Maintenance of the code

holoviews/__init__.py

@@ -139,7 +139,7 @@ def __call__(self, *args, **opts): # noqa (dummy signature)
             try:
                 exec(code)
             except Exception as e:
-                print("Warning: Could not load %r [%r]" % (filename, str(e)))
+                print(f"Warning: Could not load {filename!r} [{str(e)!r}]")
         del f, code
         break
     del filename

holoviews/annotators.py

@@ -224,7 +224,7 @@ def __init__(self, object=None, **params):
         super().__init__(None, **params)
         self.object = self._process_element(object)
         self._table_row = Row()
-        self.editor = Tabs(('%s' % param_name(self.name), self._table_row))
+        self.editor = Tabs((f'{param_name(self.name)}', self._table_row))
         self.plot = DynamicMap(self._get_plot)
         self.plot.callback.inputs[:] = [self.object]
         self._tables = []
@@ -336,19 +336,19 @@ class PathAnnotator(Annotator):
     def __init__(self, object=None, **params):
         self._vertex_table_row = Row()
         super().__init__(object, **params)
-        self.editor.append(('%s Vertices' % param_name(self.name),
+        self.editor.append((f'{param_name(self.name)} Vertices',
                             self._vertex_table_row))
 
     def _init_stream(self):
         name = param_name(self.name)
         self._stream = PolyDraw(
             source=self.plot, data={}, num_objects=self.num_objects,
-            show_vertices=self.show_vertices, tooltip='%s Tool' % name,
+            show_vertices=self.show_vertices, tooltip=f'{name} Tool',
             vertex_style=self.vertex_style, empty_value=self.empty_value
         )
         if self.edit_vertices:
             self._vertex_stream = PolyEdit(
-                source=self.plot, tooltip='%s Edit Tool' % name,
+                source=self.plot, tooltip=f'{name} Edit Tool',
                 vertex_style=self.vertex_style,
             )
 
@@ -379,7 +379,7 @@ def _process_element(self, element=None):
         # Validate annotations
         poly_data = {c: element.dimension_values(c, expanded=False)
                      for c in validate}
-        if validate and len(set(len(v) for v in poly_data.values())) != 1:
+        if validate and len({len(v) for v in poly_data.values()}) != 1:
             raise ValueError('annotations must refer to value dimensions '
                              'which vary per path while at least one of '
                              '%s varies by vertex.' % validate)
@@ -419,7 +419,7 @@ def _update_table(self):
         self._table = Table(table_data, annotations, [], label=name).opts(
             show_title=False, **self.table_opts)
         self._vertex_table = Table(
-            [], table.kdims, list(self.vertex_annotations), label='%s Vertices' % name
+            [], table.kdims, list(self.vertex_annotations), label=f'{name} Vertices'
         ).opts(show_title=False, **self.table_opts)
         self._update_links()
         self._table_row[:] = [self._table]
@@ -458,7 +458,7 @@ def _init_stream(self):
         name = param_name(self.name)
         self._stream = self._stream_type(
             source=self.plot, data={}, num_objects=self.num_objects,
-            tooltip='%s Tool' % name, empty_value=self.empty_value
+            tooltip=f'{name} Tool', empty_value=self.empty_value
         )
 
     def _process_element(self, object):
@@ -519,7 +519,7 @@ class CurveAnnotator(_GeomAnnotator):
     def _init_stream(self):
         name = param_name(self.name)
         self._stream = self._stream_type(
-            source=self.plot, data={}, tooltip='%s Tool' % name,
+            source=self.plot, data={}, tooltip=f'{name} Tool',
             style=self.vertex_style
         )
 

holoviews/core/__init__.py

@@ -1,5 +1,7 @@
 from datetime import date, datetime
 
+import pandas as pd
+
 from .boundingregion import *  # noqa (API import)
 from .data import *            # noqa (API import)
 from .dimension import *       # noqa (API import)
@@ -29,19 +31,15 @@
 Dimension.type_formatters[np.datetime64] = '%Y-%m-%d %H:%M:%S'
 Dimension.type_formatters[datetime] = '%Y-%m-%d %H:%M:%S'
 Dimension.type_formatters[date] = '%Y-%m-%d'
+Dimension.type_formatters[pd.Timestamp] = "%Y-%m-%d %H:%M:%S"
 
-try:
-    import pandas as pd
-    Dimension.type_formatters[pd.Timestamp] = "%Y-%m-%d %H:%M:%S"
-except:
-    pass
 
 def public(obj):
     if not isinstance(obj, type): return False
     baseclasses = [Dimension, Dimensioned, Operation, BoundingBox,
                    SheetCoordinateSystem, AttrTree]
     return any([issubclass(obj, bc) for bc in baseclasses])
 
-_public = list(set([_k for _k, _v in locals().items() if public(_v)]))
+_public = list({_k for _k, _v in locals().items() if public(_v)})
 __all__ = _public + ["boundingregion", "dimension", "layer", "layout",
                      "ndmapping", "operation", "options", "sheetcoords", "tree", "element"]

holoviews/core/accessors.py

@@ -86,7 +86,7 @@ def pipelined_call(*args, **kwargs):
 
 
 @add_metaclass(AccessorPipelineMeta)
-class Apply(object):
+class Apply:
     """
     Utility to apply a function or operation to all viewable elements
     inside the object.
@@ -289,7 +289,7 @@ def transform(self, *args, **kwargs):
 
 
 @add_metaclass(AccessorPipelineMeta)
-class Redim(object):
+class Redim:
     """
     Utility that supports re-dimensioning any HoloViews object via the
     redim method.
@@ -489,7 +489,7 @@ def values(self, specs=None, **ranges):
 
 
 @add_metaclass(AccessorPipelineMeta)
-class Opts(object):
+class Opts:
 
     def __init__(self, obj, mode=None):
         self._mode = mode

holoviews/core/boundingregion.py

@@ -12,7 +12,7 @@
 from .util import datetime_types
 
 
-class BoundingRegion(object):
+class BoundingRegion:
     """
     Abstract bounding region class, for any portion of a 2D plane.
 
@@ -93,9 +93,9 @@ def __str__(self):
         l, b, r, t = self._aarect.lbrt()
         if (not isinstance(r, datetime_types) and r == -l and
             not isinstance(b, datetime_types) and t == -b and r == t):
-            return 'BoundingBox(radius=%s)' % (r)
+            return f'BoundingBox(radius={r})'
         else:
-            return 'BoundingBox(points=((%s,%s),(%s,%s)))' % (l, b, r, t)
+            return f'BoundingBox(points=(({l},{b}),({r},{t})))'
 
 
     def __repr__(self):
@@ -106,7 +106,7 @@ def script_repr(self, imports=[], prefix="    "):
         # Generate import statement
         cls = self.__class__.__name__
         mod = self.__module__
-        imports.append("from %s import %s" % (mod, cls))
+        imports.append(f"from {mod} import {cls}")
         return self.__str__()
 
 
@@ -242,7 +242,7 @@ def contains(self, x, y):
 # JABALERT: Should probably remove top, bottom, etc. accessor functions,
 # and use the slot itself instead.
 ###################################################
-class AARectangle(object):
+class AARectangle:
     """
     Axis-aligned rectangle class.
 

holoviews/core/data/__init__.py

@@ -1,8 +1,3 @@
-try:
-    import itertools.izip as zip
-except ImportError:
-    pass
-
 import types
 import copy
 
@@ -70,7 +65,7 @@ def concat(datasets, datatype=None):
     return Interface.concatenate(datasets, datatype)
 
 
-class DataConversion(object):
+class DataConversion:
     """
     DataConversion is a very simple container object which can be
     given an existing Dataset Element and provides methods to convert
@@ -129,7 +124,7 @@ def __call__(self, new_type, kdims=None, vdims=None, groupby=None,
             else:
                 selected = self._element
         else:
-            if pd and issubclass(self._element.interface, PandasInterface):
+            if issubclass(self._element.interface, PandasInterface):
                 ds_dims = self._element.dimensions()
                 ds_kdims = [self._element.get_dimension(d) if d in ds_dims else d
                             for d in groupby+kdims]
@@ -283,15 +278,14 @@ class to each underlying element.
         """
         if isinstance(data, DynamicMap):
             class_name = cls.__name__
-            repr_kdims = 'kdims=%r' % kdims if kdims else None
-            repr_vdims = 'vdims=%r' % vdims if vdims else None
-            repr_kwargs = (', '.join('%s=%r' % (k,v) for k,v in kwargs.items())
+            repr_kdims = f'kdims={kdims!r}' if kdims else None
+            repr_vdims = f'vdims={vdims!r}' if vdims else None
+            repr_kwargs = (', '.join(f'{k}={v!r}' for k,v in kwargs.items())
                            if kwargs else None)
             extras = ', '.join([el for el in [repr_kdims, repr_vdims, repr_kwargs]
                                if el is not None])
             extras = ', ' + extras if extras else ''
-            apply_args= 'hv.{class_name}{extras}'.format(class_name=class_name,
-                                                         extras=extras)
+            apply_args= f'hv.{class_name}{extras}'
             msg = "Cannot construct a {class_name} from the supplied object of type DynamicMap. Implicitly creating a DynamicMap of {class_name} objects, but instead please explicitly call .apply({apply_args}) on the supplied DynamicMap."
             cls.param.warning(cls, msg.format(class_name=class_name, apply_args=apply_args))
             return data.apply(cls, per_element=True, kdims=kdims, vdims=vdims, **kwargs)
@@ -540,7 +534,7 @@ def add_dimension(self, dimension, dim_pos, dim_val, vdim=False, **kwargs):
             dimension = Dimension(dimension)
 
         if dimension.name in self.kdims:
-            raise Exception('{dim} dimension already defined'.format(dim=dimension.name))
+            raise Exception(f'{dimension.name} dimension already defined')
 
         if vdim:
             dims = self.vdims[:]
@@ -716,7 +710,7 @@ def __getitem__(self, slices):
             value_select = slices[self.ndims]
         elif len(slices) == self.ndims+1 and isinstance(slices[self.ndims],
                                                         (Dimension,str)):
-            raise IndexError("%r is not an available value dimension" % slices[self.ndims])
+            raise IndexError(f"{slices[self.ndims]!r} is not an available value dimension")
         else:
             selection = dict(zip(self.dimensions(label=True), slices))
         data = self.select(**selection)
@@ -821,7 +815,7 @@ def sample(self, samples=[], bounds=None, closest=True, **kwargs):
             return self.clone(selection, kdims=kdims, new_type=new_type,
                               datatype=datatype)
 
-        lens = set(len(util.wrap_tuple(s)) for s in samples)
+        lens = {len(util.wrap_tuple(s)) for s in samples}
         if len(lens) > 1:
             raise IndexError('Sample coordinates must all be of the same length.')
 
@@ -946,7 +940,7 @@ def aggregate(self, dimensions=None, function=None, spreadfn=None, **kwargs):
             try:
                 # Should be checking the dimensions declared on the element are compatible
                 return self.clone(aggregated, kdims=kdims, vdims=vdims)
-            except:
+            except Exception:
                 datatype = self.param.objects('existing')['datatype'].default
                 return self.clone(aggregated, kdims=kdims, vdims=vdims,
                                   new_type=new_type, datatype=datatype)
@@ -1070,12 +1064,10 @@ def __len__(self):
         "Number of values in the Dataset."
         return self.interface.length(self)
 
-    def __nonzero__(self):
+    def __bool__(self):
         "Whether the Dataset contains any values"
         return self.interface.nonzero(self)
 
-    __bool__ = __nonzero__
-
     @property
     def shape(self):
         "Returns the shape of the data."

holoviews/core/data/array.py

@@ -1,8 +1,3 @@
-try:
-    import itertools.izip as zip
-except ImportError:
-    pass
-
 import numpy as np
 
 from .interface import Interface, DataError
@@ -35,7 +30,7 @@ def init(cls, eltype, data, kdims, vdims):
         if ((isinstance(data, dict) or util.is_dataframe(data)) and
             all(d in data for d in dimensions)):
             dataset = [d if isinstance(d, np.ndarray) else np.asarray(data[d]) for d in dimensions]
-            if len(set(d.dtype.kind for d in dataset)) > 1:
+            if len({d.dtype.kind for d in dataset}) > 1:
                 raise ValueError('ArrayInterface expects all columns to be of the same dtype')
             data = np.column_stack(dataset)
         elif isinstance(data, dict) and not all(d in data for d in dimensions):
@@ -45,7 +40,7 @@ def init(cls, eltype, data, kdims, vdims):
             data = np.column_stack(list(dataset))
         elif isinstance(data, tuple):
             data = [d if isinstance(d, np.ndarray) else np.asarray(d) for d in data]
-            if len(set(d.dtype.kind for d in data)) > 1:
+            if len({d.dtype.kind for d in data}) > 1:
                 raise ValueError('ArrayInterface expects all columns to be of the same dtype')
             elif cls.expanded(data):
                 data = np.column_stack(data)
@@ -57,7 +52,7 @@ def init(cls, eltype, data, kdims, vdims):
             data = np.array([], ndmin=2).T if data is None else list(data)
             try:
                 data = np.array(data)
-            except:
+            except Exception:
                 data = None
 
         if kdims is None:

holoviews/core/data/cudf.py

@@ -1,14 +1,10 @@
 import sys
 import warnings
 
-try:
-    import itertools.izip as zip
-except ImportError:
-    pass
-
 from itertools import product
 
 import numpy as np
+import pandas as pd
 
 from .. import util
 from ..dimension import dimension_name
@@ -53,7 +49,6 @@ def applies(cls, obj):
     @classmethod
     def init(cls, eltype, data, kdims, vdims):
         import cudf
-        import pandas as pd
 
         element_params = eltype.param.objects()
         kdim_param = element_params['kdims']
@@ -199,10 +194,10 @@ def select_mask(cls, dataset, selection):
             if isinstance(sel, tuple):
                 sel = slice(*sel)
             arr = cls.values(dataset, dim, keep_index=True)
-            if util.isdatetime(arr) and util.pd:
+            if util.isdatetime(arr):
                 try:
                     sel = util.parse_datetime_selection(sel)
-                except:
+                except Exception:
                     pass
 
             new_masks = []
@@ -274,22 +269,22 @@ def aggregate(cls, dataset, dimensions, function, **kwargs):
             agg = agg_map.get(agg, agg)
             grouped = reindexed.groupby(cols, sort=False)
             if not hasattr(grouped, agg):
-                raise ValueError('%s aggregation is not supported on cudf DataFrame.' % agg)
+                raise ValueError(f'{agg} aggregation is not supported on cudf DataFrame.')
             df = getattr(grouped, agg)().reset_index()
         else:
             agg_map = {'amin': 'min', 'amax': 'max', 'size': 'count'}
             agg = agg_map.get(agg, agg)
             if not hasattr(reindexed, agg):
-                raise ValueError('%s aggregation is not supported on cudf DataFrame.' % agg)
+                raise ValueError(f'{agg} aggregation is not supported on cudf DataFrame.')
             agg = getattr(reindexed, agg)()
             try:
-                data = dict(((col, [v]) for col, v in zip(agg.index.values_host, agg.to_numpy())))
+                data = {col: [v] for col, v in zip(agg.index.values_host, agg.to_numpy())}
             except Exception:
                 # Give FutureWarning: 'The to_array method will be removed in a future cuDF release.
                 # Consider using `to_numpy` instead.'
                 # Seen in cudf=21.12.01
-                data = dict(((col, [v]) for col, v in zip(agg.index.values_host, agg.to_array())))
-            df = util.pd.DataFrame(data, columns=list(agg.index.values_host))
+                data = {col: [v] for col, v in zip(agg.index.values_host, agg.to_array())}
+            df = pd.DataFrame(data, columns=list(agg.index.values_host))
 
         dropped = []
         for vd in vdims:

holoviews/core/data/dask.py

@@ -1,8 +1,4 @@
 import sys
-try:
-    import itertools.izip as zip
-except ImportError:
-    pass
 
 import numpy as np
 import pandas as pd