refactor: Align version check

examples/conftest.py

@@ -9,7 +9,7 @@
 
 system = platform.system()
 py_version = sys.version_info[:2]
-PD2 = Version(pd.__version__) >= Version("2.0")
+PANDAS_GE_2_0_0 = Version(pd.__version__).release >= (2, 0, 0)
 
 # Having "OMP_NUM_THREADS"=1, set as an environment variable, can be needed
 # to avoid crashing when running tests with pytest-xdist on Windows.
@@ -30,7 +30,7 @@
 
 # 2023-07-14 with following error:
 # ValueError: Buffer dtype mismatch, expected 'const int64_t' but got 'int'
-if PD2 and system == "Windows":
+if PANDAS_GE_2_0_0 and system == "Windows":
     collect_ignore_glob += [
         "gallery/demos/bokeh/point_draw_triangulate.ipynb",
         "reference/elements/*/TriMesh.ipynb",
@@ -45,7 +45,7 @@
     ]
 
 # First available in Bokeh 3.2.0
-if Version(bokeh.__version__) < Version("3.2.0"):
+if Version(bokeh.__version__).release < (3, 2, 0):
     collect_ignore_glob += [
         "reference/elements/bokeh/HLines.ipynb",
         "reference/elements/bokeh/HSpans.ipynb",

holoviews/core/data/dask.py

@@ -218,7 +218,7 @@ def groupby(cls, dataset, dimensions, container_type, group_type, **kwargs):
         for coord in indices:
             if any(isinstance(c, float) and np.isnan(c) for c in coord):
                 continue
-            if len(coord) == 1 and not util.PANDAS_GE_220:
+            if len(coord) == 1 and not util.PANDAS_GE_2_2_0:
                 coord = coord[0]
             group = group_type(groupby.get_group(coord), **group_kwargs)
             data.append((coord, group))

holoviews/core/data/ibis.py

@@ -1,35 +1,18 @@
 import sys
 from collections.abc import Iterable
-from functools import lru_cache
 
 import numpy as np
-from packaging.version import Version
 
 from .. import util
 from ..element import Element
 from ..ndmapping import NdMapping, item_check, sorted_context
 from .interface import DataError, Interface
 from .util import cached
 
-
-@lru_cache
-def ibis_version():
-    import ibis
-    return Version(ibis.__version__)
-
-
-@lru_cache
-def ibis4():
-    return ibis_version() >= Version("4.0")
-
-
-@lru_cache
-def ibis5():
-    return ibis_version() >= Version("5.0")
-
-@lru_cache
-def ibis9_5():
-    return ibis_version() >= Version("9.5")
+IBIS_VERSION = util._no_import_version("ibis-framework")
+IBIS_GE_4_0_0 = IBIS_VERSION >= (4, 0, 0)
+IBIS_GE_5_0_0 = IBIS_VERSION >= (5, 0, 0)
+IBIS_GE_9_5_0 = IBIS_VERSION >= (9, 5, 0)
 
 
 class IbisInterface(Interface):
@@ -120,7 +103,7 @@ def persist(cls, dataset):
     @cached
     def length(self, dataset):
         # Get the length by counting the length of an empty query.
-        if ibis4():
+        if IBIS_GE_4_0_0:
             return dataset.data.count().execute()
         else:
             return dataset.data[[]].count().execute()
@@ -129,7 +112,7 @@ def length(self, dataset):
     @cached
     def nonzero(cls, dataset):
         # Make an empty query to see if a row is returned.
-        if ibis4():
+        if IBIS_GE_4_0_0:
             return bool(len(dataset.data.head(1).execute()))
         else:
             return bool(len(dataset.data[[]].head(1).execute()))
@@ -163,7 +146,7 @@ def values(
         dimension = dataset.get_dimension(dimension, strict=True)
         data = dataset.data[dimension.name]
         if (
-            ibis_version() > Version("3")
+            IBIS_VERSION > (3, 0, 0)
             and isinstance(data, ibis.expr.types.AnyColumn)
             and not expanded
         ):
@@ -178,12 +161,12 @@ def histogram(cls, expr, bins, density=True, weights=None):
         bins = [int(v) if bins.dtype.kind in 'iu' else float(v) for v in bins]
         binned = expr.bucket(bins).name('bucket')
         hist = np.zeros(len(bins)-1)
-        if ibis4():
+        if IBIS_GE_4_0_0:
             hist_bins = binned.value_counts().order_by('bucket').execute()
         else:
             # sort_by will be removed in Ibis 5.0
             hist_bins = binned.value_counts().sort_by('bucket').execute()
-        metric_name = 'bucket_count' if ibis5() else 'count'
+        metric_name = 'bucket_count' if IBIS_GE_5_0_0 else 'count'
         for b, v in zip(hist_bins['bucket'], hist_bins[metric_name]):
             if np.isnan(b):
                 continue
@@ -212,11 +195,11 @@ def dtype(cls, dataset, dimension):
     def sort(cls, dataset, by=None, reverse=False):
         if by is None:
             by = []
-        if ibis_version() >= Version("6.0"):
+        if IBIS_VERSION >= (6, 0, 0):
             import ibis
             order = ibis.desc if reverse else ibis.asc
             return dataset.data.order_by([order(dataset.get_dimension(x).name) for x in by])
-        elif ibis4():
+        elif IBIS_GE_4_0_0:
             # Tuple syntax will be removed in Ibis 7.0:
             # https://github.com/ibis-project/ibis/pull/6082
             return dataset.data.order_by([(dataset.get_dimension(x).name, not reverse) for x in by])
@@ -245,7 +228,7 @@ def _index_ibis_table(cls, data):
         if "hv_row_id__" in data.columns:
             return data
 
-        if ibis4():
+        if IBIS_GE_4_0_0:
             return data.mutate(hv_row_id__=ibis.row_number())
         elif cls.is_rowid_zero_indexed(data):
             return data.mutate(hv_row_id__=data.rowid())
@@ -290,7 +273,7 @@ def iloc(cls, dataset, index):
                 rows = [rows]
             data = data.filter([data.hv_row_id__.isin(rows)])
 
-        if ibis4():
+        if IBIS_GE_4_0_0:
             return data.drop("hv_row_id__")
         else:
             # Passing a sequence of fields to `drop` will be removed in Ibis 5.0
@@ -302,7 +285,7 @@ def unpack_scalar(cls, dataset, data):
         Given a dataset object and data in the appropriate format for
         the interface, return a simple scalar.
         """
-        if ibis4():
+        if IBIS_GE_4_0_0:
             count = data.count().execute()
         else:
             count = data[[]].count().execute()
@@ -326,7 +309,7 @@ def groupby(cls, dataset, dimensions, container_type, group_type, **kwargs):
         group_by = [d.name for d in index_dims]
 
         # execute a query against the table to find the unique groups.
-        if ibis4():
+        if IBIS_GE_4_0_0:
             groups = dataset.data.group_by(group_by).aggregate().execute()
         else:
             # groupby will be removed in Ibis 5.0
@@ -392,7 +375,7 @@ def select(cls, dataset, selection_mask=None, **selection):
                 data["hv_row_id__"].isin(list(map(int, selection_mask)))
             )
 
-            if ibis4():
+            if IBIS_GE_4_0_0:
                 data = data.drop("hv_row_id__")
             else:
                 # Passing a sequence of fields to `drop` will be removed in Ibis 5.0
@@ -462,7 +445,7 @@ def sample(cls, dataset, samples=None):
         if all(util.isscalar(s) or len(s) == 1 for s in samples):
             items = [s[0] if isinstance(s, tuple) else s for s in samples]
             subset = data[dims[0].name].isin(items)
-            return data.filter(subset) if ibis9_5() else data[subset]
+            return data.filter(subset) if IBIS_GE_9_5_0 else data[subset]
 
         predicates = None
         for sample in samples:
@@ -508,7 +491,7 @@ def aggregate(cls, dataset, dimensions, function, **kwargs):
         }.get(function, function)
 
         if len(dimensions):
-            if ibis4():
+            if IBIS_GE_4_0_0:
                  selection = new.group_by(columns)
             else:
                 # groupby will be removed in Ibis 5.0

holoviews/core/data/pandas.py

@@ -1,13 +1,12 @@
 import numpy as np
 import pandas as pd
-from packaging.version import Version
 from pandas.api.types import is_numeric_dtype
 
 from .. import util
 from ..dimension import Dimension, dimension_name
 from ..element import Element
 from ..ndmapping import NdMapping, item_check, sorted_context
-from ..util import PANDAS_GE_210
+from ..util import PANDAS_GE_2_1_0
 from .interface import DataError, Interface
 from .util import finite_range
 
@@ -251,14 +250,14 @@ def groupby(cls, dataset, dimensions, container_type, group_type, **kwargs):
         group_kwargs['dataset'] = dataset.dataset
 
         group_by = [d.name for d in index_dims]
-        if len(group_by) == 1 and util.pandas_version >= Version("1.5.0"):
+        if len(group_by) == 1 and util.PANDAS_VERSION >= (1, 5, 0):
             # Because of this deprecation warning from pandas 1.5.0:
             # In a future version of pandas, a length 1 tuple will be returned
             # when iterating over a groupby with a grouper equal to a list of length 1.
             # Don't supply a list with a single grouper to avoid this warning.
             group_by = group_by[0]
         groupby_kwargs = {"sort": False}
-        if PANDAS_GE_210:
+        if PANDAS_GE_2_1_0:
             groupby_kwargs["observed"] = False
         data = [(k, group_type(v, **group_kwargs)) for k, v in
                 dataset.data.groupby(group_by, **groupby_kwargs)]
@@ -296,7 +295,7 @@ def aggregate(cls, dataset, dimensions, function, **kwargs):
                     if is_numeric_dtype(d) and c not in cols
                 ]
             groupby_kwargs = {"sort": False}
-            if PANDAS_GE_210:
+            if PANDAS_GE_2_1_0:
                 groupby_kwargs["observed"] = False
             grouped = reindexed.groupby(cols, **groupby_kwargs)
             df = grouped[numeric_cols].aggregate(fn, **kwargs).reset_index()

holoviews/core/util.py

@@ -18,6 +18,7 @@
 from collections import defaultdict, namedtuple
 from contextlib import contextmanager
 from functools import partial
+from importlib.metadata import PackageNotFoundError, version
 from threading import Event, Thread
 from types import FunctionType
 
@@ -38,13 +39,13 @@
 get_keywords = operator.attrgetter('varkw')
 
 # Versions
-numpy_version = Version(Version(np.__version__).base_version)
-param_version = Version(param.__version__)
-pandas_version = Version(pd.__version__)
+NUMPY_VERSION = Version(np.__version__).release
+PARAM_VERSION = Version(param.__version__).release
+PANDAS_VERSION = Version(pd.__version__).release
 
-NUMPY_GE_200 = numpy_version >= Version("2")
-PANDAS_GE_210 = pandas_version >= Version("2.1")
-PANDAS_GE_220 = pandas_version >= Version("2.2")
+NUMPY_GE_2_0_0 = NUMPY_VERSION >= (2, 0, 0)
+PANDAS_GE_2_1_0 = PANDAS_VERSION >= (2, 1, 0)
+PANDAS_GE_2_2_0 = PANDAS_VERSION >= (2, 2, 0)
 
 # Types
 generator_types = (zip, range, types.GeneratorType)
@@ -115,6 +116,14 @@ def __init__(self, msg, version=None, min_version=None, **kwargs):
         super().__init__(msg, **kwargs)
 
 
+def _no_import_version(name) -> tuple[int, int, int]:
+    """ Get version number without importing the library """
+    try:
+        return Version(version(name)).release
+    except PackageNotFoundError:
+        return (0, 0, 0)
+
+
 class Config(param.ParameterizedFunction):
     """
     Set of boolean configuration values to change HoloViews' global

holoviews/element/util.py

@@ -10,7 +10,7 @@
 from ..core.operation import Operation
 from ..core.sheetcoords import Slice
 from ..core.util import (
-    PANDAS_GE_210,
+    PANDAS_GE_2_1_0,
     cartesian_product,
     datetime_types,
     is_cyclic,
@@ -202,7 +202,7 @@ def _aggregate_dataset(self, obj):
     def _aggregate_dataset_pandas(self, obj):
         index_cols = [d.name for d in obj.kdims]
         groupby_kwargs = {"sort": False}
-        if PANDAS_GE_210:
+        if PANDAS_GE_2_1_0:
             groupby_kwargs["observed"] = False
         df = obj.data.set_index(index_cols).groupby(index_cols, **groupby_kwargs).first()
         label = 'unique' if len(df) == len(obj) else 'non-unique'

holoviews/operation/element.py

@@ -630,7 +630,7 @@ def _process(self, element, key=None):
         if self.p.filled:
             vdims = [vdims[0].clone(range=crange)]
 
-        if Version(contourpy_version) >= Version('1.2'):
+        if Version(contourpy_version).release >= (1, 2, 0):
             line_type = LineType.ChunkCombinedNan
         else:
             line_type = LineType.ChunkCombinedOffset
@@ -821,7 +821,7 @@ def _process(self, element, key=None, groupby=False):
         is_cupy = is_cupy_array(data)
         if is_cupy:
             import cupy
-            full_cupy_support = Version(cupy.__version__) > Version('8.0')
+            full_cupy_support = Version(cupy.__version__).release > (8, 0, 0)
             if not full_cupy_support and (normed or self.p.weight_dimension):
                 data = cupy.asnumpy(data)
                 is_cupy = False
@@ -830,17 +830,17 @@ def _process(self, element, key=None, groupby=False):
 
         # Mask data
         if is_ibis_expr(data):
-            from ..core.data.ibis import ibis5, ibis9_5
+            from ..core.data.ibis import IBIS_GE_5_0_0, IBIS_GE_9_5_0
 
             mask = data.notnull()
             if self.p.nonzero:
                 mask = mask & (data != 0)
-            if ibis5():
+            if IBIS_GE_5_0_0:
                 data = data.as_table()
             else:
                 # to_projection removed in ibis 5.0.0
                 data = data.to_projection()
-            data = data.filter(mask) if ibis9_5() else data[mask]
+            data = data.filter(mask) if IBIS_GE_9_5_0 else data[mask]
             no_data = not len(data.head(1).execute())
             data = data[dim.name]
         else:

holoviews/plotting/bokeh/__init__.py

@@ -115,7 +115,7 @@
 from .stats import BivariatePlot, BoxWhiskerPlot, DistributionPlot, ViolinPlot
 from .tabular import TablePlot
 from .tiles import TilePlot
-from .util import bokeh_version  # noqa (API import)
+from .util import BOKEH_VERSION  # noqa (API import)
 
 Store.renderers['bokeh'] = BokehRenderer.instance()
 

holoviews/plotting/bokeh/annotation.py

@@ -23,7 +23,7 @@
     line_properties,
     text_properties,
 )
-from .util import bokeh32, date_to_integer
+from .util import BOKEH_GE_3_2_0, date_to_integer
 
 arrow_start = {'<->': NormalHead, '<|-|>': NormalHead}
 arrow_end = {'->': NormalHead, '-[': TeeHead, '-|>': NormalHead,
@@ -39,7 +39,7 @@ class _SyntheticAnnotationPlot(ColorbarPlot):
     _allow_implicit_categories = False
 
     def __init__(self, element, **kwargs):
-        if not bokeh32:
+        if not BOKEH_GE_3_2_0:
             name = type(getattr(element, "last", element)).__name__
             msg = f'{name} element requires Bokeh >=3.2'
             raise ImportError(msg)

holoviews/plotting/bokeh/callbacks.py

@@ -72,7 +72,7 @@
     Tap,
 )
 from ...util.warnings import warn
-from .util import bokeh33, convert_timestamp
+from .util import BOKEH_GE_3_3_0, convert_timestamp
 
 
 class Callback:
@@ -1569,7 +1569,7 @@ def initialize(self, plot_id=None):
             renderer = self._path_initialize()
         if stream.styles:
             self._create_style_callback(cds, renderer.glyph)
-        if bokeh33:
+        if BOKEH_GE_3_3_0:
             # First version with Quad support
             box_tool = BoxEditTool(renderers=[renderer], **kwargs)
             self.plot.state.tools.append(box_tool)