2018-12-16 08:58:46 +00:00
|
|
|
"""
|
|
|
|
Handle historic data (ohlcv).
|
2019-04-09 09:27:35 +00:00
|
|
|
|
|
|
|
Includes:
|
2018-12-16 08:58:46 +00:00
|
|
|
* load data for a pair (or a list of pairs) from disk
|
|
|
|
* download data from exchange and store to disk
|
|
|
|
"""
|
2019-05-25 14:51:52 +00:00
|
|
|
|
2018-12-13 05:12:10 +00:00
|
|
|
import logging
|
2019-05-25 14:51:52 +00:00
|
|
|
import operator
|
2019-10-20 12:02:53 +00:00
|
|
|
from copy import deepcopy
|
2019-11-08 05:55:07 +00:00
|
|
|
from datetime import datetime, timezone
|
2018-12-15 12:54:35 +00:00
|
|
|
from pathlib import Path
|
2019-05-25 14:51:52 +00:00
|
|
|
from typing import Any, Dict, List, Optional, Tuple
|
2018-12-13 05:12:10 +00:00
|
|
|
|
|
|
|
import arrow
|
2018-12-15 13:28:37 +00:00
|
|
|
from pandas import DataFrame
|
2018-12-13 05:12:10 +00:00
|
|
|
|
2019-05-25 14:51:52 +00:00
|
|
|
from freqtrade import OperationalException, misc
|
2019-07-11 18:23:23 +00:00
|
|
|
from freqtrade.configuration import TimeRange
|
2019-10-13 17:21:27 +00:00
|
|
|
from freqtrade.data.converter import parse_ticker_dataframe, trades_to_ohlcv
|
2019-10-20 12:02:53 +00:00
|
|
|
from freqtrade.exchange import Exchange, timeframe_to_minutes, timeframe_to_seconds
|
2019-04-04 17:56:40 +00:00
|
|
|
|
2018-12-13 05:12:10 +00:00
|
|
|
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)
|
|
|
|
|
2019-10-19 12:53:56 +00:00
|
|
|
if timerange.starttype == 'date':
|
2018-12-13 05:12:10 +00:00
|
|
|
while (start_index < len(tickerlist) and
|
|
|
|
tickerlist[start_index][0] < timerange.startts * 1000):
|
|
|
|
start_index += 1
|
|
|
|
|
2019-10-19 12:53:56 +00:00
|
|
|
if timerange.stoptype == 'date':
|
2018-12-13 05:12:10 +00:00
|
|
|
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]
|
|
|
|
|
|
|
|
|
2019-11-13 19:44:55 +00:00
|
|
|
def trim_dataframe(df: DataFrame, timerange: TimeRange, df_date_col: str = 'date') -> DataFrame:
|
2019-10-20 09:30:20 +00:00
|
|
|
"""
|
|
|
|
Trim dataframe based on given timerange
|
2019-11-13 19:44:55 +00:00
|
|
|
:param df: Dataframe to trim
|
|
|
|
:param timerange: timerange (use start and end date if available)
|
|
|
|
:param: df_date_col: Column in the dataframe to use as Date column
|
|
|
|
:return: trimmed dataframe
|
2019-10-20 09:30:20 +00:00
|
|
|
"""
|
|
|
|
if timerange.starttype == 'date':
|
2019-11-08 05:55:07 +00:00
|
|
|
start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc)
|
2019-11-13 19:44:55 +00:00
|
|
|
df = df.loc[df[df_date_col] >= start, :]
|
2019-10-20 09:30:20 +00:00
|
|
|
if timerange.stoptype == 'date':
|
2019-11-08 05:55:07 +00:00
|
|
|
stop = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc)
|
2019-11-13 19:44:55 +00:00
|
|
|
df = df.loc[df[df_date_col] <= stop, :]
|
2019-10-20 09:30:20 +00:00
|
|
|
return df
|
|
|
|
|
|
|
|
|
2019-11-02 19:19:13 +00:00
|
|
|
def load_tickerdata_file(datadir: Path, pair: str, timeframe: str,
|
2019-08-14 18:45:24 +00:00
|
|
|
timerange: Optional[TimeRange] = None) -> Optional[list]:
|
2018-12-13 05:12:10 +00:00
|
|
|
"""
|
2018-12-15 18:52:52 +00:00
|
|
|
Load a pair from file, either .json.gz or .json
|
2019-09-05 20:00:16 +00:00
|
|
|
:return: tickerlist or None if unsuccessful
|
2018-12-13 05:12:10 +00:00
|
|
|
"""
|
2019-11-02 19:19:13 +00:00
|
|
|
filename = pair_data_filename(datadir, pair, timeframe)
|
2019-05-21 17:49:02 +00:00
|
|
|
pairdata = misc.file_load_json(filename)
|
2018-12-28 09:25:12 +00:00
|
|
|
if not pairdata:
|
2019-08-14 18:45:24 +00:00
|
|
|
return []
|
2018-12-13 05:12:10 +00:00
|
|
|
|
|
|
|
if timerange:
|
|
|
|
pairdata = trim_tickerlist(pairdata, timerange)
|
|
|
|
return pairdata
|
|
|
|
|
|
|
|
|
2019-09-07 19:06:20 +00:00
|
|
|
def store_tickerdata_file(datadir: Path, pair: str,
|
2019-11-02 19:19:13 +00:00
|
|
|
timeframe: str, data: list, is_zip: bool = False):
|
2019-08-14 18:48:42 +00:00
|
|
|
"""
|
|
|
|
Stores tickerdata to file
|
|
|
|
"""
|
2019-11-02 19:19:13 +00:00
|
|
|
filename = pair_data_filename(datadir, pair, timeframe)
|
2019-08-14 18:48:42 +00:00
|
|
|
misc.file_dump_json(filename, data, is_zip=is_zip)
|
|
|
|
|
|
|
|
|
2019-10-08 18:45:35 +00:00
|
|
|
def load_trades_file(datadir: Path, pair: str,
|
2019-08-16 08:51:04 +00:00
|
|
|
timerange: Optional[TimeRange] = None) -> List[Dict]:
|
2019-08-16 08:26:38 +00:00
|
|
|
"""
|
|
|
|
Load a pair from file, either .json.gz or .json
|
2019-08-29 09:43:14 +00:00
|
|
|
:return: tradelist or empty list if unsuccesful
|
2019-08-16 08:26:38 +00:00
|
|
|
"""
|
|
|
|
filename = pair_trades_filename(datadir, pair)
|
|
|
|
tradesdata = misc.file_load_json(filename)
|
|
|
|
if not tradesdata:
|
2019-08-16 08:51:04 +00:00
|
|
|
return []
|
2019-08-16 08:26:38 +00:00
|
|
|
|
|
|
|
return tradesdata
|
|
|
|
|
|
|
|
|
2019-10-08 18:45:35 +00:00
|
|
|
def store_trades_file(datadir: Path, pair: str,
|
2019-08-16 08:26:38 +00:00
|
|
|
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)
|
|
|
|
|
|
|
|
|
2019-10-06 15:10:40 +00:00
|
|
|
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'))
|
|
|
|
|
|
|
|
|
2018-12-15 19:31:25 +00:00
|
|
|
def load_pair_history(pair: str,
|
2019-11-02 19:19:13 +00:00
|
|
|
timeframe: str,
|
2019-09-07 19:06:20 +00:00
|
|
|
datadir: Path,
|
2019-10-06 15:10:40 +00:00
|
|
|
timerange: Optional[TimeRange] = None,
|
2019-06-09 12:40:45 +00:00
|
|
|
fill_up_missing: bool = True,
|
2019-10-20 12:02:53 +00:00
|
|
|
drop_incomplete: bool = True,
|
|
|
|
startup_candles: int = 0,
|
2018-12-16 09:17:11 +00:00
|
|
|
) -> DataFrame:
|
2018-12-15 19:31:25 +00:00
|
|
|
"""
|
2019-12-17 10:43:42 +00:00
|
|
|
Load cached ticker history for the given pair.
|
|
|
|
|
2019-06-09 12:40:45 +00:00
|
|
|
:param pair: Pair to load data for
|
2019-11-02 19:19:13 +00:00
|
|
|
:param timeframe: Ticker timeframe (e.g. "5m")
|
2019-06-09 12:40:45 +00:00
|
|
|
:param datadir: Path to the data storage location.
|
|
|
|
:param timerange: Limit data to be loaded to this timerange
|
|
|
|
:param fill_up_missing: Fill missing values with "No action"-candles
|
|
|
|
:param drop_incomplete: Drop last candle assuming it may be incomplete.
|
2019-10-20 12:02:53 +00:00
|
|
|
:param startup_candles: Additional candles to load at the start of the period
|
2019-12-04 05:57:44 +00:00
|
|
|
:return: DataFrame with ohlcv data, or empty DataFrame
|
2018-12-15 19:31:25 +00:00
|
|
|
"""
|
2019-10-20 12:02:53 +00:00
|
|
|
timerange_startup = deepcopy(timerange)
|
2019-10-28 12:05:54 +00:00
|
|
|
if startup_candles > 0 and timerange_startup:
|
2019-11-02 19:19:13 +00:00
|
|
|
timerange_startup.subtract_start(timeframe_to_seconds(timeframe) * startup_candles)
|
2019-10-20 12:02:53 +00:00
|
|
|
|
2019-11-02 19:19:13 +00:00
|
|
|
pairdata = load_tickerdata_file(datadir, pair, timeframe, timerange=timerange_startup)
|
2019-01-01 12:42:30 +00:00
|
|
|
|
2018-12-15 19:31:25 +00:00
|
|
|
if pairdata:
|
2019-10-20 12:02:53 +00:00
|
|
|
if timerange_startup:
|
|
|
|
_validate_pairdata(pair, pairdata, timerange_startup)
|
2019-11-02 19:19:13 +00:00
|
|
|
return parse_ticker_dataframe(pairdata, timeframe, pair=pair,
|
2019-06-09 12:40:45 +00:00
|
|
|
fill_missing=fill_up_missing,
|
|
|
|
drop_incomplete=drop_incomplete)
|
2018-12-15 19:31:25 +00:00
|
|
|
else:
|
2019-05-17 16:05:36 +00:00
|
|
|
logger.warning(
|
2019-11-02 19:19:13 +00:00
|
|
|
f'No history data for pair: "{pair}", timeframe: {timeframe}. '
|
2019-09-20 18:16:49 +00:00
|
|
|
'Use `freqtrade download-data` to download the data'
|
2019-05-17 16:05:36 +00:00
|
|
|
)
|
2019-12-04 05:57:44 +00:00
|
|
|
return DataFrame()
|
2018-12-15 19:31:25 +00:00
|
|
|
|
|
|
|
|
2019-09-07 19:06:20 +00:00
|
|
|
def load_data(datadir: Path,
|
2019-11-02 19:19:13 +00:00
|
|
|
timeframe: str,
|
2018-12-13 05:12:10 +00:00
|
|
|
pairs: List[str],
|
2019-10-06 15:10:40 +00:00
|
|
|
timerange: Optional[TimeRange] = None,
|
2019-05-29 18:10:48 +00:00
|
|
|
fill_up_missing: bool = True,
|
2019-10-20 12:02:53 +00:00
|
|
|
startup_candles: int = 0,
|
2019-10-23 18:13:43 +00:00
|
|
|
fail_without_data: bool = False
|
2019-05-29 18:10:48 +00:00
|
|
|
) -> Dict[str, DataFrame]:
|
2018-12-13 05:12:10 +00:00
|
|
|
"""
|
2019-12-17 10:43:42 +00:00
|
|
|
Load ticker history data for a list of pairs.
|
|
|
|
|
2019-10-20 12:02:53 +00:00
|
|
|
:param datadir: Path to the data storage location.
|
2019-11-02 19:19:13 +00:00
|
|
|
:param timeframe: Ticker Timeframe (e.g. "5m")
|
2019-10-20 12:02:53 +00:00
|
|
|
:param pairs: List of pairs to load
|
|
|
|
:param timerange: Limit data to be loaded to this timerange
|
|
|
|
:param fill_up_missing: Fill missing values with "No action"-candles
|
|
|
|
:param startup_candles: Additional candles to load at the start of the period
|
2019-10-23 18:13:43 +00:00
|
|
|
:param fail_without_data: Raise OperationalException if no data is found.
|
2019-10-20 12:02:53 +00:00
|
|
|
:return: dict(<pair>:<Dataframe>)
|
2018-12-13 05:12:10 +00:00
|
|
|
"""
|
2019-05-29 18:25:07 +00:00
|
|
|
result: Dict[str, DataFrame] = {}
|
2019-10-31 05:51:36 +00:00
|
|
|
if startup_candles > 0 and timerange:
|
|
|
|
logger.info(f'Using indicator startup period: {startup_candles} ...')
|
2019-09-20 18:16:49 +00:00
|
|
|
|
|
|
|
for pair in pairs:
|
2019-11-02 19:19:13 +00:00
|
|
|
hist = load_pair_history(pair=pair, timeframe=timeframe,
|
2019-09-20 18:16:49 +00:00
|
|
|
datadir=datadir, timerange=timerange,
|
2019-10-23 18:13:43 +00:00
|
|
|
fill_up_missing=fill_up_missing,
|
|
|
|
startup_candles=startup_candles)
|
2019-12-04 05:57:44 +00:00
|
|
|
if not hist.empty:
|
2019-09-20 18:16:49 +00:00
|
|
|
result[pair] = hist
|
2019-10-23 18:13:43 +00:00
|
|
|
|
|
|
|
if fail_without_data and not result:
|
|
|
|
raise OperationalException("No data found. Terminating.")
|
2018-12-13 05:12:10 +00:00
|
|
|
return result
|
|
|
|
|
|
|
|
|
2019-12-17 10:43:42 +00:00
|
|
|
def refresh_data(datadir: Path,
|
|
|
|
timeframe: str,
|
|
|
|
pairs: List[str],
|
|
|
|
exchange: Exchange,
|
|
|
|
timerange: Optional[TimeRange] = None,
|
|
|
|
startup_candles: int = 0,
|
|
|
|
) -> None:
|
|
|
|
"""
|
|
|
|
Refresh ticker history data for a list of pairs.
|
|
|
|
|
|
|
|
:param datadir: Path to the data storage location.
|
|
|
|
:param timeframe: Ticker Timeframe (e.g. "5m")
|
|
|
|
:param pairs: List of pairs to load
|
|
|
|
:param exchange: Exchange object
|
|
|
|
:param timerange: Limit data to be loaded to this timerange
|
|
|
|
:param startup_candles: Additional candles to load at the start of the period
|
|
|
|
"""
|
|
|
|
if startup_candles > 0 and timerange:
|
|
|
|
logger.info(f'Using indicator startup period: {startup_candles} ...')
|
|
|
|
|
|
|
|
for pair in pairs:
|
2019-12-17 11:06:21 +00:00
|
|
|
_download_pair_history(pair=pair, timeframe=timeframe,
|
|
|
|
datadir=datadir, timerange=timerange,
|
|
|
|
exchange=exchange)
|
2019-12-17 10:43:42 +00:00
|
|
|
|
|
|
|
|
2019-11-02 19:19:13 +00:00
|
|
|
def pair_data_filename(datadir: Path, pair: str, timeframe: str) -> Path:
|
2019-05-21 17:49:02 +00:00
|
|
|
pair_s = pair.replace("/", "_")
|
2019-11-02 19:19:13 +00:00
|
|
|
filename = datadir.joinpath(f'{pair_s}-{timeframe}.json')
|
2019-05-21 17:49:02 +00:00
|
|
|
return filename
|
|
|
|
|
|
|
|
|
2019-08-14 16:58:27 +00:00
|
|
|
def pair_trades_filename(datadir: Path, pair: str) -> Path:
|
|
|
|
pair_s = pair.replace("/", "_")
|
2019-08-16 08:26:20 +00:00
|
|
|
filename = datadir.joinpath(f'{pair_s}-trades.json.gz')
|
2019-08-14 16:58:27 +00:00
|
|
|
return filename
|
|
|
|
|
|
|
|
|
2019-11-02 19:19:13 +00:00
|
|
|
def _load_cached_data_for_updating(datadir: Path, pair: str, timeframe: str,
|
2019-10-06 15:10:40 +00:00
|
|
|
timerange: Optional[TimeRange]) -> Tuple[List[Any],
|
|
|
|
Optional[int]]:
|
2018-12-13 05:12:10 +00:00
|
|
|
"""
|
2019-08-15 18:13:19 +00:00
|
|
|
Load cached data to download more data.
|
2019-10-06 15:10:40 +00:00
|
|
|
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.
|
2019-08-14 18:45:24 +00:00
|
|
|
Only used by download_pair_history().
|
2018-12-13 05:12:10 +00:00
|
|
|
"""
|
|
|
|
|
|
|
|
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':
|
2019-11-02 19:19:13 +00:00
|
|
|
num_minutes = timerange.stopts * timeframe_to_minutes(timeframe)
|
2018-12-13 05:12:10 +00:00
|
|
|
since_ms = arrow.utcnow().shift(minutes=num_minutes).timestamp * 1000
|
|
|
|
|
|
|
|
# read the cached file
|
2019-08-15 18:09:00 +00:00
|
|
|
# Intentionally don't pass timerange in - since we need to load the full dataset.
|
2019-11-02 19:19:13 +00:00
|
|
|
data = load_tickerdata_file(datadir, pair, timeframe)
|
2019-08-14 18:48:42 +00:00
|
|
|
# remove the last item, could be incomplete candle
|
|
|
|
if data:
|
|
|
|
data.pop()
|
2018-12-13 05:12:10 +00:00
|
|
|
else:
|
|
|
|
data = []
|
|
|
|
|
|
|
|
if data:
|
|
|
|
if since_ms and since_ms < data[0][0]:
|
2018-12-15 18:52:52 +00:00
|
|
|
# Earlier data than existing data requested, redownload all
|
2018-12-13 05:12:10 +00:00
|
|
|
data = []
|
|
|
|
else:
|
2018-12-15 18:52:52 +00:00
|
|
|
# a part of the data was already downloaded, so download unexist data only
|
2018-12-13 05:12:10 +00:00
|
|
|
since_ms = data[-1][0] + 1
|
|
|
|
|
|
|
|
return (data, since_ms)
|
|
|
|
|
|
|
|
|
2019-12-16 18:57:03 +00:00
|
|
|
def _download_pair_history(datadir: Path,
|
|
|
|
exchange: Optional[Exchange],
|
|
|
|
pair: str,
|
|
|
|
timeframe: str = '5m',
|
|
|
|
timerange: Optional[TimeRange] = None) -> bool:
|
2018-12-13 05:12:10 +00:00
|
|
|
"""
|
2019-11-13 10:28:26 +00:00
|
|
|
Download latest candles from the exchange for the pair and timeframe passed in parameters
|
2019-11-02 19:19:13 +00:00
|
|
|
The data is downloaded starting from the last correct data that
|
2018-12-13 05:12:10 +00:00
|
|
|
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
|
2019-05-17 16:05:36 +00:00
|
|
|
|
2018-12-13 05:12:10 +00:00
|
|
|
:param pair: pair to download
|
2019-11-02 19:19:13 +00:00
|
|
|
:param timeframe: Ticker Timeframe (e.g 5m)
|
2018-12-13 05:12:10 +00:00
|
|
|
:param timerange: range of time to download
|
2018-12-16 13:14:17 +00:00
|
|
|
:return: bool with success state
|
2018-12-13 05:12:10 +00:00
|
|
|
"""
|
2019-12-16 20:25:57 +00:00
|
|
|
if not exchange:
|
|
|
|
raise OperationalException(
|
|
|
|
"Exchange needs to be initialized when downloading pair history data"
|
|
|
|
)
|
|
|
|
|
2018-12-16 09:29:53 +00:00
|
|
|
try:
|
2019-05-17 16:05:36 +00:00
|
|
|
logger.info(
|
2019-11-02 19:19:13 +00:00
|
|
|
f'Download history data for pair: "{pair}", timeframe: {timeframe} '
|
2019-05-17 16:05:36 +00:00
|
|
|
f'and store in {datadir}.'
|
|
|
|
)
|
2018-12-13 05:12:10 +00:00
|
|
|
|
2019-11-02 19:19:13 +00:00
|
|
|
data, since_ms = _load_cached_data_for_updating(datadir, pair, timeframe, timerange)
|
2018-12-13 05:12:10 +00:00
|
|
|
|
2018-12-16 09:29:53 +00:00
|
|
|
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')
|
2018-12-13 05:12:10 +00:00
|
|
|
|
2018-12-16 09:29:53 +00:00
|
|
|
# Default since_ms to 30 days if nothing is given
|
2019-12-16 19:12:26 +00:00
|
|
|
new_data = exchange.get_historic_ohlcv(pair=pair,
|
|
|
|
timeframe=timeframe,
|
|
|
|
since_ms=since_ms if since_ms else
|
2019-08-14 08:14:54 +00:00
|
|
|
int(arrow.utcnow().shift(
|
2019-12-16 19:12:26 +00:00
|
|
|
days=-30).float_timestamp) * 1000
|
|
|
|
)
|
2018-12-16 09:29:53 +00:00
|
|
|
data.extend(new_data)
|
2018-12-13 05:12:10 +00:00
|
|
|
|
2018-12-16 09:29:53 +00:00
|
|
|
logger.debug("New Start: %s", misc.format_ms_time(data[0][0]))
|
|
|
|
logger.debug("New End: %s", misc.format_ms_time(data[-1][0]))
|
2018-12-13 05:12:10 +00:00
|
|
|
|
2019-11-02 19:19:13 +00:00
|
|
|
store_tickerdata_file(datadir, pair, timeframe, data=data)
|
2018-12-16 09:29:53 +00:00
|
|
|
return True
|
2019-05-17 16:05:36 +00:00
|
|
|
|
2019-05-21 17:49:02 +00:00
|
|
|
except Exception as e:
|
2019-05-17 16:05:36 +00:00
|
|
|
logger.error(
|
2019-11-02 19:19:13 +00:00
|
|
|
f'Failed to download history data for pair: "{pair}", timeframe: {timeframe}. '
|
2019-05-21 17:49:02 +00:00
|
|
|
f'Error: {e}'
|
2019-05-17 16:05:36 +00:00
|
|
|
)
|
2019-01-31 05:51:03 +00:00
|
|
|
return False
|
2019-05-25 14:51:52 +00:00
|
|
|
|
|
|
|
|
2019-08-25 13:01:27 +00:00
|
|
|
def refresh_backtest_ohlcv_data(exchange: Exchange, pairs: List[str], timeframes: List[str],
|
2019-12-16 18:43:33 +00:00
|
|
|
datadir: Path, timerange: Optional[TimeRange] = None,
|
2019-08-25 13:01:27 +00:00
|
|
|
erase=False) -> List[str]:
|
|
|
|
"""
|
|
|
|
Refresh stored ohlcv data for backtesting and hyperopt operations.
|
2019-12-16 18:43:33 +00:00
|
|
|
Used by freqtrade download-data subcommand.
|
|
|
|
:return: List of pairs that are not available.
|
2019-08-25 13:01:27 +00:00
|
|
|
"""
|
|
|
|
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
|
2019-11-02 19:19:13 +00:00
|
|
|
for timeframe in timeframes:
|
2019-08-25 13:01:27 +00:00
|
|
|
|
2019-12-16 18:43:33 +00:00
|
|
|
dl_file = pair_data_filename(datadir, pair, timeframe)
|
2019-08-25 13:01:27 +00:00
|
|
|
if erase and dl_file.exists():
|
|
|
|
logger.info(
|
2019-11-02 19:19:13 +00:00
|
|
|
f'Deleting existing data for pair {pair}, interval {timeframe}.')
|
2019-08-25 13:01:27 +00:00
|
|
|
dl_file.unlink()
|
|
|
|
|
2019-11-02 19:19:13 +00:00
|
|
|
logger.info(f'Downloading pair {pair}, interval {timeframe}.')
|
2019-12-16 18:57:03 +00:00
|
|
|
_download_pair_history(datadir=datadir, exchange=exchange,
|
|
|
|
pair=pair, timeframe=str(timeframe),
|
|
|
|
timerange=timerange)
|
2019-08-25 13:01:27 +00:00
|
|
|
return pairs_not_available
|
|
|
|
|
|
|
|
|
2019-12-16 18:57:03 +00:00
|
|
|
def _download_trades_history(datadir: Path,
|
|
|
|
exchange: Exchange,
|
|
|
|
pair: str,
|
|
|
|
timerange: Optional[TimeRange] = None) -> bool:
|
2019-08-25 12:30:09 +00:00
|
|
|
"""
|
|
|
|
Download trade history from the exchange.
|
|
|
|
Appends to previously downloaded trades data.
|
|
|
|
"""
|
2019-08-16 08:51:04 +00:00
|
|
|
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
|
|
|
|
|
2019-08-25 12:14:31 +00:00
|
|
|
logger.debug("Current Start: %s", trades[0]['datetime'] if trades else 'None')
|
2019-08-16 08:51:04 +00:00
|
|
|
logger.debug("Current End: %s", trades[-1]['datetime'] if trades else 'None')
|
|
|
|
|
2019-12-16 19:12:26 +00:00
|
|
|
# Default since_ms to 30 days if nothing is given
|
2019-08-25 12:14:31 +00:00
|
|
|
new_trades = exchange.get_historic_trades(pair=pair,
|
2019-08-25 12:30:09 +00:00
|
|
|
since=since if since else
|
|
|
|
int(arrow.utcnow().shift(
|
|
|
|
days=-30).float_timestamp) * 1000,
|
|
|
|
from_id=from_id,
|
|
|
|
)
|
2019-08-25 12:14:31 +00:00
|
|
|
trades.extend(new_trades[1])
|
2019-08-16 08:51:04 +00:00
|
|
|
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)}")
|
2019-08-29 10:56:10 +00:00
|
|
|
return True
|
2019-08-16 08:51:04 +00:00
|
|
|
|
|
|
|
except Exception as e:
|
|
|
|
logger.error(
|
|
|
|
f'Failed to download historic trades for pair: "{pair}". '
|
|
|
|
f'Error: {e}'
|
|
|
|
)
|
|
|
|
return False
|
|
|
|
|
|
|
|
|
2019-08-29 09:43:14 +00:00
|
|
|
def refresh_backtest_trades_data(exchange: Exchange, pairs: List[str], datadir: Path,
|
|
|
|
timerange: TimeRange, erase=False) -> List[str]:
|
2019-08-27 05:13:50 +00:00
|
|
|
"""
|
2019-12-16 18:43:33 +00:00
|
|
|
Refresh stored trades data for backtesting and hyperopt operations.
|
|
|
|
Used by freqtrade download-data subcommand.
|
|
|
|
:return: List of pairs that are not available.
|
2019-08-27 05:13:50 +00:00
|
|
|
"""
|
|
|
|
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
|
|
|
|
|
2019-08-29 09:36:32 +00:00
|
|
|
dl_file = pair_trades_filename(datadir, pair)
|
2019-08-27 05:13:50 +00:00
|
|
|
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}.')
|
2019-12-16 18:57:03 +00:00
|
|
|
_download_trades_history(datadir=datadir, exchange=exchange,
|
|
|
|
pair=pair,
|
|
|
|
timerange=timerange)
|
2019-08-27 05:13:50 +00:00
|
|
|
return pairs_not_available
|
|
|
|
|
|
|
|
|
2019-10-13 17:21:27 +00:00
|
|
|
def convert_trades_to_ohlcv(pairs: List[str], timeframes: List[str],
|
2019-08-29 09:43:14 +00:00
|
|
|
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()
|
2019-10-13 17:21:27 +00:00
|
|
|
ohlcv = trades_to_ohlcv(trades, timeframe)
|
2019-08-29 09:43:14 +00:00
|
|
|
# Store ohlcv
|
|
|
|
store_tickerdata_file(datadir, pair, timeframe, data=ohlcv)
|
|
|
|
|
|
|
|
|
2019-05-25 14:51:52 +00:00
|
|
|
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]
|
|
|
|
|
|
|
|
|
2019-06-15 11:31:27 +00:00
|
|
|
def validate_backtest_data(data: DataFrame, pair: str, min_date: datetime,
|
2019-12-11 06:12:37 +00:00
|
|
|
max_date: datetime, timeframe_min: int) -> bool:
|
2019-05-25 14:51:52 +00:00
|
|
|
"""
|
|
|
|
Validates preprocessed backtesting data for missing values and shows warnings about it that.
|
|
|
|
|
2019-06-15 11:31:27 +00:00
|
|
|
:param data: preprocessed backtesting data (as DataFrame)
|
|
|
|
:param pair: pair used for log output.
|
2019-05-25 14:51:52 +00:00
|
|
|
:param min_date: start-date of the data
|
|
|
|
:param max_date: end-date of the data
|
2019-12-11 06:12:37 +00:00
|
|
|
:param timeframe_min: ticker Timeframe in minutes
|
2019-05-25 14:51:52 +00:00
|
|
|
"""
|
2019-11-02 19:19:13 +00:00
|
|
|
# total difference in minutes / timeframe-minutes
|
2019-12-11 06:12:37 +00:00
|
|
|
expected_frames = int((max_date - min_date).total_seconds() // 60 // timeframe_min)
|
2019-05-25 14:51:52 +00:00
|
|
|
found_missing = False
|
2019-06-15 11:31:27 +00:00
|
|
|
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)
|
2019-05-25 14:51:52 +00:00
|
|
|
return found_missing
|