Bump minimum versions

Author: dcherian

ci/requirements/doc.yml

@@ -23,7 +23,7 @@ dependencies:
   - netcdf4>=1.5
   - numba
   - numpy>=2
-  - packaging>=21.3
+  - packaging>=23.2
   - pandas>=1.4,!=2.1.0
   - pooch
   - pip

ci/requirements/min-all-deps.yml

@@ -9,19 +9,19 @@ dependencies:
   # doc/user-guide/installing.rst, doc/user-guide/plotting.rst and setup.py.
   - python=3.10
   - array-api-strict=1.0  # dependency for testing the array api compat
-  - boto3=1.28
+  - boto3=1.29
   - bottleneck=1.3
   - cartopy=0.22
   - cftime=1.6
   - coveralls
-  - dask-core=2023.9
-  - distributed=2023.9
+  - dask-core=2023.11
+  - distributed=2023.11
   # Flox > 0.8 has a bug with numbagg versions
   # It will require numbagg > 0.6
   # so we should just skip that series eventually
   # or keep flox pinned for longer than necessary
   - flox=0.7
-  - h5netcdf=1.2
+  - h5netcdf=1.3
   # h5py and hdf5 tend to cause conflicts
   # for e.g. hdf5 1.12 conflicts with h5py=3.1
   # prioritize bumping other packages instead
@@ -30,15 +30,15 @@ dependencies:
   - hypothesis
   - iris=3.7
   - lxml=4.9  # Optional dep of pydap
-  - matplotlib-base=3.7
+  - matplotlib-base=3.8
   - nc-time-axis=1.4
   # netcdf follows a 1.major.minor[.patch] convention
   # (see https://github.com/Unidata/netcdf4-python/issues/1090)
   - netcdf4=1.6.0
   - numba=0.57
-  - numbagg=0.2.1
+  - numbagg=0.6
   - numpy=1.24
-  - packaging=23.1
+  - packaging=23.2
   - pandas=2.1
   - pint=0.22
   - pip
@@ -50,8 +50,8 @@ dependencies:
   - pytest-timeout
   - rasterio=1.3
   - scipy=1.11
-  - seaborn=0.12
+  - seaborn=0.13
   - sparse=0.14
   - toolz=0.12
-  - typing_extensions=4.7
+  - typing_extensions=4.8
   - zarr=2.16

doc/whats-new.rst

@@ -19,6 +19,21 @@ What's New
 v.2024.10.1 (unreleased)
 ------------------------
 
+
+Breaking Changes
+~~~~~~~~~~~~~~~~
+- The minimum versions of some dependencies were changed
+
+  ===================== =========  =======
+   Package                    Old      New
+  ===================== =========  =======
+    boto3                    1.28     1.29
+    dask-core             2023.9   2023.11
+    distributed           2023.9   2023.11
+    h5netcdf                 1.2      1.3
+    numbagg                0.2.1      0.6
+    typing_extensions       4.7       4.8
+  ===================== =========  =======
 New Features
 ~~~~~~~~~~~~
 - Added :py:meth:`DataTree.persist` method (:issue:`9675`, :pull:`9682`).

pyproject.toml

@@ -23,7 +23,7 @@ requires-python = ">=3.10"
 
 dependencies = [
   "numpy>=1.24",
-  "packaging>=23.1",
+  "packaging>=23.2",
   "pandas>=2.1",
 ]
 

xarray/core/duck_array_ops.py

@@ -31,13 +31,11 @@
     unravel_index,
 )
 from numpy.lib.stride_tricks import sliding_window_view  # noqa: F401
-from packaging.version import Version
 from pandas.api.types import is_extension_array_dtype
 
 from xarray.core import dask_array_ops, dtypes, nputils
 from xarray.core.options import OPTIONS
 from xarray.core.utils import is_duck_array, is_duck_dask_array, module_available
-from xarray.namedarray import pycompat
 from xarray.namedarray.parallelcompat import get_chunked_array_type
 from xarray.namedarray.pycompat import array_type, is_chunked_array
 
@@ -755,13 +753,7 @@ def _push(array, n: int | None = None, axis: int = -1):
     if OPTIONS["use_numbagg"] and module_available("numbagg"):
         import numbagg
 
-        if pycompat.mod_version("numbagg") < Version("0.6.2"):
-            warnings.warn(
-                f"numbagg >= 0.6.2 is required for bfill & ffill; {pycompat.mod_version('numbagg')} is installed. We'll attempt with bottleneck instead.",
-                stacklevel=2,
-            )
-        else:
-            return numbagg.ffill(array, limit=n, axis=axis)
+        return numbagg.ffill(array, limit=n, axis=axis)
 
     # work around for bottleneck 178
     limit = n if n is not None else array.shape[axis]

xarray/core/nputils.py

@@ -181,7 +181,6 @@ def f(values, axis=None, **kwargs):
 
         if (
             module_available("numbagg")
-            and pycompat.mod_version("numbagg") >= Version("0.5.0")
             and OPTIONS["use_numbagg"]
             and isinstance(values, np.ndarray)
             # numbagg<0.7.0 uses ddof=1 only, but numpy uses ddof=0 by default

xarray/core/rolling.py

@@ -8,7 +8,6 @@
 from typing import TYPE_CHECKING, Any, Generic, TypeVar
 
 import numpy as np
-from packaging.version import Version
 
 from xarray.core import dask_array_ops, dtypes, duck_array_ops, utils
 from xarray.core.arithmetic import CoarsenArithmetic
@@ -19,7 +18,6 @@
     is_duck_dask_array,
     module_available,
 )
-from xarray.namedarray import pycompat
 
 try:
     import bottleneck
@@ -642,7 +640,6 @@ def _array_reduce(
         if (
             OPTIONS["use_numbagg"]
             and module_available("numbagg")
-            and pycompat.mod_version("numbagg") >= Version("0.6.3")
             and numbagg_move_func is not None
             # TODO: we could at least allow this for the equivalent of `apply_ufunc`'s
             # "parallelized". `rolling_exp` does this, as an example (but rolling_exp is

xarray/core/rolling_exp.py

@@ -4,14 +4,12 @@
 from typing import Any, Generic
 
 import numpy as np
-from packaging.version import Version
 
 from xarray.core.computation import apply_ufunc
 from xarray.core.options import _get_keep_attrs
 from xarray.core.pdcompat import count_not_none
 from xarray.core.types import T_DataWithCoords
 from xarray.core.utils import module_available
-from xarray.namedarray import pycompat
 
 
 def _get_alpha(
@@ -81,14 +79,6 @@ def __init__(
             raise ImportError(
                 "numbagg >= 0.2.1 is required for rolling_exp but currently numbagg is not installed"
             )
-        elif pycompat.mod_version("numbagg") < Version("0.2.1"):
-            raise ImportError(
-                f"numbagg >= 0.2.1 is required for rolling_exp but currently version {pycompat.mod_version('numbagg')} is installed"
-            )
-        elif pycompat.mod_version("numbagg") < Version("0.3.1") and min_weight > 0:
-            raise ImportError(
-                f"numbagg >= 0.3.1 is required for `min_weight > 0` within `.rolling_exp` but currently version {pycompat.mod_version('numbagg')} is installed"
-            )
 
         self.obj: T_DataWithCoords = obj
         dim, window = next(iter(windows.items()))
@@ -192,10 +182,6 @@ def std(self) -> T_DataWithCoords:
         Dimensions without coordinates: x
         """
 
-        if pycompat.mod_version("numbagg") < Version("0.4.0"):
-            raise ImportError(
-                f"numbagg >= 0.4.0 is required for rolling_exp().std(), currently {pycompat.mod_version('numbagg')} is installed"
-            )
         import numbagg
 
         dim_order = self.obj.dims
@@ -225,10 +211,6 @@ def var(self) -> T_DataWithCoords:
         array([       nan, 0.        , 0.46153846, 0.18461538, 0.06446281])
         Dimensions without coordinates: x
         """
-        if pycompat.mod_version("numbagg") < Version("0.4.0"):
-            raise ImportError(
-                f"numbagg >= 0.4.0 is required for rolling_exp().var(), currently {pycompat.mod_version('numbagg')} is installed"
-            )
         dim_order = self.obj.dims
         import numbagg
 
@@ -258,10 +240,6 @@ def cov(self, other: T_DataWithCoords) -> T_DataWithCoords:
         Dimensions without coordinates: x
         """
 
-        if pycompat.mod_version("numbagg") < Version("0.4.0"):
-            raise ImportError(
-                f"numbagg >= 0.4.0 is required for rolling_exp().cov(), currently {pycompat.mod_version('numbagg')} is installed"
-            )
         dim_order = self.obj.dims
         import numbagg
 
@@ -292,10 +270,6 @@ def corr(self, other: T_DataWithCoords) -> T_DataWithCoords:
         Dimensions without coordinates: x
         """
 
-        if pycompat.mod_version("numbagg") < Version("0.4.0"):
-            raise ImportError(
-                f"numbagg >= 0.4.0 is required for rolling_exp().corr(), currently {pycompat.mod_version('numbagg')} is installed"
-            )
         dim_order = self.obj.dims
         import numbagg
 

xarray/namedarray/daskmanager.py

@@ -4,7 +4,6 @@
 from typing import TYPE_CHECKING, Any
 
 import numpy as np
-from packaging.version import Version
 
 from xarray.core.indexing import ImplicitToExplicitIndexingAdapter
 from xarray.namedarray.parallelcompat import ChunkManagerEntrypoint, T_ChunkedArray
@@ -182,14 +181,8 @@ def map_blocks(
         new_axis: int | Sequence[int] | None = None,
         **kwargs: Any,
     ) -> Any:
-        import dask
         from dask.array import map_blocks
 
-        if drop_axis is None and Version(dask.__version__) < Version("2022.9.1"):
-            # See https://github.com/pydata/xarray/pull/7019#discussion_r1196729489
-            # TODO remove once dask minimum version >= 2022.9.1
-            drop_axis = []
-
         # pass through name, meta, token as kwargs
         return map_blocks(
             func,

xarray/tests/__init__.py

@@ -157,34 +157,23 @@ def _importorskip(
 has_array_api_strict, requires_array_api_strict = _importorskip("array_api_strict")
 
 
-def _importorskip_h5netcdf_ros3():
-    try:
-        import h5netcdf
-
-        has_h5netcdf = True
-    except ImportError:
-        has_h5netcdf = False
-
+def _importorskip_h5netcdf_ros3(has_h5netcdf: bool):
     if not has_h5netcdf:
         return has_h5netcdf, pytest.mark.skipif(
             not has_h5netcdf, reason="requires h5netcdf"
         )
 
-    h5netcdf_with_ros3 = Version(h5netcdf.__version__) >= Version("1.3.0")
-
     import h5py
 
     h5py_with_ros3 = h5py.get_config().ros3
 
-    has_h5netcdf_ros3 = h5netcdf_with_ros3 and h5py_with_ros3
-
-    return has_h5netcdf_ros3, pytest.mark.skipif(
-        not has_h5netcdf_ros3,
+    return h5py_with_ros3, pytest.mark.skipif(
+        not h5py_with_ros3,
         reason="requires h5netcdf>=1.3.0 and h5py with ros3 support",
     )
 
 
-has_h5netcdf_ros3, requires_h5netcdf_ros3 = _importorskip_h5netcdf_ros3()
+has_h5netcdf_ros3, requires_h5netcdf_ros3 = _importorskip_h5netcdf_ros3(has_h5netcdf)
 has_netCDF4_1_6_2_or_above, requires_netCDF4_1_6_2_or_above = _importorskip(
     "netCDF4", "1.6.2"
 )