remove 3.9 as supported version (#11)

.pre-commit-config.yaml

@@ -17,7 +17,3 @@ repos:
     rev: 24.4.2
     hooks:
       - id: black
-  - repo: https://github.com/numpy/numpydoc
-    rev: v1.7.0
-    hooks:
-      - id: numpydoc-validation

ilamb3/analysis/base.py

@@ -3,7 +3,6 @@
 """
 
 from abc import ABC, abstractmethod
-from typing import Union
 
 import pandas as pd
 import xarray as xr
@@ -21,7 +20,7 @@ class ILAMBAnalysis(ABC):
     """
 
     @abstractmethod
-    def required_variables(self) -> Union[list[str], dict[str, list[str]]]:
+    def required_variables(self) -> list[str] | dict[str, list[str]]:
         """
         Return the variables used in this analysis.
 

ilamb3/analysis/bias.py

@@ -7,7 +7,7 @@
 """
 
 import warnings
-from typing import Literal, Union
+from typing import Literal
 
 import numpy as np
 import pandas as pd
@@ -56,11 +56,11 @@ def __call__(
         ref: xr.Dataset,
         com: xr.Dataset,
         method: Literal["Collier2018", "RegionalQuantiles"] = "Collier2018",
-        regions: list[Union[str, None]] = [None],
+        regions: list[str | None] = [None],
         use_uncertainty: bool = True,
         spatial_sum: bool = False,
         mass_weighting: bool = False,
-        quantile_dbase: Union[pd.DataFrame, None] = None,
+        quantile_dbase: pd.DataFrame | None = None,
         quantile_threshold: int = 70,
     ) -> tuple[pd.DataFrame, xr.Dataset, xr.Dataset]:
         """

ilamb3/analysis/nbp.py

@@ -6,8 +6,6 @@
 ILAMBAnalysis : The abstract base class from which this derives.
 """
 
-from typing import Union
-
 import numpy as np
 import pandas as pd
 import xarray as xr
@@ -47,7 +45,7 @@ def required_variables(self) -> list[str]:
         return ["nbp"]
 
     def __call__(
-        self, ref: xr.Dataset, com: xr.Dataset, evaluation_year: Union[int, None] = None
+        self, ref: xr.Dataset, com: xr.Dataset, evaluation_year: int | None = None
     ) -> tuple[pd.DataFrame, xr.Dataset, xr.Dataset]:
         """
         Apply the ILAMB bias methodology on the given datasets.

ilamb3/analysis/relationship.py

@@ -238,7 +238,7 @@ def __call__(
         self,
         ref: xr.Dataset,
         com: xr.Dataset,
-        regions: list[Union[str, None]] = [None],
+        regions: list[str | None] = [None],
     ) -> tuple[pd.DataFrame, xr.Dataset, xr.Dataset]:
         """
         Apply the ILAMB relationship methodology on the given datasets.

ilamb3/compare.py

@@ -1,7 +1,5 @@
 """Functions for preparing datasets for comparison."""
 
-from typing import Union
-
 import numpy as np
 import xarray as xr
 
@@ -94,8 +92,8 @@ def is_spatially_aligned(dsa: xr.Dataset, dsb: xr.Dataset) -> bool:
 def pick_grid_aligned(
     ref0: xr.Dataset,
     com0: xr.Dataset,
-    ref: Union[xr.Dataset, None] = None,
-    com: Union[xr.Dataset, None] = None,
+    ref: xr.Dataset | None = None,
+    com: xr.Dataset | None = None,
 ) -> tuple[xr.Dataset, xr.Dataset]:
     """Return a reference and comparison dataset that is spatially grid-aligned.
 
@@ -292,5 +290,5 @@ def _populate_renames(ds):
         return out
 
     for arg in args:
-        assert isinstance(arg, (xr.DataArray, xr.Dataset))
+        assert isinstance(arg, xr.DataArray | xr.Dataset)
     return [arg.rename(_populate_renames(arg)) for arg in args]

ilamb3/dataset.py

@@ -1,6 +1,6 @@
 """Convenience functions which operate on datasets."""
 
-from typing import Any, Literal, Union
+from typing import Any, Literal
 
 import numpy as np
 import xarray as xr
@@ -10,7 +10,7 @@
 
 
 def get_dim_name(
-    dset: Union[xr.Dataset, xr.DataArray],
+    dset: xr.Dataset | xr.DataArray,
     dim: Literal["time", "lat", "lon", "depth", "site"],
 ) -> str:
     """
@@ -70,7 +70,7 @@ def get_dim_name(
 
 
 def get_coord_name(
-    dset: Union[xr.Dataset, xr.DataArray],
+    dset: xr.Dataset | xr.DataArray,
     coord: Literal["lat", "lon"],
 ) -> str:
     """
@@ -163,7 +163,7 @@ def is_site(da: xr.DataArray) -> bool:
 
 
 def get_time_extent(
-    dset: Union[xr.Dataset, xr.DataArray]
+    dset: xr.Dataset | xr.DataArray,
 ) -> tuple[xr.DataArray, xr.DataArray]:
     """
     Return the time extent of the dataset/dataarray.
@@ -190,7 +190,7 @@ def get_time_extent(
     return time.min(), time.max()
 
 
-def compute_time_measures(dset: Union[xr.Dataset, xr.DataArray]) -> xr.DataArray:
+def compute_time_measures(dset: xr.Dataset | xr.DataArray) -> xr.DataArray:
     """
     Return the length of each time interval.
 
@@ -236,7 +236,7 @@ def _measure1d(time):  # numpydoc ignore=GL08
     return measure
 
 
-def compute_cell_measures(dset: Union[xr.Dataset, xr.DataArray]) -> xr.DataArray:
+def compute_cell_measures(dset: xr.Dataset | xr.DataArray) -> xr.DataArray:
     """
     Return the area of each spatial cell.
 
@@ -366,8 +366,8 @@ def coarsen_dataset(dset: xr.Dataset, res: float = 0.5) -> xr.Dataset:
 
 
 def integrate_time(
-    dset: Union[xr.Dataset, xr.DataArray],
-    varname: Union[str, None] = None,
+    dset: xr.Dataset | xr.DataArray,
+    varname: str | None = None,
     mean: bool = False,
 ) -> xr.DataArray:
     """
@@ -418,8 +418,8 @@ def integrate_time(
 
 
 def accumulate_time(
-    dset: Union[xr.Dataset, xr.DataArray],
-    varname: Union[str, None] = None,
+    dset: xr.Dataset | xr.DataArray,
+    varname: str | None = None,
 ) -> xr.DataArray:
     """
     Return the time accumulation of the dataset.
@@ -456,7 +456,7 @@ def accumulate_time(
 
 
 def std_time(
-    dset: Union[xr.Dataset, xr.DataArray], varname: Union[str, None] = None
+    dset: xr.Dataset | xr.DataArray, varname: str | None = None
 ) -> xr.DataArray:
     """
     Return the standard deviation of a variable in time.
@@ -489,11 +489,11 @@ def std_time(
 
 
 def integrate_space(
-    dset: Union[xr.DataArray, xr.Dataset],
+    dset: xr.DataArray | xr.Dataset,
     varname: str,
-    region: Union[None, str] = None,
+    region: None | str = None,
     mean: bool = False,
-    weight: Union[xr.DataArray, None] = None,
+    weight: xr.DataArray | None = None,
 ) -> xr.DataArray:
     """
     Return the space integral or mean of the dataset.
@@ -625,8 +625,8 @@ def _get_interval(dset, dim, value, side):  # numpydoc ignore=GL08
 
 
 def integrate_depth(
-    dset: Union[xr.Dataset, xr.DataArray],
-    varname: Union[str, None] = None,
+    dset: xr.Dataset | xr.DataArray,
+    varname: str | None = None,
     mean: bool = False,
 ) -> xr.DataArray:
     """
@@ -704,10 +704,10 @@ def scale_by_water_density(da: xr.DataArray, target: str) -> xr.DataArray:
 
 
 def convert(
-    dset: Union[xr.Dataset, xr.DataArray],
+    dset: xr.Dataset | xr.DataArray,
     unit: str,
-    varname: Union[str, None] = None,
-) -> Union[xr.Dataset, xr.DataArray]:
+    varname: str | None = None,
+) -> xr.Dataset | xr.DataArray:
     """
     Convert the units of the dataarray.
 

ilamb3/regions.py

@@ -1,14 +1,14 @@
 """Region definitions for use in the ILAMB system."""
 
 import os
-from typing import Literal, Union
+from typing import Literal
 
 import numpy as np
 import xarray as xr
 
 
 def get_dim_name(
-    dset: Union[xr.Dataset, xr.DataArray], dim: Literal["time", "lat", "lon"]
+    dset: xr.Dataset | xr.DataArray, dim: Literal["time", "lat", "lon"]
 ) -> str:
     """Return the name of the `dim` dimension from the dataset.
 
@@ -40,7 +40,7 @@ def get_dim_name(
 
 
 def restrict_to_bbox(
-    var: Union[xr.Dataset, xr.DataArray],
+    var: xr.Dataset | xr.DataArray,
     lat_name: str,
     lon_name: str,
     lat0: float,
@@ -113,7 +113,7 @@ def add_latlon_bounds(
         Regions._regions[label] = [rtype, name, lats, lons]
         Regions._sources[label] = source
 
-    def add_netcdf(self, netcdf: Union[str, xr.Dataset]) -> list[str]:
+    def add_netcdf(self, netcdf: str | xr.Dataset) -> list[str]:
         """Add regions found in a netCDF file or dataset.
 
         Region formatting guidelines can be found
@@ -173,9 +173,9 @@ def get_source(self, label: str):
 
     def restrict_to_region(
         self,
-        var: Union[xr.Dataset, xr.DataArray],
-        label: Union[str, None],
-    ) -> Union[xr.Dataset, xr.DataArray]:
+        var: xr.Dataset | xr.DataArray,
+        label: str | None,
+    ) -> xr.Dataset | xr.DataArray:
         """Given the region label and a variable, return a mask."""
         if label is None:
             return var

pyproject.toml

@@ -9,10 +9,10 @@ classifiers = [
   "Intended Audience :: Science/Research",
   "Programming Language :: Python",
   "Programming Language :: Python :: 3",
-  "Programming Language :: Python :: 3.9",
   "Programming Language :: Python :: 3.10",
   "Programming Language :: Python :: 3.11",
   "Programming Language :: Python :: 3.12",
+  "Programming Language :: Python :: 3.13",
   "Topic :: Scientific/Engineering",
 ]
 description = "Earth system model benchmarking"
@@ -82,9 +82,10 @@ exclude_lines = ["pragma: no cover"]
 
 [tool.ruff]
 extend-exclude = [
-  "doc",
+  "docs",
 ]
-target-version = "py39"
+target-version = "py310"
+[tool.ruff.lint]
 ignore = [
   "E402",
   "E501",
@@ -99,7 +100,7 @@ select = [
   "UP", # Pyupgrade
 ]
 
-[tool.ruff.isort]
+[tool.ruff.lint.isort]
 known-first-party = ["ilamb3"]
 
 [tool.numpydoc_validation]