General dependencies bump; repair CI (#28)

.github/workflows/pytest.yml

@@ -26,13 +26,13 @@ jobs:
             python-version: '3.8'
             requirements: latest
           - os: macos
-            python-version: '3.12'
+            python-version: '3.11'
             requirements: latest
           - os: windows
             python-version: '3.8'
             requirements: latest
           - os: windows
-            python-version: '3.12'
+            python-version: '3.11'
             requirements: latest
           # Test on minimal requirements
           - os: ubuntu

ci/requirements-minimal.yml

@@ -2,11 +2,11 @@ name: xarray-extras-minimal
 channels:
   - conda-forge
 dependencies:
-  - dask=2021.4
-  - numba=0.52
-  - numpy=1.18
+  - dask=2022.6.0
+  - numba=0.56
+  - numpy=1.23
   - pandas=1.5
   - pytest
   - pytest-cov
-  - scipy=1.5
-  - xarray=0.16
+  - scipy=1.9
+  - xarray=2022.6.0

doc/whats-new.rst

@@ -7,11 +7,22 @@ What's New
 
 v0.6.0 (Unreleased)
 -------------------
-- Added explicit CI tests for Python 3.10 and 3.11
-  (v0.5.0 already supports it, although not formally).
-- Dropped support for Python 3.7
-- Added support for recent versions of Pandas (tested up to 2.2)
-- Increased minimum version of Pandas  from 1.1 to 1.5
+- Bumped minimum version of all dependencies:
+
+  ========== ======   ========
+  Dependency v0.5.0   v0.6.0
+  ========== ======   ========
+  python     3.7      3.8
+  dask       2021.4.0 2022.6.0
+  numba      0.52     0.56
+  numpy      1.18     1.23
+  pandas     1.1      1.5
+  scipy      1.5      1.9
+  xarray     0.16     2022.6.0
+  ========== ======   ========
+
+- Added support for Python 3.10 and 3.11
+- Added support for recent versions of Pandas (tested up to 2.2) and xarray
 - Added support for :cls:`pathlib.Path` in function arguments
 
 .. _whats-new.0.5.0:
@@ -20,17 +31,17 @@ v0.5.0 (2021-12-01)
 -------------------
 - Bumped minimum version of all dependencies:
 
-  ========== ====== ======
+  ========== ====== ========
   Dependency v0.4.2 v0.5.0
-  ========== ====== ======
+  ========== ====== ========
   python     3.5    3.7
-  dask       0.19   2021.4
+  dask       0.19   2021.4.0
   numba      0.34   0.52
   numpy      1.13   1.18
   pandas     0.21   1.1
   scipy      1.0    1.5
   xarray     0.10.1 0.16
-  ========== ====== ======
+  ========== ====== ========
 
 - Added support for Python 3.8 and 3.9
 - Removed ``xarray_extras.backports`` module

setup.cfg

@@ -26,12 +26,12 @@ zip_safe = False  # https://mypy.readthedocs.io/en/latest/installed_packages.htm
 include_package_data = True
 python_requires = >=3.8
 install_requires =
-    dask >= 2021.4
-    numba >= 0.52
-    numpy >= 1.18
+    dask >= 2022.6
+    numba >= 0.56
+    numpy >= 1.23
     pandas >= 1.5
-    scipy >= 1.5
-    xarray >= 0.16
+    scipy >= 1.9
+    xarray >= 2022.6.0
 
 setup_requires = setuptools_scm
 

xarray_extras/csv.py

@@ -6,7 +6,7 @@
 
 from collections.abc import Callable
 from pathlib import Path
-from typing import Any
+from typing import TYPE_CHECKING, Any, cast
 
 import xarray
 from dask.base import tokenize
@@ -17,8 +17,14 @@
 
 __all__ = ("to_csv",)
 
+if TYPE_CHECKING:
+    # TODO remove TYPE_CHECKING (requires dask >=2023.9.1)
+    from dask.typing import DaskCollection, Key
 
-def to_csv(x: xarray.DataArray, path: str | Path, *, nogil: bool = True, **kwargs: Any):
+
+def to_csv(
+    x: xarray.DataArray, path: str | Path, *, nogil: bool = True, **kwargs: Any
+) -> Any:
     """Print DataArray to CSV.
 
     When x has numpy backend, this function is functionally equivalent to (but
@@ -110,7 +116,7 @@ def to_csv(x: xarray.DataArray, path: str | Path, *, nogil: bool = True, **kwarg
         return None
 
     # Merge chunks on all dimensions beyond the first
-    x = x.chunk((x.chunks[0],) + tuple((s,) for s in x.shape[1:]))
+    x = x.chunk((x.chunks[0], *((s,) for s in x.shape[1:])))  # type: ignore[arg-type]
 
     # Manually define the dask graph
     tok = tokenize(x.data, index, columns, compression, path, kwargs)
@@ -119,7 +125,7 @@ def to_csv(x: xarray.DataArray, path: str | Path, *, nogil: bool = True, **kwarg
     name3 = "to_csv_write-" + tok
     name4 = "to_csv-" + tok
 
-    dsk: dict[str | tuple, tuple] = {}
+    dsk: dict[Key, Any] = {}
 
     assert x.chunks
     assert x.chunks[0]
@@ -172,7 +178,7 @@ def to_csv(x: xarray.DataArray, path: str | Path, *, nogil: bool = True, **kwarg
     # Rename final key
     dsk[name4] = dsk.pop((name3, i))
 
-    hlg = HighLevelGraph.from_collections(name4, dsk, (x,))
+    hlg = HighLevelGraph.from_collections(name4, dsk, [cast("DaskCollection", x)])
     return Delayed(name4, hlg)
 
 

xarray_extras/cumulatives.py

@@ -49,9 +49,9 @@ def cummean(x: T, dim: Hashable, skipna: bool | None = None) -> T:
         n = xarray.DataArray(n, dims=[dim], coords={dim: x.coords[dim]})
     else:
         # heavier computation
-        n = (~x.isnull()).cumsum(dim, skipna=False)
+        n = (~x.isnull()).cumsum((dim,), skipna=False)
 
-    return x.cumsum(dim, skipna=skipna) / n
+    return x.cumsum((dim,), skipna=skipna) / n
 
 
 def compound_sum(x: T, c: xarray.DataArray, xdim: Hashable, cdim: Hashable) -> T:

xarray_extras/interpolate.py

@@ -7,10 +7,17 @@
 import dask.array as da
 import numpy as np
 import xarray
-from xarray.core.pycompat import dask_array_type
 
 from xarray_extras.kernels import interpolate as kernels
 
+try:
+    from xarray.core.pycompat import array_type
+
+    dask_array_type = array_type("dask")
+except ImportError:  # xarray <2022.11.0
+    from xarray.core.pycompat import dask_array_type  # type: ignore
+
+
 __all__ = ("splrep", "splev")
 
 
@@ -113,7 +120,7 @@ def splrep(a: xarray.DataArray, dim: Hashable, k: int = 3) -> xarray.Dataset:
 
 
 def splev(
-    x_new: xarray.DataArray, tck: xarray.Dataset, extrapolate: bool | str = True
+    x_new: object, tck: xarray.Dataset, extrapolate: bool | str = True
 ) -> xarray.DataArray:
     """Evaluate the B-spline generated with :func:`splrep`.
 

xarray_extras/stack.py

@@ -50,7 +50,7 @@ def proper_unstack(array: T, dim: Hashable) -> T:
     array.coords[dim] = mindex
 
     # Invoke builtin unstack
-    array = array.unstack(dim)
+    array = array.unstack((dim,))
 
     # Convert numpy arrays of Python objects to numpy arrays of C floats, ints,
     # strings, etc.