mirror of
https://github.com/freqtrade/freqtrade.git
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Merge branch 'develop' of https://github.com/freqtrade/freqtrade into max-open-trades
This commit is contained in:
commit
8c3ac56bc5
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@ -52,7 +52,7 @@ def _process_candles_and_indicators(pairlist, strategy_name, trades, signal_cand
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return analysed_trades_dict
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def _analyze_candles_and_indicators(pair, trades, signal_candles):
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def _analyze_candles_and_indicators(pair, trades: pd.DataFrame, signal_candles: pd.DataFrame):
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buyf = signal_candles
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if len(buyf) > 0:
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@ -120,7 +120,7 @@ def _do_group_table_output(bigdf, glist):
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else:
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agg_mask = {'profit_abs': ['count', 'sum', 'median', 'mean'],
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'profit_ratio': ['sum', 'median', 'mean']}
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'profit_ratio': ['median', 'mean', 'sum']}
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agg_cols = ['num_buys', 'profit_abs_sum', 'profit_abs_median',
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'profit_abs_mean', 'median_profit_pct', 'mean_profit_pct',
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'total_profit_pct']
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@ -197,7 +197,7 @@ def calculate_cagr(days_passed: int, starting_balance: float, final_balance: flo
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def calculate_expectancy(trades: pd.DataFrame) -> float:
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"""
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Calculate expectancy
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:param trades: DataFrame containing trades (requires columns close_date and profit_ratio)
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:param trades: DataFrame containing trades (requires columns close_date and profit_abs)
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:return: expectancy
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"""
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if len(trades) == 0:
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@ -239,7 +239,7 @@ def calculate_sortino(trades: pd.DataFrame, min_date: datetime, max_date: dateti
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down_stdev = np.std(trades.loc[trades['profit_abs'] < 0, 'profit_abs'] / starting_balance)
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if down_stdev != 0:
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if down_stdev != 0 and not np.isnan(down_stdev):
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sortino_ratio = expected_returns_mean / down_stdev * np.sqrt(365)
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else:
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# Define high (negative) sortino ratio to be clear that this is NOT optimal.
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@ -11,7 +11,7 @@ from freqtrade.enums import CandleType, MarginMode, TradingMode
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from freqtrade.exceptions import DDosProtection, OperationalException, TemporaryError
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from freqtrade.exchange import Exchange
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from freqtrade.exchange.common import retrier
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from freqtrade.exchange.types import Tickers
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from freqtrade.exchange.types import OHLCVResponse, Tickers
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from freqtrade.misc import deep_merge_dicts, json_load
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@ -112,7 +112,7 @@ class Binance(Exchange):
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since_ms: int, candle_type: CandleType,
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is_new_pair: bool = False, raise_: bool = False,
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until_ms: Optional[int] = None
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) -> Tuple[str, str, str, List]:
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) -> OHLCVResponse:
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"""
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Overwrite to introduce "fast new pair" functionality by detecting the pair's listing date
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Does not work for other exchanges, which don't return the earliest data when called with "0"
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@ -36,7 +36,7 @@ from freqtrade.exchange.exchange_utils import (CcxtModuleType, amount_to_contrac
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price_to_precision, timeframe_to_minutes,
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timeframe_to_msecs, timeframe_to_next_date,
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timeframe_to_prev_date, timeframe_to_seconds)
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from freqtrade.exchange.types import Ticker, Tickers
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from freqtrade.exchange.types import OHLCVResponse, Ticker, Tickers
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from freqtrade.misc import (chunks, deep_merge_dicts, file_dump_json, file_load_json,
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safe_value_fallback2)
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from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
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@ -1813,32 +1813,18 @@ class Exchange:
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:param candle_type: '', mark, index, premiumIndex, or funding_rate
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:return: List with candle (OHLCV) data
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"""
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pair, _, _, data = self.loop.run_until_complete(
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pair, _, _, data, _ = self.loop.run_until_complete(
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self._async_get_historic_ohlcv(pair=pair, timeframe=timeframe,
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since_ms=since_ms, until_ms=until_ms,
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is_new_pair=is_new_pair, candle_type=candle_type))
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logger.info(f"Downloaded data for {pair} with length {len(data)}.")
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return data
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def get_historic_ohlcv_as_df(self, pair: str, timeframe: str,
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since_ms: int, candle_type: CandleType) -> DataFrame:
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"""
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Minimal wrapper around get_historic_ohlcv - converting the result into a dataframe
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:param pair: Pair to download
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:param timeframe: Timeframe to get data for
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:param since_ms: Timestamp in milliseconds to get history from
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:param candle_type: Any of the enum CandleType (must match trading mode!)
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:return: OHLCV DataFrame
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"""
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ticks = self.get_historic_ohlcv(pair, timeframe, since_ms=since_ms, candle_type=candle_type)
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return ohlcv_to_dataframe(ticks, timeframe, pair=pair, fill_missing=True,
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drop_incomplete=self._ohlcv_partial_candle)
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async def _async_get_historic_ohlcv(self, pair: str, timeframe: str,
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since_ms: int, candle_type: CandleType,
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is_new_pair: bool = False, raise_: bool = False,
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until_ms: Optional[int] = None
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) -> Tuple[str, str, str, List]:
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) -> OHLCVResponse:
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"""
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Download historic ohlcv
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:param is_new_pair: used by binance subclass to allow "fast" new pair downloading
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@ -1869,15 +1855,16 @@ class Exchange:
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continue
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else:
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# Deconstruct tuple if it's not an exception
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p, _, c, new_data = res
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p, _, c, new_data, _ = res
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if p == pair and c == candle_type:
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data.extend(new_data)
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# Sort data again after extending the result - above calls return in "async order"
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data = sorted(data, key=lambda x: x[0])
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return pair, timeframe, candle_type, data
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return pair, timeframe, candle_type, data, self._ohlcv_partial_candle
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def _build_coroutine(self, pair: str, timeframe: str, candle_type: CandleType,
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since_ms: Optional[int], cache: bool) -> Coroutine:
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def _build_coroutine(
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self, pair: str, timeframe: str, candle_type: CandleType,
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since_ms: Optional[int], cache: bool) -> Coroutine[Any, Any, OHLCVResponse]:
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not_all_data = cache and self.required_candle_call_count > 1
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if cache and (pair, timeframe, candle_type) in self._klines:
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candle_limit = self.ohlcv_candle_limit(timeframe, candle_type)
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@ -1914,7 +1901,7 @@ class Exchange:
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"""
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Build Coroutines to execute as part of refresh_latest_ohlcv
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"""
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input_coroutines = []
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input_coroutines: List[Coroutine[Any, Any, OHLCVResponse]] = []
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cached_pairs = []
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for pair, timeframe, candle_type in set(pair_list):
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if (timeframe not in self.timeframes
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@ -1978,7 +1965,6 @@ class Exchange:
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:return: Dict of [{(pair, timeframe): Dataframe}]
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"""
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logger.debug("Refreshing candle (OHLCV) data for %d pairs", len(pair_list))
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drop_incomplete = self._ohlcv_partial_candle if drop_incomplete is None else drop_incomplete
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# Gather coroutines to run
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input_coroutines, cached_pairs = self._build_ohlcv_dl_jobs(pair_list, since_ms, cache)
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@ -1996,8 +1982,9 @@ class Exchange:
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if isinstance(res, Exception):
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logger.warning(f"Async code raised an exception: {repr(res)}")
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continue
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# Deconstruct tuple (has 4 elements)
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pair, timeframe, c_type, ticks = res
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# Deconstruct tuple (has 5 elements)
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pair, timeframe, c_type, ticks, drop_hint = res
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drop_incomplete = drop_hint if drop_incomplete is None else drop_incomplete
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ohlcv_df = self._process_ohlcv_df(
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pair, timeframe, c_type, ticks, cache, drop_incomplete)
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@ -2025,7 +2012,7 @@ class Exchange:
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timeframe: str,
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candle_type: CandleType,
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since_ms: Optional[int] = None,
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) -> Tuple[str, str, str, List]:
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) -> OHLCVResponse:
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"""
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Asynchronously get candle history data using fetch_ohlcv
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:param candle_type: '', mark, index, premiumIndex, or funding_rate
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@ -2065,9 +2052,9 @@ class Exchange:
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data = sorted(data, key=lambda x: x[0])
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except IndexError:
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logger.exception("Error loading %s. Result was %s.", pair, data)
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return pair, timeframe, candle_type, []
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return pair, timeframe, candle_type, [], self._ohlcv_partial_candle
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logger.debug("Done fetching pair %s, interval %s ...", pair, timeframe)
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return pair, timeframe, candle_type, data
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return pair, timeframe, candle_type, data, self._ohlcv_partial_candle
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except ccxt.NotSupported as e:
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raise OperationalException(
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@ -1,4 +1,6 @@
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from typing import Dict, Optional, TypedDict
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from typing import Dict, List, Optional, Tuple, TypedDict
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from freqtrade.enums import CandleType
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class Ticker(TypedDict):
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@ -14,3 +16,6 @@ class Ticker(TypedDict):
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Tickers = Dict[str, Ticker]
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# pair, timeframe, candleType, OHLCV, drop last?,
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OHLCVResponse = Tuple[str, str, CandleType, List, bool]
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@ -1178,6 +1178,7 @@ class Backtesting:
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open_trade_count_start = self.backtest_loop(
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row, pair, current_time, end_date, max_open_trades,
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open_trade_count_start)
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continue
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detail_data.loc[:, 'enter_long'] = row[LONG_IDX]
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detail_data.loc[:, 'exit_long'] = row[ELONG_IDX]
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detail_data.loc[:, 'enter_short'] = row[SHORT_IDX]
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@ -28,7 +28,7 @@ class FreqaiExampleStrategy(IStrategy):
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plot_config = {
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"main_plot": {},
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"subplots": {
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"prediction": {"prediction": {"color": "blue"}},
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"&-s_close": {"prediction": {"color": "blue"}},
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"do_predict": {
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"do_predict": {"color": "brown"},
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},
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@ -140,7 +140,8 @@ class FreqaiExampleStrategy(IStrategy):
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# If user wishes to use multiple targets, they can add more by
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# appending more columns with '&'. User should keep in mind that multi targets
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# requires a multioutput prediction model such as
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# templates/CatboostPredictionMultiModel.py,
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# freqai/prediction_models/CatboostRegressorMultiTarget.py,
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# freqtrade trade --freqaimodel CatboostRegressorMultiTarget
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# df["&-s_range"] = (
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# df["close"]
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@ -746,9 +746,7 @@ def test_download_data_no_exchange(mocker, caplog):
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start_download_data(pargs)
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def test_download_data_no_pairs(mocker, caplog):
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mocker.patch.object(Path, "exists", MagicMock(return_value=False))
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def test_download_data_no_pairs(mocker):
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mocker.patch('freqtrade.commands.data_commands.refresh_backtest_ohlcv_data',
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MagicMock(return_value=["ETH/BTC", "XRP/BTC"]))
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@ -770,8 +768,6 @@ def test_download_data_no_pairs(mocker, caplog):
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def test_download_data_all_pairs(mocker, markets):
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mocker.patch.object(Path, "exists", MagicMock(return_value=False))
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dl_mock = mocker.patch('freqtrade.commands.data_commands.refresh_backtest_ohlcv_data',
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MagicMock(return_value=["ETH/BTC", "XRP/BTC"]))
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patch_exchange(mocker)
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@ -557,7 +557,7 @@ async def test__async_get_historic_ohlcv_binance(default_conf, mocker, caplog, c
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exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv)
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pair = 'ETH/BTC'
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respair, restf, restype, res = await exchange._async_get_historic_ohlcv(
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respair, restf, restype, res, _ = await exchange._async_get_historic_ohlcv(
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pair, "5m", 1500000000000, is_new_pair=False, candle_type=candle_type)
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assert respair == pair
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assert restf == '5m'
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@ -566,7 +566,7 @@ async def test__async_get_historic_ohlcv_binance(default_conf, mocker, caplog, c
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assert exchange._api_async.fetch_ohlcv.call_count > 400
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# assert res == ohlcv
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exchange._api_async.fetch_ohlcv.reset_mock()
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_, _, _, res = await exchange._async_get_historic_ohlcv(
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_, _, _, res, _ = await exchange._async_get_historic_ohlcv(
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pair, "5m", 1500000000000, is_new_pair=True, candle_type=candle_type)
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# Called twice - one "init" call - and one to get the actual data.
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@ -1955,7 +1955,7 @@ def test_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name, candle_
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pair = 'ETH/BTC'
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async def mock_candle_hist(pair, timeframe, candle_type, since_ms):
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return pair, timeframe, candle_type, ohlcv
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return pair, timeframe, candle_type, ohlcv, True
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exchange._async_get_candle_history = Mock(wraps=mock_candle_hist)
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# one_call calculation * 1.8 should do 2 calls
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@ -1988,62 +1988,6 @@ def test_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name, candle_
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assert log_has_re(r"Async code raised an exception: .*", caplog)
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@pytest.mark.parametrize("exchange_name", EXCHANGES)
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@pytest.mark.parametrize('candle_type', ['mark', ''])
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def test_get_historic_ohlcv_as_df(default_conf, mocker, exchange_name, candle_type):
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exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
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ohlcv = [
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[
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arrow.utcnow().int_timestamp * 1000, # unix timestamp ms
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1, # open
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2, # high
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3, # low
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4, # close
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5, # volume (in quote currency)
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],
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[
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arrow.utcnow().shift(minutes=5).int_timestamp * 1000, # unix timestamp ms
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1, # open
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2, # high
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3, # low
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4, # close
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5, # volume (in quote currency)
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],
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[
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arrow.utcnow().shift(minutes=10).int_timestamp * 1000, # unix timestamp ms
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1, # open
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2, # high
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3, # low
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4, # close
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5, # volume (in quote currency)
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]
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]
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pair = 'ETH/BTC'
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async def mock_candle_hist(pair, timeframe, candle_type, since_ms):
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return pair, timeframe, candle_type, ohlcv
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exchange._async_get_candle_history = Mock(wraps=mock_candle_hist)
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# one_call calculation * 1.8 should do 2 calls
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since = 5 * 60 * exchange.ohlcv_candle_limit('5m', CandleType.SPOT) * 1.8
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ret = exchange.get_historic_ohlcv_as_df(
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pair,
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"5m",
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int((arrow.utcnow().int_timestamp - since) * 1000),
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candle_type=candle_type
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)
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assert exchange._async_get_candle_history.call_count == 2
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# Returns twice the above OHLCV data
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assert len(ret) == 2
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assert isinstance(ret, DataFrame)
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assert 'date' in ret.columns
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assert 'open' in ret.columns
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assert 'close' in ret.columns
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assert 'high' in ret.columns
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@pytest.mark.asyncio
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@pytest.mark.parametrize("exchange_name", EXCHANGES)
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@pytest.mark.parametrize('candle_type', [CandleType.MARK, CandleType.SPOT])
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|
@ -2063,7 +2007,7 @@ async def test__async_get_historic_ohlcv(default_conf, mocker, caplog, exchange_
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exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv)
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pair = 'ETH/USDT'
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respair, restf, _, res = await exchange._async_get_historic_ohlcv(
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respair, restf, _, res, _ = await exchange._async_get_historic_ohlcv(
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pair, "5m", 1500000000000, candle_type=candle_type, is_new_pair=False)
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assert respair == pair
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assert restf == '5m'
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|
@ -2074,7 +2018,7 @@ async def test__async_get_historic_ohlcv(default_conf, mocker, caplog, exchange_
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exchange._api_async.fetch_ohlcv.reset_mock()
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end_ts = 1_500_500_000_000
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start_ts = 1_500_000_000_000
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respair, restf, _, res = await exchange._async_get_historic_ohlcv(
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respair, restf, _, res, _ = await exchange._async_get_historic_ohlcv(
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pair, "5m", since_ms=start_ts, candle_type=candle_type, is_new_pair=False,
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until_ms=end_ts
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)
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|
@ -2306,7 +2250,7 @@ async def test__async_get_candle_history(default_conf, mocker, caplog, exchange_
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pair = 'ETH/BTC'
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res = await exchange._async_get_candle_history(pair, "5m", CandleType.SPOT)
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assert type(res) is tuple
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assert len(res) == 4
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assert len(res) == 5
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assert res[0] == pair
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assert res[1] == "5m"
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assert res[2] == CandleType.SPOT
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|
@ -2393,7 +2337,7 @@ async def test__async_get_candle_history_empty(default_conf, mocker, caplog):
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pair = 'ETH/BTC'
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res = await exchange._async_get_candle_history(pair, "5m", CandleType.SPOT)
|
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assert type(res) is tuple
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assert len(res) == 4
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assert len(res) == 5
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assert res[0] == pair
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assert res[1] == "5m"
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assert res[2] == CandleType.SPOT
|
||||
|
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