Fix ibis duckdb no rowid

holoviews/core/data/ibis.py

@@ -111,7 +111,13 @@ def nonzero(cls, dataset):
     @cached
     def range(cls, dataset, dimension):
         dimension = dataset.get_dimension(dimension, strict=True)
-        if cls.dtype(dataset, dimension).kind in 'SUO':
+        if cls.dtype(dataset, dimension).kind == 'O':
+            # Can this be done more efficiently?
+            column = dataset.data[dimension.name].execute()
+            first = column.iloc[0]
+            last = column.iloc[-1]
+            return first, last
+        if cls.dtype(dataset, dimension).kind in 'SU':
             return None, None
         if dimension.nodata is not None:
             return Interface.range(dataset, dimension)
@@ -172,7 +178,9 @@ def dtype(cls, dataset, dimension):
         dimension = dataset.get_dimension(dimension)
         return dataset.data.head(0).execute().dtypes[dimension.name]
 
-    dimension_type = dtype
+    @classmethod
+    def dimension_type(cls, dataset, dim):
+        return cls.dtype(dataset, dim).type
 
     @classmethod
     def sort(cls, dataset, by=[], reverse=False):

holoviews/core/util.py

@@ -890,7 +890,6 @@ def isfinite(val):
         return finite & (~pd.isna(val))
     return finite
 
-
 def isdatetime(value):
     """
     Whether the array or scalar is recognized datetime type.

holoviews/tests/core/data/test_ibisinterface.py

@@ -12,9 +12,12 @@
 import numpy as np
 import pandas as pd
 
+from bokeh.models import axes as bokeh_axes
+from holoviews import render
 from holoviews.core.data import Dataset
 from holoviews.core.spaces import HoloMap
 from holoviews.core.data.ibis import IbisInterface
+from holoviews.element.chart import Curve
 
 from .base import HeterogeneousColumnTests, ScalarColumnTests, InterfaceTests
 
@@ -100,6 +103,20 @@ def init_column_data(self):
             hm_db.table("hm"), kdims=[("x", "X")], vdims=[("y", "Y")]
         )
 
+        reference_df = pd.DataFrame(
+            {
+                "actual": [100, 150, 125, 140, 145, 135, 123],
+                "forecast": [90, 160, 125, 150, 141, 141, 120],
+                "numerical": [1.1, 1.9, 3.2, 3.8, 4.3, 5.0, 5.5],
+                "date": pd.date_range("2022-01-03", "2022-01-09"),
+                "string": ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"],
+            },
+        )
+        reference_db = create_temp_db(reference_df, "reference_df")
+        self.reference_table = Dataset(
+            reference_db.table("reference_df"), kdims=["numerical", "date", "string"], vdims=["actual", "forecast"]
+        )
+
     def test_dataset_array_init_hm(self):
         raise SkipTest("Not supported")
 
@@ -303,3 +320,90 @@ def test_dataset_iloc_ellipsis_list_cols(self):
 
         def test_dataset_boolean_index(self):
             raise SkipTest("Not supported")
+
+    def test_range(self):
+        assert IbisInterface.range(self.reference_table, "date") == (np.datetime64('2022-01-03'), np.datetime64('2022-01-09'))
+        assert IbisInterface.range(self.reference_table, "string") == ('Mon', 'Sun')
+        assert IbisInterface.range(self.reference_table, "numerical") == (np.float64(1.1), np.float64(5.5))
+
+    def test_dimension_type(self):
+        assert IbisInterface.dimension_type(self.reference_table, "date") is np.datetime64
+        assert IbisInterface.dimension_type(self.reference_table, "string") is np.object_
+        assert IbisInterface.dimension_type(self.reference_table, "numerical") is np.float64
+
+    def test_datetime_xaxis(self):
+        """Test to make sure a DateTimeAxis can be identified for the bokeh backend"""
+        plot_ibis = Curve(self.reference_table, kdims="date", vdims="actual")
+        # When
+        plot_bokeh = render(plot_ibis, "bokeh")
+        xaxis, yaxis = plot_bokeh.axis
+        # Then
+        assert isinstance(xaxis, bokeh_axes.DatetimeAxis)
+        assert isinstance(yaxis, bokeh_axes.LinearAxis)
+
+    def test_categorical_xaxis(self):
+        """Test to make sure a Categorical axis can be identified for the bokeh backend"""
+        plot_ibis = Curve(self.reference_table, kdims="string", vdims="actual")
+        # When
+        plot_bokeh = render(plot_ibis, "bokeh")
+        xaxis, yaxis = plot_bokeh.axis
+        # Then
+        assert isinstance(xaxis, bokeh_axes.CategoricalAxis)
+        assert isinstance(yaxis, bokeh_axes.LinearAxis)
+
+    def test_numerical_xaxis(self):
+        """Test to make sure a LinearAxis axis can be identified for the bokeh backend"""
+        plot_ibis = Curve(self.reference_table, kdims="numerical", vdims="actual")
+        # When
+        plot_bokeh = render(plot_ibis, "bokeh")
+        xaxis, yaxis = plot_bokeh.axis
+        # Then
+        assert isinstance(xaxis, bokeh_axes.LinearAxis)
+        assert isinstance(yaxis, bokeh_axes.LinearAxis)
+
+import pytest
+import ibis
+import duckdb
+from pathlib import Path
+
+def create_pandas_connection(df: pd.DataFrame, *args, **kwargs):
+    return ibis.pandas.connect({"df": df})
+
+def create_duckdb_connection(df: pd.DataFrame, *args, **kwargs):
+    tmpdir = kwargs["tmpdir"]
+    filename = str(Path(tmpdir)/"db.db")
+    duckdb_con = duckdb.connect(filename)
+    duckdb_con.execute("CREATE TABLE df AS SELECT * FROM df")
+
+    return ibis.duckdb.connect(filename)
+
+def create_sqlite_connection(df: pd.DataFrame):
+    return create_temp_db(df, "df")
+
+@pytest.fixture
+def reference_df():
+    return pd.DataFrame(
+        {
+            "actual": [100, 150, 125, 140, 145, 135, 123],
+            "forecast": [90, 160, 125, 150, 141, 141, 120],
+            "numerical": [1.1, 1.9, 3.2, 3.8, 4.3, 5.0, 5.5],
+            "date": pd.date_range("2022-01-03", "2022-01-09"),
+            "string": ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"],
+        },
+    )
+
+@pytest.fixture(params=[create_pandas_connection, create_duckdb_connection, create_sqlite_connection])
+def connection(request, reference_df, tmpdir):
+    return request.param(reference_df, tmpdir=tmpdir)
+
+@pytest.fixture
+def data(connection):
+    return connection.table("df")
+
+@pytest.fixture
+def dataset(data):
+    return Dataset(data, kdims=["numerical", "date", "string"], vdims=["actual", "forecast"])
+
+def test_index_ibis_table(data):
+        table = IbisInterface._index_ibis_table(data)
+        table.execute()