Update dependencies (#6253)

doc/install.md

@@ -8,12 +8,10 @@ provided by the [Anaconda](https://docs.anaconda.com/anaconda/install/)
 or [Miniconda](https://docs.conda.io/en/latest/miniconda.html)
 scientific Python distributions:
 
-    conda install -c pyviz holoviews
+    conda install holoviews
 
-This recommended installation includes the default
-[Matplotlib](http://matplotlib.org) plotting library backend, the more
-interactive [Bokeh](http://bokeh.pydata.org) plotting library backend,
-and the [Jupyter Notebook](http://jupyter.org).
+This installation includes the default [Matplotlib](http://matplotlib.org)
+plotting library backend, the more interactive [Bokeh](http://bokeh.pydata.org) plotting library backend.
 
 A similar set of packages can be installed using `pip`, if that command
 is available on your system:

holoviews/core/data/pandas.py

@@ -195,8 +195,7 @@ def range(cls, dataset, dimension):
         else:
             column = dataset.data[dimension.name]
         if column.dtype.kind == 'O':
-            if (not isinstance(dataset.data, pd.DataFrame) or
-                util.pandas_version < Version('0.17.0')):
+            if not isinstance(dataset.data, pd.DataFrame):
                 column = column.sort(inplace=False)
             else:
                 column = column.sort_values()
@@ -221,9 +220,7 @@ def range(cls, dataset, dimension):
 
     @classmethod
     def concat_fn(cls, dataframes, **kwargs):
-        if util.pandas_version >= Version('0.23.0'):
-            kwargs['sort'] = False
-        return pd.concat(dataframes, **kwargs)
+        return pd.concat(dataframes, sort=False, **kwargs)
 
 
     @classmethod
@@ -346,8 +343,7 @@ def sort(cls, dataset, by=None, reverse=False):
             by = []
         cols = [dataset.get_dimension(d, strict=True).name for d in by]
 
-        if (not isinstance(dataset.data, pd.DataFrame) or
-            util.pandas_version < Version('0.17.0')):
+        if not isinstance(dataset.data, pd.DataFrame):
             return dataset.data.sort(columns=cols, ascending=not reverse)
         return dataset.data.sort_values(by=cols, ascending=not reverse)
 

holoviews/core/util.py

@@ -23,6 +23,9 @@
 import pandas as pd
 import param
 from packaging.version import Version
+from pandas.core.arrays.masked import BaseMaskedArray
+from pandas.core.dtypes.dtypes import DatetimeTZDtype
+from pandas.core.dtypes.generic import ABCExtensionArray, ABCIndex, ABCSeries
 
 # Python 2 builtins
 basestring = str
@@ -31,59 +34,22 @@
 cmp = lambda a, b: (a>b)-(a<b)
 
 get_keywords = operator.attrgetter('varkw')
-generator_types = (zip, range, types.GeneratorType)
-numpy_version = Version(np.__version__)
-param_version = Version(param.__version__)
-
-datetime_types = (np.datetime64, dt.datetime, dt.date, dt.time)
-timedelta_types = (np.timedelta64, dt.timedelta,)
-arraylike_types = (np.ndarray,)
-masked_types = ()
-
-anonymous_dimension_label = '_'
-
-# Argspec was removed in Python 3.11
-ArgSpec = namedtuple('ArgSpec', 'args varargs keywords defaults')
-
-_NP_SIZE_LARGE = 1_000_000
-_NP_SAMPLE_SIZE = 1_000_000
-_PANDAS_ROWS_LARGE = 1_000_000
-_PANDAS_SAMPLE_SIZE = 1_000_000
 
+# Versions
 numpy_version = Version(Version(np.__version__).base_version)
+param_version = Version(param.__version__)
+pandas_version = Version(pd.__version__)
+
 NUMPY_GE_200 = numpy_version >= Version("2")
 
-pandas_version = Version(pd.__version__)
-try:
-    if pandas_version >= Version('1.3.0'):
-        from pandas.core.dtypes.dtypes import DatetimeTZDtype as DatetimeTZDtypeType
-        from pandas.core.dtypes.generic import (
-            ABCIndex as ABCIndexClass,
-            ABCSeries,
-        )
-    elif pandas_version >= Version('0.24.0'):
-        from pandas.core.dtypes.dtypes import DatetimeTZDtype as DatetimeTZDtypeType
-        from pandas.core.dtypes.generic import ABCIndexClass, ABCSeries
-    elif pandas_version > Version('0.20.0'):
-        from pandas.core.dtypes.dtypes import DatetimeTZDtypeType
-        from pandas.core.dtypes.generic import ABCIndexClass, ABCSeries
-    else:
-        from pandas.types.dtypes import DatetimeTZDtypeType
-        from pandas.types.dtypes.generic import ABCIndexClass, ABCSeries
-    pandas_datetime_types = (pd.Timestamp, DatetimeTZDtypeType, pd.Period)
-    pandas_timedelta_types = (pd.Timedelta,)
-    datetime_types = datetime_types + pandas_datetime_types
-    timedelta_types = timedelta_types + pandas_timedelta_types
-    arraylike_types = arraylike_types + (ABCSeries, ABCIndexClass)
-    if pandas_version > Version('0.23.0'):
-        from pandas.core.dtypes.generic import ABCExtensionArray
-        arraylike_types = arraylike_types + (ABCExtensionArray,)
-    if pandas_version > Version('1.0'):
-        from pandas.core.arrays.masked import BaseMaskedArray
-        masked_types = (BaseMaskedArray,)
-except Exception as e:
-    param.main.param.warning('pandas could not register all extension types '
-                                f'imports failed with the following error: {e}')
+# Types
+generator_types = (zip, range, types.GeneratorType)
+pandas_datetime_types = (pd.Timestamp, DatetimeTZDtype, pd.Period)
+pandas_timedelta_types = (pd.Timedelta,)
+datetime_types = (np.datetime64, dt.datetime, dt.date, dt.time, *pandas_datetime_types)
+timedelta_types = (np.timedelta64, dt.timedelta, *pandas_timedelta_types)
+arraylike_types = (np.ndarray, ABCSeries, ABCIndex, ABCExtensionArray)
+masked_types = (BaseMaskedArray,)
 
 try:
     import cftime
@@ -93,6 +59,15 @@
     cftime_types = ()
 _STANDARD_CALENDARS = {'standard', 'gregorian', 'proleptic_gregorian'}
 
+anonymous_dimension_label = '_'
+
+# Argspec was removed in Python 3.11
+ArgSpec = namedtuple('ArgSpec', 'args varargs keywords defaults')
+
+_NP_SIZE_LARGE = 1_000_000
+_NP_SAMPLE_SIZE = 1_000_000
+_PANDAS_ROWS_LARGE = 1_000_000
+_PANDAS_SAMPLE_SIZE = 1_000_000
 
 # To avoid pandas warning about using DataFrameGroupBy.function
 # introduced in Pandas 2.1.
@@ -890,10 +865,7 @@ def isnat(val):
     """
     if (isinstance(val, (np.datetime64, np.timedelta64)) or
         (isinstance(val, np.ndarray) and val.dtype.kind == 'M')):
-        if numpy_version >= Version('1.13'):
-            return np.isnat(val)
-        else:
-            return val.view('i8') == nat_as_integer
+        return np.isnat(val)
     elif val is pd.NaT:
         return True
     elif isinstance(val, pandas_datetime_types+pandas_timedelta_types):
@@ -928,19 +900,16 @@ def isfinite(val):
         elif val.dtype.kind in 'US':
             return ~pd.isna(val)
         finite = np.isfinite(val)
-        if pandas_version >= Version('1.0.0'):
-            finite &= ~pd.isna(val)
+        finite &= ~pd.isna(val)
         return finite
     elif isinstance(val, datetime_types+timedelta_types):
         return not isnat(val)
     elif isinstance(val, (str, bytes)):
         return True
     finite = np.isfinite(val)
-    if pandas_version >= Version('1.0.0'):
-        if finite is pd.NA:
-            return False
-        return finite & ~pd.isna(np.asarray(val))
-    return finite
+    if finite is pd.NA:
+        return False
+    return finite & ~pd.isna(np.asarray(val))
 
 
 def isdatetime(value):

holoviews/operation/timeseries.py

@@ -1,11 +1,10 @@
 import numpy as np
 import pandas as pd
 import param
-from packaging.version import Version
 
 from ..core import Element, Operation
 from ..core.data import PandasInterface
-from ..core.util import _PANDAS_FUNC_LOOKUP, pandas_version
+from ..core.util import _PANDAS_FUNC_LOOKUP
 from ..element import Scatter
 
 
@@ -51,8 +50,7 @@ def _process_layer(self, element, key=None):
         df = df.set_index(xdim).rolling(win_type=self.p.window_type,
                                         **self._roll_kwargs())
         if self.p.window_type is None:
-            kwargs = {'raw': True} if pandas_version >= Version('0.23.0') else {}
-            rolled = df.apply(self.p.function, **kwargs)
+            rolled = df.apply(self.p.function, raw=True)
         elif self.p.function is np.mean:
             rolled = df.mean()
         elif self.p.function is np.sum:

holoviews/plotting/renderer.py

@@ -16,21 +16,20 @@
 from bokeh.resources import CDN, INLINE
 from packaging.version import Version
 from panel import config
-from panel.io.notebook import ipywidget, load_notebook, render_mimebundle, render_model
+from panel.io.notebook import (
+    JupyterCommManagerBinary,
+    ipywidget,
+    load_notebook,
+    render_mimebundle,
+    render_model,
+)
 from panel.io.state import state
 from panel.models.comm_manager import CommManager as PnCommManager
 from panel.pane import HoloViews as HoloViewsPane
 from panel.viewable import Viewable
 from panel.widgets.player import PlayerBase
-from pyviz_comms import CommManager
-
-try:
-    # Added in Panel 1.0 to support JS -> Python binary comms
-    from panel.io.notebook import JupyterCommManagerBinary as JupyterCommManager
-except ImportError:
-    from pyviz_comms import JupyterCommManager
-
 from param.parameterized import bothmethod
+from pyviz_comms import CommManager
 
 from ..core import AdjointLayout, DynamicMap, HoloMap, Layout
 from ..core.data import disable_pipeline
@@ -665,8 +664,8 @@ def load_nb(cls, inline=False, reloading=False, enable_mathjax=False):
             if not ip or not hasattr(ip, 'kernel'):
                 return
             cls.notebook_context = True
-            cls.comm_manager = JupyterCommManager
-            state._comm_manager = JupyterCommManager
+            cls.comm_manager = JupyterCommManagerBinary
+            state._comm_manager = JupyterCommManagerBinary
 
     @classmethod
     def _delete_plot(cls, plot_id):

holoviews/util/transform.py

@@ -170,18 +170,7 @@ def categorize(values, categories, default=None):
     return result
 
 
-if hasattr(np, 'isin'):
-    isin = _maybe_map(np.isin)
-else:
-    # for 1.4 <= numpy < 1.13; in1d() available since 1.4
-    def _isin(element, test_elements, assume_unique=False, invert=False):
-        # from 1.13's numpy.lib.arraysetops
-        element = np.asarray(element)
-        return np.in1d(element, test_elements, assume_unique=assume_unique,
-                invert=invert).reshape(element.shape)
-    isin = _maybe_map(_isin)
-    del _isin
-
+isin = _maybe_map(np.isin)
 digitize = _maybe_map(np.digitize)
 astype = _maybe_map(np.asarray)
 round_ = _maybe_map(np.round)

pixi.toml

@@ -26,6 +26,7 @@ build = ["py311", "build"]
 lint = ["py311", "lint"]
 
 [dependencies]
+bokeh = ">=3.1"
 colorcet = "*"
 numpy = ">=1.0"
 packaging = "*"
@@ -35,10 +36,7 @@ param = ">=2.0,<3.0"
 pip = "*"
 pyviz_comms = ">=2.1"
 # Recommended
-bokeh = ">=3.1"
-ipython = ">=5.4.0"
 matplotlib-base = ">=3"
-notebook = "*"
 plotly = ">=4.0"
 
 [feature.py39.dependencies]
@@ -58,6 +56,7 @@ cftime = "*"
 dask-core = "*"
 datashader = ">=0.11.1"
 ffmpeg = "*"
+ipython = ">=5.4.0"
 netcdf4 = "*"
 networkx = "*"
 notebook = "*"

pyproject.toml

@@ -30,13 +30,14 @@ classifiers = [
     "Topic :: Software Development :: Libraries",
 ]
 dependencies = [
-    "param >=2.0,<3.0",
-    "numpy >=1.0",
-    "pyviz_comms >=2.1",
-    "panel >=1.0",
+    "bokeh >=3.1",
     "colorcet",
+    "numpy >=1.21",
     "packaging",
-    "pandas >=0.20.0",
+    "pandas >=1.3",
+    "panel >=1.0",
+    "param >=2.0,<3.0",
+    "pyviz_comms >=2.1",
 ]
 
 [project.urls]
@@ -45,7 +46,7 @@ Source = "https://github.com/holoviz/holoviews"
 HoloViz = "https://holoviz.org/"
 
 [project.optional-dependencies]
-recommended = ["ipython >=5.4.0", "notebook", "matplotlib >=3", "bokeh >=3.1", "plotly >=4.0"]
+recommended = ["matplotlib >=3", "plotly >=4.0"]
 tests = ["pytest", "pytest-rerunfailures"]
 
 [project.scripts]

scripts/conda/recipe/meta.yaml

@@ -30,7 +30,9 @@ requirements:
     - {{ dep }}
     {% endfor %}
     {% for dep in project['optional-dependencies']['recommended'] %}
-    - {{ dep }}
+    {% if dep.startswith('matplotlib') %}
+    - {{ dep.replace('matplotlib', 'matplotlib-base') }}
+    {% endif %}
     {% endfor %}
 
 test: