# pragma pylint: disable=missing-docstring,W0212,C0103
from datetime import datetime
from pathlib import Path
from unittest.mock import ANY, MagicMock

import pandas as pd
import pytest
from arrow import Arrow
from filelock import Timeout

from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_hyperopt
from freqtrade.data.history import load_data
from freqtrade.enums import RunMode, SellType
from freqtrade.exceptions import OperationalException
from freqtrade.optimize.hyperopt import Hyperopt
from freqtrade.optimize.hyperopt_auto import HyperOptAuto
from freqtrade.optimize.hyperopt_tools import HyperoptTools
from freqtrade.optimize.optimize_reports import generate_strategy_stats
from freqtrade.optimize.space import SKDecimal
from freqtrade.strategy.hyper import IntParameter
from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
                            patched_configuration_load_config_file)


def test_setup_hyperopt_configuration_without_arguments(mocker, default_conf, caplog) -> None:
    patched_configuration_load_config_file(mocker, default_conf)

    args = [
        'hyperopt',
        '--config', 'config.json',
        '--strategy', 'HyperoptableStrategy',
    ]

    config = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
    assert 'max_open_trades' in config
    assert 'stake_currency' in config
    assert 'stake_amount' in config
    assert 'exchange' in config
    assert 'pair_whitelist' in config['exchange']
    assert 'datadir' in config
    assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
    assert 'timeframe' in config
    assert not log_has_re('Parameter -i/--ticker-interval detected .*', caplog)

    assert 'position_stacking' not in config
    assert not log_has('Parameter --enable-position-stacking detected ...', caplog)

    assert 'timerange' not in config
    assert 'runmode' in config
    assert config['runmode'] == RunMode.HYPEROPT


def test_setup_hyperopt_configuration_with_arguments(mocker, default_conf, caplog) -> None:
    patched_configuration_load_config_file(mocker, default_conf)
    mocker.patch(
        'freqtrade.configuration.configuration.create_datadir',
        lambda c, x: x
    )

    args = [
        'hyperopt',
        '--config', 'config.json',
        '--strategy', 'HyperoptableStrategy',
        '--datadir', '/foo/bar',
        '--timeframe', '1m',
        '--timerange', ':100',
        '--enable-position-stacking',
        '--disable-max-market-positions',
        '--epochs', '1000',
        '--spaces', 'default',
        '--print-all'
    ]

    config = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
    assert 'max_open_trades' in config
    assert 'stake_currency' in config
    assert 'stake_amount' in config
    assert 'exchange' in config
    assert 'pair_whitelist' in config['exchange']
    assert 'datadir' in config
    assert config['runmode'] == RunMode.HYPEROPT

    assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
    assert 'timeframe' in config
    assert log_has('Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
                   caplog)

    assert 'position_stacking' in config
    assert log_has('Parameter --enable-position-stacking detected ...', caplog)

    assert 'use_max_market_positions' in config
    assert log_has('Parameter --disable-max-market-positions detected ...', caplog)
    assert log_has('max_open_trades set to unlimited ...', caplog)

    assert 'timerange' in config
    assert log_has('Parameter --timerange detected: {} ...'.format(config['timerange']), caplog)

    assert 'epochs' in config
    assert log_has('Parameter --epochs detected ... Will run Hyperopt with for 1000 epochs ...',
                   caplog)

    assert 'spaces' in config
    assert log_has('Parameter -s/--spaces detected: {}'.format(config['spaces']), caplog)
    assert 'print_all' in config
    assert log_has('Parameter --print-all detected ...', caplog)


def test_setup_hyperopt_configuration_stake_amount(mocker, default_conf) -> None:

    patched_configuration_load_config_file(mocker, default_conf)

    args = [
        'hyperopt',
        '--config', 'config.json',
        '--strategy', 'HyperoptableStrategy',
        '--stake-amount', '1',
        '--starting-balance', '2'
    ]
    conf = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
    assert isinstance(conf, dict)

    args = [
        'hyperopt',
        '--config', 'config.json',
        '--strategy', 'StrategyTestV2',
        '--stake-amount', '1',
        '--starting-balance', '0.5'
    ]
    with pytest.raises(OperationalException, match=r"Starting balance .* smaller .*"):
        setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)


def test_start_not_installed(mocker, default_conf, import_fails) -> None:
    start_mock = MagicMock()
    patched_configuration_load_config_file(mocker, default_conf)

    mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
    patch_exchange(mocker)

    args = [
        'hyperopt',
        '--config', 'config.json',
        '--strategy', 'HyperoptableStrategy',
        '--epochs', '5',
        '--hyperopt-loss', 'SharpeHyperOptLossDaily',
    ]
    pargs = get_args(args)

    with pytest.raises(OperationalException, match=r"Please ensure that the hyperopt dependencies"):
        start_hyperopt(pargs)


def test_start_no_hyperopt_allowed(mocker, hyperopt_conf, caplog) -> None:
    start_mock = MagicMock()
    patched_configuration_load_config_file(mocker, hyperopt_conf)
    mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
    patch_exchange(mocker)

    args = [
        'hyperopt',
        '--config', 'config.json',
        '--hyperopt', 'HyperoptTestSepFile',
        '--hyperopt-loss', 'SharpeHyperOptLossDaily',
        '--epochs', '5'
    ]
    pargs = get_args(args)
    with pytest.raises(OperationalException, match=r"Using separate Hyperopt files has been.*"):
        start_hyperopt(pargs)


def test_start_no_data(mocker, hyperopt_conf) -> None:
    patched_configuration_load_config_file(mocker, hyperopt_conf)
    mocker.patch('freqtrade.data.history.load_pair_history', MagicMock(return_value=pd.DataFrame))
    mocker.patch(
        'freqtrade.optimize.hyperopt.get_timerange',
        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
    )

    patch_exchange(mocker)
    # TODO: migrate to strategy-based hyperopt
    args = [
        'hyperopt',
        '--config', 'config.json',
        '--strategy', 'HyperoptableStrategy',
        '--hyperopt-loss', 'SharpeHyperOptLossDaily',
        '--epochs', '5'
    ]
    pargs = get_args(args)
    with pytest.raises(OperationalException, match='No data found. Terminating.'):
        start_hyperopt(pargs)


def test_start_filelock(mocker, hyperopt_conf, caplog) -> None:
    hyperopt_mock = MagicMock(side_effect=Timeout(Hyperopt.get_lock_filename(hyperopt_conf)))
    patched_configuration_load_config_file(mocker, hyperopt_conf)
    mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.__init__', hyperopt_mock)
    patch_exchange(mocker)

    args = [
        'hyperopt',
        '--config', 'config.json',
        '--strategy', 'HyperoptableStrategy',
        '--hyperopt-loss', 'SharpeHyperOptLossDaily',
        '--epochs', '5'
    ]
    pargs = get_args(args)
    start_hyperopt(pargs)
    assert log_has("Another running instance of freqtrade Hyperopt detected.", caplog)


def test_log_results_if_loss_improves(hyperopt, capsys) -> None:
    hyperopt.current_best_loss = 2
    hyperopt.total_epochs = 2

    hyperopt.print_results(
        {
            'loss': 1,
            'results_metrics':
                {
                    'trade_count': 1,
                    'avg_profit': 0.1,
                    'total_profit': 0.001,
                    'profit': 1.0,
                    'duration': 20.0
                },
            'total_profit': 0,
            'current_epoch': 2,  # This starts from 1 (in a human-friendly manner)
            'is_initial_point': False,
            'is_best': True
        }
    )
    out, err = capsys.readouterr()
    assert all(x in out
               for x in ["Best", "2/2", " 1", "0.10%", "0.00100000 BTC    (1.00%)", "20.0 m"])


def test_no_log_if_loss_does_not_improve(hyperopt, caplog) -> None:
    hyperopt.current_best_loss = 2
    hyperopt.print_results(
        {
            'is_best': False,
            'loss': 3,
            'current_epoch': 1,
        }
    )
    assert caplog.record_tuples == []


def test_roi_table_generation(hyperopt) -> None:
    params = {
        'roi_t1': 5,
        'roi_t2': 10,
        'roi_t3': 15,
        'roi_p1': 1,
        'roi_p2': 2,
        'roi_p3': 3,
    }

    assert hyperopt.custom_hyperopt.generate_roi_table(params) == {0: 6, 15: 3, 25: 1, 30: 0}


def test_params_no_optimize_details(hyperopt) -> None:
    hyperopt.config['spaces'] = ['buy']
    res = hyperopt._get_no_optimize_details()
    assert isinstance(res, dict)
    assert "trailing" in res
    assert res["trailing"]['trailing_stop'] is False
    assert "roi" in res
    assert res['roi']['0'] == 0.04
    assert "stoploss" in res
    assert res['stoploss']['stoploss'] == -0.1


def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
    dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
    dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')

    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
                 MagicMock(return_value=(MagicMock(), None)))
    mocker.patch(
        'freqtrade.optimize.hyperopt.get_timerange',
        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
    )

    parallel = mocker.patch(
        'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
        MagicMock(return_value=[{
            'loss': 1, 'results_explanation': 'foo result',
            'params': {'buy': {}, 'sell': {}, 'roi': {}, 'stoploss': 0.0},
            'results_metrics':
            {
                'trade_count': 1,
                'avg_profit': 0.1,
                'total_profit': 0.001,
                'profit': 1.0,
                'duration': 20.0
            },
        }])
    )
    patch_exchange(mocker)
    # Co-test loading timeframe from strategy
    del hyperopt_conf['timeframe']

    hyperopt = Hyperopt(hyperopt_conf)
    hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})

    hyperopt.start()

    parallel.assert_called_once()

    out, err = capsys.readouterr()
    assert 'Best result:\n\n*    1/1: foo result Objective: 1.00000\n' in out
    # Should be called for historical candle data
    assert dumper.call_count == 1
    assert dumper2.call_count == 1
    assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
    assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
    assert hasattr(hyperopt, "max_open_trades")
    assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
    assert hasattr(hyperopt, "position_stacking")


def test_hyperopt_format_results(hyperopt):

    bt_result = {
        'results': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
                                          "UNITTEST/BTC", "UNITTEST/BTC"],
                                 "profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780],
                                 "profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
                                 "open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
                                               Arrow(2017, 11, 14, 21, 36, 00).datetime,
                                               Arrow(2017, 11, 14, 22, 12, 00).datetime,
                                               Arrow(2017, 11, 14, 22, 44, 00).datetime],
                                 "close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
                                                Arrow(2017, 11, 14, 22, 10, 00).datetime,
                                                Arrow(2017, 11, 14, 22, 43, 00).datetime,
                                                Arrow(2017, 11, 14, 22, 58, 00).datetime],
                                 "open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
                                 "close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
                                 "trade_duration": [123, 34, 31, 14],
                                 "is_open": [False, False, False, True],
                                 "stake_amount": [0.01, 0.01, 0.01, 0.01],
                                 "sell_reason": [SellType.ROI, SellType.STOP_LOSS,
                                                 SellType.ROI, SellType.FORCE_SELL]
                                 }),
        'config': hyperopt.config,
        'locks': [],
        'final_balance': 0.02,
        'rejected_signals': 2,
        'backtest_start_time': 1619718665,
        'backtest_end_time': 1619718665,
    }
    results_metrics = generate_strategy_stats({'XRP/BTC': None}, '', bt_result,
                                              Arrow(2017, 11, 14, 19, 32, 00),
                                              Arrow(2017, 12, 14, 19, 32, 00), market_change=0)

    results_explanation = HyperoptTools.format_results_explanation_string(results_metrics, 'BTC')
    total_profit = results_metrics['profit_total_abs']

    results = {
        'loss': 0.0,
        'params_dict': None,
        'params_details': None,
        'results_metrics': results_metrics,
        'results_explanation': results_explanation,
        'total_profit': total_profit,
        'current_epoch': 1,
        'is_initial_point': True,
    }

    result = HyperoptTools._format_explanation_string(results, 1)
    assert ' 0.71%' in result
    assert 'Total profit  0.00003100 BTC' in result
    assert '0:50:00 min' in result


def test_populate_indicators(hyperopt, testdatadir) -> None:
    data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], fill_up_missing=True)
    dataframes = hyperopt.backtesting.strategy.advise_all_indicators(data)
    dataframe = dataframes['UNITTEST/BTC']

    # Check if some indicators are generated. We will not test all of them
    assert 'adx' in dataframe
    assert 'macd' in dataframe
    assert 'rsi' in dataframe


def test_generate_optimizer(mocker, hyperopt_conf) -> None:
    hyperopt_conf.update({'spaces': 'all',
                          'hyperopt_min_trades': 1,
                          })

    backtest_result = {
        'results': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
                                          "UNITTEST/BTC", "UNITTEST/BTC"],
                                 "profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780],
                                 "profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
                                 "open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
                                               Arrow(2017, 11, 14, 21, 36, 00).datetime,
                                               Arrow(2017, 11, 14, 22, 12, 00).datetime,
                                               Arrow(2017, 11, 14, 22, 44, 00).datetime],
                                 "close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
                                                Arrow(2017, 11, 14, 22, 10, 00).datetime,
                                                Arrow(2017, 11, 14, 22, 43, 00).datetime,
                                                Arrow(2017, 11, 14, 22, 58, 00).datetime],
                                 "open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
                                 "close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
                                 "trade_duration": [123, 34, 31, 14],
                                 "is_open": [False, False, False, True],
                                 "stake_amount": [0.01, 0.01, 0.01, 0.01],
                                 "sell_reason": [SellType.ROI, SellType.STOP_LOSS,
                                                 SellType.ROI, SellType.FORCE_SELL]
                                 }),
        'config': hyperopt_conf,
        'locks': [],
        'rejected_signals': 20,
        'final_balance': 1000,
    }

    mocker.patch('freqtrade.optimize.hyperopt.Backtesting.backtest', return_value=backtest_result)
    mocker.patch('freqtrade.optimize.hyperopt.get_timerange',
                 return_value=(Arrow(2017, 12, 10), Arrow(2017, 12, 13)))
    patch_exchange(mocker)
    mocker.patch.object(Path, 'open')
    mocker.patch('freqtrade.optimize.hyperopt.load', return_value={'XRP/BTC': None})

    optimizer_param = {
        'buy_plusdi': 0.02,
        'buy_rsi': 35,
        'sell_minusdi': 0.02,
        'sell_rsi': 75,
        'protection_cooldown_lookback': 20,
        'protection_enabled': True,
        'roi_t1': 60.0,
        'roi_t2': 30.0,
        'roi_t3': 20.0,
        'roi_p1': 0.01,
        'roi_p2': 0.01,
        'roi_p3': 0.1,
        'stoploss': -0.4,
        'trailing_stop': True,
        'trailing_stop_positive': 0.02,
        'trailing_stop_positive_offset_p1': 0.05,
        'trailing_only_offset_is_reached': False,
    }
    response_expected = {
        'loss': 1.9147239021396234,
        'results_explanation': ('     4 trades. 4/0/0 Wins/Draws/Losses. '
                                'Avg profit   0.77%. Median profit   0.71%. Total profit  '
                                '0.00003100 BTC (   0.00%). '
                                'Avg duration 0:50:00 min.'
                                ),
        'params_details': {'buy': {'buy_plusdi': 0.02,
                                   'buy_rsi': 35,
                                   },
                           'roi': {"0": 0.12000000000000001,
                                   "20.0": 0.02,
                                   "50.0": 0.01,
                                   "110.0": 0},
                           'protection': {'protection_cooldown_lookback': 20,
                                          'protection_enabled': True,
                                          },
                           'sell': {'sell_minusdi': 0.02,
                                    'sell_rsi': 75,
                                    },
                           'stoploss': {'stoploss': -0.4},
                           'trailing': {'trailing_only_offset_is_reached': False,
                                        'trailing_stop': True,
                                        'trailing_stop_positive': 0.02,
                                        'trailing_stop_positive_offset': 0.07}},
        'params_dict': optimizer_param,
        'params_not_optimized': {'buy': {}, 'protection': {}, 'sell': {}},
        'results_metrics': ANY,
        'total_profit': 3.1e-08
    }

    hyperopt = Hyperopt(hyperopt_conf)
    hyperopt.min_date = Arrow(2017, 12, 10)
    hyperopt.max_date = Arrow(2017, 12, 13)
    hyperopt.init_spaces()
    hyperopt.dimensions = hyperopt.dimensions
    generate_optimizer_value = hyperopt.generate_optimizer(list(optimizer_param.values()))
    assert generate_optimizer_value == response_expected


def test_clean_hyperopt(mocker, hyperopt_conf, caplog):
    patch_exchange(mocker)

    mocker.patch("freqtrade.strategy.hyper.HyperStrategyMixin.load_params_from_file",
                 MagicMock(return_value={}))
    mocker.patch("freqtrade.optimize.hyperopt.Path.is_file", MagicMock(return_value=True))
    unlinkmock = mocker.patch("freqtrade.optimize.hyperopt.Path.unlink", MagicMock())
    h = Hyperopt(hyperopt_conf)

    assert unlinkmock.call_count == 2
    assert log_has(f"Removing `{h.data_pickle_file}`.", caplog)


def test_print_json_spaces_all(mocker, hyperopt_conf, capsys) -> None:
    dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
    dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')

    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
                 MagicMock(return_value=(MagicMock(), None)))
    mocker.patch(
        'freqtrade.optimize.hyperopt.get_timerange',
        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
    )

    parallel = mocker.patch(
        'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
        MagicMock(return_value=[{
            'loss': 1, 'results_explanation': 'foo result', 'params': {},
            'params_details': {
                'buy': {'mfi-value': None},
                'sell': {'sell-mfi-value': None},
                'roi': {}, 'stoploss': {'stoploss': None},
                'trailing': {'trailing_stop': None}
            },
            'results_metrics':
            {
                'trade_count': 1,
                'avg_profit': 0.1,
                'total_profit': 0.001,
                'profit': 1.0,
                'duration': 20.0
            }
        }])
    )
    patch_exchange(mocker)

    hyperopt_conf.update({'spaces': 'all',
                          'hyperopt_jobs': 1,
                          'print_json': True,
                          })

    hyperopt = Hyperopt(hyperopt_conf)
    hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})

    hyperopt.start()

    parallel.assert_called_once()

    out, err = capsys.readouterr()
    result_str = (
        '{"params":{"mfi-value":null,"sell-mfi-value":null},"minimal_roi"'
        ':{},"stoploss":null,"trailing_stop":null}'
    )
    assert result_str in out  # noqa: E501
    # Should be called for historical candle data
    assert dumper.call_count == 1
    assert dumper2.call_count == 1


def test_print_json_spaces_default(mocker, hyperopt_conf, capsys) -> None:
    dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
    dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
                 MagicMock(return_value=(MagicMock(), None)))
    mocker.patch(
        'freqtrade.optimize.hyperopt.get_timerange',
        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
    )

    parallel = mocker.patch(
        'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
        MagicMock(return_value=[{
            'loss': 1, 'results_explanation': 'foo result', 'params': {},
            'params_details': {
                'buy': {'mfi-value': None},
                'sell': {'sell-mfi-value': None},
                'roi': {}, 'stoploss': {'stoploss': None}
            },
            'results_metrics':
            {
                'trade_count': 1,
                'avg_profit': 0.1,
                'total_profit': 0.001,
                'profit': 1.0,
                'duration': 20.0
            }
        }])
    )
    patch_exchange(mocker)

    hyperopt_conf.update({'print_json': True})

    hyperopt = Hyperopt(hyperopt_conf)
    hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})

    hyperopt.start()

    parallel.assert_called_once()

    out, err = capsys.readouterr()
    assert '{"params":{"mfi-value":null,"sell-mfi-value":null},"minimal_roi":{},"stoploss":null}' in out  # noqa: E501
    # Should be called for historical candle data
    assert dumper.call_count == 1
    assert dumper2.call_count == 1


def test_print_json_spaces_roi_stoploss(mocker, hyperopt_conf, capsys) -> None:
    dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
    dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
                 MagicMock(return_value=(MagicMock(), None)))
    mocker.patch(
        'freqtrade.optimize.hyperopt.get_timerange',
        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
    )

    parallel = mocker.patch(
        'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
        MagicMock(return_value=[{
            'loss': 1, 'results_explanation': 'foo result', 'params': {},
            'params_details': {'roi': {}, 'stoploss': {'stoploss': None}},
            'results_metrics':
            {
                'trade_count': 1,
                'avg_profit': 0.1,
                'total_profit': 0.001,
                'profit': 1.0,
                'duration': 20.0
            }
        }])
    )
    patch_exchange(mocker)

    hyperopt_conf.update({'spaces': 'roi stoploss',
                          'hyperopt_jobs': 1,
                          'print_json': True,
                          })

    hyperopt = Hyperopt(hyperopt_conf)
    hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})

    hyperopt.start()

    parallel.assert_called_once()

    out, err = capsys.readouterr()
    assert '{"minimal_roi":{},"stoploss":null}' in out

    assert dumper.call_count == 1
    assert dumper2.call_count == 1


def test_simplified_interface_roi_stoploss(mocker, hyperopt_conf, capsys) -> None:
    dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
    dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
                 MagicMock(return_value=(MagicMock(), None)))
    mocker.patch(
        'freqtrade.optimize.hyperopt.get_timerange',
        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
    )

    parallel = mocker.patch(
        'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
        MagicMock(return_value=[{
            'loss': 1, 'results_explanation': 'foo result', 'params': {'stoploss': 0.0},
            'results_metrics':
            {
                'trade_count': 1,
                'avg_profit': 0.1,
                'total_profit': 0.001,
                'profit': 1.0,
                'duration': 20.0
            }
        }])
    )
    patch_exchange(mocker)

    hyperopt_conf.update({'spaces': 'roi stoploss'})

    hyperopt = Hyperopt(hyperopt_conf)
    hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})

    hyperopt.start()

    parallel.assert_called_once()

    out, err = capsys.readouterr()
    assert 'Best result:\n\n*    1/1: foo result Objective: 1.00000\n' in out
    assert dumper.call_count == 1
    assert dumper2.call_count == 1

    assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
    assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
    assert hasattr(hyperopt, "max_open_trades")
    assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
    assert hasattr(hyperopt, "position_stacking")


def test_simplified_interface_all_failed(mocker, hyperopt_conf) -> None:
    mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
                 MagicMock(return_value=(MagicMock(), None)))
    mocker.patch(
        'freqtrade.optimize.hyperopt.get_timerange',
        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
    )

    patch_exchange(mocker)

    hyperopt_conf.update({'spaces': 'all', })

    mocker.patch('freqtrade.optimize.hyperopt_auto.HyperOptAuto._generate_indicator_space',
                 return_value=[])

    hyperopt = Hyperopt(hyperopt_conf)
    hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})

    with pytest.raises(OperationalException, match=r"The 'protection' space is included into *"):
        hyperopt.start()


def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None:
    dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
    dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
                 MagicMock(return_value=(MagicMock(), None)))
    mocker.patch(
        'freqtrade.optimize.hyperopt.get_timerange',
        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
    )

    parallel = mocker.patch(
        'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
        MagicMock(return_value=[{
            'loss': 1, 'results_explanation': 'foo result', 'params': {},
            'results_metrics':
            {
                'trade_count': 1,
                'avg_profit': 0.1,
                'total_profit': 0.001,
                'profit': 1.0,
                'duration': 20.0
            }
        }])
    )
    patch_exchange(mocker)

    hyperopt_conf.update({'spaces': 'buy'})

    hyperopt = Hyperopt(hyperopt_conf)
    hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})

    hyperopt.start()

    parallel.assert_called_once()

    out, err = capsys.readouterr()
    assert 'Best result:\n\n*    1/1: foo result Objective: 1.00000\n' in out
    assert dumper.called
    assert dumper.call_count == 1
    assert dumper2.call_count == 1
    assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
    assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
    assert hasattr(hyperopt, "max_open_trades")
    assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
    assert hasattr(hyperopt, "position_stacking")


def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None:
    dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
    dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
                 MagicMock(return_value=(MagicMock(), None)))
    mocker.patch(
        'freqtrade.optimize.hyperopt.get_timerange',
        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
    )

    parallel = mocker.patch(
        'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
        MagicMock(return_value=[{
            'loss': 1, 'results_explanation': 'foo result', 'params': {},
            'results_metrics':
            {
                'trade_count': 1,
                'avg_profit': 0.1,
                'total_profit': 0.001,
                'profit': 1.0,
                'duration': 20.0
            }
        }])
    )
    patch_exchange(mocker)

    hyperopt_conf.update({'spaces': 'sell', })

    hyperopt = Hyperopt(hyperopt_conf)
    hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})

    hyperopt.start()

    parallel.assert_called_once()

    out, err = capsys.readouterr()
    assert 'Best result:\n\n*    1/1: foo result Objective: 1.00000\n' in out
    assert dumper.called
    assert dumper.call_count == 1
    assert dumper2.call_count == 1
    assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
    assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
    assert hasattr(hyperopt, "max_open_trades")
    assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
    assert hasattr(hyperopt, "position_stacking")


@pytest.mark.parametrize("space", [
    ('buy'),
    ('sell'),
    ('protection'),
])
def test_simplified_interface_failed(mocker, hyperopt_conf, space) -> None:
    mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
                 MagicMock(return_value=(MagicMock(), None)))
    mocker.patch(
        'freqtrade.optimize.hyperopt.get_timerange',
        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
    )
    mocker.patch('freqtrade.optimize.hyperopt_auto.HyperOptAuto._generate_indicator_space',
                 return_value=[])

    patch_exchange(mocker)

    hyperopt_conf.update({'spaces': space})

    hyperopt = Hyperopt(hyperopt_conf)
    hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})

    with pytest.raises(OperationalException, match=f"The '{space}' space is included into *"):
        hyperopt.start()


def test_in_strategy_auto_hyperopt(mocker, hyperopt_conf, tmpdir, fee) -> None:
    patch_exchange(mocker)
    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
    (Path(tmpdir) / 'hyperopt_results').mkdir(parents=True)
    # No hyperopt needed
    hyperopt_conf.update({
        'strategy': 'HyperoptableStrategy',
        'user_data_dir': Path(tmpdir),
        'hyperopt_random_state': 42,
        'spaces': ['all']
    })
    hyperopt = Hyperopt(hyperopt_conf)
    assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto)
    assert isinstance(hyperopt.backtesting.strategy.buy_rsi, IntParameter)

    assert hyperopt.backtesting.strategy.buy_rsi.in_space is True
    assert hyperopt.backtesting.strategy.buy_rsi.value == 35
    assert hyperopt.backtesting.strategy.sell_rsi.value == 74
    assert hyperopt.backtesting.strategy.protection_cooldown_lookback.value == 30
    buy_rsi_range = hyperopt.backtesting.strategy.buy_rsi.range
    assert isinstance(buy_rsi_range, range)
    # Range from 0 - 50 (inclusive)
    assert len(list(buy_rsi_range)) == 51

    hyperopt.start()
    # All values should've changed.
    assert hyperopt.backtesting.strategy.protection_cooldown_lookback.value != 30
    assert hyperopt.backtesting.strategy.buy_rsi.value != 35
    assert hyperopt.backtesting.strategy.sell_rsi.value != 74

    hyperopt.custom_hyperopt.generate_estimator = lambda *args, **kwargs: 'ET1'
    with pytest.raises(OperationalException, match="Estimator ET1 not supported."):
        hyperopt.get_optimizer([], 2)


def test_SKDecimal():
    space = SKDecimal(1, 2, decimals=2)
    assert 1.5 in space
    assert 2.5 not in space
    assert space.low == 100
    assert space.high == 200

    assert space.inverse_transform([200]) == [2.0]
    assert space.inverse_transform([100]) == [1.0]
    assert space.inverse_transform([150, 160]) == [1.5, 1.6]

    assert space.transform([1.5]) == [150]
    assert space.transform([2.0]) == [200]
    assert space.transform([1.0]) == [100]
    assert space.transform([1.5, 1.6]) == [150, 160]
