style(ruff): clear ruff check violations (#175)

.pre-commit-config.yaml

@@ -4,7 +4,7 @@ repos:
     hooks:
       - id: prettier
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.3.2
+    rev: v0.8.0
     hooks:
       - id: ruff
         args: [--fix]

examples/Preprocess your data with recipes.ipynb

@@ -490,7 +490,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "id": "dc04f24e-c8cb-4580-b502-a9410c64a126",
    "metadata": {},
    "outputs": [],
@@ -510,7 +510,7 @@
     "    from skorch import NeuralNetClassifier\n",
     "\n",
     "    class MyModule(nn.Module):\n",
-    "        def __init__(self, num_units=10, nonlin=nn.ReLU()):\n",
+    "        def __init__(self, num_units=10, nonlin=nn.ReLU()):  # noqa: B008\n",
     "            super().__init__()\n",
     "\n",
     "            self.dense0 = nn.Linear(10, num_units)\n",
@@ -525,7 +525,7 @@
     "            X = self.dropout(X)\n",
     "            X = self.nonlin(self.dense1(X))\n",
     "            X = self.softmax(self.output(X))\n",
-    "            return X\n",
+    "            return X  # noqa: RET504\n",
     "\n",
     "    mod = NeuralNetClassifier(\n",
     "        MyModule,\n",

ibis_ml/core.py

@@ -478,7 +478,7 @@ def _name_estimators(estimators):
     for i in reversed(range(len(estimators))):
         name = names[i]
         if name in namecount:
-            names[i] += "-%d" % namecount[name]
+            names[i] += f"-{namecount[name]}"
             namecount[name] -= 1
 
     return list(zip(names, estimators))

ibis_ml/select.py

@@ -30,7 +30,7 @@ def __repr__(self):
         return f"{name}({args})"
 
     def __eq__(self, other):
-        return type(self) == type(other) and all(
+        return isinstance(other, type(self)) and all(
             getattr(self, name) == getattr(other, name) for name in self._fields
         )
 

ibis_ml/steps/_discretize.py

@@ -30,7 +30,7 @@ class DiscretizeKBins(Step):
 
 
     Raises
-    ----------
+    ------
     ValueError
         If `n_bins` is less than or equal to 1 or if an unsupported
         `strategy` is provided.

ibis_ml/utils/_pprint.py

@@ -111,7 +111,7 @@ def _safe_repr(self, object, context, maxlevels, level):
             if krecur or vrecur:
                 recursive = True
         del context[objid]
-        return "{%s}" % ", ".join(components), readable, recursive
+        return f"{{{', '.join(components)}}}", readable, recursive
 
     if (issubclass(typ, list) and r is list.__repr__) or (
         issubclass(typ, tuple) and r is tuple.__repr__

pyproject.toml

@@ -86,6 +86,7 @@ ignore = [
 [tool.ruff.lint.per-file-ignores]
 "__init__.py" = ["F401", "F403"]
 "docs/**/*.py" = ["INP001"]
+"examples/*.ipynb" = ["E501", "ERA001", "I001", "T201"]
 
 [tool.ruff.lint.isort]
 split-on-trailing-comma = false

tests/test_core.py

@@ -22,7 +22,7 @@ def transform_table(self, table):
         return table.order_by(ibis.random())
 
 
-@pytest.fixture()
+@pytest.fixture
 def df():
     return pd.DataFrame(
         {
@@ -34,7 +34,7 @@ def df():
     )
 
 
-@pytest.fixture()
+@pytest.fixture
 def table(df):
     return ibis.memtable(df)
 
@@ -410,12 +410,11 @@ def test_set_params_passes_all_parameters():
 def test_set_params_updates_valid_params():
     # Check that set_params tries to set `replacement_mutateat.inputs`, not
     # `original_mutateat.inputs`.
-    original_mutateat = ml.MutateAt("dep_time", ibis._.hour() * 60 + ibis._.minute())  # noqa: SLF001
+    original_mutateat = ml.MutateAt("dep_time", ibis._.hour() * 60 + ibis._.minute())
     rec = ml.Recipe(
-        original_mutateat,
-        ml.MutateAt(ml.timestamp(), ibis._.epoch_seconds()),  # noqa: SLF001
+        original_mutateat, ml.MutateAt(ml.timestamp(), ibis._.epoch_seconds())
     )
-    replacement_mutateat = ml.MutateAt("arr_time", ibis._.hour() * 60 + ibis._.minute())  # noqa: SLF001
+    replacement_mutateat = ml.MutateAt("arr_time", ibis._.hour() * 60 + ibis._.minute())
     rec.set_params(
         **{"mutateat-1": replacement_mutateat, "mutateat-1__inputs": ml.cols("arrival")}
     )

tests/test_encode.py

@@ -8,7 +8,7 @@
 import ibis_ml as ml
 
 
-@pytest.fixture()
+@pytest.fixture
 def t_train():
     return ibis.memtable(
         {
@@ -27,7 +27,7 @@ def t_train():
     )
 
 
-@pytest.fixture()
+@pytest.fixture
 def t_test():
     return ibis.memtable(
         {

tests/test_generate_features.py

@@ -5,7 +5,7 @@
 import ibis_ml as ml
 
 
-@pytest.fixture()
+@pytest.fixture
 def train_table():
     N = 100
     return ibis.memtable({"x": list(range(N)), "y": [10] * N, "z": ["s"] * N})

tests/test_impute.py

@@ -9,7 +9,7 @@
 import ibis_ml as ml
 
 
-@pytest.fixture()
+@pytest.fixture
 def train_table():
     return ibis.memtable(
         {

tests/test_pprint.py

@@ -3,15 +3,15 @@
 import ibis_ml as ml
 
 
-@pytest.fixture()
+@pytest.fixture
 def rec():
     imputer = ml.ImputeMean(ml.numeric())
     scaler = ml.ScaleStandard(ml.numeric())
     encoder = ml.OneHotEncode(ml.string(), min_frequency=20, max_categories=10)
     return ml.Recipe(imputer, scaler, encoder)
 
 
-@pytest.fixture()
+@pytest.fixture
 def pipe(rec):
     pytest.importorskip("sklearn")
     from sklearn.pipeline import Pipeline