ruff format: update strategy tests

tests/strategy/test_default_strategy.py

@@ -9,22 +9,25 @@ from .strats.strategy_test_v3 import StrategyTestV3
 
 
 def test_strategy_test_v3_structure():
-    assert hasattr(StrategyTestV3, 'minimal_roi')
+    assert hasattr(StrategyTestV3, "minimal_roi")
-    assert hasattr(StrategyTestV3, 'stoploss')
+    assert hasattr(StrategyTestV3, "stoploss")
-    assert hasattr(StrategyTestV3, 'timeframe')
+    assert hasattr(StrategyTestV3, "timeframe")
-    assert hasattr(StrategyTestV3, 'populate_indicators')
+    assert hasattr(StrategyTestV3, "populate_indicators")
-    assert hasattr(StrategyTestV3, 'populate_entry_trend')
+    assert hasattr(StrategyTestV3, "populate_entry_trend")
-    assert hasattr(StrategyTestV3, 'populate_exit_trend')
+    assert hasattr(StrategyTestV3, "populate_exit_trend")
 
 
-@pytest.mark.parametrize('is_short,side', [
+@pytest.mark.parametrize(
-    (True, 'short'),
+    "is_short,side",
-    (False, 'long'),
+    [
-])
+        (True, "short"),
+        (False, "long"),
+    ],
+)
 def test_strategy_test_v3(dataframe_1m, fee, is_short, side):
     strategy = StrategyTestV3({})
 
-    metadata = {'pair': 'ETH/BTC'}
+    metadata = {"pair": "ETH/BTC"}
     assert isinstance(strategy.minimal_roi, dict)
     assert isinstance(strategy.stoploss, float)
     assert isinstance(strategy.timeframe, str)
@@ -34,23 +37,46 @@ def test_strategy_test_v3(dataframe_1m, fee, is_short, side):
     assert isinstance(strategy.populate_sell_trend(indicators, metadata), DataFrame)
 
     trade = Trade(
-        open_rate=19_000,
+        open_rate=19_000, amount=0.1, pair="ETH/BTC", fee_open=fee.return_value, is_short=is_short
-        amount=0.1,
-        pair='ETH/BTC',
-        fee_open=fee.return_value,
-        is_short=is_short
     )
 
-    assert strategy.confirm_trade_entry(pair='ETH/BTC', order_type='limit', amount=0.1,
+    assert (
-                                        rate=20000, time_in_force='gtc',
+        strategy.confirm_trade_entry(
+            pair="ETH/BTC",
+            order_type="limit",
+            amount=0.1,
+            rate=20000,
+            time_in_force="gtc",
             current_time=datetime.now(timezone.utc),
-                                        side=side, entry_tag=None) is True
+            side=side,
-    assert strategy.confirm_trade_exit(pair='ETH/BTC', trade=trade, order_type='limit', amount=0.1,
+            entry_tag=None,
-                                       rate=20000, time_in_force='gtc', exit_reason='roi',
+        )
-                                       sell_reason='roi',
+        is True
+    )
+    assert (
+        strategy.confirm_trade_exit(
+            pair="ETH/BTC",
+            trade=trade,
+            order_type="limit",
+            amount=0.1,
+            rate=20000,
+            time_in_force="gtc",
+            exit_reason="roi",
+            sell_reason="roi",
             current_time=datetime.now(timezone.utc),
-                                       side=side) is True
+            side=side,
+        )
+        is True
+    )
 
-    assert strategy.custom_stoploss(pair='ETH/BTC', trade=trade, current_time=datetime.now(),
+    assert (
-                                    current_rate=20_000, current_profit=0.05, after_fill=False
+        strategy.custom_stoploss(
-                                    ) == strategy.stoploss
+            pair="ETH/BTC",
+            trade=trade,
+            current_time=datetime.now(),
+            current_rate=20_000,
+            current_profit=0.05,
+            after_fill=False,
+        )
+        == strategy.stoploss
+    )

tests/strategy/test_strategy_helpers.py

@@ -10,217 +10,221 @@ from tests.conftest import generate_test_data, get_patched_exchange
 
 
 def test_merge_informative_pair():
-    data = generate_test_data('15m', 40)
+    data = generate_test_data("15m", 40)
-    informative = generate_test_data('1h', 40)
+    informative = generate_test_data("1h", 40)
     cols_inf = list(informative.columns)
 
-    result = merge_informative_pair(data, informative, '15m', '1h', ffill=True)
+    result = merge_informative_pair(data, informative, "15m", "1h", ffill=True)
     assert isinstance(result, pd.DataFrame)
     assert list(informative.columns) == cols_inf
     assert len(result) == len(data)
-    assert 'date' in result.columns
+    assert "date" in result.columns
-    assert result['date'].equals(data['date'])
+    assert result["date"].equals(data["date"])
-    assert 'date_1h' in result.columns
+    assert "date_1h" in result.columns
 
-    assert 'open' in result.columns
+    assert "open" in result.columns
-    assert 'open_1h' in result.columns
+    assert "open_1h" in result.columns
-    assert result['open'].equals(data['open'])
+    assert result["open"].equals(data["open"])
 
-    assert 'close' in result.columns
+    assert "close" in result.columns
-    assert 'close_1h' in result.columns
+    assert "close_1h" in result.columns
-    assert result['close'].equals(data['close'])
+    assert result["close"].equals(data["close"])
 
-    assert 'volume' in result.columns
+    assert "volume" in result.columns
-    assert 'volume_1h' in result.columns
+    assert "volume_1h" in result.columns
-    assert result['volume'].equals(data['volume'])
+    assert result["volume"].equals(data["volume"])
 
     # First 3 rows are empty
-    assert result.iloc[0]['date_1h'] is pd.NaT
+    assert result.iloc[0]["date_1h"] is pd.NaT
-    assert result.iloc[1]['date_1h'] is pd.NaT
+    assert result.iloc[1]["date_1h"] is pd.NaT
-    assert result.iloc[2]['date_1h'] is pd.NaT
+    assert result.iloc[2]["date_1h"] is pd.NaT
     # Next 4 rows contain the starting date (0:00)
-    assert result.iloc[3]['date_1h'] == result.iloc[0]['date']
+    assert result.iloc[3]["date_1h"] == result.iloc[0]["date"]
-    assert result.iloc[4]['date_1h'] == result.iloc[0]['date']
+    assert result.iloc[4]["date_1h"] == result.iloc[0]["date"]
-    assert result.iloc[5]['date_1h'] == result.iloc[0]['date']
+    assert result.iloc[5]["date_1h"] == result.iloc[0]["date"]
-    assert result.iloc[6]['date_1h'] == result.iloc[0]['date']
+    assert result.iloc[6]["date_1h"] == result.iloc[0]["date"]
     # Next 4 rows contain the next Hourly date original date row 4
-    assert result.iloc[7]['date_1h'] == result.iloc[4]['date']
+    assert result.iloc[7]["date_1h"] == result.iloc[4]["date"]
-    assert result.iloc[8]['date_1h'] == result.iloc[4]['date']
+    assert result.iloc[8]["date_1h"] == result.iloc[4]["date"]
 
-    informative = generate_test_data('1h', 40)
+    informative = generate_test_data("1h", 40)
-    result = merge_informative_pair(data, informative, '15m', '1h', ffill=False)
+    result = merge_informative_pair(data, informative, "15m", "1h", ffill=False)
     # First 3 rows are empty
-    assert result.iloc[0]['date_1h'] is pd.NaT
+    assert result.iloc[0]["date_1h"] is pd.NaT
-    assert result.iloc[1]['date_1h'] is pd.NaT
+    assert result.iloc[1]["date_1h"] is pd.NaT
-    assert result.iloc[2]['date_1h'] is pd.NaT
+    assert result.iloc[2]["date_1h"] is pd.NaT
     # Next 4 rows contain the starting date (0:00)
-    assert result.iloc[3]['date_1h'] == result.iloc[0]['date']
+    assert result.iloc[3]["date_1h"] == result.iloc[0]["date"]
-    assert result.iloc[4]['date_1h'] is pd.NaT
+    assert result.iloc[4]["date_1h"] is pd.NaT
-    assert result.iloc[5]['date_1h'] is pd.NaT
+    assert result.iloc[5]["date_1h"] is pd.NaT
-    assert result.iloc[6]['date_1h'] is pd.NaT
+    assert result.iloc[6]["date_1h"] is pd.NaT
     # Next 4 rows contain the next Hourly date original date row 4
-    assert result.iloc[7]['date_1h'] == result.iloc[4]['date']
+    assert result.iloc[7]["date_1h"] == result.iloc[4]["date"]
-    assert result.iloc[8]['date_1h'] is pd.NaT
+    assert result.iloc[8]["date_1h"] is pd.NaT
 
 
 def test_merge_informative_pair_weekly():
     # Covers roughly 2 months - until 2023-01-10
-    data = generate_test_data('1h', 1040, '2022-11-28')
+    data = generate_test_data("1h", 1040, "2022-11-28")
-    informative = generate_test_data('1w', 40, '2022-11-01')
+    informative = generate_test_data("1w", 40, "2022-11-01")
-    informative['day'] = informative['date'].dt.day_name()
+    informative["day"] = informative["date"].dt.day_name()
 
-    result = merge_informative_pair(data, informative, '1h', '1w', ffill=True)
+    result = merge_informative_pair(data, informative, "1h", "1w", ffill=True)
     assert isinstance(result, pd.DataFrame)
     # 2022-12-24 is a Saturday
-    candle1 = result.loc[(result['date'] == '2022-12-24T22:00:00.000Z')]
+    candle1 = result.loc[(result["date"] == "2022-12-24T22:00:00.000Z")]
-    assert candle1.iloc[0]['date'] == pd.Timestamp('2022-12-24T22:00:00.000Z')
+    assert candle1.iloc[0]["date"] == pd.Timestamp("2022-12-24T22:00:00.000Z")
-    assert candle1.iloc[0]['date_1w'] == pd.Timestamp('2022-12-12T00:00:00.000Z')
+    assert candle1.iloc[0]["date_1w"] == pd.Timestamp("2022-12-12T00:00:00.000Z")
 
-    candle2 = result.loc[(result['date'] == '2022-12-24T23:00:00.000Z')]
+    candle2 = result.loc[(result["date"] == "2022-12-24T23:00:00.000Z")]
-    assert candle2.iloc[0]['date'] == pd.Timestamp('2022-12-24T23:00:00.000Z')
+    assert candle2.iloc[0]["date"] == pd.Timestamp("2022-12-24T23:00:00.000Z")
-    assert candle2.iloc[0]['date_1w'] == pd.Timestamp('2022-12-12T00:00:00.000Z')
+    assert candle2.iloc[0]["date_1w"] == pd.Timestamp("2022-12-12T00:00:00.000Z")
 
     # 2022-12-25 is a Sunday
-    candle3 = result.loc[(result['date'] == '2022-12-25T22:00:00.000Z')]
+    candle3 = result.loc[(result["date"] == "2022-12-25T22:00:00.000Z")]
-    assert candle3.iloc[0]['date'] == pd.Timestamp('2022-12-25T22:00:00.000Z')
+    assert candle3.iloc[0]["date"] == pd.Timestamp("2022-12-25T22:00:00.000Z")
     # Still old candle
-    assert candle3.iloc[0]['date_1w'] == pd.Timestamp('2022-12-12T00:00:00.000Z')
+    assert candle3.iloc[0]["date_1w"] == pd.Timestamp("2022-12-12T00:00:00.000Z")
 
-    candle4 = result.loc[(result['date'] == '2022-12-25T23:00:00.000Z')]
+    candle4 = result.loc[(result["date"] == "2022-12-25T23:00:00.000Z")]
-    assert candle4.iloc[0]['date'] == pd.Timestamp('2022-12-25T23:00:00.000Z')
+    assert candle4.iloc[0]["date"] == pd.Timestamp("2022-12-25T23:00:00.000Z")
-    assert candle4.iloc[0]['date_1w'] == pd.Timestamp('2022-12-19T00:00:00.000Z')
+    assert candle4.iloc[0]["date_1w"] == pd.Timestamp("2022-12-19T00:00:00.000Z")
 
 
 def test_merge_informative_pair_monthly():
     # Covers roughly 2 months - until 2023-01-10
-    data = generate_test_data('1h', 1040, '2022-11-28')
+    data = generate_test_data("1h", 1040, "2022-11-28")
-    informative = generate_test_data('1M', 40, '2022-01-01')
+    informative = generate_test_data("1M", 40, "2022-01-01")
 
-    result = merge_informative_pair(data, informative, '1h', '1M', ffill=True)
+    result = merge_informative_pair(data, informative, "1h", "1M", ffill=True)
     assert isinstance(result, pd.DataFrame)
-    candle1 = result.loc[(result['date'] == '2022-12-31T22:00:00.000Z')]
+    candle1 = result.loc[(result["date"] == "2022-12-31T22:00:00.000Z")]
-    assert candle1.iloc[0]['date'] == pd.Timestamp('2022-12-31T22:00:00.000Z')
+    assert candle1.iloc[0]["date"] == pd.Timestamp("2022-12-31T22:00:00.000Z")
-    assert candle1.iloc[0]['date_1M'] == pd.Timestamp('2022-11-01T00:00:00.000Z')
+    assert candle1.iloc[0]["date_1M"] == pd.Timestamp("2022-11-01T00:00:00.000Z")
 
-    candle2 = result.loc[(result['date'] == '2022-12-31T23:00:00.000Z')]
+    candle2 = result.loc[(result["date"] == "2022-12-31T23:00:00.000Z")]
-    assert candle2.iloc[0]['date'] == pd.Timestamp('2022-12-31T23:00:00.000Z')
+    assert candle2.iloc[0]["date"] == pd.Timestamp("2022-12-31T23:00:00.000Z")
-    assert candle2.iloc[0]['date_1M'] == pd.Timestamp('2022-12-01T00:00:00.000Z')
+    assert candle2.iloc[0]["date_1M"] == pd.Timestamp("2022-12-01T00:00:00.000Z")
 
     # Candle is empty, as the start-date did fail.
-    candle3 = result.loc[(result['date'] == '2022-11-30T22:00:00.000Z')]
+    candle3 = result.loc[(result["date"] == "2022-11-30T22:00:00.000Z")]
-    assert candle3.iloc[0]['date'] == pd.Timestamp('2022-11-30T22:00:00.000Z')
+    assert candle3.iloc[0]["date"] == pd.Timestamp("2022-11-30T22:00:00.000Z")
-    assert candle3.iloc[0]['date_1M'] is pd.NaT
+    assert candle3.iloc[0]["date_1M"] is pd.NaT
 
     # First candle with 1M data merged.
-    candle4 = result.loc[(result['date'] == '2022-11-30T23:00:00.000Z')]
+    candle4 = result.loc[(result["date"] == "2022-11-30T23:00:00.000Z")]
-    assert candle4.iloc[0]['date'] == pd.Timestamp('2022-11-30T23:00:00.000Z')
+    assert candle4.iloc[0]["date"] == pd.Timestamp("2022-11-30T23:00:00.000Z")
-    assert candle4.iloc[0]['date_1M'] == pd.Timestamp('2022-11-01T00:00:00.000Z')
+    assert candle4.iloc[0]["date_1M"] == pd.Timestamp("2022-11-01T00:00:00.000Z")
 
 
 def test_merge_informative_pair_same():
-    data = generate_test_data('15m', 40)
+    data = generate_test_data("15m", 40)
-    informative = generate_test_data('15m', 40)
+    informative = generate_test_data("15m", 40)
 
-    result = merge_informative_pair(data, informative, '15m', '15m', ffill=True)
+    result = merge_informative_pair(data, informative, "15m", "15m", ffill=True)
     assert isinstance(result, pd.DataFrame)
     assert len(result) == len(data)
-    assert 'date' in result.columns
+    assert "date" in result.columns
-    assert result['date'].equals(data['date'])
+    assert result["date"].equals(data["date"])
-    assert 'date_15m' in result.columns
+    assert "date_15m" in result.columns
 
-    assert 'open' in result.columns
+    assert "open" in result.columns
-    assert 'open_15m' in result.columns
+    assert "open_15m" in result.columns
-    assert result['open'].equals(data['open'])
+    assert result["open"].equals(data["open"])
 
-    assert 'close' in result.columns
+    assert "close" in result.columns
-    assert 'close_15m' in result.columns
+    assert "close_15m" in result.columns
-    assert result['close'].equals(data['close'])
+    assert result["close"].equals(data["close"])
 
-    assert 'volume' in result.columns
+    assert "volume" in result.columns
-    assert 'volume_15m' in result.columns
+    assert "volume_15m" in result.columns
-    assert result['volume'].equals(data['volume'])
+    assert result["volume"].equals(data["volume"])
 
     # Dates match 1:1
-    assert result['date_15m'].equals(result['date'])
+    assert result["date_15m"].equals(result["date"])
 
 
 def test_merge_informative_pair_lower():
-    data = generate_test_data('1h', 40)
+    data = generate_test_data("1h", 40)
-    informative = generate_test_data('15m', 40)
+    informative = generate_test_data("15m", 40)
 
     with pytest.raises(ValueError, match=r"Tried to merge a faster timeframe .*"):
-        merge_informative_pair(data, informative, '1h', '15m', ffill=True)
+        merge_informative_pair(data, informative, "1h", "15m", ffill=True)
 
 
 def test_merge_informative_pair_empty():
-    data = generate_test_data('1h', 40)
+    data = generate_test_data("1h", 40)
     informative = pd.DataFrame(columns=data.columns)
 
-    result = merge_informative_pair(data, informative, '1h', '2h', ffill=True)
+    result = merge_informative_pair(data, informative, "1h", "2h", ffill=True)
-    assert result['date'].equals(data['date'])
+    assert result["date"].equals(data["date"])
 
     assert list(result.columns) == [
-        'date',
+        "date",
-        'open',
+        "open",
-        'high',
+        "high",
-        'low',
+        "low",
-        'close',
+        "close",
-        'volume',
+        "volume",
-        'date_2h',
+        "date_2h",
-        'open_2h',
+        "open_2h",
-        'high_2h',
+        "high_2h",
-        'low_2h',
+        "low_2h",
-        'close_2h',
+        "close_2h",
-        'volume_2h'
+        "volume_2h",
     ]
     # We merge an empty dataframe, so all values should be NaN
-    for col in ['date_2h', 'open_2h', 'high_2h', 'low_2h', 'close_2h', 'volume_2h']:
+    for col in ["date_2h", "open_2h", "high_2h", "low_2h", "close_2h", "volume_2h"]:
         assert result[col].isnull().all()
 
 
 def test_merge_informative_pair_suffix():
-    data = generate_test_data('15m', 20)
+    data = generate_test_data("15m", 20)
-    informative = generate_test_data('1h', 20)
+    informative = generate_test_data("1h", 20)
 
-    result = merge_informative_pair(data, informative, '15m', '1h',
+    result = merge_informative_pair(
-                                    append_timeframe=False, suffix="suf")
+        data, informative, "15m", "1h", append_timeframe=False, suffix="suf"
+    )
 
-    assert 'date' in result.columns
+    assert "date" in result.columns
-    assert result['date'].equals(data['date'])
+    assert result["date"].equals(data["date"])
-    assert 'date_suf' in result.columns
+    assert "date_suf" in result.columns
 
-    assert 'open_suf' in result.columns
+    assert "open_suf" in result.columns
-    assert 'open_1h' not in result.columns
+    assert "open_1h" not in result.columns
 
     assert list(result.columns) == [
-        'date',
+        "date",
-        'open',
+        "open",
-        'high',
+        "high",
-        'low',
+        "low",
-        'close',
+        "close",
-        'volume',
+        "volume",
-        'date_suf',
+        "date_suf",
-        'open_suf',
+        "open_suf",
-        'high_suf',
+        "high_suf",
-        'low_suf',
+        "low_suf",
-        'close_suf',
+        "close_suf",
-        'volume_suf'
+        "volume_suf",
     ]
 
 
 def test_merge_informative_pair_suffix_append_timeframe():
-    data = generate_test_data('15m', 20)
+    data = generate_test_data("15m", 20)
-    informative = generate_test_data('1h', 20)
+    informative = generate_test_data("1h", 20)
 
     with pytest.raises(ValueError, match=r"You can not specify `append_timeframe` .*"):
-        merge_informative_pair(data, informative, '15m', '1h', suffix="suf")
+        merge_informative_pair(data, informative, "15m", "1h", suffix="suf")
 
 
-@pytest.mark.parametrize("side,profitrange", [
+@pytest.mark.parametrize(
+    "side,profitrange",
+    [
         # profit range for long is [-1, inf] while for shorts is [-inf, 1]
         ("long", [-0.99, 2, 30]),
         ("short", [-2.0, 0.99, 30]),
-])
+    ],
+)
 def test_stoploss_from_open(side, profitrange):
     open_price_ranges = [
         [0.01, 1.00, 30],
@@ -231,8 +235,7 @@ def test_stoploss_from_open(side, profitrange):
     for open_range in open_price_ranges:
         for open_price in np.linspace(*open_range):
             for desired_stop in np.linspace(-0.50, 0.50, 30):
-
+                if side == "long":
-                if side == 'long':
                     # -1 is not a valid current_profit, should return 1
                     assert stoploss_from_open(desired_stop, -1) == 1
                 else:
@@ -240,7 +243,7 @@ def test_stoploss_from_open(side, profitrange):
                     assert stoploss_from_open(desired_stop, 1, True) == 1
 
                 for current_profit in np.linspace(*profitrange):
-                    if side == 'long':
+                    if side == "long":
                         current_price = open_price * (1 + current_profit)
                         expected_stop_price = open_price * (1 + desired_stop)
                         stoploss = stoploss_from_open(desired_stop, current_profit)
@@ -254,19 +257,22 @@ def test_stoploss_from_open(side, profitrange):
                     assert stoploss >= 0
                     # Technically the formula can yield values greater than 1 for shorts
                     # even though it doesn't make sense because the position would be liquidated
-                    if side == 'long':
+                    if side == "long":
                         assert stoploss <= 1
 
                     # there is no correct answer if the expected stop price is above
                     # the current price
-                    if ((side == 'long' and expected_stop_price > current_price)
+                    if (side == "long" and expected_stop_price > current_price) or (
-                            or (side == 'short' and expected_stop_price < current_price)):
+                        side == "short" and expected_stop_price < current_price
+                    ):
                         assert stoploss == 0
                     else:
                         assert pytest.approx(stop_price) == expected_stop_price
 
 
-@pytest.mark.parametrize("side,rel_stop,curr_profit,leverage,expected", [
+@pytest.mark.parametrize(
+    "side,rel_stop,curr_profit,leverage,expected",
+    [
         # profit range for long is [-1, inf] while for shorts is [-inf, 1]
         ("long", 0, -1, 1, 1),
         ("long", 0, 0.1, 1, 0.09090909),
@@ -277,20 +283,19 @@ def test_stoploss_from_open(side, profitrange):
         ("long", 0, 5, 10, 3.3333333),  # 500% profit, set stoploss break even
         ("long", 0.1, 5, 10, 3.26666666),  # 500% profit, set stoploss to 10% above open price
         ("long", -0.1, 5, 10, 3.3999999),  # 500% profit, set stoploss to 10% belowopen price
-
         ("short", 0, 0.1, 1, 0.1111111),
         ("short", -0.1, 0.1, 1, 0.2222222),
         ("short", 0.1, 0.2, 1, 0.125),
         ("short", 0.1, 1, 1, 1),
         ("short", -0.01, 5, 10, 10.01999999),  # 500% profit at 10x
-])
+    ],
+)
 def test_stoploss_from_open_leverage(side, rel_stop, curr_profit, leverage, expected):
-
+    stoploss = stoploss_from_open(rel_stop, curr_profit, side == "short", leverage)
-    stoploss = stoploss_from_open(rel_stop, curr_profit, side == 'short', leverage)
     assert pytest.approx(stoploss) == expected
     open_rate = 100
     if stoploss != 1:
-        if side == 'long':
+        if side == "long":
             current_rate = open_rate * (1 + curr_profit / leverage)
             stop = current_rate * (1 - stoploss / leverage)
             assert pytest.approx(stop) == open_rate * (1 + rel_stop / leverage)
@@ -322,73 +327,79 @@ def test_stoploss_from_absolute():
     assert pytest.approx(stoploss_from_absolute(100, 1, is_short=True, leverage=5)) == 5
 
 
-@pytest.mark.parametrize('trading_mode', ['futures', 'spot'])
+@pytest.mark.parametrize("trading_mode", ["futures", "spot"])
 def test_informative_decorator(mocker, default_conf_usdt, trading_mode):
     candle_def = CandleType.get_default(trading_mode)
-    default_conf_usdt['candle_type_def'] = candle_def
+    default_conf_usdt["candle_type_def"] = candle_def
-    test_data_5m = generate_test_data('5m', 40)
+    test_data_5m = generate_test_data("5m", 40)
-    test_data_30m = generate_test_data('30m', 40)
+    test_data_30m = generate_test_data("30m", 40)
-    test_data_1h = generate_test_data('1h', 40)
+    test_data_1h = generate_test_data("1h", 40)
     data = {
-        ('XRP/USDT', '5m', candle_def): test_data_5m,
+        ("XRP/USDT", "5m", candle_def): test_data_5m,
-        ('XRP/USDT', '30m', candle_def): test_data_30m,
+        ("XRP/USDT", "30m", candle_def): test_data_30m,
-        ('XRP/USDT', '1h', candle_def): test_data_1h,
+        ("XRP/USDT", "1h", candle_def): test_data_1h,
-        ('XRP/BTC', '1h', candle_def): test_data_1h,  # from {base}/BTC
+        ("XRP/BTC", "1h", candle_def): test_data_1h,  # from {base}/BTC
-        ('LTC/USDT', '5m', candle_def): test_data_5m,
+        ("LTC/USDT", "5m", candle_def): test_data_5m,
-        ('LTC/USDT', '30m', candle_def): test_data_30m,
+        ("LTC/USDT", "30m", candle_def): test_data_30m,
-        ('LTC/USDT', '1h', candle_def): test_data_1h,
+        ("LTC/USDT", "1h", candle_def): test_data_1h,
-        ('LTC/BTC', '1h', candle_def): test_data_1h,  # from {base}/BTC
+        ("LTC/BTC", "1h", candle_def): test_data_1h,  # from {base}/BTC
-        ('NEO/USDT', '30m', candle_def): test_data_30m,
+        ("NEO/USDT", "30m", candle_def): test_data_30m,
-        ('NEO/USDT', '5m', CandleType.SPOT): test_data_5m,  # Explicit request with '' as candletype
+        ("NEO/USDT", "5m", CandleType.SPOT): test_data_5m,  # Explicit request with '' as candletype
-        ('NEO/USDT', '15m', candle_def): test_data_5m,  # Explicit request with '' as candletype
+        ("NEO/USDT", "15m", candle_def): test_data_5m,  # Explicit request with '' as candletype
-        ('NEO/USDT', '1h', candle_def): test_data_1h,
+        ("NEO/USDT", "1h", candle_def): test_data_1h,
-        ('ETH/USDT', '1h', candle_def): test_data_1h,
+        ("ETH/USDT", "1h", candle_def): test_data_1h,
-        ('ETH/USDT', '30m', candle_def): test_data_30m,
+        ("ETH/USDT", "30m", candle_def): test_data_30m,
-        ('ETH/BTC', '1h', CandleType.SPOT): test_data_1h,  # Explicitly selected as spot
+        ("ETH/BTC", "1h", CandleType.SPOT): test_data_1h,  # Explicitly selected as spot
     }
-    default_conf_usdt['strategy'] = 'InformativeDecoratorTest'
+    default_conf_usdt["strategy"] = "InformativeDecoratorTest"
     strategy = StrategyResolver.load_strategy(default_conf_usdt)
     exchange = get_patched_exchange(mocker, default_conf_usdt)
     strategy.dp = DataProvider({}, exchange, None)
-    mocker.patch.object(strategy.dp, 'current_whitelist', return_value=[
+    mocker.patch.object(
-        'XRP/USDT', 'LTC/USDT', 'NEO/USDT'
+        strategy.dp, "current_whitelist", return_value=["XRP/USDT", "LTC/USDT", "NEO/USDT"]
-    ])
+    )
 
     assert len(strategy._ft_informative) == 7  # Equal to number of decorators used
     informative_pairs = [
-        ('XRP/USDT', '1h', candle_def),
+        ("XRP/USDT", "1h", candle_def),
-        ('XRP/BTC', '1h', candle_def),
+        ("XRP/BTC", "1h", candle_def),
-        ('LTC/USDT', '1h', candle_def),
+        ("LTC/USDT", "1h", candle_def),
-        ('LTC/BTC', '1h', candle_def),
+        ("LTC/BTC", "1h", candle_def),
-        ('XRP/USDT', '30m', candle_def),
+        ("XRP/USDT", "30m", candle_def),
-        ('LTC/USDT', '30m', candle_def),
+        ("LTC/USDT", "30m", candle_def),
-        ('NEO/USDT', '1h', candle_def),
+        ("NEO/USDT", "1h", candle_def),
-        ('NEO/USDT', '30m', candle_def),
+        ("NEO/USDT", "30m", candle_def),
-        ('NEO/USDT', '5m', candle_def),
+        ("NEO/USDT", "5m", candle_def),
-        ('NEO/USDT', '15m', candle_def),
+        ("NEO/USDT", "15m", candle_def),
-        ('NEO/USDT', '2h', CandleType.FUTURES),
+        ("NEO/USDT", "2h", CandleType.FUTURES),
-        ('ETH/BTC', '1h', CandleType.SPOT),  # One candle remains as spot
+        ("ETH/BTC", "1h", CandleType.SPOT),  # One candle remains as spot
-        ('ETH/USDT', '30m', candle_def)]
+        ("ETH/USDT", "30m", candle_def),
+    ]
     for inf_pair in informative_pairs:
         assert inf_pair in strategy.gather_informative_pairs()
 
     def test_historic_ohlcv(pair, timeframe, candle_type):
         return data[
-            (pair, timeframe or strategy.timeframe, CandleType.from_string(candle_type))].copy()
+            (pair, timeframe or strategy.timeframe, CandleType.from_string(candle_type))
+        ].copy()
 
-    mocker.patch('freqtrade.data.dataprovider.DataProvider.historic_ohlcv',
+    mocker.patch(
-                 side_effect=test_historic_ohlcv)
+        "freqtrade.data.dataprovider.DataProvider.historic_ohlcv", side_effect=test_historic_ohlcv
+    )
 
     analyzed = strategy.advise_all_indicators(
-        {p: data[(p, strategy.timeframe, candle_def)] for p in ('XRP/USDT', 'LTC/USDT')})
+        {p: data[(p, strategy.timeframe, candle_def)] for p in ("XRP/USDT", "LTC/USDT")}
+    )
     expected_columns = [
-        'rsi_1h', 'rsi_30m',                    # Stacked informative decorators
+        "rsi_1h",
-        'neo_usdt_rsi_1h',                      # NEO 1h informative
+        "rsi_30m",  # Stacked informative decorators
-        'rsi_NEO_USDT_neo_usdt_NEO/USDT_30m',   # Column formatting
+        "neo_usdt_rsi_1h",  # NEO 1h informative
-        'rsi_from_callable',                    # Custom column formatter
+        "rsi_NEO_USDT_neo_usdt_NEO/USDT_30m",  # Column formatting
-        'eth_btc_rsi_1h',                       # Quote currency not matching stake currency
+        "rsi_from_callable",  # Custom column formatter
-        'rsi', 'rsi_less',                      # Non-informative columns
+        "eth_btc_rsi_1h",  # Quote currency not matching stake currency
-        'rsi_5m',                               # Manual informative dataframe
+        "rsi",
+        "rsi_less",  # Non-informative columns
+        "rsi_5m",  # Manual informative dataframe
     ]
     for _, dataframe in analyzed.items():
         for col in expected_columns:

tests/strategy/test_strategy_loading.py

@@ -14,7 +14,7 @@ from tests.conftest import CURRENT_TEST_STRATEGY, log_has, log_has_re
 
 
 def test_search_strategy():
-    default_location = Path(__file__).parent / 'strats'
+    default_location = Path(__file__).parent / "strats"
 
     s, _ = StrategyResolver._search_object(
         directory=default_location,
@@ -25,7 +25,7 @@ def test_search_strategy():
 
     s, _ = StrategyResolver._search_object(
         directory=default_location,
-        object_name='NotFoundStrategy',
+        object_name="NotFoundStrategy",
         add_source=True,
     )
     assert s is None
@@ -46,9 +46,9 @@ def test_search_all_strategies_with_failed():
     assert len(strategies) == 14
     # with enum_failed=True search_all_objects() shall find 2 good strategies
     # and 1 which fails to load
-    assert len([x for x in strategies if x['class'] is not None]) == 13
+    assert len([x for x in strategies if x["class"] is not None]) == 13
 
-    assert len([x for x in strategies if x['class'] is None]) == 1
+    assert len([x for x in strategies if x["class"] is None]) == 1
 
     directory = Path(__file__).parent / "strats_nonexistingdir"
     strategies = StrategyResolver._search_all_objects(directory, enum_failed=True)
@@ -56,123 +56,126 @@ def test_search_all_strategies_with_failed():
 
 
 def test_load_strategy(default_conf, dataframe_1m):
-    default_conf.update({'strategy': 'SampleStrategy',
+    default_conf.update(
-                         'strategy_path': str(Path(__file__).parents[2] / 'freqtrade/templates')
+        {
-                         })
+            "strategy": "SampleStrategy",
+            "strategy_path": str(Path(__file__).parents[2] / "freqtrade/templates"),
+        }
+    )
     strategy = StrategyResolver.load_strategy(default_conf)
     assert isinstance(strategy.__source__, str)
-    assert 'class SampleStrategy' in strategy.__source__
+    assert "class SampleStrategy" in strategy.__source__
     assert isinstance(strategy.__file__, str)
-    assert 'rsi' in strategy.advise_indicators(dataframe_1m, {'pair': 'ETH/BTC'})
+    assert "rsi" in strategy.advise_indicators(dataframe_1m, {"pair": "ETH/BTC"})
 
 
 def test_load_strategy_base64(dataframe_1m, caplog, default_conf):
-    filepath = Path(__file__).parents[2] / 'freqtrade/templates/sample_strategy.py'
+    filepath = Path(__file__).parents[2] / "freqtrade/templates/sample_strategy.py"
     encoded_string = urlsafe_b64encode(filepath.read_bytes()).decode("utf-8")
-    default_conf.update({'strategy': f'SampleStrategy:{encoded_string}'})
+    default_conf.update({"strategy": f"SampleStrategy:{encoded_string}"})
 
     strategy = StrategyResolver.load_strategy(default_conf)
-    assert 'rsi' in strategy.advise_indicators(dataframe_1m, {'pair': 'ETH/BTC'})
+    assert "rsi" in strategy.advise_indicators(dataframe_1m, {"pair": "ETH/BTC"})
     # Make sure strategy was loaded from base64 (using temp directory)!!
-    assert log_has_re(r"Using resolved strategy SampleStrategy from '"
+    assert log_has_re(
-                      r".*(/|\\).*(/|\\)SampleStrategy\.py'\.\.\.", caplog)
+        r"Using resolved strategy SampleStrategy from '"
+        r".*(/|\\).*(/|\\)SampleStrategy\.py'\.\.\.",
+        caplog,
+    )
 
 
 def test_load_strategy_invalid_directory(caplog, default_conf, tmp_path):
-    default_conf['user_data_dir'] = tmp_path
+    default_conf["user_data_dir"] = tmp_path
 
-    extra_dir = Path.cwd() / 'some/path'
+    extra_dir = Path.cwd() / "some/path"
     with pytest.raises(OperationalException, match=r"Impossible to load Strategy.*"):
-        StrategyResolver._load_strategy('StrategyTestV333', config=default_conf,
+        StrategyResolver._load_strategy(
-                                        extra_dir=extra_dir)
+            "StrategyTestV333", config=default_conf, extra_dir=extra_dir
+        )
 
-    assert log_has_re(r'Path .*' + r'some.*path.*' + r'.* does not exist', caplog)
+    assert log_has_re(r"Path .*" + r"some.*path.*" + r".* does not exist", caplog)
 
 
 def test_load_not_found_strategy(default_conf, tmp_path):
-    default_conf['user_data_dir'] = tmp_path
+    default_conf["user_data_dir"] = tmp_path
-    default_conf['strategy'] = 'NotFoundStrategy'
+    default_conf["strategy"] = "NotFoundStrategy"
-    with pytest.raises(OperationalException,
+    with pytest.raises(
+        OperationalException,
         match=r"Impossible to load Strategy 'NotFoundStrategy'. "
-                             r"This class does not exist or contains Python code errors."):
+        r"This class does not exist or contains Python code errors.",
+    ):
         StrategyResolver.load_strategy(default_conf)
 
 
 def test_load_strategy_noname(default_conf):
-    default_conf['strategy'] = ''
+    default_conf["strategy"] = ""
-    with pytest.raises(OperationalException,
+    with pytest.raises(
-                       match="No strategy set. Please use `--strategy` to specify "
+        OperationalException,
-                             "the strategy class to use."):
+        match="No strategy set. Please use `--strategy` to specify " "the strategy class to use.",
+    ):
         StrategyResolver.load_strategy(default_conf)
 
 
-@ pytest.mark.filterwarnings("ignore:deprecated")
+@pytest.mark.filterwarnings("ignore:deprecated")
-@ pytest.mark.parametrize('strategy_name', ['StrategyTestV2'])
+@pytest.mark.parametrize("strategy_name", ["StrategyTestV2"])
 def test_strategy_pre_v3(dataframe_1m, default_conf, strategy_name):
-    default_conf.update({'strategy': strategy_name})
+    default_conf.update({"strategy": strategy_name})
 
     strategy = StrategyResolver.load_strategy(default_conf)
-    metadata = {'pair': 'ETH/BTC'}
+    metadata = {"pair": "ETH/BTC"}
     assert strategy.minimal_roi[0] == 0.04
-    assert default_conf["minimal_roi"]['0'] == 0.04
+    assert default_conf["minimal_roi"]["0"] == 0.04
 
     assert strategy.stoploss == -0.10
-    assert default_conf['stoploss'] == -0.10
+    assert default_conf["stoploss"] == -0.10
 
-    assert strategy.timeframe == '5m'
+    assert strategy.timeframe == "5m"
-    assert default_conf['timeframe'] == '5m'
+    assert default_conf["timeframe"] == "5m"
 
     df_indicators = strategy.advise_indicators(dataframe_1m, metadata=metadata)
-    assert 'adx' in df_indicators
+    assert "adx" in df_indicators
 
     dataframe = strategy.advise_entry(df_indicators, metadata=metadata)
-    assert 'buy' not in dataframe.columns
+    assert "buy" not in dataframe.columns
-    assert 'enter_long' in dataframe.columns
+    assert "enter_long" in dataframe.columns
 
     dataframe = strategy.advise_exit(df_indicators, metadata=metadata)
-    assert 'sell' not in dataframe.columns
+    assert "sell" not in dataframe.columns
-    assert 'exit_long' in dataframe.columns
+    assert "exit_long" in dataframe.columns
 
 
 def test_strategy_can_short(caplog, default_conf):
     caplog.set_level(logging.INFO)
-    default_conf.update({
+    default_conf.update(
-        'strategy': CURRENT_TEST_STRATEGY,
+        {
-    })
+            "strategy": CURRENT_TEST_STRATEGY,
+        }
+    )
     strat = StrategyResolver.load_strategy(default_conf)
     assert isinstance(strat, IStrategy)
-    default_conf['strategy'] = 'StrategyTestV3Futures'
+    default_conf["strategy"] = "StrategyTestV3Futures"
     with pytest.raises(ImportError, match=""):
         StrategyResolver.load_strategy(default_conf)
 
-    default_conf['trading_mode'] = 'futures'
+    default_conf["trading_mode"] = "futures"
     strat = StrategyResolver.load_strategy(default_conf)
     assert isinstance(strat, IStrategy)
 
 
 def test_strategy_override_minimal_roi(caplog, default_conf):
     caplog.set_level(logging.INFO)
-    default_conf.update({
+    default_conf.update({"strategy": CURRENT_TEST_STRATEGY, "minimal_roi": {"20": 0.1, "0": 0.5}})
-        'strategy': CURRENT_TEST_STRATEGY,
-        'minimal_roi': {
-            "20": 0.1,
-            "0": 0.5
-        }
-    })
     strategy = StrategyResolver.load_strategy(default_conf)
 
     assert strategy.minimal_roi[0] == 0.5
     assert log_has(
-        "Override strategy 'minimal_roi' with value in config file: {'20': 0.1, '0': 0.5}.",
+        "Override strategy 'minimal_roi' with value in config file: {'20': 0.1, '0': 0.5}.", caplog
-        caplog)
+    )
 
 
 def test_strategy_override_stoploss(caplog, default_conf):
     caplog.set_level(logging.INFO)
-    default_conf.update({
+    default_conf.update({"strategy": CURRENT_TEST_STRATEGY, "stoploss": -0.5})
-        'strategy': CURRENT_TEST_STRATEGY,
-        'stoploss': -0.5
-    })
     strategy = StrategyResolver.load_strategy(default_conf)
 
     assert strategy.stoploss == -0.5
@@ -181,10 +184,7 @@ def test_strategy_override_stoploss(caplog, default_conf):
 
 def test_strategy_override_max_open_trades(caplog, default_conf):
     caplog.set_level(logging.INFO)
-    default_conf.update({
+    default_conf.update({"strategy": CURRENT_TEST_STRATEGY, "max_open_trades": 7})
-        'strategy': CURRENT_TEST_STRATEGY,
-        'max_open_trades': 7
-    })
     strategy = StrategyResolver.load_strategy(default_conf)
 
     assert strategy.max_open_trades == 7
@@ -193,10 +193,7 @@ def test_strategy_override_max_open_trades(caplog, default_conf):
 
 def test_strategy_override_trailing_stop(caplog, default_conf):
     caplog.set_level(logging.INFO)
-    default_conf.update({
+    default_conf.update({"strategy": CURRENT_TEST_STRATEGY, "trailing_stop": True})
-        'strategy': CURRENT_TEST_STRATEGY,
-        'trailing_stop': True
-    })
     strategy = StrategyResolver.load_strategy(default_conf)
 
     assert strategy.trailing_stop
@@ -206,84 +203,81 @@ def test_strategy_override_trailing_stop(caplog, default_conf):
 
 def test_strategy_override_trailing_stop_positive(caplog, default_conf):
     caplog.set_level(logging.INFO)
-    default_conf.update({
+    default_conf.update(
-        'strategy': CURRENT_TEST_STRATEGY,
+        {
-        'trailing_stop_positive': -0.1,
+            "strategy": CURRENT_TEST_STRATEGY,
-        'trailing_stop_positive_offset': -0.2
+            "trailing_stop_positive": -0.1,
-
+            "trailing_stop_positive_offset": -0.2,
-    })
+        }
+    )
     strategy = StrategyResolver.load_strategy(default_conf)
 
     assert strategy.trailing_stop_positive == -0.1
-    assert log_has("Override strategy 'trailing_stop_positive' with value in config file: -0.1.",
+    assert log_has(
-                   caplog)
+        "Override strategy 'trailing_stop_positive' with value in config file: -0.1.", caplog
+    )
 
     assert strategy.trailing_stop_positive_offset == -0.2
-    assert log_has("Override strategy 'trailing_stop_positive' with value in config file: -0.1.",
+    assert log_has(
-                   caplog)
+        "Override strategy 'trailing_stop_positive' with value in config file: -0.1.", caplog
+    )
 
 
 def test_strategy_override_timeframe(caplog, default_conf):
     caplog.set_level(logging.INFO)
 
-    default_conf.update({
+    default_conf.update(
-        'strategy': CURRENT_TEST_STRATEGY,
+        {"strategy": CURRENT_TEST_STRATEGY, "timeframe": 60, "stake_currency": "ETH"}
-        'timeframe': 60,
+    )
-        'stake_currency': 'ETH'
-    })
     strategy = StrategyResolver.load_strategy(default_conf)
 
     assert strategy.timeframe == 60
-    assert strategy.stake_currency == 'ETH'
+    assert strategy.stake_currency == "ETH"
-    assert log_has("Override strategy 'timeframe' with value in config file: 60.",
+    assert log_has("Override strategy 'timeframe' with value in config file: 60.", caplog)
-                   caplog)
 
 
 def test_strategy_override_process_only_new_candles(caplog, default_conf):
     caplog.set_level(logging.INFO)
 
-    default_conf.update({
+    default_conf.update({"strategy": CURRENT_TEST_STRATEGY, "process_only_new_candles": False})
-        'strategy': CURRENT_TEST_STRATEGY,
-        'process_only_new_candles': False
-    })
     strategy = StrategyResolver.load_strategy(default_conf)
 
     assert not strategy.process_only_new_candles
-    assert log_has("Override strategy 'process_only_new_candles' with value in config file: False.",
+    assert log_has(
-                   caplog)
+        "Override strategy 'process_only_new_candles' with value in config file: False.", caplog
+    )
 
 
 def test_strategy_override_order_types(caplog, default_conf):
     caplog.set_level(logging.INFO)
 
     order_types = {
-        'entry': 'market',
+        "entry": "market",
-        'exit': 'limit',
+        "exit": "limit",
-        'stoploss': 'limit',
+        "stoploss": "limit",
-        'stoploss_on_exchange': True,
+        "stoploss_on_exchange": True,
     }
-    default_conf.update({
+    default_conf.update({"strategy": CURRENT_TEST_STRATEGY, "order_types": order_types})
-        'strategy': CURRENT_TEST_STRATEGY,
-        'order_types': order_types
-    })
     strategy = StrategyResolver.load_strategy(default_conf)
 
     assert strategy.order_types
-    for method in ['entry', 'exit', 'stoploss', 'stoploss_on_exchange']:
+    for method in ["entry", "exit", "stoploss", "stoploss_on_exchange"]:
         assert strategy.order_types[method] == order_types[method]
 
-    assert log_has("Override strategy 'order_types' with value in config file:"
+    assert log_has(
+        "Override strategy 'order_types' with value in config file:"
         " {'entry': 'market', 'exit': 'limit', 'stoploss': 'limit',"
-                   " 'stoploss_on_exchange': True}.", caplog)
+        " 'stoploss_on_exchange': True}.",
+        caplog,
+    )
 
-    default_conf.update({
+    default_conf.update({"strategy": CURRENT_TEST_STRATEGY, "order_types": {"exit": "market"}})
-        'strategy': CURRENT_TEST_STRATEGY,
-        'order_types': {'exit': 'market'}
-    })
     # Raise error for invalid configuration
-    with pytest.raises(ImportError,
+    with pytest.raises(
+        ImportError,
         match=r"Impossible to load Strategy '" + CURRENT_TEST_STRATEGY + "'. "
-                             r"Order-types mapping is incomplete."):
+        r"Order-types mapping is incomplete.",
+    ):
         StrategyResolver.load_strategy(default_conf)
 
 
@@ -291,50 +285,57 @@ def test_strategy_override_order_tif(caplog, default_conf):
     caplog.set_level(logging.INFO)
 
     order_time_in_force = {
-        'entry': 'FOK',
+        "entry": "FOK",
-        'exit': 'GTC',
+        "exit": "GTC",
     }
 
-    default_conf.update({
+    default_conf.update(
-        'strategy': CURRENT_TEST_STRATEGY,
+        {"strategy": CURRENT_TEST_STRATEGY, "order_time_in_force": order_time_in_force}
-        'order_time_in_force': order_time_in_force
+    )
-    })
     strategy = StrategyResolver.load_strategy(default_conf)
 
     assert strategy.order_time_in_force
-    for method in ['entry', 'exit']:
+    for method in ["entry", "exit"]:
         assert strategy.order_time_in_force[method] == order_time_in_force[method]
 
-    assert log_has("Override strategy 'order_time_in_force' with value in config file:"
+    assert log_has(
-                   " {'entry': 'FOK', 'exit': 'GTC'}.", caplog)
+        "Override strategy 'order_time_in_force' with value in config file:"
+        " {'entry': 'FOK', 'exit': 'GTC'}.",
+        caplog,
+    )
 
-    default_conf.update({
+    default_conf.update(
-        'strategy': CURRENT_TEST_STRATEGY,
+        {"strategy": CURRENT_TEST_STRATEGY, "order_time_in_force": {"entry": "FOK"}}
-        'order_time_in_force': {'entry': 'FOK'}
+    )
-    })
     # Raise error for invalid configuration
-    with pytest.raises(ImportError,
+    with pytest.raises(
+        ImportError,
         match=f"Impossible to load Strategy '{CURRENT_TEST_STRATEGY}'. "
-                             "Order-time-in-force mapping is incomplete."):
+        "Order-time-in-force mapping is incomplete.",
+    ):
         StrategyResolver.load_strategy(default_conf)
 
 
 def test_strategy_override_use_exit_signal(caplog, default_conf):
     caplog.set_level(logging.INFO)
-    default_conf.update({
+    default_conf.update(
-        'strategy': CURRENT_TEST_STRATEGY,
+        {
-    })
+            "strategy": CURRENT_TEST_STRATEGY,
+        }
+    )
     strategy = StrategyResolver.load_strategy(default_conf)
     assert strategy.use_exit_signal
     assert isinstance(strategy.use_exit_signal, bool)
     # must be inserted to configuration
-    assert 'use_exit_signal' in default_conf
+    assert "use_exit_signal" in default_conf
-    assert default_conf['use_exit_signal']
+    assert default_conf["use_exit_signal"]
 
-    default_conf.update({
+    default_conf.update(
-        'strategy': CURRENT_TEST_STRATEGY,
+        {
-        'use_exit_signal': False,
+            "strategy": CURRENT_TEST_STRATEGY,
-    })
+            "use_exit_signal": False,
+        }
+    )
     strategy = StrategyResolver.load_strategy(default_conf)
 
     assert not strategy.use_exit_signal
@@ -344,20 +345,24 @@ def test_strategy_override_use_exit_signal(caplog, default_conf):
 
 def test_strategy_override_use_exit_profit_only(caplog, default_conf):
     caplog.set_level(logging.INFO)
-    default_conf.update({
+    default_conf.update(
-        'strategy': CURRENT_TEST_STRATEGY,
+        {
-    })
+            "strategy": CURRENT_TEST_STRATEGY,
+        }
+    )
     strategy = StrategyResolver.load_strategy(default_conf)
     assert not strategy.exit_profit_only
     assert isinstance(strategy.exit_profit_only, bool)
     # must be inserted to configuration
-    assert 'exit_profit_only' in default_conf
+    assert "exit_profit_only" in default_conf
-    assert not default_conf['exit_profit_only']
+    assert not default_conf["exit_profit_only"]
 
-    default_conf.update({
+    default_conf.update(
-        'strategy': CURRENT_TEST_STRATEGY,
+        {
-        'exit_profit_only': True,
+            "strategy": CURRENT_TEST_STRATEGY,
-    })
+            "exit_profit_only": True,
+        }
+    )
     strategy = StrategyResolver.load_strategy(default_conf)
 
     assert strategy.exit_profit_only
@@ -367,138 +372,135 @@ def test_strategy_override_use_exit_profit_only(caplog, default_conf):
 
 def test_strategy_max_open_trades_infinity_from_strategy(caplog, default_conf):
     caplog.set_level(logging.INFO)
-    default_conf.update({
+    default_conf.update(
-        'strategy': CURRENT_TEST_STRATEGY,
+        {
-    })
+            "strategy": CURRENT_TEST_STRATEGY,
-    del default_conf['max_open_trades']
+        }
+    )
+    del default_conf["max_open_trades"]
 
     strategy = StrategyResolver.load_strategy(default_conf)
 
     # this test assumes -1 set to 'max_open_trades' in CURRENT_TEST_STRATEGY
-    assert strategy.max_open_trades == float('inf')
+    assert strategy.max_open_trades == float("inf")
-    assert default_conf['max_open_trades'] == float('inf')
+    assert default_conf["max_open_trades"] == float("inf")
 
 
 def test_strategy_max_open_trades_infinity_from_config(caplog, default_conf, mocker):
     caplog.set_level(logging.INFO)
-    default_conf.update({
+    default_conf.update(
-        'strategy': CURRENT_TEST_STRATEGY,
+        {"strategy": CURRENT_TEST_STRATEGY, "max_open_trades": -1, "exchange": "binance"}
-        'max_open_trades': -1,
+    )
-        'exchange': 'binance'
-    })
 
     configuration = Configuration(args=default_conf)
     parsed_config = configuration.get_config()
 
-    assert parsed_config['max_open_trades'] == float('inf')
+    assert parsed_config["max_open_trades"] == float("inf")
 
     strategy = StrategyResolver.load_strategy(parsed_config)
 
-    assert strategy.max_open_trades == float('inf')
+    assert strategy.max_open_trades == float("inf")
 
 
-@ pytest.mark.filterwarnings("ignore:deprecated")
+@pytest.mark.filterwarnings("ignore:deprecated")
 def test_missing_implements(default_conf, caplog):
-
     default_location = Path(__file__).parent / "strats"
-    default_conf.update({'strategy': 'StrategyTestV2',
+    default_conf.update({"strategy": "StrategyTestV2", "strategy_path": default_location})
-                         'strategy_path': default_location})
     StrategyResolver.load_strategy(default_conf)
 
     log_has_re(r"DEPRECATED: .*use_sell_signal.*use_exit_signal.", caplog)
 
-    default_conf['trading_mode'] = 'futures'
+    default_conf["trading_mode"] = "futures"
-    with pytest.raises(OperationalException,
+    with pytest.raises(
-                       match=r"DEPRECATED: .*use_sell_signal.*use_exit_signal."):
+        OperationalException, match=r"DEPRECATED: .*use_sell_signal.*use_exit_signal."
+    ):
         StrategyResolver.load_strategy(default_conf)
 
-    default_conf['trading_mode'] = 'spot'
+    default_conf["trading_mode"] = "spot"
 
     default_location = Path(__file__).parent / "strats/broken_strats"
-    default_conf.update({'strategy': 'TestStrategyNoImplements',
+    default_conf.update({"strategy": "TestStrategyNoImplements", "strategy_path": default_location})
-                         'strategy_path': default_location})
+    with pytest.raises(
-    with pytest.raises(OperationalException,
+        OperationalException, match=r"`populate_entry_trend` or `populate_buy_trend`.*"
-                       match=r"`populate_entry_trend` or `populate_buy_trend`.*"):
+    ):
         StrategyResolver.load_strategy(default_conf)
 
-    default_conf['strategy'] = 'TestStrategyNoImplementSell'
+    default_conf["strategy"] = "TestStrategyNoImplementSell"
 
-    with pytest.raises(OperationalException,
+    with pytest.raises(
-                       match=r"`populate_exit_trend` or `populate_sell_trend`.*"):
+        OperationalException, match=r"`populate_exit_trend` or `populate_sell_trend`.*"
+    ):
         StrategyResolver.load_strategy(default_conf)
 
     # Futures mode is more strict ...
-    default_conf['trading_mode'] = 'futures'
+    default_conf["trading_mode"] = "futures"
 
-    with pytest.raises(OperationalException,
+    with pytest.raises(OperationalException, match=r"`populate_exit_trend` must be implemented.*"):
-                       match=r"`populate_exit_trend` must be implemented.*"):
         StrategyResolver.load_strategy(default_conf)
 
-    default_conf['strategy'] = 'TestStrategyNoImplements'
+    default_conf["strategy"] = "TestStrategyNoImplements"
-    with pytest.raises(OperationalException,
+    with pytest.raises(OperationalException, match=r"`populate_entry_trend` must be implemented.*"):
-                       match=r"`populate_entry_trend` must be implemented.*"):
         StrategyResolver.load_strategy(default_conf)
 
-    default_conf['strategy'] = 'TestStrategyImplementCustomSell'
+    default_conf["strategy"] = "TestStrategyImplementCustomSell"
-    with pytest.raises(OperationalException,
+    with pytest.raises(
-                       match=r"Please migrate your implementation of `custom_sell`.*"):
+        OperationalException, match=r"Please migrate your implementation of `custom_sell`.*"
+    ):
         StrategyResolver.load_strategy(default_conf)
 
-    default_conf['strategy'] = 'TestStrategyImplementBuyTimeout'
+    default_conf["strategy"] = "TestStrategyImplementBuyTimeout"
-    with pytest.raises(OperationalException,
+    with pytest.raises(
-                       match=r"Please migrate your implementation of `check_buy_timeout`.*"):
+        OperationalException, match=r"Please migrate your implementation of `check_buy_timeout`.*"
+    ):
         StrategyResolver.load_strategy(default_conf)
 
-    default_conf['strategy'] = 'TestStrategyImplementSellTimeout'
+    default_conf["strategy"] = "TestStrategyImplementSellTimeout"
-    with pytest.raises(OperationalException,
+    with pytest.raises(
-                       match=r"Please migrate your implementation of `check_sell_timeout`.*"):
+        OperationalException, match=r"Please migrate your implementation of `check_sell_timeout`.*"
+    ):
         StrategyResolver.load_strategy(default_conf)
 
 
 def test_call_deprecated_function(default_conf):
     default_location = Path(__file__).parent / "strats/broken_strats/"
-    del default_conf['timeframe']
+    del default_conf["timeframe"]
-    default_conf.update({'strategy': 'TestStrategyLegacyV1',
+    default_conf.update({"strategy": "TestStrategyLegacyV1", "strategy_path": default_location})
-                         'strategy_path': default_location})
+    with pytest.raises(
-    with pytest.raises(OperationalException,
+        OperationalException, match=r"Strategy Interface v1 is no longer supported.*"
-                       match=r"Strategy Interface v1 is no longer supported.*"):
+    ):
         StrategyResolver.load_strategy(default_conf)
 
 
 def test_strategy_interface_versioning(dataframe_1m, default_conf):
-    default_conf.update({'strategy': 'StrategyTestV2'})
+    default_conf.update({"strategy": "StrategyTestV2"})
     strategy = StrategyResolver.load_strategy(default_conf)
-    metadata = {'pair': 'ETH/BTC'}
+    metadata = {"pair": "ETH/BTC"}
 
     assert strategy.INTERFACE_VERSION == 2
 
     indicator_df = strategy.advise_indicators(dataframe_1m, metadata=metadata)
     assert isinstance(indicator_df, DataFrame)
-    assert 'adx' in indicator_df.columns
+    assert "adx" in indicator_df.columns
 
     enterdf = strategy.advise_entry(dataframe_1m, metadata=metadata)
     assert isinstance(enterdf, DataFrame)
 
-    assert 'buy' not in enterdf.columns
+    assert "buy" not in enterdf.columns
-    assert 'enter_long' in enterdf.columns
+    assert "enter_long" in enterdf.columns
 
     exitdf = strategy.advise_exit(dataframe_1m, metadata=metadata)
     assert isinstance(exitdf, DataFrame)
-    assert 'sell' not in exitdf
+    assert "sell" not in exitdf
-    assert 'exit_long' in exitdf
+    assert "exit_long" in exitdf
 
 
 def test_strategy_ft_load_params_from_file(mocker, default_conf):
-    default_conf.update({'strategy': 'StrategyTestV2'})
+    default_conf.update({"strategy": "StrategyTestV2"})
-    del default_conf['max_open_trades']
+    del default_conf["max_open_trades"]
-    mocker.patch('freqtrade.strategy.hyper.HyperStrategyMixin.load_params_from_file',
+    mocker.patch(
-                 return_value={
+        "freqtrade.strategy.hyper.HyperStrategyMixin.load_params_from_file",
-                     'params': {
+        return_value={"params": {"max_open_trades": {"max_open_trades": -1}}},
-                         'max_open_trades':  {
+    )
-                            'max_open_trades': -1
-                         }
-                         }
-                     })
     strategy = StrategyResolver.load_strategy(default_conf)
-    assert strategy.max_open_trades == float('inf')
+    assert strategy.max_open_trades == float("inf")
-    assert strategy.config['max_open_trades'] == float('inf')
+    assert strategy.config["max_open_trades"] == float("inf")