Update Python support for 3.13

.github/workflows/nightly.yaml

@@ -42,7 +42,7 @@ jobs:
       with:
         # If the "Latest version testable on GitHub Actions" in pytest.yaml
         # is not the latest 3.x stable version, adjust here to match:
-        python-version: "3.10"
+        python-version: "3.12"
         cache: pip
         cache-dependency-path: "**/setup.cfg"
 

.github/workflows/pytest.yaml

@@ -26,19 +26,19 @@ jobs:
         - ubuntu-latest
         - windows-latest
         python-version:
-        - "3.8"   # Earliest version supported by message_ix
-        - "3.9"
+        - "3.9"   # Earliest version supported by message_ix
         - "3.10"
         - "3.11"
-        - "3.12"  # Latest version supported by message_ix
+        - "3.12"
+        - "3.13"  # Latest version supported by message_ix
 
         # Below this comment are newly released or development versions of
         # Python. For these versions, binary wheels are not available for some
         # dependencies, e.g. llvmlite, numba, numpy, and/or pandas. Compiling
         # these on the job runner requires a more elaborate build environment,
         # currently out of scope for the message_ix project.
 
-        # - "3.13.0-alpha.1"  # Development version
+        # - "3.14.0-alpha.1"  # Development version
 
       fail-fast: false
 
@@ -128,7 +128,7 @@ jobs:
 
     - uses: actions/setup-python@v5
       with:
-        python-version: "3.11"
+        python-version: "3.12"
         cache: pip
         cache-dependency-path: "**/pyproject.toml"
 

INSTALL.rst

@@ -16,7 +16,7 @@ Use the :ref:`install-quick` steps on this page if *all* of the following apply:
 
 - You have already installed on your system:
 
-  - :ref:`Python <install-python>` (version 3.8 or later) installed, along with either :program:`pip` or :program:`conda`;
+  - :ref:`Python <install-python>` (version 3.9 or later) installed, along with either :program:`pip` or :program:`conda`;
   - a :ref:`Java Runtime Environment (JRE) <install-java>` (if *not* using :program:`conda`; see :ref:`here <install-java>`); and
   - :ref:`GAMS <install-gams>` (version 24.8.1 or later).
 

doc/install-adv.rst

@@ -18,8 +18,8 @@ Install system dependencies
 Python (required)
 -----------------
 
-|MESSAGEix| requires Python version 3.8 or greater.
-We recommend the latest version; currently Python 3.12.
+|MESSAGEix| requires Python version 3.9 or greater.
+We recommend the latest version; currently Python 3.13.
 Common ways to install Python include:
 
 - Use the official `Python releases <https://www.python.org/downloads/>`_.

message_ix/__init__.py

@@ -1,12 +1,8 @@
 import logging
 import sys
+from importlib.metadata import PackageNotFoundError, version
 from pathlib import Path
 
-try:
-    from importlib.metadata import PackageNotFoundError, version
-except ImportError:  # Python 3.7
-    from importlib_metadata import PackageNotFoundError, version  # type: ignore
-
 from ixmp import ModelError, config
 from ixmp.model import MODELS
 from ixmp.util import DeprecatedPathFinder

message_ix/core.py

@@ -2,7 +2,7 @@
 import os
 from functools import lru_cache, partial
 from itertools import chain, product, zip_longest
-from typing import Dict, Iterable, List, Mapping, Optional, Sequence, Tuple, Union
+from typing import Iterable, Mapping, Optional, Sequence, Union
 from warnings import warn
 
 import ixmp
@@ -236,7 +236,7 @@ def add_par(
         self,
         name: str,
         key_or_data: Optional[
-            Union[int, str, Sequence[Union[int, str]], Dict, pd.DataFrame]
+            Union[int, str, Sequence[Union[int, str]], dict, pd.DataFrame]
         ] = None,
         value=None,
         unit: Optional[str] = None,
@@ -253,7 +253,7 @@ def add_par(
     def add_set(
         self,
         name: str,
-        key: Union[int, str, Sequence[Union[str, int]], Dict, pd.DataFrame],
+        key: Union[int, str, Sequence[Union[str, int]], dict, pd.DataFrame],
         comment: Union[str, Sequence[str], None] = None,
     ) -> None:
         # ixmp.Scenario.add_par() is typed as accepting only str, but this method also
@@ -450,7 +450,7 @@ def add_horizon(
 
     def vintage_and_active_years(
         self,
-        ya_args: Union[Tuple[str, str], Tuple[str, str, Union[int, str]], None] = None,
+        ya_args: Union[tuple[str, str], tuple[str, str, Union[int, str]], None] = None,
         tl_only: bool = True,
         **kwargs,
     ) -> pd.DataFrame:
@@ -600,7 +600,7 @@ def _valid(elem):
     #: Alias for :meth:`vintage_and_active_years`.
     yv_ya = vintage_and_active_years
 
-    def years_active(self, node: str, tec: str, yr_vtg: Union[int, str]) -> List[int]:
+    def years_active(self, node: str, tec: str, yr_vtg: Union[int, str]) -> list[int]:
         """Return periods in which `tec` hnology of `yr_vtg` can be active in `node`.
 
         The :ref:`parameters <params-tech>` ``duration_period`` and

message_ix/macro.py

@@ -9,11 +9,9 @@
     Collection,
     Hashable,
     Iterable,
-    List,
     Mapping,
     MutableMapping,
     Optional,
-    Set,
     Union,
 )
 
@@ -129,11 +127,11 @@ def add_par(
 class Structures:
     """MACRO structure information."""
 
-    level: Set[str]
-    node: Set[str]
-    sector: Set[str]
+    level: set[str]
+    node: set[str]
+    sector: set[str]
     #: Model years for which MACRO is calibrated.
-    year: Set[int]
+    year: set[int]
 
 
 def add_structure(
@@ -323,7 +321,7 @@ def growth(gdp_calibrate) -> "DataFrame":
     return growth.dropna()
 
 
-def macro_periods(demand: "Quantity", config: "DataFrame") -> Set[int]:
+def macro_periods(demand: "Quantity", config: "DataFrame") -> set[int]:
     """Periods ("years") for the MACRO model.
 
     The intersection of those appearing in the `config` data and in the ``DEMAND``
@@ -433,7 +431,7 @@ def total_cost(model_cost: "DataFrame", cost_ref: "DataFrame", ym1: int) -> "Dat
     )
 
 
-def unique_set(column: str, df: "DataFrame") -> Set:
+def unique_set(column: str, df: "DataFrame") -> set:
     """A :class:`set` of the unique elements in `column` of `df`."""
     return set(df[column].dropna().unique())
 
@@ -475,7 +473,7 @@ def validate_transform(
     return df.set_index(idx)["value"]
 
 
-def _validate_data(name: Optional[str], df: "DataFrame", s: Structures) -> List:
+def _validate_data(name: Optional[str], df: "DataFrame", s: Structures) -> list:
     """Validate input `df` against `s` for MACRO parameter `name` calibration .
 
     Parameters
@@ -502,7 +500,7 @@ def _validate_data(name: Optional[str], df: "DataFrame", s: Structures) -> List:
 
     # Check required dimensions
     if name is None:
-        dims: List[str] = []
+        dims: list[str] = []
     else:
         item_name = name.replace("_ref", "_MESSAGE")
         item = MACRO.items[item_name]

message_ix/report/__init__.py

@@ -1,7 +1,7 @@
 import logging
 from functools import lru_cache, partial
 from operator import itemgetter
-from typing import TYPE_CHECKING, List, Mapping, Tuple, Union, cast
+from typing import TYPE_CHECKING, Mapping, Union, cast
 
 from genno.operator import broadcast_map
 from ixmp.report import (
@@ -53,7 +53,7 @@
 #:    contains the value 1 at every valid (type_addon, ta) location, and 0 elsewhere.
 #: 2. Simple products of 2 or mode quantities.
 #: 3. Other derived quantities.
-TASKS0: Tuple[Tuple, ...] = (
+TASKS0: tuple[tuple, ...] = (
     # Mapping sets
     ("map_addon", "map_as_qty", "cat_addon", "t"),
     ("map_emission", "map_as_qty", "cat_emission", "e"),
@@ -112,7 +112,7 @@
 
 #: Quantities to automatically convert to IAMC format using
 #: :func:`~genno.compat.pyam.operator.as_pyam`.
-PYAM_CONVERT: List[Tuple[str, "CollapseMessageColsKw"]] = [
+PYAM_CONVERT: list[tuple[str, "CollapseMessageColsKw"]] = [
     ("out:nl-t-ya-m-nd-c-l", dict(kind="ene", var="out")),
     ("in:nl-t-ya-m-no-c-l", dict(kind="ene", var="in")),
     ("CAP:nl-t-ya", dict(var="capacity")),
@@ -148,19 +148,19 @@
 
 
 @lru_cache(1)
-def get_tasks() -> List[Tuple[Tuple, Mapping]]:
+def get_tasks() -> list[tuple[tuple, Mapping]]:
     """Return a list of tasks describing MESSAGE reporting calculations."""
     # Assemble queue of items to add. Each element is a 2-tuple of (positional, keyword)
     # arguments for Reporter.add()
-    to_add: List[Tuple[Tuple, Mapping]] = []
+    to_add: list[tuple[tuple, Mapping]] = []
 
     strict = dict(strict=True)
 
     for t in TASKS0:
         if len(t) == 2 and isinstance(t[1], dict):
             # (args, kwargs) → update kwargs with strict
             t[1].update(strict)
-            to_add.append(cast(Tuple[Tuple, Mapping], t))
+            to_add.append(cast(tuple[tuple, Mapping], t))
         else:
             # args only → use strict as kwargs
             to_add.append((t, strict))

message_ix/report/operator.py

@@ -1,10 +1,7 @@
 from typing import (
     TYPE_CHECKING,
-    Dict,
-    List,
     Literal,
     Mapping,
-    Tuple,
     overload,
 )
 
@@ -30,7 +27,7 @@ def as_message_df(
     dims: Mapping,
     common: Mapping,
     wrap: Literal[True] = True,
-) -> Dict[str, pd.DataFrame]: ...
+) -> dict[str, pd.DataFrame]: ...
 
 
 @overload
@@ -87,7 +84,7 @@ def as_message_df(qty, name, dims, common, wrap=True):
     return {name: df} if wrap else df
 
 
-def model_periods(y: List[int], cat_year: pd.DataFrame) -> List[int]:
+def model_periods(y: list[int], cat_year: pd.DataFrame) -> list[int]:
     """Return the elements of `y` beyond the firstmodelyear of `cat_year`."""
     return list(
         filter(
@@ -98,7 +95,7 @@ def model_periods(y: List[int], cat_year: pd.DataFrame) -> List[int]:
     )
 
 
-def plot_cumulative(x: "AnyQuantity", y: "AnyQuantity", labels: Tuple[str, str, str]):
+def plot_cumulative(x: "AnyQuantity", y: "AnyQuantity", labels: tuple[str, str, str]):
     """Plot a supply curve.
 
     - `x` and `y` must share the first two dimensions.
@@ -161,7 +158,7 @@ def plot_cumulative(x: "AnyQuantity", y: "AnyQuantity", labels: Tuple[str, str,
 
 def stacked_bar(
     qty: "AnyQuantity",
-    dims: Tuple[str, ...] = ("nl", "t", "ya"),
+    dims: tuple[str, ...] = ("nl", "t", "ya"),
     units: str = "",
     title: str = "",
     cf: float = 1.0,

message_ix/report/pyam.py

@@ -1,4 +1,4 @@
-from typing import TYPE_CHECKING, List, Optional, TypedDict
+from typing import TYPE_CHECKING, Optional, TypedDict
 
 if TYPE_CHECKING:
     import pandas
@@ -10,7 +10,7 @@ class CollapseMessageColsKw(TypedDict, total=False):
     df: "pandas.DataFrame"
     var: Optional[str]
     kind: Optional[str]
-    var_cols: List[str]
+    var_cols: list[str]
 
 
 def collapse_message_cols(

message_ix/testing/__init__.py

@@ -2,7 +2,7 @@
 import os
 from itertools import product
 from pathlib import Path
-from typing import TYPE_CHECKING, Generator, List, Optional, Union
+from typing import TYPE_CHECKING, Generator, Optional, Union
 
 import numpy as np
 import pandas as pd
@@ -48,7 +48,7 @@ def pytest_sessionstart():
 
 # Create and populate ixmp databases
 
-_ms: List[Union[str, float]] = [
+_ms: list[Union[str, float]] = [
     SCENARIO["dantzig"]["model"],
     SCENARIO["dantzig"]["scenario"],
 ]

message_ix/tests/report/test_operator.py

@@ -1,5 +1,5 @@
 from functools import partial
-from typing import Any, Mapping, Tuple
+from typing import Any, Mapping
 
 import matplotlib
 import pandas as pd
@@ -17,7 +17,7 @@ def test_as_message_df(test_mp) -> None:
     q = random_qty(dict(c=3, h=2, nl=5))
     q.units = "kg"
 
-    args: Tuple[Any, Mapping, Mapping] = (
+    args: tuple[Any, Mapping, Mapping] = (
         literal("demand"),
         dict(commodity="c", node="nl", time="h"),
         dict(level="l", year=2022),

message_ix/tests/test_feature_duration_time.py

@@ -13,8 +13,7 @@
 
 
 # A function for generating a simple model with sub-annual time slices
-# FIXME reduce complexity 14 → ≤13
-def model_generator(  # noqa: C901
+def model_generator(
     test_mp,
     comment,
     tec_time,
@@ -66,23 +65,21 @@ def model_generator(  # noqa: C901
     map_time = {}
     for [tmp_lvl, number, parent] in time_steps:
         scen.add_set("lvl_temporal", tmp_lvl)
-        if parent == "year":
-            times = [tmp_lvl[0] + "-" + str(x + 1) for x in range(number)]
-        else:
-            times = [
+        times = (
+            [tmp_lvl[0] + "-" + str(x + 1) for x in range(number)]
+            if parent == "year"
+            else [
                 p + "_" + tmp_lvl[0] + "-" + str(x + 1)
                 for (p, x) in product(map_time[parent], range(number))
             ]
+        )
 
         map_time[tmp_lvl] = times
         scen.add_set("time", times)
 
         # Adding "map_temporal_hierarchy" and "duration_time"
         for h in times:
-            if parent == "year":
-                p = "year"
-            else:
-                p = h.split("_" + tmp_lvl[0])[0]
+            p = "year" if parent == "year" else h.split("_" + tmp_lvl[0])[0]
             # Temporal hierarchy (order: temporal level, time, parent time)
             scen.add_set("map_temporal_hierarchy", [tmp_lvl, h, p])
 
@@ -111,10 +108,11 @@ def model_generator(  # noqa: C901
             "time"
         ]
         # If technology is linking two different temporal levels
-        if tmp_lvl_in != tmp_lvl_out:
-            time_pairs = product(times_in, times_out)
-        else:
-            time_pairs = zip(times_in, times_out)
+        time_pairs = (
+            product(times_in, times_out)
+            if tmp_lvl_in != tmp_lvl_out
+            else zip(times_in, times_out)
+        )
 
         # Configuring data for "time_origin" and "time" in "input"
         for h_in, h_act in time_pairs: