Merge pull request #199 from Ouranosinc/abandon38

Remove Python 3.8 support and fix other requirements

.github/workflows/conda-build.yml

@@ -25,7 +25,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.8"]
+        python-version: ["3.9"]
     steps:
       - uses: actions/checkout@v3
         if: ${{ github.event.inputs.tag == '' }}

.github/workflows/main.yml

@@ -26,7 +26,7 @@ jobs:
       - uses: actions/checkout@v3
       - uses: actions/setup-python@v4
         with:
-          python-version: "3.8"
+          python-version: "3.9"
       - name: Install tox
         run: |
           pip install tox~=3.0
@@ -46,8 +46,6 @@ jobs:
             tox-build: "py39"
           - python-version: "3.10"
             tox-build: "py310"
-          - python-version: "3.8"
-            tox-build: "doctests"
     defaults:
       run:
         shell: bash -l {0}

.pre-commit-config.yaml

@@ -6,7 +6,7 @@ repos:
     rev: v3.4.0
     hooks:
     -   id: pyupgrade
-        args: [--py38-plus]
+        args: [--py39-plus]
   - repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v4.4.0
     hooks:
@@ -57,9 +57,9 @@ repos:
     rev: 1.7.0
     hooks:
       - id: nbqa-pyupgrade
-        args: [ '--py38-plus' ]
+        args: [ '--py39-plus' ]
       - id: nbqa-black
-        args: [ '--target-version=py38' ]
+        args: [ '--target-version=py39' ]
       - id: nbqa-isort
         args: [ "--settings-file=setup.cfg" ]
   - repo: https://github.com/kynan/nbstripout

CONTRIBUTING.rst

@@ -145,7 +145,7 @@ Before you submit a pull request, check that it meets these guidelines:
    your new functionality into a function with a docstring, and add the
    feature to the list in README.rst.
 3. The pull request should not break the templates.
-4. The pull request should work for Python 3.8, 3.9, and 3.10.
+4. The pull request should work for Python 3.9 and 3.10.
 
 Tips
 ----

HISTORY.rst

@@ -2,6 +2,30 @@
 History
 =======
 
+v0.7.0 (unreleased)
+-------------------
+Contributors to this version: Gabriel Rondeau-Genesse (:user:`RondeauG`).
+
+Announcements
+^^^^^^^^^^^^^
+* Dropped support for Python 3.8. (:pull:`199`).
+
+New features and enhancements
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+* N/A
+
+Breaking changes
+^^^^^^^^^^^^^^^^
+* N/A
+
+Bug fixes
+^^^^^^^^^
+* N/A
+
+Internal changes
+^^^^^^^^^^^^^^^^
+* Removed the pin on xarray's version. (:issue:`175`, :pull:`199`).
+
 v0.6.0 (2023-05-04)
 -------------------
 Contributors to this version: Trevor James Smith (:user:`Zeitsperre`), Juliette Lavoie (:user:`juliettelavoie`), Pascal Bourgault (:user:`aulemahal`), Gabriel Rondeau-Genesse (:user:`RondeauG`).

environment-dev.yml

@@ -2,7 +2,7 @@ name: xscen-dev
 channels:
   - conda-forge
 dependencies:
-  - python >=3.8
+  - python >=3.9
   # Don't forget to sync the changes here with environment.yml!
   # Some pins here are meant to accelerate conda and might not be related to real needs
   # Main packages
@@ -25,7 +25,7 @@ dependencies:
   - pyyaml
   - rechunker
   - shapely
-  - xarray <2023.3.0  # See https://github.com/Ouranosinc/xscen/pull/173
+  - xarray
   - xclim >=0.37
   - xesmf >=0.7
   - zarr

environment.yml

@@ -2,7 +2,7 @@ name: xscen
 channels:
   - conda-forge
 dependencies:
-  - python >=3.8
+  - python >=3.9
   # Don't forget to sync the changes here with environment-dev.yml!
   # Main packages
   - cartopy
@@ -24,7 +24,7 @@ dependencies:
   - pyyaml
   - rechunker
   - shapely
-  - xarray <2023.3.0  # See https://github.com/Ouranosinc/xscen/pull/173
+  - xarray
   - xclim >=0.37
   - xesmf >=0.7
   - zarr

setup.py

@@ -45,7 +45,7 @@
     "pyyaml",
     "rechunker",
     "shapely",
-    "xarray<2023.3.0",  # See https://github.com/Ouranosinc/xscen/pull/173
+    "xarray",
     "xclim>=0.37",
     "xesmf>=0.7",  # This is not available on pypi.
     "zarr",
@@ -54,15 +54,14 @@
 setup(
     author="Gabriel Rondeau-Genesse",
     author_email="rondeau-genesse.gabriel@ouranos.ca",
-    python_requires=">=3.8",
+    python_requires=">=3.9",
     classifiers=[
         "Development Status :: 3 - Alpha",
         "Intended Audience :: Developers",
         "Intended Audience :: Science/Research",
         "License :: OSI Approved :: Apache Software License",
         "Natural Language :: English",
         "Programming Language :: Python :: 3",
-        "Programming Language :: Python :: 3.8",
         "Programming Language :: Python :: 3.9",
         "Programming Language :: Python :: 3.10",
         "Topic :: Scientific/Engineering :: Atmospheric Science",

tox.ini

@@ -1,5 +1,5 @@
 [tox]
-envlist = black, py{38,39,310}, docs, doctests
+envlist = black, py{39,310}, docs, doctests
 requires =
     pip >= 20.0
     tox < 4.0

xscen/aggregate.py

@@ -2,16 +2,18 @@
 import datetime
 import logging
 import warnings
+from collections.abc import Sequence
 from copy import deepcopy
 from pathlib import Path, PosixPath
 from types import ModuleType
-from typing import Sequence, Tuple, Union
+from typing import Tuple, Union
 
 import geopandas as gpd
 import numpy as np
 import pandas as pd
 import pygeos
 import xarray as xr
+import xclim as xc
 import xclim.core.calendar
 import xesmf as xe
 from shapely.geometry import Polygon
@@ -211,6 +213,8 @@ def compute_deltas(
     """
     if isinstance(reference_horizon, str):
         # Separate the reference from the other horizons
+        if xc.core.utils.uses_dask(ds["horizon"]):
+            ds["horizon"].load()
         ref = ds.where(ds.horizon == reference_horizon, drop=True)
     elif isinstance(reference_horizon, xr.Dataset):
         ref = reference_horizon
@@ -640,7 +644,7 @@ def spatial_mean(
 def produce_horizon(
     ds: xr.Dataset,
     indicators: Union[
-        str, PosixPath, Sequence[Indicator], Sequence[Tuple[str, Indicator]], ModuleType
+        str, PosixPath, Sequence[Indicator], Sequence[tuple[str, Indicator]], ModuleType
     ],
     period: list = None,
     to_level: str = "climatology{period0}-{period1}",

xscen/catalog.py

@@ -7,11 +7,12 @@
 import re
 import subprocess
 import warnings
+from collections.abc import Mapping, Sequence
 from copy import deepcopy
 from datetime import datetime
 from glob import glob
 from pathlib import Path, PosixPath
-from typing import Any, Dict, List, Mapping, Optional, Sequence, Tuple, Union
+from typing import Any, Dict, List, Optional, Tuple, Union
 
 import cftime
 import dask
@@ -223,11 +224,11 @@ def from_csv(
         # Create the intake catalog
         return cls({"esmcat": esmdata, "df": df}, **intake_kwargs)
 
-    def __dir__(self) -> List[str]:  # noqa: D105
+    def __dir__(self) -> list[str]:  # noqa: D105
         rv = ["iter_unique", "drop_duplicates", "check_valid"]
         return super().__dir__() + rv
 
-    def _unique(self, columns) -> Dict:
+    def _unique(self, columns) -> dict:
         def _find_unique(series):
             values = series.dropna()
             if series.name in self.esmcat.columns_with_iterables:
@@ -283,7 +284,7 @@ def search(self, **columns):
             )
         return cat
 
-    def drop_duplicates(self, columns: Optional[List[str]] = None):  # noqa: D102
+    def drop_duplicates(self, columns: Optional[list[str]] = None):  # noqa: D102
         # In case variables are being added in an existing Zarr, append them
         if columns is None:
             columns = ["id", "path"]
@@ -364,8 +365,8 @@ def exists_in_cat(self, **columns):
 
     def to_dataset(
         self,
-        concat_on: Optional[Union[List[str], str]] = None,
-        create_ensemble_on: Optional[Union[List[str], str]] = None,
+        concat_on: Optional[Union[list[str], str]] = None,
+        create_ensemble_on: Optional[Union[list[str], str]] = None,
         calendar: Optional[str] = "standard",
         **kwargs,
     ) -> xr.Dataset:
@@ -1013,8 +1014,8 @@ def parse_directory(
     read_from_file: Union[
         bool,
         Sequence[str],
-        Tuple[Sequence[str], Sequence[str]],
-        Sequence[Tuple[Sequence[str], Sequence[str]]],
+        tuple[Sequence[str], Sequence[str]],
+        Sequence[tuple[Sequence[str], Sequence[str]]],
     ] = False,
     homogenous_info: dict = None,
     cvs: Union[str, PosixPath, dict] = None,
@@ -1481,7 +1482,7 @@ def _parse_date(date, fmts):
     return date
 
 
-def _build_id(element: pd.Series, columns: List[str]):
+def _build_id(element: pd.Series, columns: list[str]):
     """Build an ID from a catalog's row and a list of columns."""
     return "_".join(map(str, filter(pd.notna, element[columns].values)))
 

xscen/config.py

@@ -117,7 +117,7 @@ def recursive_update(d, other):
     return d
 
 
-def args_as_str(*args: Tuple[Any, ...]) -> Tuple[str, ...]:
+def args_as_str(*args: tuple[Any, ...]) -> tuple[str, ...]:
     """Return arguments as strings."""
     new_args = []
     for i, arg in enumerate(*args):

xscen/diagnostics.py

@@ -1,9 +1,10 @@
 # noqa: D100
 import logging
 import warnings
+from collections.abc import Sequence
 from pathlib import Path, PosixPath
 from types import ModuleType
-from typing import Optional, Sequence, Tuple, Union
+from typing import Optional, Tuple, Union
 
 import numpy as np
 import xarray as xr
@@ -78,7 +79,7 @@ def fix_unphysical_values(
 
 def _invert_unphysical_temperatures(
     tasmin: xr.DataArray, tasmax: xr.Dataset
-) -> Tuple[xr.DataArray, xr.DataArray, xr.DataArray]:
+) -> tuple[xr.DataArray, xr.DataArray, xr.DataArray]:
     """
     Invert tasmin and tasmax points where tasmax <  tasmin.
 
@@ -109,7 +110,7 @@ def _invert_unphysical_temperatures(
 def properties_and_measures(
     ds: xr.Dataset,
     properties: Union[
-        str, PosixPath, Sequence[Indicator], Sequence[Tuple[str, Indicator]], ModuleType
+        str, PosixPath, Sequence[Indicator], Sequence[tuple[str, Indicator]], ModuleType
     ],
     period: list = None,
     unstack: bool = False,

xscen/extract.py

@@ -501,7 +501,7 @@ def resample(
 @parse_config
 def search_data_catalogs(
     data_catalogs: Union[
-        Union[str, os.PathLike], List[Union[str, os.PathLike]], DataCatalog
+        Union[str, os.PathLike], list[Union[str, os.PathLike]], DataCatalog
     ],
     variables_and_freqs: dict,
     *,
@@ -510,7 +510,7 @@ def search_data_catalogs(
     match_hist_and_fut: bool = False,
     periods: list = None,
     coverage_kwargs: dict = None,
-    id_columns: Optional[List[str]] = None,
+    id_columns: Optional[list[str]] = None,
     allow_resampling: bool = False,
     allow_conversion: bool = False,
     conversion_yaml: str = None,

xscen/indicators.py

@@ -1,9 +1,10 @@
 # noqa: D100
 import logging
+from collections.abc import Sequence
 from functools import partial
 from pathlib import Path, PosixPath
 from types import ModuleType
-from typing import Sequence, Tuple, Union
+from typing import Tuple, Union
 
 import xarray as xr
 import xclim as xc
@@ -60,7 +61,7 @@ def load_xclim_module(filename, reload=False) -> ModuleType:
 def compute_indicators(
     ds: xr.Dataset,
     indicators: Union[
-        str, PosixPath, Sequence[Indicator], Sequence[Tuple[str, Indicator]], ModuleType
+        str, PosixPath, Sequence[Indicator], Sequence[tuple[str, Indicator]], ModuleType
     ],
     *,
     periods: list = None,

xscen/io.py

@@ -2,8 +2,9 @@
 import logging
 import os
 import shutil as sh
+from collections.abc import Sequence
 from pathlib import Path
-from typing import Optional, Sequence, Union
+from typing import Optional, Union
 
 import h5py
 import netCDF4

xscen/scripting.py

@@ -39,7 +39,7 @@ def send_mail(
     server: str = "127.0.0.1",
     port: int = 25,
     attachments: Optional[
-        List[Union[Tuple[str, Union[Figure, os.PathLike]], Figure, os.PathLike]]
+        list[Union[tuple[str, Union[Figure, os.PathLike]], Figure, os.PathLike]]
     ] = None,
 ) -> None:
     """Send email.

xscen/utils.py

@@ -3,11 +3,12 @@
 import logging
 import os
 import re
+from collections.abc import Sequence
 from io import StringIO
 from itertools import chain
 from pathlib import Path
 from types import ModuleType
-from typing import Dict, Optional, Sequence, TextIO, Union
+from typing import Dict, Optional, TextIO, Union
 
 import flox.xarray
 import numpy as np
@@ -746,7 +747,7 @@ def publish_release_notes(
 
 def unstack_dates(
     ds: xr.Dataset,
-    seasons: Dict[int, str] = None,
+    seasons: dict[int, str] = None,
     new_dim: str = "season",
     winter_starts_year: bool = False,
 ):