MAINT: address linting issues

.cspell.json

@@ -38,6 +38,7 @@
     "typings"
   ],
   "ignoreWords": [
+    "FURB",
     "MAINT",
     "Nelder",
     "PYDEVD",

.pre-commit-config.yaml

@@ -23,8 +23,10 @@ repos:
           - |
             cell.attachments
             cell.metadata.code_folding
+            cell.metadata.editable
             cell.metadata.id
             cell.metadata.pycharm
+            cell.metadata.slideshow
             cell.metadata.user_expressions
             metadata.celltoolbar
             metadata.colab.name
@@ -40,7 +42,7 @@ repos:
             metadata.vscode
 
   - repo: https://github.com/ComPWA/policy
-    rev: 0.3.11
+    rev: 0.3.16
     hooks:
       - id: check-dev-files
         args:
@@ -53,6 +55,7 @@ repos:
           - --repo-title=TensorWaves
       - id: colab-toc-visible
       - id: fix-nbformat-version
+      - id: remove-empty-tags
       - id: set-nb-cells
         args:
           - --add-install-cell

.vscode/settings.json

@@ -33,6 +33,9 @@
   "cSpell.enabled": true,
   "diffEditor.experimental.showMoves": true,
   "editor.formatOnSave": true,
+  "files.associations": {
+    "**/.constraints/py*.txt": "pip-requirements"
+  },
   "files.watcherExclude": {
     "**/*_cache/**": true,
     "**/.eggs/**": true,

benchmarks/ampform.py

@@ -197,8 +197,8 @@ def test_fit(self, backend, benchmark, model, size):
 
 def print_data_sample(data: DataSample, sample_size: int) -> None:
     """Print a `.DataSample`, so it can be pasted into the expected sample."""
-    print()  # noqa: T201
-    pprint({  # noqa: T203
+    print()
+    pprint({
         i: np.round(four_momenta[:sample_size], decimals=11).tolist()
         for i, four_momenta in data.items()
     })

benchmarks/expression.py

@@ -114,7 +114,7 @@ def test_data(backend, benchmark, size):
 def test_fit(
     backend: str,
     benchmark,
-    optimizer_type: type[Minuit2] | type[ScipyMinimizer],
+    optimizer_type: type[Minuit2 | ScipyMinimizer],
     size: int,
 ):
     domain, data = generate_data_and_domain(backend, n_data=size, n_domain=10 * size)
@@ -131,7 +131,7 @@ def test_fit(
     result = benchmark(optimizer.optimize, estimator, function.parameters)
 
     assert pytest.approx(result.estimator_value, rel=1e-2) == original_nll
-    if optimizer_type not in {ScipyMinimizer}:
+    if optimizer_type != ScipyMinimizer:
         assert result.minimum_valid
     for par in function.parameters:
         original_value = original_parameters[par]

docs/conf.py

@@ -17,7 +17,7 @@
 def create_tensorflow_inventory() -> None:
     if os.path.exists("tensorflow.inv"):
         return
-    subprocess.check_call(
+    subprocess.check_call(  # noqa: S603
         ("sphobjinv", "convert", "-o", "zlib", "tensorflow.txt"),
     )
 

pyproject.toml

@@ -220,6 +220,10 @@ module = ["phasespace"]
 ignore_missing_imports = true
 module = ["scipy.optimize"]
 
+[[tool.mypy.overrides]]
+ignore_missing_imports = true
+module = ["sympy.*"]
+
 [[tool.mypy.overrides]]
 ignore_missing_imports = true
 module = ["tensorflow.python.ops.numpy_ops"]
@@ -309,40 +313,11 @@ docstring-code-format = true
 line-ending = "lf"
 
 [tool.ruff.lint]
-extend-select = [
-    "A",
-    "B",
-    "BLE",
-    "C4",
-    "C90",
-    "D",
-    "EM",
-    "ERA",
-    "FA",
-    "I",
-    "ICN",
-    "INP",
-    "ISC",
-    "N",
-    "NPY",
-    "PGH",
-    "PIE",
-    "PL",
-    "Q",
-    "RET",
-    "RSE",
-    "RUF",
-    "S",
-    "SIM",
-    "T20",
-    "TCH",
-    "TID",
-    "TRY",
-    "UP",
-    "YTT",
-]
 ignore = [
+    "ANN401",
     "C408",
+    "COM812",
+    "CPY001",
     "D101",
     "D102",
     "D103",
@@ -352,23 +327,48 @@ ignore = [
     "D213",
     "D407",
     "D416",
+    "DOC",
+    "DTZ005",
     "E501",
+    "FBT00",
+    "FURB10",
+    "FURB140",
+    "G004",
     "ISC001",
     "PLW1514",
+    "PT001",
+    "PTH",
     "RUF012",
     "S307",
     "SIM108",
 ]
+select = ["ALL"]
 task-tags = ["cspell"]
 
+[tool.ruff.lint.flake8-builtins]
+builtins-ignorelist = ["display"]
+
+[tool.ruff.lint.flake8-comprehensions]
+allow-dict-calls-with-keyword-arguments = true
+
+[tool.ruff.lint.flake8-self]
+ignore-names = [
+    "_latex",
+    "_numpycode",
+    "_print",
+]
+
 [tool.ruff.lint.isort]
 split-on-trailing-comma = false
 
 [tool.ruff.lint.per-file-ignores]
 "*.ipynb" = [
+    "ANN",
+    "ARG002",
     "B018",
     "C90",
     "D",
+    "E303",
     "E402",
     "E703",
     "F404",
@@ -389,14 +389,21 @@ split-on-trailing-comma = false
     "F821",
 ]
 "benchmarks/*" = [
+    "ANN",
     "D",
+    "INP001",
+    "PGH001",
     "PLC0415",
+    "PLC2701",
     "PLR0913",
     "PLR0917",
     "PLR2004",
     "PLR6301",
     "S101",
+    "SLF001",
+    "T20",
 ]
+"callbacks.py" = ["ARG002"]
 "docs/*" = [
     "E402",
     "INP001",
@@ -413,6 +420,8 @@ split-on-trailing-comma = false
 "src/tensorwaves/function/_backend.py" = ["PLC0415"]
 "src/tensorwaves/function/sympy/__init__.py" = ["PLC0415"]
 "tests/*" = [
+    "ANN",
+    "ARG002",
     "D",
     "INP001",
     "PGH001",
@@ -424,6 +433,7 @@ split-on-trailing-comma = false
     "PLR2004",
     "PLR6301",
     "S101",
+    "SLF001",
     "T20",
 ]
 

src/tensorwaves/data/_data_sample.py

@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import operator
 from typing import TYPE_CHECKING, Any, Callable
 
 import numpy as np
@@ -27,7 +28,7 @@ def _determine_merge_method(
     sample: DataSample,
 ) -> Callable[[tuple[np.ndarray, np.ndarray]], np.ndarray]:
     if len(sample) == 0:
-        return lambda sample_tuple: sample_tuple[1]
+        return operator.itemgetter(1)
     some_array = next(iter(sample.values()))
     rank = len(some_array.shape)
     if rank == 1:

src/tensorwaves/data/rng.py

@@ -18,7 +18,7 @@
 class NumpyUniformRNG(RealNumberGenerator):
     """Implements a uniform real random number generator using `numpy`."""
 
-    def __init__(self, seed: float | None = None):
+    def __init__(self, seed: float | None = None) -> None:
         self.seed = seed
 
     def __call__(
@@ -45,7 +45,7 @@ def seed(self, value: float | None) -> None:
 class TFUniformRealNumberGenerator(RealNumberGenerator):
     """Implements a uniform real random number generator using tensorflow."""
 
-    def __init__(self, seed: float | None = None):
+    def __init__(self, seed: float | None = None) -> None:
         try:
             from tensorflow import float64  # noqa: PLC0415
         except ImportError:  # pragma: no cover

src/tensorwaves/estimator.py

@@ -86,7 +86,7 @@ def gradient_creator(
         return jax.grad(function)
 
     def raise_gradient_not_implemented(
-        parameters: Mapping[str, ParameterValue],
+        parameters: Mapping[str, ParameterValue],  # noqa: ARG001
     ) -> dict[str, ParameterValue]:
         msg = f"Gradient not implemented for back-end {backend}."
         raise NotImplementedError(msg)

src/tensorwaves/function/sympy/__init__.py

@@ -468,7 +468,7 @@ def prepare_caching(
         transformer_expressions[symbol] = sub_expr
         undefined_variables.update(variables - _get_free_symbols(sub_expr))
     for symbol in undefined_variables:
-        transformer_expressions[symbol] = symbol
+        transformer_expressions[symbol] = symbol  # noqa: PERF403
     return cache_expression, transformer_expressions
 
 

src/tensorwaves/function/sympy/_printer.py

@@ -23,8 +23,8 @@ def __init__(self) -> None:
                 "allow_unknown_functions": True,
             }
         )
-        self._kc = _replace_module(NumPyPrinter._kc, "numpy", self._module)
-        self._kf = _replace_module(NumPyPrinter._kf, "numpy", self._module)
+        self._kc = _replace_module(NumPyPrinter._kc, "numpy", self._module)  # noqa: SLF001
+        self._kf = _replace_module(NumPyPrinter._kf, "numpy", self._module)  # noqa: SLF001
         self.printmethod = "_numpycode"  # force using _numpycode methods
 
 

src/tensorwaves/interface.py

@@ -142,7 +142,7 @@ def _repr_pretty_(self, p: PrettyPrinter, cycle: bool) -> None:
         else:
             with p.group(indent=1, open=f"{class_name}("):
                 for attribute in attrs.fields(type(self)):  # type: ignore[misc]
-                    if attribute.name in {"specifics"}:
+                    if attribute.name == "specifics":
                         continue
                     value = getattr(self, attribute.name)
                     if value != attribute.default:

src/tensorwaves/optimizer/scipy.py

@@ -80,8 +80,7 @@ def create_parameter_dict(
             )
 
         def wrapped_function(pars: list) -> float:
-            nonlocal n_function_calls
-            nonlocal estimator_value
+            nonlocal n_function_calls, estimator_value
             n_function_calls += 1
             update_parameters(pars)
             parameters = parameter_handler.unflatten(flattened_parameters)

tests/function/test_function.py

@@ -117,7 +117,7 @@ def test_variadic_args(self):
 
 
 def test_get_source_code():
-    def inline_function(a, x):
+    def inline_function(a, x):  # noqa: FURB118
         return a * x
 
     function = PositionalArgumentFunction(

tests/optimizer/test_fit_simple_model.py

@@ -116,7 +116,7 @@ def test_optimize_all_parameters(
     backend: str,
     domain_and_data_sample: tuple[DataSample, DataSample],
     expression_and_parameters: tuple[sp.Expr, dict[sp.Symbol, float]],
-    optimizer_type: type[Minuit2] | type[ScipyMinimizer],
+    optimizer_type: type[Minuit2 | ScipyMinimizer],
     output_dir: Path,
 ):
     domain, data = domain_and_data_sample
@@ -157,7 +157,7 @@ def test_optimize_all_parameters(
         assert pytest.approx(yaml[par]) == result.parameter_values[par]
 
     assert pytest.approx(result.estimator_value, rel=5e-3) == original_nll
-    if optimizer_type not in {ScipyMinimizer}:
+    if optimizer_type != ScipyMinimizer:
         assert result.minimum_valid
     for par in function.parameters:
         original_value = original_parameters[par]

tests/optimizer/test_minuit.py

@@ -37,7 +37,8 @@ def __call__(self, parameters: Mapping[str, ParameterValue]) -> float:
         return self.__polynomial(_x, _y)
 
     def gradient(
-        self, parameters: Mapping[str, ParameterValue]
+        self,
+        parameters: Mapping[str, ParameterValue],
     ) -> dict[str, ParameterValue]:
         return NotImplemented
 

tests/optimizer/test_scipy.py

@@ -22,7 +22,8 @@ def __call__(self, parameters: Mapping[str, ParameterValue]) -> float:
         return self.__polynomial(_x)
 
     def gradient(
-        self, parameters: Mapping[str, ParameterValue]
+        self,
+        parameters: Mapping[str, ParameterValue],
     ) -> dict[str, ParameterValue]:
         return NotImplemented
 
@@ -37,7 +38,8 @@ def __call__(self, parameters: Mapping[str, ParameterValue]) -> float:
         return self.__polynomial(_x, _y)
 
     def gradient(
-        self, parameters: Mapping[str, ParameterValue]
+        self,
+        parameters: Mapping[str, ParameterValue],
     ) -> dict[str, ParameterValue]:
         return NotImplemented
 

tests/test_interface.py

@@ -1,3 +1,5 @@
+import math
+
 import pytest
 from IPython.lib.pretty import pretty
 
@@ -13,7 +15,7 @@ def fit_result(self) -> FitResult:
             function_calls=50,
             estimator_value=-2e4,
             parameter_values={
-                R"\pi": 3.14,
+                R"\pi": math.pi,
                 "a": -5.0,
                 "complex": 1 + 1j,
             },