style: Sort imports

docs/examples/modelling/plot_classifier_bettor.py

@@ -13,6 +13,7 @@
 from sklearn.model_selection import TimeSeriesSplit, cross_val_score
 from sklearn.neighbors import KNeighborsClassifier
 from sklearn.pipeline import make_pipeline
+
 from sportsbet.datasets import SoccerDataLoader
 from sportsbet.evaluation import ClassifierBettor, backtest
 

src/sportsbet/datasets/_soccer/_data.py

@@ -22,9 +22,7 @@
 
 MODELLING_URL = 'https://github.com/georgedouzas/sports-betting/tree/data/data/soccer/modelling'
 TRAINING_URL = 'https://raw.githubusercontent.com/georgedouzas/sports-betting/data/data/soccer/modelling/{league}_{division}_{year}.csv'
-FIXTURES_URL = (
-    'https://raw.githubusercontent.com/georgedouzas/sports-betting/data/data/soccer/modelling/fixtures.csv'
-)
+FIXTURES_URL = 'https://raw.githubusercontent.com/georgedouzas/sports-betting/data/data/soccer/modelling/fixtures.csv'
 
 
 class SoccerDataLoader(_BaseDataLoader):

tests/cli/test_bettor.py

@@ -1,6 +1,7 @@
 """Test the bettor commands."""
 
 import pytest
+
 from sportsbet.cli import main
 
 

tests/cli/test_dataloader.py

@@ -1,6 +1,7 @@
 """Test the dataloader commands."""
 
 import pytest
+
 from sportsbet.cli import main
 
 

tests/cli/test_main.py

@@ -1,6 +1,7 @@
 """Test the main commands."""
 
 import pytest
+
 from sportsbet.cli import main
 
 

tests/conftest.py

@@ -25,7 +25,7 @@ def pandas_terminal_width() -> None:  # noqa: PT004
     pd.set_option('display.max_columns', 1000)
 
 
-@pytest.fixture()
+@pytest.fixture
 def cli_config_path(tmp_path: Path) -> Path:
     """Create configuration file."""
     with Path.open(tmp_path / 'config.py', 'wt') as config_file:

tests/datasets/test_dummy.py

@@ -7,6 +7,7 @@
 import pandas as pd
 import pytest
 from sklearn.model_selection import ParameterGrid
+
 from sportsbet.datasets import DummySoccerDataLoader
 
 

tests/evaluation/__init__.py

@@ -4,10 +4,11 @@
 
 import numpy as np
 import pandas as pd
+from typing_extensions import Self
+
 from sportsbet import Data
 from sportsbet.datasets import DummySoccerDataLoader
 from sportsbet.evaluation._base import _BaseBettor
-from typing_extensions import Self
 
 X_train, Y_train, O_train = DummySoccerDataLoader().extract_train_data(odds_type='williamhill')
 

tests/evaluation/test_base.py

@@ -6,8 +6,8 @@
 import pandas as pd
 import pytest
 from sklearn.exceptions import NotFittedError
-from sportsbet.evaluation._base import _BaseBettor
 
+from sportsbet.evaluation._base import _BaseBettor
 from tests.evaluation import O_train, TestBettor, X_train, Y_train
 
 

tests/evaluation/test_classifier.py

@@ -5,6 +5,7 @@
 from sklearn.dummy import DummyClassifier, DummyRegressor
 from sklearn.exceptions import NotFittedError
 from sklearn.utils.validation import check_is_fitted
+
 from sportsbet.datasets import DummySoccerDataLoader
 from sportsbet.evaluation import ClassifierBettor
 

tests/evaluation/test_model_selection.py

@@ -8,8 +8,8 @@
 import pytest
 from sklearn.dummy import DummyClassifier
 from sklearn.model_selection import KFold, TimeSeriesSplit
-from sportsbet.evaluation import BettorGridSearchCV, ClassifierBettor, OddsComparisonBettor, backtest
 
+from sportsbet.evaluation import BettorGridSearchCV, ClassifierBettor, OddsComparisonBettor, backtest
 from tests.evaluation import O_train, TestBettor, X_train, Y_train
 
 

tests/evaluation/test_rules.py

@@ -2,6 +2,7 @@
 
 import numpy as np
 import pytest
+
 from sportsbet.datasets import DummySoccerDataLoader
 from sportsbet.evaluation import OddsComparisonBettor