filepair}-{tick_interval}.json')
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logger.info('Download the pair: "%s", Interval: %s', pair, tick_interval)
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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')
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
new_data = exchange.get_history(pair=pair, tick_interval=tick_interval,
since_ms=since_ms if since_ms
else
int(arrow.utcnow().shift(days=-30).float_timestamp) * 1000)
data.extend(new_data)
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logger.debug("New Start: %s", misc.format_ms_time(data[0][0]))
logger.debug("New End: %s", misc.format_ms_time(data[-1][0]))
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misc.file_dump_json(filename, data)
return True
except BaseException:
logger.info('Failed to download the pair: "%s", Interval: %s',
pair, tick_interval)
return False