fix: testing with python version 3.9.13 and 3.9.17

.github/workflows/check.yml

@@ -22,7 +22,7 @@ jobs:
           - macos-latest
         python-version:
           - '3.9.13'
-          - '3.9.20'
+          - '3.9.17'
     runs-on: ${{ matrix.os }}
     name: Run tests on Python ${{ matrix.python-version }}, on ${{ matrix.os }}
     timeout-minutes: 60

psyki/fuzzifiers/netbuilder/__init__.py

@@ -324,4 +324,4 @@ def _visit_unary(self, node: Unary):
     def _visit_negation(self, node: Negation, local_mapping, substitutions):
         return Dense(
             1, kernel_initializer=Ones, activation=eta_abs_one, trainable=False
-        )(self._visit(node.predicate, local_mapping, substitutions))
+        )(self._visit(node.predicate, local_mapping, substitutions))

psyki/fuzzifiers/towell/__init__.py

@@ -9,7 +9,15 @@
 from tensorflow import Tensor, sigmoid
 from tensorflow.keras.initializers import constant, Zeros
 from psyki.fuzzifiers import StructuringFuzzifier
-from psyki.logic.operators import Disjunction, Conjunction, Equal, Less, LessEqual, Greater, GreaterEqual
+from psyki.logic.operators import (
+    Disjunction,
+    Conjunction,
+    Equal,
+    Less,
+    LessEqual,
+    Greater,
+    GreaterEqual,
+)
 from psyki.ski import EnrichedModel
 from psyki.utils import eta_one_abs, eta, concat, match_case
 

setup.py

@@ -7,15 +7,15 @@
 
 here = pathlib.Path(__file__).parent.resolve()
 
-version_file = here / 'VERSION'
+version_file = here / "VERSION"
 
 # Get the long description from the README file
-long_description = (here / 'README.md').read_text(encoding='utf-8')
+long_description = (here / "README.md").read_text(encoding="utf-8")
 
 
 def format_git_describe_version(version):
-    if '-' in version:
-        splitted = version.split('-')
+    if "-" in version:
+        splitted = version.split("-")
         tag = splitted[0]
         index = f"dev{splitted[1]}"
         return f"{tag}.{index}"
@@ -25,17 +25,19 @@ def format_git_describe_version(version):
 
 def get_version_from_git():
     try:
-        process = subprocess.run(["git", "describe"], cwd=str(here), check=True, capture_output=True)
-        version = process.stdout.decode('utf-8').strip()
+        process = subprocess.run(
+            ["git", "describe"], cwd=str(here), check=True, capture_output=True
+        )
+        version = process.stdout.decode("utf-8").strip()
         version = format_git_describe_version(version)
-        with version_file.open('w') as f:
+        with version_file.open("w") as f:
             f.write(version)
         return version
     except subprocess.CalledProcessError:
         if version_file.exists():
             return version_file.read_text().strip()
         else:
-            return '0.1.0'
+            return "0.1.0"
 
 
 version = get_version_from_git()
@@ -47,7 +49,7 @@ def get_version_from_git():
 class GetVersionCommand(distutils.cmd.Command):
     """A custom command to get the current project version inferred from git describe."""
 
-    description = 'gets the project version from git describe'
+    description = "gets the project version from git describe"
     user_options = []
 
     def initialize_options(self):
@@ -63,7 +65,7 @@ def run(self):
 class DownloadDatasets(distutils.cmd.Command):
     """A custom command to download the datasets used in the examples."""
 
-    description = 'downloads the datasets used in the examples'
+    description = "downloads the datasets used in the examples"
     user_options = []
 
     def initialize_options(self):
@@ -74,6 +76,7 @@ def finalize_options(self):
 
     def run(self):
         import psyki
+
         try:
             from test.resources.data import DATASETS
 
@@ -84,50 +87,50 @@ def run(self):
 
 
 setup(
-    name='psyki',  # Required
+    name="psyki",  # Required
     version=version,
-    description='Python-based implementation of PSyKI, i.e. a Platform for Symbolic Knowledge Injection',
-    license='Apache 2.0 License',
+    description="Python-based implementation of PSyKI, i.e. a Platform for Symbolic Knowledge Injection",
+    license="Apache 2.0 License",
     long_description=long_description,
-    long_description_content_type='text/markdown',
-    url='https://github.com/psykei/psyki-python',
-    author='Matteo Magnini',
-    author_email='[email protected]',
+    long_description_content_type="text/markdown",
+    url="https://github.com/psykei/psyki-python",
+    author="Matteo Magnini",
+    author_email="[email protected]",
     classifiers=[
-        'Development Status :: 3 - Alpha',
-        'Intended Audience :: Developers',
-        'Topic :: Software Development :: Libraries',
-        'Topic :: Scientific/Engineering :: Artificial Intelligence',
-        'License :: OSI Approved :: Apache Software License',
-        'Programming Language :: Python :: 3',
-        'Programming Language :: Python :: 3.9',
-        'Programming Language :: Python :: 3 :: Only',
-        'Programming Language :: Prolog'
+        "Development Status :: 3 - Alpha",
+        "Intended Audience :: Developers",
+        "Topic :: Software Development :: Libraries",
+        "Topic :: Scientific/Engineering :: Artificial Intelligence",
+        "License :: OSI Approved :: Apache Software License",
+        "Programming Language :: Python :: 3",
+        "Programming Language :: Python :: 3.9",
+        "Programming Language :: Python :: 3 :: Only",
+        "Programming Language :: Prolog",
     ],
-    keywords='symbolic knowledge injection, ski, symbolic ai',  # Optional
+    keywords="symbolic knowledge injection, ski, symbolic ai",  # Optional
     # package_dir={'': 'src'},  # Optional
     packages=find_packages(),  # Required
     include_package_data=True,
-    python_requires='>=3.9.13, <3.10',
+    python_requires=">=3.9.13, <3.10",
     install_requires=[
-        'tensorflow>=2.14.1,<2.15.0',
-        'numpy>=1.22.3',
-        '2ppy>=0.4.0',
-        'scikit-learn>=1.0.2',
-        'pandas>=1.4.2',
-        'codecarbon>=2.2.4,<2.3.0',
-        'prometheus_client>=0.17.0'
+        "tensorflow>=2.14.1,<2.15.0",
+        "numpy>=1.22.3",
+        "2ppy>=0.4.0",
+        "scikit-learn>=1.0.2",
+        "pandas>=1.4.2",
+        "codecarbon>=2.2.4,<2.3.0",
+        "prometheus_client>=0.17.0",
     ],  # Optional
-    zip_safe = False,
-    platforms = "Independant",
+    zip_safe=False,
+    platforms="Independant",
     project_urls={  # Optional
-        'Bug Reports': 'https://github.com/psykei/psyki-python/issues',
+        "Bug Reports": "https://github.com/psykei/psyki-python/issues",
         # 'Funding': 'https://donate.pypi.org',
         # 'Say Thanks!': 'http://saythanks.io/to/example',
-        'Source': 'https://github.com/psykei/psyki-python',
+        "Source": "https://github.com/psykei/psyki-python",
     },
     cmdclass={
-        'get_project_version': GetVersionCommand,
-        'download_datasets': DownloadDatasets
+        "get_project_version": GetVersionCommand,
+        "download_datasets": DownloadDatasets,
     },
 )

test/psyki/ski/__init__.py

@@ -12,7 +12,7 @@
 
 
 SEED = 0  # Set seed to make sure that the test is reproducible
-TEST_SIZE = 1/3  # 1/3 is a fairly common test size
+TEST_SIZE = 1 / 3  # 1/3 is a fairly common test size
 EPOCHS = 2  # Just check if it runs without errors (2 epochs are required because only one could not catch some errors)
 BATCH_SIZE = 32  # 32 is a fairly common batch size
 VERBOSE = 0  # 0 = silent, 1 = progress bar, 2 = one line per epoch
@@ -33,7 +33,12 @@ def _test_educated_training(self, educated: Model, dataset: pd.DataFrame):
         psyki.logger.info(f"testing educated training")
         time = datetime.now()
         set_seed(SEED)
-        train, test = train_test_split(dataset, test_size=TEST_SIZE, random_state=SEED, stratify=dataset.iloc[:, -1:])
+        train, test = train_test_split(
+            dataset,
+            test_size=TEST_SIZE,
+            random_state=SEED,
+            stratify=dataset.iloc[:, -1:],
+        )
         train_x, train_y = train.iloc[:, :-1], to_categorical(train.iloc[:, -1:])
         test_x, test_y = test.iloc[:, :-1], to_categorical(test.iloc[:, -1:])
         history = educated.fit(