don't copy tickerdata_to_dataframe into backtesting
it's used only once, so this does not make sense and hides the origin of the function
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@@ -89,7 +89,7 @@ def simple_backtest(config, contour, num_results, mocker) -> None:
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backtesting = Backtesting(config)
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data = load_data_test(contour)
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processed = backtesting.tickerdata_to_dataframe(data)
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processed = backtesting.strategy.tickerdata_to_dataframe(data)
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assert isinstance(processed, dict)
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results = backtesting.backtest(
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{
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@@ -125,7 +125,7 @@ def _make_backtest_conf(mocker, conf=None, pair='UNITTEST/BTC', record=None):
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backtesting = Backtesting(conf)
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return {
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'stake_amount': conf['stake_amount'],
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'processed': backtesting.tickerdata_to_dataframe(data),
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'processed': backtesting.strategy.tickerdata_to_dataframe(data),
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'max_open_trades': 10,
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'position_stacking': False,
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'record': record
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@@ -313,7 +313,7 @@ def test_backtesting_init(mocker, default_conf) -> None:
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backtesting = Backtesting(default_conf)
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assert backtesting.config == default_conf
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assert backtesting.ticker_interval == '5m'
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assert callable(backtesting.tickerdata_to_dataframe)
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assert callable(backtesting.strategy.tickerdata_to_dataframe)
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assert callable(backtesting.advise_buy)
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assert callable(backtesting.advise_sell)
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get_fee.assert_called()
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@@ -327,7 +327,7 @@ def test_tickerdata_to_dataframe(default_conf, mocker) -> None:
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tickerlist = {'UNITTEST/BTC': tick}
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backtesting = Backtesting(default_conf)
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data = backtesting.tickerdata_to_dataframe(tickerlist)
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data = backtesting.strategy.tickerdata_to_dataframe(tickerlist)
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assert len(data['UNITTEST/BTC']) == 99
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# Load strategy to compare the result between Backtesting function and strategy are the same
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@@ -340,7 +340,7 @@ def test_get_timeframe(default_conf, mocker) -> None:
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patch_exchange(mocker)
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backtesting = Backtesting(default_conf)
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data = backtesting.tickerdata_to_dataframe(
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data = backtesting.strategy.tickerdata_to_dataframe(
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optimize.load_data(
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None,
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ticker_interval='1m',
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@@ -520,7 +520,7 @@ def test_backtest(default_conf, fee, mocker) -> None:
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pair = 'UNITTEST/BTC'
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data = optimize.load_data(None, ticker_interval='5m', pairs=['UNITTEST/BTC'])
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data = trim_dictlist(data, -200)
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data_processed = backtesting.tickerdata_to_dataframe(data)
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data_processed = backtesting.strategy.tickerdata_to_dataframe(data)
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results = backtesting.backtest(
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{
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'stake_amount': default_conf['stake_amount'],
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@@ -571,7 +571,7 @@ def test_backtest_1min_ticker_interval(default_conf, fee, mocker) -> None:
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results = backtesting.backtest(
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{
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'stake_amount': default_conf['stake_amount'],
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'processed': backtesting.tickerdata_to_dataframe(data),
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'processed': backtesting.strategy.tickerdata_to_dataframe(data),
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'max_open_trades': 1,
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'position_stacking': False
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}
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@@ -585,7 +585,7 @@ def test_processed(default_conf, mocker) -> None:
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backtesting = Backtesting(default_conf)
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dict_of_tickerrows = load_data_test('raise')
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dataframes = backtesting.tickerdata_to_dataframe(dict_of_tickerrows)
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dataframes = backtesting.strategy.tickerdata_to_dataframe(dict_of_tickerrows)
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dataframe = dataframes['UNITTEST/BTC']
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cols = dataframe.columns
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# assert the dataframe got some of the indicator columns
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@@ -194,7 +194,7 @@ def test_start_calls_optimizer(mocker, default_conf, caplog) -> None:
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default_conf.update({'spaces': 'all'})
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hyperopt = Hyperopt(default_conf)
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hyperopt.tickerdata_to_dataframe = MagicMock()
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hyperopt.strategy.tickerdata_to_dataframe = MagicMock()
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hyperopt.start()
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parallel.assert_called_once()
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@@ -242,7 +242,7 @@ def test_has_space(hyperopt):
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def test_populate_indicators(hyperopt) -> None:
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tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m')
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tickerlist = {'UNITTEST/BTC': tick}
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dataframes = hyperopt.tickerdata_to_dataframe(tickerlist)
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dataframes = hyperopt.strategy.tickerdata_to_dataframe(tickerlist)
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dataframe = hyperopt.populate_indicators(dataframes['UNITTEST/BTC'], {'pair': 'UNITTEST/BTC'})
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# Check if some indicators are generated. We will not test all of them
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@@ -254,7 +254,7 @@ def test_populate_indicators(hyperopt) -> None:
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def test_buy_strategy_generator(hyperopt) -> None:
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tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m')
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tickerlist = {'UNITTEST/BTC': tick}
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dataframes = hyperopt.tickerdata_to_dataframe(tickerlist)
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dataframes = hyperopt.strategy.tickerdata_to_dataframe(tickerlist)
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dataframe = hyperopt.populate_indicators(dataframes['UNITTEST/BTC'], {'pair': 'UNITTEST/BTC'})
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populate_buy_trend = hyperopt.buy_strategy_generator(
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