452 lines
17 KiB
Python
452 lines
17 KiB
Python
"""
|
|
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 logging
|
|
import operator
|
|
from datetime import datetime
|
|
from pathlib import Path
|
|
from typing import Any, Dict, List, Optional, Tuple
|
|
|
|
import arrow
|
|
from pandas import DataFrame
|
|
|
|
from freqtrade import OperationalException, misc
|
|
from freqtrade.configuration import TimeRange
|
|
from freqtrade.data.converter import parse_ticker_dataframe
|
|
from freqtrade.exchange import Exchange, timeframe_to_minutes
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
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 = max(len(tickerlist) + timerange.stopts, 0)
|
|
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(datadir: Path, pair: str, ticker_interval: str,
|
|
timerange: Optional[TimeRange] = None) -> Optional[list]:
|
|
"""
|
|
Load a pair from file, either .json.gz or .json
|
|
:return: tickerlist or None if unsuccessful
|
|
"""
|
|
filename = pair_data_filename(datadir, pair, ticker_interval)
|
|
pairdata = misc.file_load_json(filename)
|
|
if not pairdata:
|
|
return []
|
|
|
|
if timerange:
|
|
pairdata = trim_tickerlist(pairdata, timerange)
|
|
return pairdata
|
|
|
|
|
|
def store_tickerdata_file(datadir: Path, pair: str,
|
|
ticker_interval: str, data: list, is_zip: bool = False):
|
|
"""
|
|
Stores tickerdata to file
|
|
"""
|
|
filename = pair_data_filename(datadir, pair, ticker_interval)
|
|
misc.file_dump_json(filename, data, is_zip=is_zip)
|
|
|
|
|
|
def load_trades_file(datadir: Path, pair: str,
|
|
timerange: Optional[TimeRange] = None) -> List[Dict]:
|
|
"""
|
|
Load a pair from file, either .json.gz or .json
|
|
:return: tradelist or empty list if unsuccesful
|
|
"""
|
|
filename = pair_trades_filename(datadir, pair)
|
|
tradesdata = misc.file_load_json(filename)
|
|
if not tradesdata:
|
|
return []
|
|
|
|
# TODO: trim trades based on timerange... ?
|
|
return tradesdata
|
|
|
|
|
|
def store_trades_file(datadir: Path, pair: str,
|
|
data: list, is_zip: bool = True):
|
|
"""
|
|
Stores tickerdata to file
|
|
"""
|
|
filename = pair_trades_filename(datadir, pair)
|
|
misc.file_dump_json(filename, data, is_zip=is_zip)
|
|
|
|
|
|
def _validate_pairdata(pair, pairdata, timerange: TimeRange):
|
|
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'))
|
|
|
|
|
|
def load_pair_history(pair: str,
|
|
ticker_interval: str,
|
|
datadir: Path,
|
|
timerange: Optional[TimeRange] = None,
|
|
refresh_pairs: bool = False,
|
|
exchange: Optional[Exchange] = None,
|
|
fill_up_missing: bool = True,
|
|
drop_incomplete: bool = True
|
|
) -> DataFrame:
|
|
"""
|
|
Loads cached ticker history for the given pair.
|
|
:param pair: Pair to load data for
|
|
:param ticker_interval: Ticker-interval (e.g. "5m")
|
|
:param datadir: Path to the data storage location.
|
|
:param timerange: Limit data to be loaded to this timerange
|
|
:param refresh_pairs: Refresh pairs from exchange.
|
|
(Note: Requires exchange to be passed as well.)
|
|
:param exchange: Exchange object (needed when using "refresh_pairs")
|
|
:param fill_up_missing: Fill missing values with "No action"-candles
|
|
:param drop_incomplete: Drop last candle assuming it may be incomplete.
|
|
:return: DataFrame with ohlcv data
|
|
"""
|
|
|
|
# The user forced the refresh of pairs
|
|
if refresh_pairs:
|
|
download_pair_history(datadir=datadir,
|
|
exchange=exchange,
|
|
pair=pair,
|
|
ticker_interval=ticker_interval,
|
|
timerange=timerange)
|
|
|
|
pairdata = load_tickerdata_file(datadir, pair, ticker_interval, timerange=timerange)
|
|
|
|
if pairdata:
|
|
if timerange:
|
|
_validate_pairdata(pair, pairdata, timerange)
|
|
return parse_ticker_dataframe(pairdata, ticker_interval, pair=pair,
|
|
fill_missing=fill_up_missing,
|
|
drop_incomplete=drop_incomplete)
|
|
else:
|
|
logger.warning(
|
|
f'No history data for pair: "{pair}", interval: {ticker_interval}. '
|
|
'Use `freqtrade download-data` to download the data'
|
|
)
|
|
return None
|
|
|
|
|
|
def load_data(datadir: Path,
|
|
ticker_interval: str,
|
|
pairs: List[str],
|
|
refresh_pairs: bool = False,
|
|
exchange: Optional[Exchange] = None,
|
|
timerange: Optional[TimeRange] = None,
|
|
fill_up_missing: bool = True,
|
|
) -> Dict[str, DataFrame]:
|
|
"""
|
|
Loads ticker history data for a list of pairs
|
|
:return: dict(<pair>:<tickerlist>)
|
|
TODO: refresh_pairs is still used by edge to keep the data uptodate.
|
|
This should be replaced in the future. Instead, writing the current candles to disk
|
|
from dataprovider should be implemented, as this would avoid loading ohlcv data twice.
|
|
exchange and refresh_pairs are then not needed here nor in load_pair_history.
|
|
"""
|
|
result: Dict[str, DataFrame] = {}
|
|
|
|
for pair in pairs:
|
|
hist = load_pair_history(pair=pair, ticker_interval=ticker_interval,
|
|
datadir=datadir, timerange=timerange,
|
|
refresh_pairs=refresh_pairs,
|
|
exchange=exchange,
|
|
fill_up_missing=fill_up_missing)
|
|
if hist is not None:
|
|
result[pair] = hist
|
|
return result
|
|
|
|
|
|
def pair_data_filename(datadir: Path, pair: str, ticker_interval: str) -> Path:
|
|
pair_s = pair.replace("/", "_")
|
|
filename = datadir.joinpath(f'{pair_s}-{ticker_interval}.json')
|
|
return filename
|
|
|
|
|
|
def pair_trades_filename(datadir: Path, pair: str) -> Path:
|
|
pair_s = pair.replace("/", "_")
|
|
filename = datadir.joinpath(f'{pair_s}-trades.json.gz')
|
|
return filename
|
|
|
|
|
|
def _load_cached_data_for_updating(datadir: Path, pair: str, ticker_interval: str,
|
|
timerange: Optional[TimeRange]) -> Tuple[List[Any],
|
|
Optional[int]]:
|
|
"""
|
|
Load cached data to download more data.
|
|
If timerange is passed in, checks whether data from an before the stored data will be
|
|
downloaded.
|
|
If that's the case then what's available should be completely overwritten.
|
|
Only used by download_pair_history().
|
|
"""
|
|
|
|
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 * timeframe_to_minutes(ticker_interval)
|
|
since_ms = arrow.utcnow().shift(minutes=num_minutes).timestamp * 1000
|
|
|
|
# read the cached file
|
|
# Intentionally don't pass timerange in - since we need to load the full dataset.
|
|
data = load_tickerdata_file(datadir, pair, ticker_interval)
|
|
# 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: Path,
|
|
exchange: Optional[Exchange],
|
|
pair: str,
|
|
ticker_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 ticker_interval: ticker interval
|
|
:param timerange: range of time to download
|
|
:return: bool with success state
|
|
"""
|
|
if not exchange:
|
|
raise OperationalException(
|
|
"Exchange needs to be initialized when downloading pair history data"
|
|
)
|
|
|
|
try:
|
|
logger.info(
|
|
f'Download history data for pair: "{pair}", interval: {ticker_interval} '
|
|
f'and store in {datadir}.'
|
|
)
|
|
|
|
data, since_ms = _load_cached_data_for_updating(datadir, pair, ticker_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')
|
|
|
|
# Default since_ms to 30 days if nothing is given
|
|
new_data = exchange.get_historic_ohlcv(pair=pair, ticker_interval=ticker_interval,
|
|
since_ms=since_ms if since_ms
|
|
else
|
|
int(arrow.utcnow().shift(
|
|
days=-30).float_timestamp) * 1000)
|
|
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]))
|
|
|
|
store_tickerdata_file(datadir, pair, ticker_interval, data=data)
|
|
return True
|
|
|
|
except Exception as e:
|
|
logger.error(
|
|
f'Failed to download history data for pair: "{pair}", interval: {ticker_interval}. '
|
|
f'Error: {e}'
|
|
)
|
|
return False
|
|
|
|
|
|
def refresh_backtest_ohlcv_data(exchange: Exchange, pairs: List[str], timeframes: List[str],
|
|
dl_path: Path, timerange: Optional[TimeRange] = None,
|
|
erase=False) -> List[str]:
|
|
"""
|
|
Refresh stored ohlcv data for backtesting and hyperopt operations.
|
|
Used by freqtrade download-data
|
|
:return: Pairs not available
|
|
"""
|
|
pairs_not_available = []
|
|
for pair in pairs:
|
|
if pair not in exchange.markets:
|
|
pairs_not_available.append(pair)
|
|
logger.info(f"Skipping pair {pair}...")
|
|
continue
|
|
for ticker_interval in timeframes:
|
|
|
|
dl_file = pair_data_filename(dl_path, pair, ticker_interval)
|
|
if erase and dl_file.exists():
|
|
logger.info(
|
|
f'Deleting existing data for pair {pair}, interval {ticker_interval}.')
|
|
dl_file.unlink()
|
|
|
|
logger.info(f'Downloading pair {pair}, interval {ticker_interval}.')
|
|
download_pair_history(datadir=dl_path, exchange=exchange,
|
|
pair=pair, ticker_interval=str(ticker_interval),
|
|
timerange=timerange)
|
|
return pairs_not_available
|
|
|
|
|
|
def download_trades_history(datadir: Path,
|
|
exchange: Exchange,
|
|
pair: str,
|
|
timerange: Optional[TimeRange] = None) -> bool:
|
|
"""
|
|
Download trade history from the exchange.
|
|
Appends to previously downloaded trades data.
|
|
"""
|
|
try:
|
|
|
|
since = timerange.startts * 1000 if timerange and timerange.starttype == 'date' else None
|
|
|
|
trades = load_trades_file(datadir, pair)
|
|
|
|
from_id = trades[-1]['id'] if trades else None
|
|
|
|
logger.debug("Current Start: %s", trades[0]['datetime'] if trades else 'None')
|
|
logger.debug("Current End: %s", trades[-1]['datetime'] if trades else 'None')
|
|
|
|
new_trades = exchange.get_historic_trades(pair=pair,
|
|
since=since if since else
|
|
int(arrow.utcnow().shift(
|
|
days=-30).float_timestamp) * 1000,
|
|
# until=xxx,
|
|
from_id=from_id,
|
|
)
|
|
trades.extend(new_trades[1])
|
|
store_trades_file(datadir, pair, trades)
|
|
|
|
logger.debug("New Start: %s", trades[0]['datetime'])
|
|
logger.debug("New End: %s", trades[-1]['datetime'])
|
|
logger.info(f"New Amount of trades: {len(trades)}")
|
|
return True
|
|
|
|
except Exception as e:
|
|
logger.error(
|
|
f'Failed to download historic trades for pair: "{pair}". '
|
|
f'Error: {e}'
|
|
)
|
|
return False
|
|
|
|
|
|
def refresh_backtest_trades_data(exchange: Exchange, pairs: List[str], datadir: Path,
|
|
timerange: TimeRange, erase=False) -> List[str]:
|
|
"""
|
|
Refresh stored trades data.
|
|
Used by freqtrade download-data
|
|
:return: Pairs not available
|
|
"""
|
|
pairs_not_available = []
|
|
for pair in pairs:
|
|
if pair not in exchange.markets:
|
|
pairs_not_available.append(pair)
|
|
logger.info(f"Skipping pair {pair}...")
|
|
continue
|
|
|
|
dl_file = pair_trades_filename(datadir, pair)
|
|
if erase and dl_file.exists():
|
|
logger.info(
|
|
f'Deleting existing data for pair {pair}.')
|
|
dl_file.unlink()
|
|
|
|
logger.info(f'Downloading trades for pair {pair}.')
|
|
download_trades_history(datadir=datadir, exchange=exchange,
|
|
pair=pair,
|
|
timerange=timerange)
|
|
return pairs_not_available
|
|
|
|
|
|
def convert_trades_to_ohlcv(exchange: Exchange, pairs: List[str], timeframes: List[str],
|
|
datadir: Path, timerange: TimeRange, erase=False) -> None:
|
|
"""
|
|
Convert stored trades data to ohlcv data
|
|
"""
|
|
for pair in pairs:
|
|
trades = load_trades_file(datadir, pair)
|
|
for timeframe in timeframes:
|
|
ohlcv_file = pair_data_filename(datadir, pair, timeframe)
|
|
if erase and ohlcv_file.exists():
|
|
logger.info(f'Deleting existing data for pair {pair}, interval {timeframe}.')
|
|
ohlcv_file.unlink()
|
|
ohlcv = exchange.build_ohlcv(trades, timeframe)
|
|
# Store ohlcv
|
|
store_tickerdata_file(datadir, pair, timeframe, data=ohlcv)
|
|
|
|
|
|
def get_timeframe(data: Dict[str, DataFrame]) -> Tuple[arrow.Arrow, arrow.Arrow]:
|
|
"""
|
|
Get the maximum timeframe for the given backtest data
|
|
:param data: dictionary with preprocessed backtesting data
|
|
:return: tuple containing min_date, max_date
|
|
"""
|
|
timeframe = [
|
|
(arrow.get(frame['date'].min()), arrow.get(frame['date'].max()))
|
|
for frame in data.values()
|
|
]
|
|
return min(timeframe, key=operator.itemgetter(0))[0], \
|
|
max(timeframe, key=operator.itemgetter(1))[1]
|
|
|
|
|
|
def validate_backtest_data(data: DataFrame, pair: str, min_date: datetime,
|
|
max_date: datetime, ticker_interval_mins: int) -> bool:
|
|
"""
|
|
Validates preprocessed backtesting data for missing values and shows warnings about it that.
|
|
|
|
:param data: preprocessed backtesting data (as DataFrame)
|
|
:param pair: pair used for log output.
|
|
:param min_date: start-date of the data
|
|
:param max_date: end-date of the data
|
|
:param ticker_interval_mins: ticker interval in minutes
|
|
"""
|
|
# total difference in minutes / interval-minutes
|
|
expected_frames = int((max_date - min_date).total_seconds() // 60 // ticker_interval_mins)
|
|
found_missing = False
|
|
dflen = len(data)
|
|
if dflen < expected_frames:
|
|
found_missing = True
|
|
logger.warning("%s has missing frames: expected %s, got %s, that's %s missing values",
|
|
pair, expected_frames, dflen, expected_frames - dflen)
|
|
return found_missing
|