update dependencies

Author: OriolAbril

.github/workflows/test.yml

@@ -11,7 +11,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.9", "3.10", "3.11"]
+        python-version: ["3.10", "3.11", "3.12"]
       fail-fast: false
     steps:
       - uses: actions/checkout@v3

.readthedocs.yaml

@@ -5,7 +5,7 @@ version: 2
 build:
   os: ubuntu-22.04
   tools:
-    python: "3.10"
+    python: "3.11"
 
 sphinx:
   fail_on_warning: false

external_tests/helpers.py

@@ -5,7 +5,7 @@
 import logging
 import os
 import sys
-from typing import Any, Optional
+from typing import Any
 
 import cloudpickle
 import numpy as np
@@ -135,18 +135,18 @@ def pystan_noncentered_schools(data, draws, chains):
     schools_code = """
         data {
             int<lower=0> J;
-            real y[J];
-            real<lower=0> sigma[J];
+            array[J] real y;
+            array[J] real<lower=0> sigma;
         }
 
         parameters {
             real mu;
             real<lower=0> tau;
-            real eta[J];
+            array[J] real eta;
         }
 
         transformed parameters {
-            real theta[J];
+            array[J] real theta;
             for (j in 1:J)
                 theta[j] = mu + tau * eta[j];
         }
@@ -159,8 +159,8 @@ def pystan_noncentered_schools(data, draws, chains):
         }
 
         generated quantities {
-            vector[J] log_lik;
-            vector[J] y_hat;
+            array[J] real log_lik;
+            array[J] real y_hat;
             for (j in 1:J) {
                 log_lik[j] = normal_lpdf(y[j] | theta[j], sigma[j]);
                 y_hat[j] = normal_rng(theta[j], sigma[j]);
@@ -185,10 +185,10 @@ def load_cached_models(eight_schools_data, draws, chains, libs=None):
     """Load pystan, emcee, and pyro models from pickle."""
     here = os.path.dirname(os.path.abspath(__file__))
     supported = (
-        ("pystan", pystan_noncentered_schools),
+        # ("pystan", pystan_noncentered_schools),
         ("emcee", emcee_schools_model),
-        ("pyro", pyro_noncentered_schools),
-        ("numpyro", numpyro_schools_model),
+        # ("pyro", pyro_noncentered_schools),
+        # ("numpyro", numpyro_schools_model),
     )
     data_directory = os.path.join(here, "saved_models")
     if not os.path.isdir(data_directory):
@@ -241,9 +241,7 @@ def running_on_ci() -> bool:
     return os.environ.get("ARVIZ_CI_MACHINE") is not None
 
 
-def importorskip(
-    modname: str, minversion: Optional[str] = None, reason: Optional[str] = None
-) -> Any:
+def importorskip(modname: str, minversion: str | None = None, reason: str | None = None) -> Any:
     """Import and return the requested module ``modname``.
 
         Doesn't allow skips on CI machine.

pyproject.toml

@@ -5,7 +5,7 @@ build-backend = "flit_core.buildapi"
 [project]
 name = "arviz-base"
 readme = "README.md"
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 license = {file = "LICENSE"}
 authors = [
     {name = "ArviZ team", email = "[email protected]"}
@@ -19,14 +19,14 @@ classifiers = [
     "Operating System :: OS Independent",
     "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",
 ]
 dynamic = ["version", "description"]
 dependencies = [
-  "numpy>=1.20",
-  "xarray>=0.18.0",
+  "numpy>=1.23",
+  "xarray>=2022.6.0",
   "xarray-datatree",
   "typing-extensions>=3.10",
 ]

src/arviz_base/base.py

@@ -3,9 +3,9 @@
 import importlib
 import re
 import warnings
-from collections.abc import Hashable, Iterable, Mapping
+from collections.abc import Callable, Hashable, Iterable, Mapping
 from copy import deepcopy
-from typing import TYPE_CHECKING, Any, Callable, Optional, TypeVar, Union
+from typing import TYPE_CHECKING, Any, TypeVar
 
 import numpy as np
 import xarray as xr
@@ -24,9 +24,9 @@
 def generate_dims_coords(
     shape: Iterable[int],
     var_name: Hashable,
-    dims: Optional[Iterable[Hashable]] = None,
-    coords: Optional[CoordSpec] = None,
-    index_origin: Optional[int] = None,
+    dims: Iterable[Hashable] | None = None,
+    coords: CoordSpec | None = None,
+    index_origin: int | None = None,
     skip_event_dims: bool = False,
     check_conventions: bool = True,
 ) -> tuple[list[Hashable], CoordSpec]:
@@ -216,12 +216,12 @@ def ndarray_to_dataarray(
 def dict_to_dataset(
     data: DictData,
     *,
-    attrs: Optional[Mapping[Any, Any]] = None,
-    inference_library: Optional[str] = None,
-    coords: Optional[CoordSpec] = None,
-    dims: Optional[DimSpec] = None,
-    sample_dims: Optional[Iterable[Hashable]] = None,
-    index_origin: Optional[int] = None,
+    attrs: Mapping[Any, Any] | None = None,
+    inference_library: str | None = None,
+    coords: CoordSpec | None = None,
+    dims: DimSpec | None = None,
+    sample_dims: Iterable[Hashable] | None = None,
+    index_origin: int | None = None,
     skip_event_dims: bool = False,
     check_conventions: bool = True,
 ):
@@ -377,15 +377,15 @@ class requires:  # pylint: disable=invalid-name
     See https://github.com/arviz-devs/arviz/pull/1504 for more discussion.
     """
 
-    def __init__(self, *props: Union[str, list[str]]) -> None:
-        self.props: tuple[Union[str, list[str]], ...] = props
+    def __init__(self, *props: str | list[str]) -> None:
+        self.props: tuple[str | list[str], ...] = props
 
     def __call__(
         self, func: Callable[[RequiresArgTypeT], RequiresReturnTypeT]
-    ) -> Callable[[RequiresArgTypeT], Optional[RequiresReturnTypeT]]:  # noqa: D202
+    ) -> Callable[[RequiresArgTypeT], RequiresReturnTypeT | None]:  # noqa: D202
         """Wrap the decorated function."""
 
-        def wrapped(cls: RequiresArgTypeT) -> Optional[RequiresReturnTypeT]:
+        def wrapped(cls: RequiresArgTypeT) -> RequiresReturnTypeT | None:
             """Return None if not all props are available."""
             for prop in self.props:
                 prop_list = [prop] if isinstance(prop, str) else prop

src/arviz_base/io_dict.py

@@ -1,6 +1,5 @@
 """Dictionary specific conversion code."""
 import warnings
-from typing import Optional
 
 from datatree import DataTree
 
@@ -14,7 +13,7 @@ def from_dict(
     name=None,
     sample_dims=None,
     save_warmup=None,
-    index_origin: Optional[int] = None,
+    index_origin: int | None = None,
     coords=None,
     dims=None,
     pred_dims=None,

src/arviz_base/labels.py

@@ -1,6 +1,5 @@
 # pylint: disable=unused-argument
 """Utilities to generate labels from xarray objects."""
-from typing import Union
 
 __all__ = [
     "mix_labellers",
@@ -92,7 +91,7 @@ def sel_to_str(self, sel: dict, isel: dict):
             )
         return ""
 
-    def var_name_to_str(self, var_name: Union[str, None]):  # pylint: disable=no-self-use
+    def var_name_to_str(self, var_name: str | None):  # pylint: disable=no-self-use
         """WIP."""
         return var_name
 
@@ -106,7 +105,7 @@ def model_name_to_str(self, model_name):  # pylint: disable=no-self-use
         """WIP."""
         return model_name
 
-    def make_label_vert(self, var_name: Union[str, None], sel: dict, isel: dict):
+    def make_label_vert(self, var_name: str | None, sel: dict, isel: dict):
         """WIP."""
         var_name_str = self.var_name_to_str(var_name)
         sel_str = self.sel_to_str(sel, isel)

src/arviz_base/rcparams.py

@@ -7,10 +7,9 @@
 import sys
 from collections.abc import MutableMapping
 from pathlib import Path
-from typing import Any, Literal
+from typing import Any, Literal, get_args
 
 import numpy as np
-from typing_extensions import get_args
 
 _log = logging.getLogger("arviz")
 
@@ -203,7 +202,7 @@ def validate_iterable(value):
             if allow_auto and value.lower() == "auto":
                 return "auto"
             value = tuple(v.strip("([ ])") for v in value.split(",") if v.strip())
-        if np.iterable(value) and not isinstance(value, (set, frozenset)):
+        if np.iterable(value) and not isinstance(value, set | frozenset):
             val = tuple(scalar_validator(v) for v in value)
             if length is not None and len(val) != length:
                 raise ValueError(f"Iterable must be of length: {length}")

src/arviz_base/testing.py

@@ -1,13 +1,12 @@
 """ArviZ testing utilities."""
 
-from typing import Union
 
 from datatree import DataTree
 
 
 def check_multiple_attrs(
     test_dict: dict[str, list[str]], parent: DataTree
-) -> list[Union[str, tuple[str, str]]]:
+) -> list[str | tuple[str, str]]:
     """Perform multiple hasattr checks on InferenceData objects.
 
     It is thought to first check if the parent object contains a given dataset,
@@ -50,7 +49,7 @@ def check_multiple_attrs(
     in ``sample_stats``, also against what was expected.
 
     """
-    failed_attrs: list[Union[str, tuple[str, str]]] = []
+    failed_attrs: list[str | tuple[str, str]] = []
     for dataset_name, attributes in test_dict.items():
         if dataset_name.startswith("~"):
             if hasattr(parent, dataset_name[1:]):

src/arviz_base/utils.py

@@ -32,7 +32,7 @@ def _var_names(var_names, data, filter_vars=None):
         )
 
     if var_names is not None:
-        if isinstance(data, (list, tuple)):
+        if isinstance(data, list | tuple):
             all_vars = []
             for dataset in data:
                 dataset_vars = list(dataset.data_vars)
@@ -156,7 +156,7 @@ def _get_coords(data, coords):
     data : Dataset or DataArray
         Return type is of the same type as the input
     """
-    if not isinstance(data, (list, tuple)):
+    if not isinstance(data, list | tuple):
         try:
             return data.sel(**coords)
 
@@ -170,7 +170,7 @@ def _get_coords(data, coords):
                 "Check that coords structure is correct and"
                 f" dimensions are valid. {err}"
             ) from err
-    if not isinstance(coords, (list, tuple)):
+    if not isinstance(coords, list | tuple):
         coords = [coords] * len(data)
     data_subset = []
     for idx, (datum, coords_dict) in enumerate(zip(data, coords)):

tox.ini

@@ -2,22 +2,22 @@
 envlist =
     check
     docs
-    {py39,py310,py311}{,-coverage}
+    {py310,py311,py312}{,-coverage}
 # See https://tox.readthedocs.io/en/latest/example/package.html#flit
 isolated_build = True
 isolated_build_env = build
 
 [gh-actions]
 python =
-    3.9: py39
     3.10: py310
     3.11: py311
+    3.12: py312
 
 [testenv]
 basepython =
-    py39: python3.9
     py310: python3.10
     py311: python3.11
+    py312: python3.12
     # See https://github.com/tox-dev/tox/issues/1548
     {check,docs,cleandocs,viewdocs,build}: python3
 setenv =