optimized tests imports statements, unused imports removed.

DanielAvdar · Jan 30, 2024 · 2135803 · 2135803
1 parent 36cdb43
commit 2135803
Show file tree

Hide file tree

Showing 53 changed files with 106 additions and 221 deletions.
diff --git a/tests/checks/check_automl_with_regression.py b/tests/checks/check_automl_with_regression.py
@@ -1,16 +1,9 @@
 import unittest
-import tempfile
-import json
-import numpy as np
+
 import pandas as pd
+import sklearn.model_selection
 
-from numpy.testing import assert_almost_equal
-from sklearn import datasets
 from supervised.automl import AutoML
-from supervised.metric import Metric
-
-import sklearn.model_selection
-from sklearn.metrics import log_loss
 
 
 class AutoMLWithRegressionTest(unittest.TestCase):

diff --git a/tests/checks/run_ml_tests.py b/tests/checks/run_ml_tests.py
@@ -1,5 +1,3 @@
-import os
-import sys
 import unittest
 
 from tests.tests_bin_class.run import *

diff --git a/tests/checks/run_performance_tests.py b/tests/checks/run_performance_tests.py
@@ -1,5 +1,3 @@
-import os
-import sys
 import unittest
 
 from tests.tests_bin_class.test_performance import *

diff --git a/tests/tests_algorithms/test_baseline.py b/tests/tests_algorithms/test_baseline.py
@@ -1,9 +1,6 @@
-import unittest
-import tempfile
-import json
-import numpy as np
 import os
-import pandas as pd
+import tempfile
+import unittest
 
 from numpy.testing import assert_almost_equal
 from sklearn import datasets
@@ -14,8 +11,6 @@
 )
 from supervised.utils.metric import Metric
 
-import tempfile
-
 
 class BaselineTest(unittest.TestCase):
     @classmethod

diff --git a/tests/tests_algorithms/test_catboost.py b/tests/tests_algorithms/test_catboost.py
@@ -1,16 +1,13 @@
-import unittest
+import os
 import tempfile
-import json
-import copy
-import numpy as np
+import unittest
+
 import pandas as pd
-import os
 from numpy.testing import assert_almost_equal
 from sklearn import datasets
 
 from supervised.algorithms.catboost import CatBoostAlgorithm, additional
 from supervised.utils.metric import Metric
-import tempfile
 
 additional["max_rounds"] = 1
 

diff --git a/tests/tests_algorithms/test_decision_tree.py b/tests/tests_algorithms/test_decision_tree.py
@@ -1,20 +1,15 @@
-import unittest
-import tempfile
-import json
-import numpy as np
-import pandas as pd
 import os
+import tempfile
+import unittest
+
 from numpy.testing import assert_almost_equal
 from sklearn import datasets
 
 from supervised.algorithms.decision_tree import (
-    DecisionTreeAlgorithm,
     DecisionTreeRegressorAlgorithm,
 )
 from supervised.utils.metric import Metric
 
-import tempfile
-
 
 class DecisionTreeTest(unittest.TestCase):
     @classmethod

diff --git a/tests/tests_algorithms/test_extra_trees.py b/tests/tests_algorithms/test_extra_trees.py
@@ -1,9 +1,6 @@
-import unittest
-import tempfile
-import json
-import numpy as np
-import pandas as pd
 import os
+import tempfile
+import unittest
 
 from numpy.testing import assert_almost_equal
 from sklearn import datasets
@@ -16,8 +13,6 @@
 )
 from supervised.utils.metric import Metric
 
-import tempfile
-
 additional["trees_in_step"] = 1
 regression_additional["trees_in_step"] = 1
 additional["max_steps"] = 1

diff --git a/tests/tests_algorithms/test_factory.py b/tests/tests_algorithms/test_factory.py
@@ -1,11 +1,6 @@
 import unittest
-import tempfile
-import json
-import numpy as np
-import pandas as pd
 
 from supervised.algorithms.factory import AlgorithmFactory
-
 from supervised.algorithms.xgboost import XgbAlgorithm
 
 

diff --git a/tests/tests_algorithms/test_knn.py b/tests/tests_algorithms/test_knn.py
@@ -1,17 +1,12 @@
 import unittest
-import tempfile
-import json
-import numpy as np
-import pandas as pd
 
+import numpy as np
 from numpy.testing import assert_almost_equal
 from sklearn import datasets
 
 from supervised.algorithms.knn import KNeighborsAlgorithm, KNeighborsRegressorAlgorithm
 from supervised.utils.metric import Metric
 
-import tempfile
-
 
 class KNeighborsRegressorAlgorithmTest(unittest.TestCase):
     @classmethod

diff --git a/tests/tests_algorithms/test_lightgbm.py b/tests/tests_algorithms/test_lightgbm.py
@@ -1,8 +1,6 @@
-import unittest
-import tempfile
-import json
-import copy
 import os
+import tempfile
+import unittest
 
 import numpy as np
 import pandas as pd

diff --git a/tests/tests_algorithms/test_linear.py b/tests/tests_algorithms/test_linear.py
@@ -1,18 +1,13 @@
-import unittest
-import tempfile
-import json
-import numpy as np
-import pandas as pd
 import os
+import tempfile
+import unittest
 
 from numpy.testing import assert_almost_equal
 from sklearn import datasets
 
 from supervised.algorithms.linear import LinearAlgorithm, LinearRegressorAlgorithm
 from supervised.utils.metric import Metric
 
-import tempfile
-
 
 class LinearRegressorAlgorithmTest(unittest.TestCase):
     @classmethod

diff --git a/tests/tests_algorithms/test_nn.py b/tests/tests_algorithms/test_nn.py
@@ -1,9 +1,6 @@
-import unittest
-import tempfile
-import json
-import numpy as np
-import pandas as pd
 import os
+import tempfile
+import unittest
 
 from numpy.testing import assert_almost_equal
 from sklearn import datasets

diff --git a/tests/tests_algorithms/test_random_forest.py b/tests/tests_algorithms/test_random_forest.py
@@ -1,10 +1,7 @@
-import unittest
+import os
 import tempfile
-import json
-import numpy as np
-import pandas as pd
+import unittest
 
-import os
 from numpy.testing import assert_almost_equal
 from sklearn import datasets
 
@@ -16,8 +13,6 @@
 )
 from supervised.utils.metric import Metric
 
-import tempfile
-
 additional["trees_in_step"] = 1
 regression_additional["trees_in_step"] = 1
 additional["max_steps"] = 1

diff --git a/tests/tests_algorithms/test_registry.py b/tests/tests_algorithms/test_registry.py
@@ -1,8 +1,4 @@
 import unittest
-import tempfile
-import json
-import numpy as np
-import pandas as pd
 
 from supervised.algorithms.registry import AlgorithmsRegistry
 

diff --git a/tests/tests_algorithms/test_xgboost.py b/tests/tests_algorithms/test_xgboost.py
@@ -1,18 +1,15 @@
-import unittest
+import os
 import tempfile
-import json
+import unittest
+
 import numpy as np
 import pandas as pd
-import os
-
 from numpy.testing import assert_almost_equal
 from sklearn import datasets
 
 from supervised.algorithms.xgboost import XgbAlgorithm, additional
-from supervised.utils.metric import Metric
 from supervised.utils.constants import BINARY_CLASSIFICATION
-
-import tempfile
+from supervised.utils.metric import Metric
 
 additional["max_rounds"] = 1
 

diff --git a/tests/tests_automl/test_adjust_validation.py b/tests/tests_automl/test_adjust_validation.py
@@ -1,13 +1,10 @@
 import os
+import shutil
 import unittest
-import tempfile
-import json
+
 import numpy as np
-import pandas as pd
-import shutil
 
 from supervised import AutoML
-from supervised.exceptions import AutoMLException
 
 
 class AutoMLAdjustValidationTest(unittest.TestCase):

diff --git a/tests/tests_automl/test_automl_time_constraints.py b/tests/tests_automl/test_automl_time_constraints.py
@@ -1,15 +1,8 @@
-import os
-import unittest
-import tempfile
-import json
-import time
-import numpy as np
-import pandas as pd
 import shutil
+import time
+import unittest
+
 from supervised import AutoML
-from numpy.testing import assert_almost_equal
-from sklearn import datasets
-from supervised.exceptions import AutoMLException
 from supervised.tuner.time_controller import TimeController
 
 

diff --git a/tests/tests_automl/test_data_types.py b/tests/tests_automl/test_data_types.py
@@ -1,14 +1,10 @@
-import os
+import shutil
 import unittest
-import tempfile
-import json
+
 import numpy as np
 import pandas as pd
-import shutil
+
 from supervised import AutoML
-from numpy.testing import assert_almost_equal
-from sklearn import datasets
-from supervised.exceptions import AutoMLException
 
 
 class AutoMLDataTypesTest(unittest.TestCase):

diff --git a/tests/tests_automl/test_dir_change.py b/tests/tests_automl/test_dir_change.py
@@ -1,15 +1,12 @@
 import os
-import json
 import shutil
 import unittest
-import tempfile
+
 import numpy as np
-import pandas as pd
-from sklearn import datasets
 from numpy.testing import assert_almost_equal
+from sklearn import datasets
 
 from supervised import AutoML
-from supervised.exceptions import AutoMLException
 
 
 class AutoMLDirChangeTest(unittest.TestCase):

diff --git a/tests/tests_automl/test_golden_features.py b/tests/tests_automl/test_golden_features.py
@@ -1,14 +1,12 @@
+import json
 import os
+import shutil
 import unittest
-import tempfile
-import json
-import numpy as np
+
 import pandas as pd
-import shutil
-from supervised import AutoML
-from numpy.testing import assert_almost_equal
 from sklearn import datasets
-from supervised.exceptions import AutoMLException
+
+from supervised import AutoML
 
 
 class AutoMLGoldenFeaturesTest(unittest.TestCase):

diff --git a/tests/tests_automl/test_models_needed_for_predict.py b/tests/tests_automl/test_models_needed_for_predict.py
@@ -1,10 +1,7 @@
+import json
 import os
-import unittest
 import tempfile
-import json
-import numpy as np
-import pandas as pd
-import shutil
+import unittest
 
 from supervised import AutoML
 from supervised.exceptions import AutoMLException

diff --git a/tests/tests_automl/test_restore.py b/tests/tests_automl/test_restore.py
@@ -1,15 +1,12 @@
+import json
 import os
+import shutil
 import unittest
-import tempfile
-import json
+
 import numpy as np
 import pandas as pd
-import shutil
-from supervised import AutoML
-from numpy.testing import assert_almost_equal
-from sklearn import datasets
-from supervised.exceptions import AutoMLException
 
+from supervised import AutoML
 from supervised.algorithms.xgboost import additional
 
 additional["max_rounds"] = 1

diff --git a/tests/tests_automl/test_targets.py b/tests/tests_automl/test_targets.py
@@ -1,15 +1,12 @@
-import os
+import shutil
 import unittest
-import json
+
 import numpy as np
 import pandas as pd
-import shutil
-from supervised import AutoML
-from numpy.testing import assert_almost_equal
-from sklearn import datasets
-from supervised.exceptions import AutoMLException
 
+from supervised import AutoML
 from supervised.algorithms.xgboost import additional
+from supervised.exceptions import AutoMLException
 
 additional["max_rounds"] = 1