RFC: support python 3.12 (but drop 3.8)

.github/workflows/docs.yml

@@ -25,7 +25,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest]
-        python-version: [3.8]
+        python-version: [3.9]
 
     timeout-minutes: 30
 
@@ -37,7 +37,7 @@ jobs:
     - name: Install dependencies
       run: |
         pip install tox
-        
+
         # Install markdown-spellcheck
         sudo npm install -g markdown-spellcheck
     - name: Generate Documentation

.github/workflows/lint.yml

@@ -14,7 +14,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest]
-        python-version: [3.8]
+        python-version: [3.9]
 
     timeout-minutes: 30
 
@@ -36,4 +36,4 @@ jobs:
       run: tox -e check-copyright
     - name: Misc checks
       run: |
-        tox -e bandit,safety
+        tox -e bandit

.github/workflows/test.yml

@@ -14,7 +14,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: [3.8, 3.9, "3.10", "3.11"]
+        python-version: [3.9, "3.10", "3.11", "3.12"]
 
     timeout-minutes: 30
 

.ruff.toml

@@ -42,8 +42,8 @@ dummy-variable-rgx = "^(_+|(_+[a-zA-Z0-9_]*[a-zA-Z0-9]+?))$"
 # Whether to enable preview mode. When preview mode is enabled, Ruff will use unstable rules and fixes.
 preview = true
 
-# Assume Python 3.8
-target-version = "py38"
+# Assume Python 3.9
+target-version = "py39"
 
 [per-file-ignores]
 "examples/docker-sir.py" = ["INP001", "T201"]

CONTRIBUTING.md

@@ -66,7 +66,6 @@ We have various commands which are helpful during development.
 ```
 make lint-all
 make static
-make safety
 make bandit
 ```
 

Makefile

@@ -67,7 +67,7 @@ clean-test: ## remove test and coverage artifacts
 	rm -fr coverage.xml
 
 .PHONY: lint-all
-lint-all: black check-copyright ruff static bandit safety vulture darglint ## run all linters
+lint-all: black check-copyright ruff static bandit vulture darglint ## run all linters
 
 .PHONY: lint-all-files
 lint-all-files: black-files ruff-files static-files bandit-files vulture-files darglint-files ## run all linters for specific files (specified with files="file1 file2 somedir ...")
@@ -130,10 +130,6 @@ bandit-files: ## run bandit for specific files (specified with files="file1 file
 	$(call check_defined, files)
 	bandit $(files)
 
-.PHONY: safety
-safety: ## run safety
-	safety check
-
 .PHONY: vulture
 vulture: ## run vulture
 	vulture black_it scripts/whitelists/package_whitelist.py

black_it/calibrator.py

@@ -22,7 +22,7 @@
 import time
 import warnings
 from pathlib import Path
-from typing import TYPE_CHECKING, Callable, Sequence, cast
+from typing import TYPE_CHECKING, Callable, cast
 
 import numpy as np
 from joblib import Parallel, delayed  # type: ignore[import]
@@ -39,6 +39,7 @@
 
 if TYPE_CHECKING:
     import os
+    from collections.abc import Sequence
 
     from numpy.typing import NDArray
 
@@ -127,9 +128,11 @@ def __init__(  # noqa: PLR0913
         # initialize arrays
         self.params_samp = np.zeros((0, self.param_grid.dims))
         self.losses_samp = np.zeros(0)
-        self.batch_num_samp = np.zeros(0, dtype=int)
-        self.method_samp = np.zeros(0, dtype=int)
-        self.series_samp = np.zeros((0, self.ensemble_size, self.N, self.D))
+        self.batch_num_samp: NDArray[np.int64] = np.zeros(0, dtype=int)
+        self.method_samp: NDArray[np.int64] = np.zeros(0, dtype=int)
+        self.series_samp: NDArray[np.float64] = np.zeros(
+            (0, self.ensemble_size, self.N, self.D),
+        )
 
         # initialize variables before calibration
         self.n_sampled_params = 0

black_it/loss_functions/base.py

@@ -18,13 +18,16 @@
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
-from typing import Callable, Optional, Sequence
+from typing import TYPE_CHECKING, Callable, Optional
 
 import numpy as np
 from numpy.typing import NDArray
 
 from black_it.utils.base import _assert
 
+if TYPE_CHECKING:
+    from collections.abc import Sequence
+
 TimeSeriesFilter = Optional[Callable[[NDArray[np.float64]], NDArray[np.float64]]]
 """A filter that receives a time series and returns its filtered version. Used by the BaseLoss constructor."""
 

black_it/loss_functions/gsl_div.py

@@ -270,7 +270,7 @@ def get_words(time_series: NDArray[np.float64], length: int) -> NDArray:
             "the chosen word length is too high",
             exception_class=ValueError,
         )
-        tsw = np.zeros(shape=(tswlen,), dtype=np.int32)
+        tsw: NDArray[np.float64] = np.zeros(shape=(tswlen,), dtype=np.int32)
 
         for i in range(length):
             k = 10 ** (length - i - 1)

black_it/loss_functions/likelihood.py

@@ -18,7 +18,7 @@
 from __future__ import annotations
 
 import warnings
-from typing import TYPE_CHECKING, Callable
+from typing import TYPE_CHECKING, Callable, cast
 
 import numpy as np
 
@@ -82,9 +82,13 @@ def compute_loss(
         Returns:
             The loss value.
         """
-        r = sim_data_ensemble.shape[0]  # number of repetitions
-        s = sim_data_ensemble.shape[1]  # simulation length
-        d = sim_data_ensemble.shape[2]  # number of dimensions
+        sim_data_ensemble_shape: tuple[int, int, int] = cast(
+            tuple[int, int, int],
+            sim_data_ensemble.shape,
+        )
+        r = sim_data_ensemble_shape[0]  # number of repetitions
+        s = sim_data_ensemble_shape[1]  # simulation length
+        d = sim_data_ensemble_shape[2]  # time series dimension
 
         if self.coordinate_weights is not None:
             warnings.warn(  # noqa: B028

black_it/plot/plot_results.py

@@ -19,7 +19,7 @@
 
 import pickle  # nosec B403
 from pathlib import Path
-from typing import TYPE_CHECKING, Collection
+from typing import TYPE_CHECKING
 
 import matplotlib.pyplot as plt  # type: ignore[import]
 import numpy as np
@@ -31,6 +31,9 @@
 
 if TYPE_CHECKING:
     import os
+    from collections.abc import Collection
+
+    from numpy.typing import NDArray
 
 
 def _get_samplers_id_table(saving_folder: str | os.PathLike) -> dict[str, int]:
@@ -298,7 +301,7 @@ def plot_sampling_interact(saving_folder: str | os.PathLike) -> None:
     data_frame = pd.read_csv(calibration_results_file)
 
     max_bn = int(max(data_frame["batch_num_samp"]))
-    all_bns = np.arange(max_bn + 1, dtype=int)
+    all_bns: NDArray[np.int64] = np.arange(max_bn + 1, dtype=int)
     indices_bns = np.array_split(all_bns, min(max_bn, 3))
 
     dict_bns = {}

black_it/samplers/halton.py

@@ -18,14 +18,16 @@
 from __future__ import annotations
 
 import itertools
-from typing import TYPE_CHECKING, Iterator
+from typing import TYPE_CHECKING
 
 import numpy as np
 
 from black_it.samplers.base import BaseSampler
 from black_it.utils.base import check_arg, digitize_data
 
 if TYPE_CHECKING:
+    from collections.abc import Iterator
+
     from numpy.typing import NDArray
 
     from black_it.search_space import SearchSpace

black_it/samplers/xgboost.py

@@ -28,9 +28,9 @@
 if TYPE_CHECKING:
     from numpy.typing import NDArray
 
-MAX_FLOAT32 = np.finfo(np.float32).max
-MIN_FLOAT32 = np.finfo(np.float32).min
-EPS_FLOAT32 = np.finfo(np.float32).eps
+MAX_FLOAT32: float = cast(float, np.finfo(np.float32).max)
+MIN_FLOAT32: float = cast(float, np.finfo(np.float32).min)
+EPS_FLOAT32: float = cast(float, np.finfo(np.float32).eps)
 
 
 class XGBoostSampler(MLSurrogateSampler):

black_it/schedulers/base.py

@@ -19,11 +19,13 @@
 
 import contextlib
 from abc import ABC, abstractmethod
-from typing import TYPE_CHECKING, Generator, Sequence
+from typing import TYPE_CHECKING
 
 from black_it.utils.seedable import BaseSeedable
 
 if TYPE_CHECKING:
+    from collections.abc import Generator, Sequence
+
     import numpy as np
     from numpy.typing import NDArray
 

black_it/schedulers/rl/rl_scheduler.py

@@ -18,7 +18,7 @@
 from __future__ import annotations
 
 import threading
-from typing import TYPE_CHECKING, List, Sequence, cast
+from typing import TYPE_CHECKING, cast
 
 import numpy as np
 
@@ -27,6 +27,7 @@
 from black_it.schedulers.base import BaseScheduler
 
 if TYPE_CHECKING:
+    from collections.abc import Sequence
     from queue import Queue
 
     from numpy._typing import NDArray
@@ -103,7 +104,7 @@ def _add_or_get_bootstrap_sampler(
             return samplers, sampler_types[HaltonSampler]
 
         new_sampler = HaltonSampler(batch_size=1)
-        return tuple(list(samplers) + cast(List[BaseSampler], [new_sampler])), len(
+        return tuple(list(samplers) + cast(list[BaseSampler], [new_sampler])), len(
             samplers,
         )
 

black_it/search_space.py

@@ -72,7 +72,7 @@ def __init__(
         self._param_grid: list[NDArray[np.float64]] = []
         self._space_size = 1
         for i in range(self.dims):
-            new_col = np.arange(
+            new_col: NDArray[np.float64] = np.arange(
                 parameters_bounds[0][i],
                 parameters_bounds[1][i] + 0.0000001,
                 parameters_precision[i],

black_it/utils/json_pandas_checkpointing.py

@@ -20,7 +20,7 @@
 import json
 import pickle  # nosec B403
 from pathlib import Path
-from typing import TYPE_CHECKING, Mapping
+from typing import TYPE_CHECKING
 
 import numpy as np
 import pandas as pd  # type: ignore[import]
@@ -29,6 +29,8 @@
 from black_it.utils.base import NumpyArrayEncoder, PathLike
 
 if TYPE_CHECKING:
+    from collections.abc import Mapping
+
     from numpy.typing import NDArray
 
     from black_it.loss_functions.base import BaseLoss

black_it/utils/sqlite3_checkpointing.py

@@ -23,12 +23,14 @@
 import pickle  # nosec B403
 import sqlite3
 from pathlib import Path
-from typing import TYPE_CHECKING, Mapping, Sequence
+from typing import TYPE_CHECKING
 
 import numpy as np
 from numpy.typing import NDArray
 
 if TYPE_CHECKING:
+    from collections.abc import Mapping, Sequence
+
     from black_it.loss_functions.base import BaseLoss
     from black_it.samplers.base import BaseSampler
     from black_it.utils.base import PathLike

examples/models/economics/brock_hommes.py

@@ -17,12 +17,14 @@
 """Implementation of the model in (Brock and Hommes, 1998)."""
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Sequence
+from typing import TYPE_CHECKING
 
 import numpy as np
 from scipy.special import softmax
 
 if TYPE_CHECKING:
+    from collections.abc import Sequence
+
     from numpy.typing import NDArray
 
 

examples/models/simple_models.py

@@ -28,12 +28,14 @@
 """
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Sequence
+from typing import TYPE_CHECKING
 
 import numpy as np
 from scipy.stats import alpha, bernoulli
 
 if TYPE_CHECKING:
+    from collections.abc import Sequence
+
     from numpy.typing import NDArray