clean up

Author: hoxbro

holoviews/plotting/bokeh/element.py

@@ -3260,7 +3260,7 @@ def _get_colormapper(
         cmapper = self.handles.get(name)
         if cmapper is not None:
             try:
-                palette_changed = cmapper.palette != palette
+                palette_changed = bool(cmapper.palette != palette)
             except Exception:
                 palette_changed = True
             if palette_changed:

holoviews/tests/element/test_selection.py

@@ -10,6 +10,7 @@
 
 import holoviews as hv
 from holoviews.element.selection import spatial_select_columnar
+from holoviews.streams import Selection1D, SelectionXY
 from holoviews.testing import assert_data_equal, assert_dict_equal, assert_element_equal
 
 from .._deps import dd, dd_skip, ds_skip, shapely_skip, spd_skip
@@ -222,8 +223,6 @@ def test_distribution_single_inverted(self):
 
 
 class TestSelectionBarsExpr:
-    """Tests for SelectionBarsExpr — tap/click-to-select on Bars elements."""
-
     def setup_method(self):
         import holoviews.plotting.bokeh  # noqa: F401
 
@@ -234,16 +233,11 @@ def teardown_method(self):
         hv.Store.current_backend = self._backend
 
     def _make_bars(self):
-        from holoviews.element import Bars
-
-        return Bars(
-            (["A", "B", "C", "D"], [10, 20, 5, 15]),
-            kdims=["category"],
-            vdims=["count"],
+        return hv.Bars(
+            (["A", "B", "C", "D"], [10, 20, 5, 15]), kdims=["category"], vdims=["count"]
         )
 
     def test_bars_tap_single_category(self):
-        """Clicking the second bar (index 1 → 'B') returns isin(['B'])."""
         bars = self._make_bars()
         expr, bbox, region = bars._get_selection_expr_for_stream_value(index=[1])
         assert bbox is None
@@ -255,7 +249,6 @@ def test_bars_tap_single_category(self):
         )
 
     def test_bars_tap_multiple_categories(self):
-        """Clicking bars at indices 0 and 2 returns isin(['A', 'C'])."""
         bars = self._make_bars()
         expr, bbox, region = bars._get_selection_expr_for_stream_value(index=[0, 2])
         assert bbox is None
@@ -267,21 +260,18 @@ def test_bars_tap_multiple_categories(self):
         )
 
     def test_bars_tap_empty_index(self):
-        """An empty index list (clicked outside all bars) returns (None, None, None)."""
         bars = self._make_bars()
         expr, bbox, region = bars._get_selection_expr_for_stream_value(index=[])
         assert expr is None
         assert bbox is None
         assert region is None
 
     def test_bars_tap_no_index_kwarg(self):
-        """No index kwarg at all falls through to the parent (no-op for no bounds)."""
         bars = self._make_bars()
         expr, _bbox, _region = bars._get_selection_expr_for_stream_value()
         assert expr is None
 
     def test_bars_box_select_categorical(self):
-        """Box-select over categorical x-axis still works via Selection1DExpr."""
         bars = self._make_bars()
         expr, bbox, _region = bars._get_selection_expr_for_stream_value(
             bounds=(0, 0, 2, 25), x_selection=["A", "B", "C"]
@@ -293,13 +283,10 @@ def test_bars_box_select_categorical(self):
         )
 
     def test_bars_selection_streams_include_selection1d(self):
-        from holoviews.streams import Selection1D, SelectionXY
-
         assert Selection1D in hv.Bars._selection_streams
         assert SelectionXY in hv.Bars._selection_streams
 
     def test_barplot_default_tools_include_tap(self):
-        import holoviews.plotting.bokeh  # noqa: F401
         from holoviews.plotting.bokeh.chart import BarPlot
 
         assert "tap" in BarPlot.param.default_tools.default

holoviews/tests/operation/test_operation.py

@@ -997,8 +997,9 @@ def test_decimate_same_y(self):
         pd.testing.assert_series_equal(data["x"], output["x"])
         pd.testing.assert_series_equal(data["y"], output["y"])
 
+
+class TestCategoricalAgg:
     def test_categorical_agg_count(self):
-        """Default aggregation counts rows per category."""
         df = pd.DataFrame(
             {
                 "x": [1, 2, 3, 4, 5],
@@ -1020,13 +1021,8 @@ def test_categorical_agg_count(self):
         assert data["B"] == 2
 
     def test_categorical_agg_sum(self):
-        """Sum aggregation on a value dimension."""
         df = pd.DataFrame(
-            {
-                "x": [1, 2, 3, 4],
-                "y": [10, 20, 30, 40],
-                "category": ["A", "B", "A", "B"],
-            }
+            {"x": [1, 2, 3, 4], "y": [10, 20, 30, 40], "category": ["A", "B", "A", "B"]}
         )
         points = hv.Points(df, kdims=["x", "y"], vdims=["category"])
         bars = categorical_agg(
@@ -1045,13 +1041,8 @@ def test_categorical_agg_sum(self):
         assert data["B"] == 60  # 20 + 40
 
     def test_categorical_agg_mean(self):
-        """Mean aggregation on a value dimension."""
         df = pd.DataFrame(
-            {
-                "x": [1, 2, 3, 4],
-                "y": [10, 20, 30, 40],
-                "category": ["A", "B", "A", "B"],
-            }
+            {"x": [1, 2, 3, 4], "y": [10, 20, 30, 40], "category": ["A", "B", "A", "B"]}
         )
         points = hv.Points(df, kdims=["x", "y"], vdims=["category"])
         bars = categorical_agg(points, dimension="category", value_dimension="y", function=np.mean)
@@ -1065,33 +1056,23 @@ def test_categorical_agg_mean(self):
         assert data["B"] == 30.0  # (20 + 40) / 2
 
     def test_categorical_agg_custom_label(self):
-        """Custom label overrides auto-generated label."""
-        df = pd.DataFrame(
-            {
-                "x": [1, 2, 3],
-                "y": [10, 20, 30],
-                "category": ["A", "B", "A"],
-            }
-        )
+        df = pd.DataFrame({"x": [1, 2, 3], "y": [10, 20, 30], "category": ["A", "B", "A"]})
         points = hv.Points(df, kdims=["x", "y"], vdims=["category"])
         bars = categorical_agg(points, dimension="category", label="Total")
 
         assert bars.vdims[0].name == "Total"
 
     def test_categorical_agg_missing_dimension_error(self):
-        """Raises ValueError when the specified dimension doesn't exist."""
         points = hv.Points([(1, 2), (3, 4)])
         with pytest.raises(ValueError, match="not found"):
             categorical_agg(points, dimension="nonexistent")
 
     def test_categorical_agg_no_dimension_error(self):
-        """Raises ValueError when dimension param is not provided."""
         points = hv.Points([(1, 2), (3, 4)])
         with pytest.raises(ValueError, match="required"):
             categorical_agg(points)
 
     def test_categorical_agg_empty_element(self):
-        """Returns an empty Bars element when the input is empty."""
         df = pd.DataFrame({"x": [], "y": [], "category": []})
         points = hv.Points(df, kdims=["x", "y"], vdims=["category"])
         bars = categorical_agg(points, dimension="category")
@@ -1100,14 +1081,7 @@ def test_categorical_agg_empty_element(self):
         assert len(bars) == 0
 
     def test_categorical_agg_preserves_lineage(self):
-        """Operation output has a pipeline that references the source element."""
-        df = pd.DataFrame(
-            {
-                "x": [1, 2, 3],
-                "y": [10, 20, 30],
-                "category": ["A", "B", "A"],
-            }
-        )
+        df = pd.DataFrame({"x": [1, 2, 3], "y": [10, 20, 30], "category": ["A", "B", "A"]})
         points = hv.Points(df, kdims=["x", "y"], vdims=["category"])
         bars = categorical_agg(points, dimension="category")