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Merge branch 'develop' into move_datadownload

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This commit is contained in:
Matthias
2022-08-31 10:23:45 +00:00
parent bb3523f383 4aec2db14d
commit a88ffd2c9d
101 changed files with 3154 additions and 1523 deletions
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28
freqtrade/data/history/hdf5datahandler.py
View File

@@ -7,9 +7,8 @@ import numpy as np
import pandas as pd
from freqtrade.configuration import TimeRange
from freqtrade.constants import (DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS,
ListPairsWithTimeframes, TradeList)
from freqtrade.enums import CandleType, TradingMode
from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS, TradeList
from freqtrade.enums import CandleType
from .idatahandler import IDataHandler
@@ -21,29 +20,6 @@ class HDF5DataHandler(IDataHandler):
_columns = DEFAULT_DATAFRAME_COLUMNS
@classmethod
def ohlcv_get_available_data(
cls, datadir: Path, trading_mode: TradingMode) -> ListPairsWithTimeframes:
"""
Returns a list of all pairs with ohlcv data available in this datadir
:param datadir: Directory to search for ohlcv files
:param trading_mode: trading-mode to be used
:return: List of Tuples of (pair, timeframe)
"""
if trading_mode == TradingMode.FUTURES:
datadir = datadir.joinpath('futures')
_tmp = [
re.search(
cls._OHLCV_REGEX, p.name
) for p in datadir.glob("*.h5")
]
return [
(
cls.rebuild_pair_from_filename(match[1]),
cls.rebuild_timeframe_from_filename(match[2]),
CandleType.from_string(match[3])
) for match in _tmp if match and len(match.groups()) > 1]
@classmethod
def ohlcv_get_pairs(cls, datadir: Path, timeframe: str, candle_type: CandleType) -> List[str]:
"""

17
freqtrade/data/history/history_utils.py
View File

@@ -56,7 +56,7 @@ def load_pair_history(pair: str,
fill_missing=fill_up_missing,
drop_incomplete=drop_incomplete,
startup_candles=startup_candles,
candle_type=candle_type
candle_type=candle_type,
)
@@ -97,14 +97,15 @@ def load_data(datadir: Path,
fill_up_missing=fill_up_missing,
startup_candles=startup_candles,
data_handler=data_handler,
candle_type=candle_type
candle_type=candle_type,
)
if not hist.empty:
result[pair] = hist
else:
if candle_type is CandleType.FUNDING_RATE and user_futures_funding_rate is not None:
logger.warn(f"{pair} using user specified [{user_futures_funding_rate}]")
result[pair] = DataFrame(columns=["open", "close", "high", "low", "volume"])
elif candle_type not in (CandleType.SPOT, CandleType.FUTURES):
result[pair] = DataFrame(columns=["date", "open", "close", "high", "low", "volume"])
if fail_without_data and not result:
raise OperationalException("No data found. Terminating.")
@@ -301,8 +302,8 @@ def refresh_backtest_ohlcv_data(exchange: Exchange, pairs: List[str], timeframes
if trading_mode == 'futures':
# Predefined candletype (and timeframe) depending on exchange
# Downloads what is necessary to backtest based on futures data.
tf_mark = exchange._ft_has['mark_ohlcv_timeframe']
fr_candle_type = CandleType.from_string(exchange._ft_has['mark_ohlcv_price'])
tf_mark = exchange.get_option('mark_ohlcv_timeframe')
fr_candle_type = CandleType.from_string(exchange.get_option('mark_ohlcv_price'))
# All exchanges need FundingRate for futures trading.
# The timeframe is aligned to the mark-price timeframe.
for funding_candle_type in (CandleType.FUNDING_RATE, fr_candle_type):
@@ -329,13 +330,12 @@ def _download_trades_history(exchange: Exchange,
try:
until = None
since = 0
if timerange:
if timerange.starttype == 'date':
since = timerange.startts * 1000
if timerange.stoptype == 'date':
until = timerange.stopts * 1000
else:
since = arrow.utcnow().shift(days=-new_pairs_days).int_timestamp * 1000
trades = data_handler.trades_load(pair)
@@ -348,6 +348,9 @@ def _download_trades_history(exchange: Exchange,
logger.info(f"Start earlier than available data. Redownloading trades for {pair}...")
trades = []
if not since:
since = arrow.utcnow().shift(days=-new_pairs_days).int_timestamp * 1000
from_id = trades[-1][1] if trades else None
if trades and since < trades[-1][0]:
# Reset since to the last available point

29
freqtrade/data/history/idatahandler.py
View File

@@ -9,7 +9,7 @@ from abc import ABC, abstractmethod
from copy import deepcopy
from datetime import datetime, timezone
from pathlib import Path
from typing import List, Optional, Type
from typing import List, Optional, Tuple, Type
from pandas import DataFrame
@@ -39,15 +39,26 @@ class IDataHandler(ABC):
raise NotImplementedError()
@classmethod
@abstractmethod
def ohlcv_get_available_data(
cls, datadir: Path, trading_mode: TradingMode) -> ListPairsWithTimeframes:
"""
Returns a list of all pairs with ohlcv data available in this datadir
:param datadir: Directory to search for ohlcv files
:param trading_mode: trading-mode to be used
:return: List of Tuples of (pair, timeframe)
:return: List of Tuples of (pair, timeframe, CandleType)
"""
if trading_mode == TradingMode.FUTURES:
datadir = datadir.joinpath('futures')
_tmp = [
re.search(
cls._OHLCV_REGEX, p.name
) for p in datadir.glob(f"*.{cls._get_file_extension()}")]
return [
(
cls.rebuild_pair_from_filename(match[1]),
cls.rebuild_timeframe_from_filename(match[2]),
CandleType.from_string(match[3])
) for match in _tmp if match and len(match.groups()) > 1]
@classmethod
@abstractmethod
@@ -73,6 +84,18 @@ class IDataHandler(ABC):
:return: None
"""
def ohlcv_data_min_max(self, pair: str, timeframe: str,
candle_type: CandleType) -> Tuple[datetime, datetime]:
"""
Returns the min and max timestamp for the given pair and timeframe.
:param pair: Pair to get min/max for
:param timeframe: Timeframe to get min/max for
:param candle_type: Any of the enum CandleType (must match trading mode!)
:return: (min, max)
"""
data = self._ohlcv_load(pair, timeframe, None, candle_type)
return data.iloc[0]['date'].to_pydatetime(), data.iloc[-1]['date'].to_pydatetime()
@abstractmethod
def _ohlcv_load(self, pair: str, timeframe: str, timerange: Optional[TimeRange],
candle_type: CandleType

26
freqtrade/data/history/jsondatahandler.py
View File

@@ -8,9 +8,9 @@ from pandas import DataFrame, read_json, to_datetime
from freqtrade import misc
from freqtrade.configuration import TimeRange
from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, ListPairsWithTimeframes, TradeList
from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, TradeList
from freqtrade.data.converter import trades_dict_to_list
from freqtrade.enums import CandleType, TradingMode
from freqtrade.enums import CandleType
from .idatahandler import IDataHandler
@@ -23,28 +23,6 @@ class JsonDataHandler(IDataHandler):
_use_zip = False
_columns = DEFAULT_DATAFRAME_COLUMNS
@classmethod
def ohlcv_get_available_data(
cls, datadir: Path, trading_mode: TradingMode) -> ListPairsWithTimeframes:
"""
Returns a list of all pairs with ohlcv data available in this datadir
:param datadir: Directory to search for ohlcv files
:param trading_mode: trading-mode to be used
:return: List of Tuples of (pair, timeframe)
"""
if trading_mode == 'futures':
datadir = datadir.joinpath('futures')
_tmp = [
re.search(
cls._OHLCV_REGEX, p.name
) for p in datadir.glob(f"*.{cls._get_file_extension()}")]
return [
(
cls.rebuild_pair_from_filename(match[1]),
cls.rebuild_timeframe_from_filename(match[2]),
CandleType.from_string(match[3])
) for match in _tmp if match and len(match.groups()) > 1]
@classmethod
def ohlcv_get_pairs(cls, datadir: Path, timeframe: str, candle_type: CandleType) -> List[str]:
"""