Extract tests for backtest_reports to their own test module
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Matthias
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904e1647e1
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10ee23622a
96
tests/optimize/test_backtest_reports.py
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96
tests/optimize/test_backtest_reports.py
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@ -0,0 +1,96 @@
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import pandas as pd
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from freqtrade.optimize.backtest_reports import (
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generate_text_table, generate_text_table_sell_reason,
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generate_text_table_strategy)
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from freqtrade.strategy.interface import SellType
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def test_generate_text_table(default_conf, mocker):
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results = pd.DataFrame(
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{
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'pair': ['ETH/BTC', 'ETH/BTC'],
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'profit_percent': [0.1, 0.2],
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'profit_abs': [0.2, 0.4],
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'trade_duration': [10, 30],
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'profit': [2, 0],
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'loss': [0, 0]
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}
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)
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result_str = (
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'| pair | buy count | avg profit % | cum profit % | '
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'tot profit BTC | tot profit % | avg duration | profit | loss |\n'
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'|:--------|------------:|---------------:|---------------:|'
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'-----------------:|---------------:|:---------------|---------:|-------:|\n'
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'| ETH/BTC | 2 | 15.00 | 30.00 | '
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'0.60000000 | 15.00 | 0:20:00 | 2 | 0 |\n'
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'| TOTAL | 2 | 15.00 | 30.00 | '
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'0.60000000 | 15.00 | 0:20:00 | 2 | 0 |'
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)
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assert generate_text_table(data={'ETH/BTC': {}},
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stake_currency='BTC', max_open_trades=2,
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results=results) == result_str
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def test_generate_text_table_sell_reason(default_conf, mocker):
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results = pd.DataFrame(
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{
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'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
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'profit_percent': [0.1, 0.2, -0.3],
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'profit_abs': [0.2, 0.4, -0.5],
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'trade_duration': [10, 30, 10],
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'profit': [2, 0, 0],
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'loss': [0, 0, 1],
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'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
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}
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)
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result_str = (
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'| Sell Reason | Count | Profit | Loss |\n'
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'|:--------------|--------:|---------:|-------:|\n'
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'| roi | 2 | 2 | 0 |\n'
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'| stop_loss | 1 | 0 | 1 |'
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)
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assert generate_text_table_sell_reason(
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data={'ETH/BTC': {}}, results=results) == result_str
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def test_generate_text_table_strategy(default_conf, mocker):
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results = {}
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results['ETH/BTC'] = pd.DataFrame(
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{
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'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
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'profit_percent': [0.1, 0.2, 0.3],
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'profit_abs': [0.2, 0.4, 0.5],
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'trade_duration': [10, 30, 10],
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'profit': [2, 0, 0],
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'loss': [0, 0, 1],
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'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
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}
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)
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results['LTC/BTC'] = pd.DataFrame(
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{
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'pair': ['LTC/BTC', 'LTC/BTC', 'LTC/BTC'],
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'profit_percent': [0.4, 0.2, 0.3],
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'profit_abs': [0.4, 0.4, 0.5],
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'trade_duration': [15, 30, 15],
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'profit': [4, 1, 0],
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'loss': [0, 0, 1],
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'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
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}
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)
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result_str = (
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'| Strategy | buy count | avg profit % | cum profit % '
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'| tot profit BTC | tot profit % | avg duration | profit | loss |\n'
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'|:-----------|------------:|---------------:|---------------:'
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'|-----------------:|---------------:|:---------------|---------:|-------:|\n'
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'| ETH/BTC | 3 | 20.00 | 60.00 '
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'| 1.10000000 | 30.00 | 0:17:00 | 3 | 0 |\n'
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'| LTC/BTC | 3 | 30.00 | 90.00 '
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'| 1.30000000 | 45.00 | 0:20:00 | 3 | 0 |'
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)
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assert generate_text_table_strategy('BTC', 2, all_results=results) == result_str
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@ -19,9 +19,6 @@ from freqtrade.data.dataprovider import DataProvider
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from freqtrade.data.history import get_timerange
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from freqtrade.exceptions import DependencyException, OperationalException
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from freqtrade.optimize import setup_configuration, start_backtesting
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from freqtrade.optimize.backtest_reports import (
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generate_text_table, generate_text_table_sell_reason,
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generate_text_table_strategy)
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from freqtrade.optimize.backtesting import Backtesting
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from freqtrade.state import RunMode
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from freqtrade.strategy.default_strategy import DefaultStrategy
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@ -361,96 +358,6 @@ def test_tickerdata_to_dataframe_bt(default_conf, mocker, testdatadir) -> None:
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assert data['UNITTEST/BTC'].equals(data2['UNITTEST/BTC'])
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def test_generate_text_table(default_conf, mocker):
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results = pd.DataFrame(
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{
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'pair': ['ETH/BTC', 'ETH/BTC'],
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'profit_percent': [0.1, 0.2],
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'profit_abs': [0.2, 0.4],
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'trade_duration': [10, 30],
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'profit': [2, 0],
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'loss': [0, 0]
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}
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)
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result_str = (
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'| pair | buy count | avg profit % | cum profit % | '
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'tot profit BTC | tot profit % | avg duration | profit | loss |\n'
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'|:--------|------------:|---------------:|---------------:|'
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'-----------------:|---------------:|:---------------|---------:|-------:|\n'
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'| ETH/BTC | 2 | 15.00 | 30.00 | '
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'0.60000000 | 15.00 | 0:20:00 | 2 | 0 |\n'
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'| TOTAL | 2 | 15.00 | 30.00 | '
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'0.60000000 | 15.00 | 0:20:00 | 2 | 0 |'
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)
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assert generate_text_table(data={'ETH/BTC': {}},
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stake_currency='BTC', max_open_trades=2,
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results=results) == result_str
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def test_generate_text_table_sell_reason(default_conf, mocker):
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results = pd.DataFrame(
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{
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'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
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'profit_percent': [0.1, 0.2, -0.3],
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'profit_abs': [0.2, 0.4, -0.5],
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'trade_duration': [10, 30, 10],
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'profit': [2, 0, 0],
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'loss': [0, 0, 1],
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'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
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}
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)
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result_str = (
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'| Sell Reason | Count | Profit | Loss |\n'
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'|:--------------|--------:|---------:|-------:|\n'
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'| roi | 2 | 2 | 0 |\n'
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'| stop_loss | 1 | 0 | 1 |'
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)
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assert generate_text_table_sell_reason(
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data={'ETH/BTC': {}}, results=results) == result_str
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def test_generate_text_table_strategy(default_conf, mocker):
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results = {}
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results['ETH/BTC'] = pd.DataFrame(
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{
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'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
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'profit_percent': [0.1, 0.2, 0.3],
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'profit_abs': [0.2, 0.4, 0.5],
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'trade_duration': [10, 30, 10],
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'profit': [2, 0, 0],
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'loss': [0, 0, 1],
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'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
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}
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)
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results['LTC/BTC'] = pd.DataFrame(
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{
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'pair': ['LTC/BTC', 'LTC/BTC', 'LTC/BTC'],
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'profit_percent': [0.4, 0.2, 0.3],
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'profit_abs': [0.4, 0.4, 0.5],
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'trade_duration': [15, 30, 15],
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'profit': [4, 1, 0],
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'loss': [0, 0, 1],
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'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
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}
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)
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result_str = (
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'| Strategy | buy count | avg profit % | cum profit % '
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'| tot profit BTC | tot profit % | avg duration | profit | loss |\n'
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'|:-----------|------------:|---------------:|---------------:'
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'|-----------------:|---------------:|:---------------|---------:|-------:|\n'
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'| ETH/BTC | 3 | 20.00 | 60.00 '
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'| 1.10000000 | 30.00 | 0:17:00 | 3 | 0 |\n'
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'| LTC/BTC | 3 | 30.00 | 90.00 '
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'| 1.30000000 | 45.00 | 0:20:00 | 3 | 0 |'
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)
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assert generate_text_table_strategy('BTC', 2, all_results=results) == result_str
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def test_backtesting_start(default_conf, mocker, testdatadir, caplog) -> None:
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def get_timerange(input1):
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return Arrow(2017, 11, 14, 21, 17), Arrow(2017, 11, 14, 22, 59)
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