Merge branch 'freqtrade:develop' into develop
This commit is contained in:
@@ -10,7 +10,7 @@ from typing import Any, Dict, List, Optional, Union
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import numpy as np
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import pandas as pd
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from freqtrade.constants import LAST_BT_RESULT_FN
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from freqtrade.constants import LAST_BT_RESULT_FN, IntOrInf
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from freqtrade.exceptions import OperationalException
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from freqtrade.misc import json_load
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from freqtrade.optimize.backtest_caching import get_backtest_metadata_filename
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@@ -90,7 +90,8 @@ def get_latest_hyperopt_filename(directory: Union[Path, str]) -> str:
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return 'hyperopt_results.pickle'
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def get_latest_hyperopt_file(directory: Union[Path, str], predef_filename: str = None) -> Path:
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def get_latest_hyperopt_file(
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directory: Union[Path, str], predef_filename: Optional[str] = None) -> Path:
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"""
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Get latest hyperopt export based on '.last_result.json'.
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:param directory: Directory to search for last result
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@@ -193,7 +194,7 @@ def get_backtest_resultlist(dirname: Path):
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def find_existing_backtest_stats(dirname: Union[Path, str], run_ids: Dict[str, str],
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min_backtest_date: datetime = None) -> Dict[str, Any]:
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min_backtest_date: Optional[datetime] = None) -> Dict[str, Any]:
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"""
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Find existing backtest stats that match specified run IDs and load them.
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:param dirname: pathlib.Path object, or string pointing to the file.
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@@ -332,7 +333,7 @@ def analyze_trade_parallelism(results: pd.DataFrame, timeframe: str) -> pd.DataF
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def evaluate_result_multi(results: pd.DataFrame, timeframe: str,
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max_open_trades: int) -> pd.DataFrame:
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max_open_trades: IntOrInf) -> pd.DataFrame:
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"""
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Find overlapping trades by expanding each trade once per period it was open
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and then counting overlaps
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@@ -345,7 +346,7 @@ def evaluate_result_multi(results: pd.DataFrame, timeframe: str,
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return df_final[df_final['open_trades'] > max_open_trades]
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def trade_list_to_dataframe(trades: List[LocalTrade]) -> pd.DataFrame:
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def trade_list_to_dataframe(trades: Union[List[Trade], List[LocalTrade]]) -> pd.DataFrame:
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"""
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Convert list of Trade objects to pandas Dataframe
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:param trades: List of trade objects
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@@ -372,7 +373,7 @@ def load_trades_from_db(db_url: str, strategy: Optional[str] = None) -> pd.DataF
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filters = []
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if strategy:
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filters.append(Trade.strategy == strategy)
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trades = trade_list_to_dataframe(Trade.get_trades(filters).all())
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trades = trade_list_to_dataframe(list(Trade.get_trades(filters).all()))
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return trades
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@@ -9,7 +9,7 @@ from collections import deque
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from datetime import datetime, timezone
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from typing import Any, Dict, List, Optional, Tuple
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from pandas import DataFrame, to_timedelta
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from pandas import DataFrame, Timedelta, Timestamp, to_timedelta
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from freqtrade.configuration import TimeRange
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from freqtrade.constants import (FULL_DATAFRAME_THRESHOLD, Config, ListPairsWithTimeframes,
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@@ -18,6 +18,7 @@ from freqtrade.data.history import load_pair_history
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from freqtrade.enums import CandleType, RPCMessageType, RunMode
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from freqtrade.exceptions import ExchangeError, OperationalException
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from freqtrade.exchange import Exchange, timeframe_to_seconds
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from freqtrade.exchange.types import OrderBook
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from freqtrade.misc import append_candles_to_dataframe
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from freqtrade.rpc import RPCManager
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from freqtrade.util import PeriodicCache
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@@ -206,9 +207,11 @@ class DataProvider:
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existing_df, _ = self.__producer_pairs_df[producer_name][pair_key]
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# CHECK FOR MISSING CANDLES
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timeframe_delta = to_timedelta(timeframe) # Convert the timeframe to a timedelta for pandas
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local_last = existing_df.iloc[-1]['date'] # We want the last date from our copy
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incoming_first = dataframe.iloc[0]['date'] # We want the first date from the incoming
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# Convert the timeframe to a timedelta for pandas
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timeframe_delta: Timedelta = to_timedelta(timeframe)
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local_last: Timestamp = existing_df.iloc[-1]['date'] # We want the last date from our copy
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# We want the first date from the incoming
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incoming_first: Timestamp = dataframe.iloc[0]['date']
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# Remove existing candles that are newer than the incoming first candle
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existing_df1 = existing_df[existing_df['date'] < incoming_first]
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@@ -221,7 +224,7 @@ class DataProvider:
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# we missed some candles between our data and the incoming
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# so return False and candle_difference.
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if candle_difference > 1:
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return (False, candle_difference)
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return (False, int(candle_difference))
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if existing_df1.empty:
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appended_df = dataframe
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else:
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@@ -281,7 +284,7 @@ class DataProvider:
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def historic_ohlcv(
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self,
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pair: str,
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timeframe: str = None,
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timeframe: Optional[str] = None,
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candle_type: str = ''
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) -> DataFrame:
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"""
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@@ -333,7 +336,7 @@ class DataProvider:
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def get_pair_dataframe(
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self,
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pair: str,
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timeframe: str = None,
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timeframe: Optional[str] = None,
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candle_type: str = ''
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) -> DataFrame:
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"""
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@@ -415,16 +418,14 @@ class DataProvider:
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def refresh(self,
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pairlist: ListPairsWithTimeframes,
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helping_pairs: ListPairsWithTimeframes = None) -> None:
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helping_pairs: Optional[ListPairsWithTimeframes] = None) -> None:
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"""
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Refresh data, called with each cycle
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"""
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if self._exchange is None:
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raise OperationalException(NO_EXCHANGE_EXCEPTION)
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if helping_pairs:
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self._exchange.refresh_latest_ohlcv(pairlist + helping_pairs)
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else:
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self._exchange.refresh_latest_ohlcv(pairlist)
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final_pairs = (pairlist + helping_pairs) if helping_pairs else pairlist
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self._exchange.refresh_latest_ohlcv(final_pairs)
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@property
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def available_pairs(self) -> ListPairsWithTimeframes:
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@@ -439,7 +440,7 @@ class DataProvider:
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def ohlcv(
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self,
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pair: str,
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timeframe: str = None,
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timeframe: Optional[str] = None,
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copy: bool = True,
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candle_type: str = ''
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) -> DataFrame:
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@@ -487,7 +488,7 @@ class DataProvider:
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except ExchangeError:
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return {}
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def orderbook(self, pair: str, maximum: int) -> Dict[str, List]:
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def orderbook(self, pair: str, maximum: int) -> OrderBook:
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"""
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Fetch latest l2 orderbook data
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Warning: Does a network request - so use with common sense.
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6
freqtrade/data/entryexitanalysis.py
Executable file → Normal file
6
freqtrade/data/entryexitanalysis.py
Executable file → Normal file
@@ -24,9 +24,9 @@ def _load_signal_candles(backtest_dir: Path):
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scpf = Path(backtest_dir.parent / f"{backtest_dir.stem}_signals.pkl")
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try:
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scp = open(scpf, "rb")
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signal_candles = joblib.load(scp)
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logger.info(f"Loaded signal candles: {str(scpf)}")
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with scpf.open("rb") as scp:
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signal_candles = joblib.load(scp)
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logger.info(f"Loaded signal candles: {str(scpf)}")
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except Exception as e:
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logger.error("Cannot load signal candles from pickled results: ", e)
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@@ -28,8 +28,8 @@ def load_pair_history(pair: str,
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fill_up_missing: bool = True,
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drop_incomplete: bool = False,
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startup_candles: int = 0,
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data_format: str = None,
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data_handler: IDataHandler = None,
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data_format: Optional[str] = None,
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data_handler: Optional[IDataHandler] = None,
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candle_type: CandleType = CandleType.SPOT
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) -> DataFrame:
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"""
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@@ -69,7 +69,7 @@ def load_data(datadir: Path,
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fail_without_data: bool = False,
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data_format: str = 'json',
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candle_type: CandleType = CandleType.SPOT,
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user_futures_funding_rate: int = None,
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user_futures_funding_rate: Optional[int] = None,
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) -> Dict[str, DataFrame]:
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"""
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Load ohlcv history data for a list of pairs.
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@@ -116,7 +116,7 @@ def refresh_data(*, datadir: Path,
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timeframe: str,
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pairs: List[str],
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exchange: Exchange,
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data_format: str = None,
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data_format: Optional[str] = None,
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timerange: Optional[TimeRange] = None,
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candle_type: CandleType,
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) -> None:
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@@ -189,7 +189,7 @@ def _download_pair_history(pair: str, *,
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timeframe: str = '5m',
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process: str = '',
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new_pairs_days: int = 30,
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data_handler: IDataHandler = None,
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data_handler: Optional[IDataHandler] = None,
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timerange: Optional[TimeRange] = None,
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candle_type: CandleType,
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erase: bool = False,
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@@ -272,7 +272,7 @@ def refresh_backtest_ohlcv_data(exchange: Exchange, pairs: List[str], timeframes
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datadir: Path, trading_mode: str,
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timerange: Optional[TimeRange] = None,
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new_pairs_days: int = 30, erase: bool = False,
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data_format: str = None,
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data_format: Optional[str] = None,
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prepend: bool = False,
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) -> List[str]:
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"""
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@@ -308,7 +308,7 @@ class IDataHandler(ABC):
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timerange=timerange_startup,
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candle_type=candle_type
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)
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if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data, True):
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if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data):
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return pairdf
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else:
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enddate = pairdf.iloc[-1]['date']
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@@ -316,7 +316,7 @@ class IDataHandler(ABC):
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if timerange_startup:
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self._validate_pairdata(pair, pairdf, timeframe, candle_type, timerange_startup)
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pairdf = trim_dataframe(pairdf, timerange_startup)
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if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data):
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if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data, True):
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return pairdf
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# incomplete candles should only be dropped if we didn't trim the end beforehand.
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@@ -418,8 +418,8 @@ def get_datahandlerclass(datatype: str) -> Type[IDataHandler]:
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raise ValueError(f"No datahandler for datatype {datatype} available.")
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def get_datahandler(datadir: Path, data_format: str = None,
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data_handler: IDataHandler = None) -> IDataHandler:
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def get_datahandler(datadir: Path, data_format: Optional[str] = None,
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data_handler: Optional[IDataHandler] = None) -> IDataHandler:
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"""
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:param datadir: Folder to save data
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:param data_format: dataformat to use
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