Update .model.transport type hints for Python >= 3.9

- Use standard collections, e.g. list[str] instead of typing.List[str].
- Import certain types from collections.abc, instead of deprecated aliases in
  typing.

Author: khaeru

message_ix_models/model/transport/base.py

@@ -3,7 +3,7 @@
 from functools import partial
 from itertools import pairwise, product
 from pathlib import Path
-from typing import TYPE_CHECKING, Any, List, Optional
+from typing import TYPE_CHECKING, Any, Optional
 
 import genno
 import numpy as np
@@ -423,7 +423,7 @@ def to_csv(
 
 
 def format_share_constraints(
-    qty: "AnyQuantity", config: dict, *, kind: str, groupby: List[str] = []
+    qty: "AnyQuantity", config: dict, *, kind: str, groupby: list[str] = []
 ) -> pd.DataFrame:
     """Produce values for :file:`ue_share_constraints.xlsx`.
 

message_ix_models/model/transport/build.py

@@ -3,7 +3,7 @@
 import logging
 from importlib import import_module
 from pathlib import Path
-from typing import TYPE_CHECKING, Any, Dict, Optional, Tuple
+from typing import TYPE_CHECKING, Any, Optional
 
 import pandas as pd
 from genno import Computer, KeyExistsError, Quantity, quote
@@ -179,7 +179,7 @@ def add_exogenous_data(c: Computer, info: ScenarioInfo) -> None:
     # Identify appropriate source keyword arguments for loading GDP and population data
     source = str(config.ssp)
     if config.ssp in SSP_2017:
-        source_kw: Tuple[Dict[str, Any], ...] = (
+        source_kw: tuple[dict[str, Any], ...] = (
             dict(measure="GDP", model="IIASA GDP"),
             dict(measure="POP", model="IIASA GDP"),
         )
@@ -471,7 +471,7 @@ def get_computer(
 def main(
     context: Context,
     scenario: Scenario,
-    options: Optional[Dict] = None,
+    options: Optional[dict] = None,
     **option_kwargs,
 ):
     """Build MESSAGEix-Transport on `scenario`.

message_ix_models/model/transport/config.py

@@ -1,7 +1,7 @@
 import logging
 from dataclasses import InitVar, dataclass, field, replace
 from enum import Enum
-from typing import TYPE_CHECKING, Dict, List, Literal, Optional, Tuple, Union
+from typing import TYPE_CHECKING, Literal, Optional, Union
 
 import message_ix
 from genno import Quantity
@@ -63,7 +63,7 @@ class Config(ConfigHelper):
     #:    for transport modes *other than* LDV. See :func:`non_ldv.growth_new_capacity`.
     #: "* initial_*_up"
     #:    Base value for growth constraints. These values are arbitrary.
-    constraint: Dict = field(
+    constraint: dict = field(
         default_factory=lambda: {
             "LDV growth_activity_lo": -0.0192,
             "LDV growth_activity_up": 0.0192 * 3.0,
@@ -93,7 +93,7 @@ class Config(ConfigHelper):
     #:      'updateTRPdata', with the comment "Original data from Sei (PAO)."
     #:    - This probably refers to some source that gave relative costs of different
     #:      buses, in PAO, for this year; it is applied across all years.
-    cost: Dict = field(
+    cost: dict = field(
         default_factory=lambda: {
             #
             "ldv nga": 0.85,
@@ -114,7 +114,7 @@ class Config(ConfigHelper):
     #: specified in the corresponding technology.yaml file.
     #:
     #: .. todo:: Read directly from technology.yaml
-    demand_modes: List[str] = field(
+    demand_modes: list[str] = field(
         default_factory=lambda: ["LDV", "2W", "AIR", "BUS", "RAIL"]
     )
 
@@ -129,7 +129,7 @@ class Config(ConfigHelper):
     dummy_supply: bool = False
 
     #: Various efficiency factors.
-    efficiency: Dict = field(
+    efficiency: dict = field(
         default_factory=lambda: {
             "*": 0.2,
             "hev": 0.2,
@@ -150,7 +150,7 @@ class Config(ConfigHelper):
     emission_relations: bool = True
 
     #: Various other factors.
-    factor: Dict = field(default_factory=dict)
+    factor: dict = field(default_factory=dict)
 
     #: If :obj:`True` (the default), do not record/preserve parameter data when removing
     #: set elements from the base model.
@@ -171,7 +171,7 @@ class Config(ConfigHelper):
     #:
     #: ``F ROAD``: similar to IEA “Future of Trucks” (2017) values; see
     #: .transport.freight. Alternately use 5.0, similar to Roadmap 2017 values.
-    load_factor: Dict = field(
+    load_factor: dict = field(
         default_factory=lambda: {
             "F ROAD": 10.0,
             "F RAIL": 10.0,
@@ -183,7 +183,7 @@ class Config(ConfigHelper):
 
     #: Period in which LDV costs match those of a reference region.
     #: Dimensions: (node,).
-    ldv_cost_catch_up_year: Dict = field(default_factory=dict)
+    ldv_cost_catch_up_year: dict = field(default_factory=dict)
 
     #: Method for calibrating LDV stock and sales:
     #:
@@ -193,7 +193,7 @@ class Config(ConfigHelper):
 
     #: Tuples of (node, technology (transport mode), commodity) for which minimum
     #: activity should be enforced. See :func:`.non_ldv.bound_activity_lo`.
-    minimum_activity: Dict[Tuple[str, Tuple[str, ...], str], float] = field(
+    minimum_activity: dict[tuple[str, tuple[str, ...], str], float] = field(
         default_factory=dict
     )
 
@@ -202,15 +202,15 @@ class Config(ConfigHelper):
     mode_share: str = "default"
 
     #: List of modules containing model-building calculations.
-    modules: List[str] = field(
+    modules: list[str] = field(
         default_factory=lambda: (
             "groups demand freight ikarus ldv disutility non_ldv plot data"
         ).split()
     )
 
     #: Used by :func:`.get_USTIMES_MA3T` to map MESSAGE regions to U.S. census divisions
     #: appearing in MA³T.
-    node_to_census_division: Dict = field(default_factory=dict)
+    node_to_census_division: dict = field(default_factory=dict)
 
     #: **Temporary** setting for the SSP 2024 project: indicates whether the base
     #: scenario used is a policy (carbon pricing) scenario, or not. This currently does
@@ -226,7 +226,7 @@ class Config(ConfigHelper):
     #:
     #: :mod:`.transport.build` and :mod:`.transport.report` code will respond to these
     #: settings in documented ways.
-    project: Dict[str, Enum] = field(
+    project: dict[str, Enum] = field(
         default_factory=lambda: dict(
             futures=FUTURES_SCENARIO.BASE, navigate=NAVIGATE_SCENARIO.REF
         )
@@ -236,7 +236,7 @@ class Config(ConfigHelper):
     scaling: float = 1.0
 
     #: Mapping from nodes to other nodes towards which share weights should converge.
-    share_weight_convergence: Dict = field(default_factory=dict)
+    share_weight_convergence: dict = field(default_factory=dict)
 
     #: Specification for the structure of MESSAGEix-Transport, processed from contents
     #: of :file:`set.yaml` and :file:`technology.yaml`.
@@ -282,7 +282,7 @@ class Config(ConfigHelper):
     #: space-delimited string (:py:`"module_a -module_b"`) or sequence of strings.
     #: Values prefixed with a hyphen (:py:`"-module_b"`) are *removed* from
     #: :attr:`.modules`.
-    extra_modules: InitVar[Union[str, List[str]]] = None
+    extra_modules: InitVar[Union[str, list[str]]] = None
 
     #: Identifier of a Transport Futures scenario, used to update :attr:`project` via
     #: :meth:`.ScenarioFlags.parse_futures`.
@@ -315,7 +315,7 @@ def from_context(
         cls,
         context: Context,
         scenario: Optional[message_ix.Scenario] = None,
-        options: Optional[Dict] = None,
+        options: Optional[dict] = None,
     ) -> "Config":
         """Configure `context` for building MESSAGEix-Transport.
 

message_ix_models/model/transport/data.py

@@ -2,10 +2,11 @@
 
 import logging
 from collections import defaultdict
+from collections.abc import Callable, Mapping
 from copy import deepcopy
 from functools import partial
 from operator import le
-from typing import TYPE_CHECKING, Callable, Dict, List, Mapping, Optional, Set, Tuple
+from typing import TYPE_CHECKING, Optional
 
 import pandas as pd
 from genno import Computer, Key, Quantity
@@ -51,8 +52,8 @@ def prepare_computer(c: Computer):
 
 
 def conversion(
-    nodes: List[str], years: List[int], config: dict
-) -> Dict[str, pd.DataFrame]:
+    nodes: list[str], years: list[int], config: dict
+) -> dict[str, pd.DataFrame]:
     """Input and output data for conversion technologies:
 
     The technologies are named 'transport {service} load factor'.
@@ -72,7 +73,7 @@ def conversion(
         ("pax", 1.0, "Gp km / a"),
     ]
 
-    data0: Mapping[str, List] = defaultdict(list)
+    data0: Mapping[str, list] = defaultdict(list)
     for service, factor, output_unit in service_info:
         i_o = make_io(
             (f"transport {service} vehicle", "useful", "Gv km"),
@@ -98,7 +99,7 @@ def conversion(
     return data1
 
 
-def dummy_supply(technologies: List["Code"], info, config) -> Dict[str, pd.DataFrame]:
+def dummy_supply(technologies: list["Code"], info, config) -> dict[str, pd.DataFrame]:
     """Dummy fuel supply for the bare RES."""
     if not config["transport"].dummy_supply:
         return dict()
@@ -116,7 +117,7 @@ def dummy_supply(technologies: List["Code"], info, config) -> Dict[str, pd.DataF
         else:
             raise TypeError(type(commodity))
 
-    result: Dict[str, pd.DataFrame] = dict()
+    result: dict[str, pd.DataFrame] = dict()
     common = dict(mode="all", time="year", time_dest="year", unit="GWa")
     values = dict(output=1.0, var_cost=1.0)
 
@@ -133,7 +134,7 @@ def dummy_supply(technologies: List["Code"], info, config) -> Dict[str, pd.DataF
     return result
 
 
-def misc(info: ScenarioInfo, nodes: List[str], y: List[int]):
+def misc(info: ScenarioInfo, nodes: list[str], y: list[int]):
     """Miscellaneous bounds for calibration/vetting."""
 
     # Limit activity of methanol LDVs in the model base year
@@ -157,8 +158,8 @@ def misc(info: ScenarioInfo, nodes: List[str], y: List[int]):
 
 
 def navigate_ele(
-    nodes: List[str], techs: List["Code"], t_groups, years: List[int], config
-) -> Dict[str, pd.DataFrame]:
+    nodes: list[str], techs: list["Code"], t_groups, years: list[int], config
+) -> dict[str, pd.DataFrame]:
     """Return constraint data for :attr:`ScenarioFlags.ELE`.
 
     The text reads as follows as of 2023-02-15:
@@ -307,7 +308,7 @@ class MaybeAdaptR11Source(ExoDataSource):
     """
 
     #: Set of measures recognized by a subclass.
-    measures: Set[str] = set()
+    measures: set[str] = set()
 
     #: Mapping from :attr:`.measures` entries to file names.
     filename: Mapping[str, str] = dict()
@@ -364,7 +365,7 @@ def __call__(self):
     def __repr__(self) -> str:
         return self._repr
 
-    def get_keys(self) -> Tuple[Key, Key]:
+    def get_keys(self) -> tuple[Key, Key]:
         """Return the target keys for the (1) raw and (2) transformed data."""
         k = self.key or Key(
             self.name or self.measure.lower(), ("n", "y") + self.extra_dims

message_ix_models/model/transport/demand.py

@@ -1,7 +1,7 @@
 """Demand calculation for MESSAGEix-Transport."""
 
 import logging
-from typing import TYPE_CHECKING, Dict, List
+from typing import TYPE_CHECKING
 
 import genno
 import numpy as np
@@ -48,8 +48,8 @@
 
 
 def dummy(
-    commodities: List, nodes: List[str], y: List[int], config: dict
-) -> Dict[str, pd.DataFrame]:
+    commodities: list, nodes: list[str], y: list[int], config: dict
+) -> dict[str, pd.DataFrame]:
     """Dummy demands.
 
 
@@ -241,7 +241,7 @@ def pdt_per_capita(c: Computer) -> None:
     # Add `y` dimension. Here for the future fixed point we use y=2 * max(y), e.g.
     # 4220 for y=2110. The value doesn't matter, we just need to avoid overlap with y
     # in the model.
-    def _future(qty: "AnyQuantity", years: List[int]) -> "AnyQuantity":
+    def _future(qty: "AnyQuantity", years: list[int]) -> "AnyQuantity":
         return qty.expand_dims(y=[years[-1] * 2])
 
     # Same, but adding y0

message_ix_models/model/transport/factor.py

@@ -11,20 +11,10 @@
 import operator
 import re
 from abc import ABC, abstractmethod
+from collections.abc import Callable, Mapping, Sequence
 from dataclasses import dataclass, field
 from functools import partial
-from typing import (
-    TYPE_CHECKING,
-    Any,
-    Callable,
-    Dict,
-    List,
-    Mapping,
-    Optional,
-    Sequence,
-    Tuple,
-    Union,
-)
+from typing import TYPE_CHECKING, Any, Optional, Union
 
 import pandas as pd
 from genno import Computer, Key, Quantity
@@ -95,7 +85,7 @@ class Constant(Layer):
     value: Quantity
 
     #: Dimensions of the result.
-    dims: Tuple[str, ...]
+    dims: tuple[str, ...]
 
     operation = operator.mul
 
@@ -183,12 +173,12 @@ class Map(Layer):
     """
 
     dim: str
-    values: Dict[str, Layer]
+    values: dict[str, Layer]
 
     operation = operator.mul
 
     def __init__(
-        self, dim: str, values: Optional[Dict[str, Layer]] = None, **value_kwargs: Layer
+        self, dim: str, values: Optional[dict[str, Layer]] = None, **value_kwargs: Layer
     ):
         self.dim = dim
         self.values = values or value_kwargs
@@ -215,7 +205,7 @@ class ScenarioSetting(Layer):
     """
 
     #: Mapping from scenario identifier to setting label.
-    setting: Dict[Any, str]
+    setting: dict[Any, str]
 
     #: Default setting.
     default: str
@@ -310,7 +300,7 @@ class Factor:
     """
 
     #: Ordered list of :class:`.Layer`.
-    layers: List[Layer] = field(default_factory=list)
+    layers: list[Layer] = field(default_factory=list)
 
     def __hash__(self):
         return hash(tuple(self.layers))
@@ -360,7 +350,7 @@ def add_tasks(
         )
 
     def __call__(
-        self, config, *coords, dims: Tuple[str, ...], scenario_expr: str
+        self, config, *coords, dims: tuple[str, ...], scenario_expr: str
     ) -> Quantity:
         """Invoke :meth:`quantify`, for use with :mod:`genno`."""
         kw = dict(zip(dims, coords))