Move load_trades to bt_anlaysis
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@ -1,12 +1,18 @@
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"""
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Helpers when analyzing backtest data
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"""
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import logging
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from pathlib import Path
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import numpy as np
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import pandas as pd
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import pytz
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from freqtrade import persistence
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from freqtrade.misc import json_load
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from freqtrade.persistence import Trade
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logger = logging.getLogger(__name__)
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# must align with columns in backtest.py
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BT_DATA_COLUMNS = ["pair", "profitperc", "open_time", "close_time", "index", "duration",
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@ -65,3 +71,40 @@ def evaluate_result_multi(results: pd.DataFrame, freq: str, max_open_trades: int
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df2 = df2.set_index('date')
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df_final = df2.resample(freq)[['pair']].count()
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return df_final[df_final['pair'] > max_open_trades]
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def load_trades(db_url: str = None, exportfilename: str = None) -> pd.DataFrame:
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"""
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Load trades, either from a DB (using dburl) or via a backtest export file.
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:param db_url: Sqlite url (default format sqlite:///tradesv3.dry-run.sqlite)
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:param exportfilename: Path to a file exported from backtesting
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:returns: Dataframe containing Trades
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"""
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timeZone = pytz.UTC
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trades: pd.DataFrame = pd.DataFrame([], columns=BT_DATA_COLUMNS)
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if db_url:
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persistence.init(db_url, clean_open_orders=False)
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columns = ["pair", "profit", "open_time", "close_time",
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"open_rate", "close_rate", "duration"]
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for x in Trade.query.all():
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logger.info("date: {}".format(x.open_date))
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trades = pd.DataFrame([(t.pair, t.calc_profit(),
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t.open_date.replace(tzinfo=timeZone),
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t.close_date.replace(tzinfo=timeZone) if t.close_date else None,
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t.open_rate, t.close_rate,
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t.close_date.timestamp() - t.open_date.timestamp()
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if t.close_date else None)
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for t in Trade.query.all()],
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columns=columns)
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elif exportfilename:
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file = Path(exportfilename)
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if file.exists():
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trades = load_backtest_data(file)
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return trades
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@ -31,60 +31,19 @@ from pathlib import Path
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from typing import Any, Dict, List
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import pandas as pd
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import pytz
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from freqtrade import persistence
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from freqtrade.arguments import Arguments, TimeRange
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from freqtrade.data import history
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from freqtrade.data.btanalysis import BT_DATA_COLUMNS, load_backtest_data
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from freqtrade.data.btanalysis import load_trades
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from freqtrade.plot.plotting import generate_graph, generate_plot_file
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from freqtrade.exchange import Exchange
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from freqtrade.optimize import setup_configuration
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from freqtrade.persistence import Trade
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from freqtrade.resolvers import StrategyResolver
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from freqtrade.state import RunMode
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logger = logging.getLogger(__name__)
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_CONF: Dict[str, Any] = {}
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timeZone = pytz.UTC
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def load_trades(db_url: str = None, exportfilename: str = None) -> pd.DataFrame:
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"""
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Load trades, either from a DB (using dburl) or via a backtest export file.
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:param db_url: Sqlite url (default format sqlite:///tradesv3.dry-run.sqlite)
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:param exportfilename: Path to a file exported from backtesting
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:returns: Dataframe containing Trades
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"""
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# TODO: Document and move to btanalysis
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trades: pd.DataFrame = pd.DataFrame([], columns=BT_DATA_COLUMNS)
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if db_url:
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persistence.init(db_url, clean_open_orders=False)
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columns = ["pair", "profit", "open_time", "close_time",
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"open_rate", "close_rate", "duration"]
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for x in Trade.query.all():
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logger.info("date: {}".format(x.open_date))
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trades = pd.DataFrame([(t.pair, t.calc_profit(),
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t.open_date.replace(tzinfo=timeZone),
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t.close_date.replace(tzinfo=timeZone) if t.close_date else None,
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t.open_rate, t.close_rate,
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t.close_date.timestamp() - t.open_date.timestamp()
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if t.close_date else None)
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for t in Trade.query.all()],
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columns=columns)
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elif exportfilename:
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file = Path(exportfilename)
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if file.exists():
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trades = load_backtest_data(file)
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return trades
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def get_trading_env(args: Namespace):
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"""
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