Activate additional ruff rules

conftest.py

@@ -0,0 +1,30 @@
+"""Configure our testing suite."""
+
+import networkx as nx
+import numpy as np
+import pytest
+import toponetx as tnx
+
+
+@pytest.fixture(autouse=True)
+def doctest_default_imports(doctest_namespace) -> None:
+    """Add default imports to the doctest namespace.
+
+    This fixture adds the following default imports to every doctest, so that their use
+    is consistent across all doctests without boilerplate imports polluting the
+    doctests themselves:
+
+    .. code-block:: python
+
+        import numpy as np
+        import networkx as nx
+        import toponetx as tnx
+
+    Parameters
+    ----------
+    doctest_namespace : dict
+        The namespace of the doctest.
+    """
+    doctest_namespace["np"] = np
+    doctest_namespace["nx"] = nx
+    doctest_namespace["tnx"] = tnx

docs/conf.py

@@ -3,7 +3,7 @@
 # -- Project information -----------------------------------------------------
 
 project = "TopoEmbedX"
-copyright = "2022-2023, PyT-Team, Inc."
+copyright = "2022-2023, PyT-Team, Inc."  # noqa: A001
 author = "PyT-Team Authors"
 language = "en"
 

pyproject.toml

@@ -113,20 +113,49 @@ select = [
     "E", # code style
     "W", # warnings
     "I", # import order
+    "D", # pydocstyle rules
     "UP", # pyupgrade rules
+    "YTT", # flake8-2020 rules
+    "S", # bandit rules
+    "BLE", # blind except
     "B", # bugbear rules
+    "A", # builtin shadowing
+    "COM", # comma rules
+    "C4", # comprehensions
+    "DTZ", # datetime rules
+    "T10", # debugger calls
+    "FA", # future annotations
+    "ISC", # implicit str concatenation
+    "ICN", # import conventions
+    "LOG", # logging rules
+    "G", # logging format rules
     "PIE", # pie rules
     "Q", # quote rules
+    "RSE", # raise rules
     "RET", # return rules
+    "SLOT", # slot rules
     "SIM", # code simplifications
+    "TID", # tidy imports
+    "TC", # type checking rules
+    "PTH", # use pathlib
+    "PD", # pandas rules
+    "PLC", # pylint conventions
+    "PLE", # pylint errors
+    "FLY", # flynt
     "NPY", # numpy rules
     "PERF", # performance rules
+    "FURB", # refurb
     "RUF", # miscellaneous rules
 ]
-ignore = ["E501"] # line too long
+ignore = [
+    "E501",    # line too long
+    "COM812",  # trailing commas; conflict with `ruff format`
+    "ISC001",  # implicitly single-line str concat; conflict with `ruff format`
+]
 
 [tool.ruff.lint.per-file-ignores]
-"__init__.py" = ["F401", "F403"]
+"__init__.py" = ["F403"]
+"test/**.py" = ["S101"]
 
 [tool.ruff.lint.pydocstyle]
 convention = "numpy"

test/test_neighborhood.py

@@ -29,21 +29,21 @@ def test_neighborhood_from_complex_matrix_dimension_cell_complex(self):
         cc2 = tnx.classes.CellComplex([[0, 1, 2], [1, 2, 3]])
 
         ind, A = tex.neighborhood.neighborhood_from_complex(cc1)
-        assert A.todense().shape == tuple([9, 9])
+        assert A.todense().shape == (9, 9)
         assert len(ind) == 9
 
         ind, A = tex.neighborhood.neighborhood_from_complex(cc2)
-        assert A.todense().shape == tuple([4, 4])
+        assert A.todense().shape == (4, 4)
         assert len(ind) == 4
 
         ind, A = tex.neighborhood.neighborhood_from_complex(
             cc1, neighborhood_type="coadj"
         )
-        assert A.todense().shape == tuple([9, 9])
+        assert A.todense().shape == (9, 9)
         assert len(ind) == 9
 
         ind, A = tex.neighborhood.neighborhood_from_complex(
             cc2, neighborhood_type="coadj"
         )
-        assert A.todense().shape == tuple([4, 4])
+        assert A.todense().shape == (4, 4)
         assert len(ind) == 4

test/test_tutorials.py

@@ -1,13 +1,20 @@
 """Unit tests for the tutorials."""
 
-import glob
 import subprocess
 import tempfile
+from pathlib import Path
 
 import pytest
 
 
 def _exec_tutorial(path):
+    """Execute the notebooks for testing in the given directory.
+
+    Parameters
+    ----------
+    path : str
+        Path to the tutorials directory.
+    """
     with tempfile.NamedTemporaryFile(suffix=".ipynb") as tmp_file:
         args = [
             "jupyter",
@@ -21,14 +28,20 @@ def _exec_tutorial(path):
             tmp_file.name,
             path,
         ]
-        subprocess.check_call(args)
+        subprocess.check_call(args)  # noqa: S603
 
 
 TUTORIALS_DIR = "tutorials"
-paths = sorted(glob.glob(f"{TUTORIALS_DIR}/*.ipynb"))
+paths = sorted(Path(TUTORIALS_DIR).glob("*.ipynb"))
 
 
 @pytest.mark.parametrize("path", paths)
 def test_tutorial(path):
-    """Test the tutorials."""
+    """Test the tutorials.
+
+    Parameters
+    ----------
+    path : str
+        Path to the tutorials directory.
+    """
     _exec_tutorial(path)

topoembedx/__init__.py

@@ -1,8 +1,3 @@
 """Initialize the library with modules and other content."""
 
-from .classes.cell2vec import Cell2Vec
-from .classes.cell_diff2vec import CellDiff2Vec
-from .classes.deepcell import DeepCell
-from .classes.higher_order_laplacian_eigenmaps import HigherOrderLaplacianEigenmaps
-from .classes.hoglee import HOGLEE
-from .classes.hope import HOPE
+from .classes import *

topoembedx/classes/__init__.py

@@ -1 +1,9 @@
 """Initialize the classes module of TopoEmbedX."""
+
+from .cell2vec import *
+from .cell_diff2vec import *
+from .deepcell import *
+from .higher_order_laplacian_eigenmaps import *
+from .hoglee import *
+from .hope import *
+from .random_walks import *

topoembedx/classes/cell2vec.py

@@ -93,15 +93,15 @@ def __init__(
 
     def fit(
         self,
-        complex: tnx.Complex,
+        domain: tnx.Complex,
         neighborhood_type: Literal["adj", "coadj"] = "adj",
         neighborhood_dim=None,
     ) -> None:
         """Fit a Cell2Vec model.
 
         Parameters
         ----------
-        complex : toponetx.classes.Complex
+        domain : toponetx.classes.Complex
             A complex object. The complex object can be one of the following:
             - CellComplex
             - CombinatorialComplex
@@ -111,7 +111,7 @@ def fit(
         neighborhood_type : {"adj", "coadj"}, default="adj"
             The type of neighborhood to compute. "adj" for adjacency matrix, "coadj" for coadjacency matrix.
         neighborhood_dim : dict
-            The integer parmaters needed to specify the neighborhood of the cells to generate the embedding.
+            The integer parameters needed to specify the neighborhood of the cells to generate the embedding.
             In TopoNetX  (co)adjacency neighborhood matrices are specified via one or two parameters.
             - For Cell/Simplicial/Path complexes (co)adjacency matrix is specified by a single parameter, this is precisely
             neighborhood_dim["rank"].
@@ -128,7 +128,7 @@ def fit(
         colored hypergraph.
         """
         self.ind, self.A = neighborhood_from_complex(
-            complex, neighborhood_type, neighborhood_dim
+            domain, neighborhood_type, neighborhood_dim
         )
 
         g = nx.from_numpy_array(self.A)

topoembedx/classes/cell_diff2vec.py

@@ -73,15 +73,15 @@ def __init__(
 
     def fit(
         self,
-        complex: tnx.Complex,
+        domain: tnx.Complex,
         neighborhood_type: Literal["adj", "coadj"] = "adj",
         neighborhood_dim=None,
     ) -> None:
         """Fit a CellDiff2Vec model.
 
         Parameters
         ----------
-        complex : toponetx.classes.Complex
+        domain : toponetx.classes.Complex
             A complex object. The complex object can be one of the following:
             - CellComplex
             - CombinatorialComplex
@@ -91,7 +91,7 @@ def fit(
         neighborhood_type : {"adj", "coadj"}, default="adj"
             The type of neighborhood to compute. "adj" for adjacency matrix, "coadj" for coadjacency matrix.
         neighborhood_dim : dict
-            The integer parmaters needed to specify the neighborhood of the cells to generate the embedding.
+            The integer parameters needed to specify the neighborhood of the cells to generate the embedding.
             In TopoNetX  (co)adjacency neighborhood matrices are specified via one or two parameters.
             - For Cell/Simplicial/Path complexes (co)adjacency matrix is specified by a single parameter, this is precisely
             neighborhood_dim["rank"].
@@ -108,7 +108,7 @@ def fit(
         colored hypergraph.
         """
         self.ind, self.A = neighborhood_from_complex(
-            complex, neighborhood_type, neighborhood_dim
+            domain, neighborhood_type, neighborhood_dim
         )
 
         self.A.setdiag(1)

topoembedx/classes/deepcell.py

@@ -73,15 +73,15 @@ def __init__(
 
     def fit(
         self,
-        complex: tnx.Complex,
+        domain: tnx.Complex,
         neighborhood_type: Literal["adj", "coadj"] = "adj",
         neighborhood_dim=None,
     ) -> None:
         """Fit the model.
 
         Parameters
         ----------
-        complex : toponetx.classes.Complex
+        domain : toponetx.classes.Complex
             A complex object. The complex object can be one of the following:
             - CellComplex
             - CombinatorialComplex
@@ -91,7 +91,7 @@ def fit(
         neighborhood_type : {"adj", "coadj"}, default="adj"
             The type of neighborhood to compute. "adj" for adjacency matrix, "coadj" for coadjacency matrix.
         neighborhood_dim : dict
-            The integer parmaters needed to specify the neighborhood of the cells to generate the embedding.
+            The integer parameters needed to specify the neighborhood of the cells to generate the embedding.
             In TopoNetX  (co)adjacency neighborhood matrices are specified via one or two parameters.
             - For Cell/Simplicial/Path complexes (co)adjacency matrix is specified by a single parameter, this is precisely
             neighborhood_dim["rank"].
@@ -108,7 +108,7 @@ def fit(
         colored hypergraph.
         """
         self.ind, self.A = neighborhood_from_complex(
-            complex, neighborhood_type, neighborhood_dim
+            domain, neighborhood_type, neighborhood_dim
         )
 
         self.A.setdiag(1)

topoembedx/classes/higher_order_laplacian_eigenmaps.py

@@ -38,15 +38,15 @@ def __init__(
 
     def fit(
         self,
-        complex: tnx.Complex,
+        domain: tnx.Complex,
         neighborhood_type: Literal["adj", "coadj"] = "adj",
         neighborhood_dim=None,
     ) -> None:
         """Fit a Higher Order Laplacian Eigenmaps model.
 
         Parameters
         ----------
-        complex : toponetx.classes.Complex
+        domain : toponetx.classes.Complex
             A complex object. The complex object can be one of the following:
             - CellComplex
             - CombinatorialComplex
@@ -56,7 +56,7 @@ def fit(
         neighborhood_type : {"adj", "coadj"}, default="adj"
             The type of neighborhood to compute. "adj" for adjacency matrix, "coadj" for coadjacency matrix.
         neighborhood_dim : dict
-            The integer parmaters needed to specify the neighborhood of the cells to generate the embedding.
+            The integer parameters needed to specify the neighborhood of the cells to generate the embedding.
             In TopoNetX  (co)adjacency neighborhood matrices are specified via one or two parameters.
             - For Cell/Simplicial/Path complexes (co)adjacency matrix is specified by a single parameter, this is precisely
             neighborhood_dim["rank"].
@@ -73,7 +73,7 @@ def fit(
         colored hypergraph.
         """
         self.ind, self.A = neighborhood_from_complex(
-            complex, neighborhood_type, neighborhood_dim
+            domain, neighborhood_type, neighborhood_dim
         )
 
         self.A.setdiag(1)

topoembedx/classes/hoglee.py

@@ -30,15 +30,15 @@ def __init__(self, dimensions: int = 128, seed: int = 42):
 
     def fit(
         self,
-        complex: tnx.Complex,
+        domain: tnx.Complex,
         neighborhood_type: Literal["adj", "coadj"] = "adj",
         neighborhood_dim=None,
     ) -> None:
         """Fit a Higher Order Geometric Laplacian EigenMaps model.
 
         Parameters
         ----------
-        complex : toponetx.classes.Complex
+        domain : toponetx.classes.Complex
             A complex object. The complex object can be one of the following:
             - CellComplex
             - CombinatorialComplex
@@ -48,7 +48,7 @@ def fit(
         neighborhood_type : {"adj", "coadj"}, default="adj"
             The type of neighborhood to compute. "adj" for adjacency matrix, "coadj" for coadjacency matrix.
         neighborhood_dim : dict
-            The integer parmaters needed to specify the neighborhood of the cells to generate the embedding.
+            The integer parameters needed to specify the neighborhood of the cells to generate the embedding.
             In TopoNetX  (co)adjacency neighborhood matrices are specified via one or two parameters.
             - For Cell/Simplicial/Path complexes (co)adjacency matrix is specified by a single parameter, this is precisely
             neighborhood_dim["rank"].
@@ -65,7 +65,7 @@ def fit(
         colored hypergraph.
         """
         self.ind, self.A = neighborhood_from_complex(
-            complex, neighborhood_type, neighborhood_dim
+            domain, neighborhood_type, neighborhood_dim
         )
 
         self.A.setdiag(1)