Extract .last_result.json to constant
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@ -33,6 +33,8 @@ DEFAULT_DATAFRAME_COLUMNS = ['date', 'open', 'high', 'low', 'close', 'volume']
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# it has wide consequences for stored trades files
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DEFAULT_TRADES_COLUMNS = ['timestamp', 'id', 'type', 'side', 'price', 'amount', 'cost']
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LAST_BT_RESULT_FN = '.last_result.json'
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USERPATH_HYPEROPTS = 'hyperopts'
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USERPATH_STRATEGIES = 'strategies'
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USERPATH_NOTEBOOKS = 'notebooks'
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@ -10,6 +10,7 @@ import pandas as pd
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from datetime import timezone
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from freqtrade import persistence
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from freqtrade.constants import LAST_BT_RESULT_FN
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from freqtrade.misc import json_load
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from freqtrade.persistence import Trade
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@ -34,7 +35,7 @@ def get_latest_backtest_filename(directory: Union[Path, str]) -> str:
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directory = Path(directory)
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if not directory.is_dir():
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raise ValueError(f"Directory '{directory}' does not exist.")
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filename = directory / '.last_result.json'
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filename = directory / LAST_BT_RESULT_FN
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if not filename.is_file():
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raise ValueError(f"Directory '{directory}' does not seem to contain backtest statistics yet.")
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@ -43,7 +44,7 @@ def get_latest_backtest_filename(directory: Union[Path, str]) -> str:
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data = json_load(file)
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if 'latest_backtest' not in data:
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raise ValueError("Invalid '.last_result.json' format.")
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raise ValueError(f"Invalid '{LAST_BT_RESULT_FN}' format.")
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return data['latest_backtest']
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@ -7,7 +7,7 @@ from arrow import Arrow
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from pandas import DataFrame
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from tabulate import tabulate
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from freqtrade.constants import DATETIME_PRINT_FORMAT
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from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN
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from freqtrade.data.btanalysis import calculate_max_drawdown, calculate_market_change
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from freqtrade.misc import file_dump_json
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@ -21,8 +21,7 @@ def store_backtest_stats(recordfilename: Path, stats: Dict[str, DataFrame]) -> N
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).with_suffix(recordfilename.suffix)
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file_dump_json(filename, stats)
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latest_filename = Path.joinpath(recordfilename.parent,
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'.last_result.json')
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latest_filename = Path.joinpath(recordfilename.parent, LAST_BT_RESULT_FN)
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file_dump_json(latest_filename, {'latest_backtest': str(filename.name)})
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@ -6,6 +6,7 @@ from arrow import Arrow
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from pandas import DataFrame, DateOffset, Timestamp, to_datetime
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from freqtrade.configuration import TimeRange
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from freqtrade.constants import LAST_BT_RESULT_FN
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from freqtrade.data.btanalysis import (BT_DATA_COLUMNS,
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analyze_trade_parallelism,
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calculate_market_change,
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@ -73,7 +74,7 @@ def test_load_backtest_data_new_format(testdatadir):
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load_backtest_data(str("filename") + "nofile")
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with pytest.raises(ValueError, match=r"Unknown dataformat."):
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load_backtest_data(testdatadir / '.last_result.json')
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load_backtest_data(testdatadir / LAST_BT_RESULT_FN)
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def test_load_backtest_data_multi(testdatadir):
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@ -1,15 +1,15 @@
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from datetime import datetime
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import re
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from pathlib import Path
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import pandas as pd
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import re
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import pytest
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from arrow import Arrow
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from freqtrade.configuration import TimeRange
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from freqtrade.constants import LAST_BT_RESULT_FN
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from freqtrade.data import history
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from freqtrade.edge import PairInfo
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from freqtrade.data.btanalysis import get_latest_backtest_filename
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from freqtrade.edge import PairInfo
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from freqtrade.optimize.optimize_reports import (generate_backtest_stats,
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generate_edge_table,
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generate_pair_metrics,
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@ -93,25 +93,25 @@ def test_generate_backtest_stats(default_conf, testdatadir):
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# Above sample had no loosing trade
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assert strat_stats['max_drawdown'] == 0.0
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results = {'DefStrat': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
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"UNITTEST/BTC", "UNITTEST/BTC"],
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"profit_percent": [0.003312, 0.010801, -0.013803, 0.002780],
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"profit_abs": [0.000003, 0.000011, -0.000014, 0.000003],
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"open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
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Arrow(2017, 11, 14, 21, 36, 00).datetime,
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Arrow(2017, 11, 14, 22, 12, 00).datetime,
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Arrow(2017, 11, 14, 22, 44, 00).datetime],
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"close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
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Arrow(2017, 11, 14, 22, 10, 00).datetime,
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Arrow(2017, 11, 14, 22, 43, 00).datetime,
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Arrow(2017, 11, 14, 22, 58, 00).datetime],
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"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
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"close_rate": [0.002546, 0.003014, 0.0032903, 0.003217],
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"trade_duration": [123, 34, 31, 14],
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"open_at_end": [False, False, False, True],
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"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
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SellType.ROI, SellType.FORCE_SELL]
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})}
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results = {'DefStrat': pd.DataFrame(
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{"pair": ["UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC"],
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"profit_percent": [0.003312, 0.010801, -0.013803, 0.002780],
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"profit_abs": [0.000003, 0.000011, -0.000014, 0.000003],
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"open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
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Arrow(2017, 11, 14, 21, 36, 00).datetime,
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Arrow(2017, 11, 14, 22, 12, 00).datetime,
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Arrow(2017, 11, 14, 22, 44, 00).datetime],
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"close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
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Arrow(2017, 11, 14, 22, 10, 00).datetime,
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Arrow(2017, 11, 14, 22, 43, 00).datetime,
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Arrow(2017, 11, 14, 22, 58, 00).datetime],
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"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
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"close_rate": [0.002546, 0.003014, 0.0032903, 0.003217],
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"trade_duration": [123, 34, 31, 14],
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"open_at_end": [False, False, False, True],
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"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
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SellType.ROI, SellType.FORCE_SELL]
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})}
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assert strat_stats['max_drawdown'] == 0.0
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assert strat_stats['drawdown_start'] == Arrow.fromtimestamp(0).datetime
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@ -122,7 +122,7 @@ def test_generate_backtest_stats(default_conf, testdatadir):
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# Test storing stats
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filename = Path(testdatadir / 'btresult.json')
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filename_last = Path(testdatadir / '.last_result.json')
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filename_last = Path(testdatadir / LAST_BT_RESULT_FN)
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_backup_file(filename_last, copy_file=True)
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assert not filename.is_file()
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