Polars in hvplot.plot: avoid registering the hvplot accessor and simple test

hvplot/plotting/__init__.py

@@ -31,7 +31,7 @@ def plot(data, kind, **kwargs):
             no_none_kwargs[k] = v
 
     if is_polars(data):
-        from hvplot.polars import hvPlotTabularPolars
+        from .core import hvPlotTabularPolars
         return hvPlotTabularPolars(data)(kind=kind, **no_none_kwargs)
     return hvPlotTabular(data)(kind=kind, **no_none_kwargs)
 

hvplot/plotting/core.py

@@ -1,3 +1,4 @@
+import itertools
 from collections import defaultdict
 
 import param
@@ -1862,6 +1863,47 @@ def labels(self, x=None, y=None, text=None, **kwds):
         return self(x, y, text=text, kind="labels", **kwds)
 
 
+class hvPlotTabularPolars(hvPlotTabular):
+    def _get_converter(self, x=None, y=None, kind=None, **kwds):
+        import polars as pl
+
+        params = dict(self._metadata, **kwds)
+        x = x or params.pop("x", None)
+        y = y or params.pop("y", None)
+        kind = kind or params.pop("kind", None)
+
+        # Find columns which should be converted for LazyDataFrame and DataFrame
+        if isinstance(self._data, (pl.LazyFrame, pl.DataFrame)):
+            if params.get("hover_cols") == "all":
+                columns = list(self._data.columns)
+            else:
+                possible_columns = [
+                    [v] if isinstance(v, str) else v
+                    for v in params.values()
+                    if isinstance(v, (str, list))
+                ]
+                columns = (
+                    set(self._data.columns) & set(itertools.chain(*possible_columns))
+                ) or {self._data.columns[0]}
+                xs = x if is_list_like(x) else (x,)
+                ys = y if is_list_like(y) else (y,)
+                columns |= {*xs, *ys}
+                columns.discard(None)
+
+        if isinstance(self._data, pl.DataFrame):
+            data = self._data.select(columns).to_pandas()
+        elif isinstance(self._data, pl.Series):
+            data = self._data.to_pandas()
+        elif isinstance(self._data, pl.LazyFrame):
+            data = self._data.select(columns).collect().to_pandas()
+        else:
+            raise ValueError(
+                "Only Polars DataFrame, Series, and LazyFrame are supported"
+            )
+
+        return HoloViewsConverter(data, x, y, kind=kind, **params)
+
+
 class hvPlot(hvPlotTabular):
     """
     The plotting method: `df.hvplot(...)` creates a plot similarly to the familiar Pandas

hvplot/polars.py

@@ -1,50 +1,6 @@
 """Adds the `.hvplot` method to pl.DataFrame, pl.LazyFrame and pl.Series"""
-import itertools
-
-from hvplot import hvPlotTabular, post_patch
-from hvplot.converter import HoloViewsConverter
-from hvplot.util import is_list_like
-
-
-class hvPlotTabularPolars(hvPlotTabular):
-    def _get_converter(self, x=None, y=None, kind=None, **kwds):
-        import polars as pl
-
-        params = dict(self._metadata, **kwds)
-        x = x or params.pop("x", None)
-        y = y or params.pop("y", None)
-        kind = kind or params.pop("kind", None)
-
-        # Find columns which should be converted for LazyDataFrame and DataFrame
-        if isinstance(self._data, (pl.LazyFrame, pl.DataFrame)):
-            if params.get("hover_cols") == "all":
-                columns = list(self._data.columns)
-            else:
-                possible_columns = [
-                    [v] if isinstance(v, str) else v
-                    for v in params.values()
-                    if isinstance(v, (str, list))
-                ]
-                columns = (
-                    set(self._data.columns) & set(itertools.chain(*possible_columns))
-                ) or {self._data.columns[0]}
-                xs = x if is_list_like(x) else (x,)
-                ys = y if is_list_like(y) else (y,)
-                columns |= {*xs, *ys}
-                columns.discard(None)
-
-        if isinstance(self._data, pl.DataFrame):
-            data = self._data.select(columns).to_pandas()
-        elif isinstance(self._data, pl.Series):
-            data = self._data.to_pandas()
-        elif isinstance(self._data, pl.LazyFrame):
-            data = self._data.select(columns).collect().to_pandas()
-        else:
-            raise ValueError(
-                "Only Polars DataFrame, Series, and LazyFrame are supported"
-            )
-
-        return HoloViewsConverter(data, x, y, kind=kind, **params)
+from hvplot import post_patch
+from hvplot.plotting.core import hvPlotTabularPolars
 
 
 def patch(name="hvplot", extension="bokeh", logo=False):

hvplot/tests/testplotting.py

@@ -1,13 +1,23 @@
 """
 Tests pandas.options.backend setting
 """
-from packaging.version import Version
 from unittest import TestCase, SkipTest
+
+import holoviews as hv
 import pandas as pd
+import pytest
 
+from packaging.version import Version
 from parameterized import parameterized
 
-from ..converter import HoloViewsConverter
+from hvplot.converter import HoloViewsConverter
+from hvplot.plotting import plot
+
+try:
+    import polars as pl
+    skip_polar = False
+except ImportError:
+    skip_polar = True
 
 
 no_args = ['line', 'area', 'hist', 'box', 'kde', 'density', 'bar', 'barh']
@@ -58,3 +68,10 @@ def setUp(self):
             raise SkipTest('entrypoints for plotting.backends was added '
                            'in pandas 0.25.1')
         pd.options.plotting.backend = 'hvplot'
+
+
+@pytest.mark.skipif(skip_polar, reason="polars not installed")
+def test_plot_supports_polars():
+    dfp = pl.DataFrame(pd._testing.makeDataFrame())
+    out = plot(dfp, 'line')
+    assert isinstance(out, hv.Curve)