style: fix up tests

pyproject.toml

@@ -314,8 +314,8 @@ flake8-tidy-imports.ban-relative-imports = "all"
 "docs/lite/jupyterlite.py" = ["F401", "F704"]
 "**.ipynb" = ["T20"]
 "noxfile.py" = ["T20"]
-"tests/**" = ["ARG001", "ARG002", "NPY002", "PLR0124", "PT012", "T20"]
-"validation/**" = ["T20", "PTH123", "NPY002"]
+"tests/**" = ["NPY002"]
+"validation/**" = ["T20", "NPY002"]
 
 [tool.pixi.workspace]
 channels = ["conda-forge"]

tests/benchmarks/test_benchmark.py

@@ -69,7 +69,8 @@ def hypotest(pdf, data):
 
 
 @pytest.mark.parametrize("n_bins", bins, ids=bin_ids)
-def test_hypotest(benchmark, backend, n_bins):
+@pytest.mark.usefixtures("backend")
+def test_hypotest(benchmark, n_bins):
     """
     Benchmark the performance of pyhf.utils.hypotest()
     for various numbers of bins and different backends

tests/conftest.py

@@ -145,6 +145,12 @@ def backend(request):
     return (tensor, optimizer)
 
 
+@pytest.fixture
+def _backend(backend):
+    """Alias for the backend fixture for use in fixtures that need the backend
+    side-effect but don't use the return value."""
+
+
 @pytest.fixture(
     params=[0, 1, 2, 4],
     ids=["interpcode0", "interpcode1", "interpcode2", "interpcode4"],

tests/test_backend_consistency.py

@@ -122,10 +122,5 @@ def test_hypotest_qmu_tilde(n_bins, invert_order):
     numpy_ratio = np.divide(test_statistic, test_statistic[0])
     numpy_ratio_delta_unity = np.absolute(np.subtract(numpy_ratio, 1))
 
-    try:
-        assert (numpy_ratio_delta_unity < tolerance["numpy"]).all()
-    except AssertionError:
-        print(
-            f"Ratio to NumPy+SciPy exceeded tolerance of {tolerance['numpy']}: {numpy_ratio_delta_unity.tolist()}"
-        )
-        raise AssertionError from None
+    err_msg = f"Ratio to NumPy+SciPy exceeded tolerance of {tolerance['numpy']}: {numpy_ratio_delta_unity.tolist()}"
+    assert (numpy_ratio_delta_unity < tolerance["numpy"]).all(), err_msg

tests/test_backends.py

@@ -86,7 +86,8 @@ def test_tensor_array_types():
 
 
 @pytest.mark.only_jax
-def test_jax_data_shape_mismatch_during_jitting(backend):
+@pytest.mark.usefixtures("backend")
+def test_jax_data_shape_mismatch_during_jitting():
     """
     Validate that during JAX tracing time pyhf doesn't try
     to convert the data to a list, which is not possible with tracers,

tests/test_combined_modifiers.py

@@ -1,4 +1,5 @@
 import numpy as np
+import pytest
 
 import pyhf
 from pyhf.modifiers.histosys import histosys_combined
@@ -44,7 +45,8 @@ def param_set(self, name):
         return self.par_map[name]["paramset"]
 
 
-def test_histosys(backend):
+@pytest.mark.usefixtures("backend")
+def test_histosys():
     mc = MockConfig(
         par_map={
             "hello": {
@@ -149,7 +151,8 @@ def test_histosys(backend):
     assert np.allclose(mod[0, 0, 3], [1.0, 2.0, 3.0])
 
 
-def test_normsys(backend):
+@pytest.mark.usefixtures("backend")
+def test_normsys():
     mc = MockConfig(
         par_map={
             "hello": {
@@ -256,7 +259,8 @@ def test_normsys(backend):
     assert np.allclose(mod[0, 0, 3], [1.1, 1.1, 1.1])
 
 
-def test_lumi(backend):
+@pytest.mark.usefixtures("backend")
+def test_lumi():
     mc = MockConfig(
         par_map={
             "lumi": {
@@ -315,7 +319,8 @@ def test_lumi(backend):
     assert np.allclose(mod[0, 0, 3], [4.0, 4.0, 4.0])
 
 
-def test_stat(backend):
+@pytest.mark.usefixtures("backend")
+def test_stat():
     mc = MockConfig(
         par_map={
             "staterror_chan1": {
@@ -406,7 +411,8 @@ def test_stat(backend):
     assert np.allclose(mod[1, 0, 0], [1, 1.2, 1.3])
 
 
-def test_shapesys(backend):
+@pytest.mark.usefixtures("backend")
+def test_shapesys():
     mc = MockConfig(
         par_map={
             "dummy1": {
@@ -519,7 +525,8 @@ def test_shapesys(backend):
     assert np.allclose(mod[1, 0, 0], [1, 1.2, 1.3])
 
 
-def test_normfactor(backend):
+@pytest.mark.usefixtures("backend")
+def test_normfactor():
     mc = MockConfig(
         par_map={
             "mu1": {
@@ -609,7 +616,8 @@ def test_normfactor(backend):
     assert np.allclose(mod[1, 0, 3], [1.0, 8.0, 8.0])
 
 
-def test_shapesys_zero(backend):
+@pytest.mark.usefixtures("backend")
+def test_shapesys_zero():
     mc = MockConfig(
         par_map={
             "SigXsecOverSM": {
@@ -675,7 +683,8 @@ def test_shapesys_zero(backend):
     assert mod[0, 1, 0, 2] == 1.0
 
 
-def test_shapefactor(backend):
+@pytest.mark.usefixtures("backend")
+def test_shapefactor():
     mc = MockConfig(
         par_map={
             "shapefac1": {

tests/test_constraints.py

@@ -32,7 +32,8 @@ def param_set(self, name):
         return self.par_map[name]["paramset"]
 
 
-def test_numpy_pdf_inputs(backend):
+@pytest.mark.usefixtures("backend")
+def test_numpy_pdf_inputs():
     spec = {
         "channels": [
             {
@@ -131,7 +132,8 @@ def fast(self, auxdata, pars):
     assert pytest.approx(slow_result) == fast_result
 
 
-def test_batched_constraints(backend):
+@pytest.mark.usefixtures("backend")
+def test_batched_constraints():
     config = MockConfig(
         par_order=["pois1", "pois2", "norm1", "norm2"],
         par_map={

tests/test_custom_mods.py

@@ -82,7 +82,7 @@ def test_missing_poi():
     modifier_set.update(**pyhf.modifiers.histfactory_set)
 
     with pytest.raises(exceptions.InvalidModel):
-        model = pyhf.Model(
+        pyhf.Model(
             {
                 "channels": [
                     {
@@ -108,4 +108,3 @@ def test_missing_poi():
             poi_name="non_existent_poi",
             validate=False,
         )
-        assert model

tests/test_events.py

@@ -76,7 +76,7 @@ def test_subscribe_function(capsys):
     ename = "test"
 
     def add(a, b):
-        print(a + b)
+        print(a + b)  # noqa: T201
 
     events.subscribe(ename)(add)
     events.trigger(ename)(1, 2)
@@ -91,7 +91,7 @@ def test_trigger_function(capsys):
     ename = "test"
 
     def add(a, b):
-        print(a + b)
+        print(a + b)  # noqa: T201
 
     precall = mock.Mock()
     postcall = mock.Mock()

tests/test_examples.py

@@ -1,7 +1,10 @@
 import shlex
 
+import pytest
 
-def test_2bin_1channel(tmp_path, script_runner):
+
+@pytest.mark.usefixtures("tmp_path")
+def test_2bin_1channel(script_runner):
     command = f"pyhf inspect {'docs/examples/json/2-bin_1-channel.json':s}"
     ret = script_runner.run(shlex.split(command))
     assert ret.success

tests/test_infer.py

@@ -23,7 +23,8 @@ def check_uniform_type(in_list):
     )
 
 
-def test_toms748_scan(tmp_path, hypotest_args):
+@pytest.mark.usefixtures("tmp_path")
+def test_toms748_scan(hypotest_args):
     """
     Test the upper limit toms748 scan returns the correct structure and values
     """
@@ -206,7 +207,8 @@ def test_upper_limit_return_tail_probs(hypotest_args):
     assert observed_limit == pytest.approx(1.01156939, abs=0.1)
 
 
-def test_mle_fit_default(tmp_path, hypotest_args):
+@pytest.mark.usefixtures("tmp_path")
+def test_mle_fit_default(hypotest_args):
     """
     Check that the default return structure of pyhf.infer.mle.fit is as expected
     """
@@ -220,7 +222,8 @@ def test_mle_fit_default(tmp_path, hypotest_args):
     assert pyhf.tensorlib.shape(result) == (model.config.npars,)
 
 
-def test_mle_fit_return_fitted_val(tmp_path, hypotest_args):
+@pytest.mark.usefixtures("tmp_path")
+def test_mle_fit_return_fitted_val(hypotest_args):
     """
     Check that the return structure of pyhf.infer.mle.fit with the
     return_fitted_val keyword arg is as expected
@@ -236,7 +239,8 @@ def test_mle_fit_return_fitted_val(tmp_path, hypotest_args):
     assert pyhf.tensorlib.shape(result[1]) == ()
 
 
-def test_hypotest_default(tmp_path, hypotest_args):
+@pytest.mark.usefixtures("tmp_path")
+def test_hypotest_default(hypotest_args):
     """
     Check that the default return structure of pyhf.infer.hypotest is as expected
     """
@@ -249,7 +253,8 @@ def test_hypotest_default(tmp_path, hypotest_args):
     assert isinstance(result, type(tb.astensor(result)))
 
 
-def test_hypotest_poi_outofbounds(tmp_path, hypotest_args):
+@pytest.mark.usefixtures("tmp_path", "hypotest_args")
+def test_hypotest_poi_outofbounds():
     """
     Check that the fit errors for POI outside of parameter bounds
     """
@@ -270,7 +275,8 @@ def test_hypotest_poi_outofbounds(tmp_path, hypotest_args):
 
 
 @pytest.mark.parametrize("test_stat", ["q0", "q", "qtilde"])
-def test_hypotest_return_tail_probs(tmp_path, hypotest_args, test_stat):
+@pytest.mark.usefixtures("tmp_path")
+def test_hypotest_return_tail_probs(hypotest_args, test_stat):
     """
     Check that the return structure of pyhf.infer.hypotest with the
     return_tail_probs keyword arg is as expected
@@ -287,7 +293,8 @@ def test_hypotest_return_tail_probs(tmp_path, hypotest_args, test_stat):
 
 
 @pytest.mark.parametrize("test_stat", ["q0", "q", "qtilde"])
-def test_hypotest_return_expected(tmp_path, hypotest_args, test_stat):
+@pytest.mark.usefixtures("tmp_path")
+def test_hypotest_return_expected(hypotest_args, test_stat):
     """
     Check that the return structure of pyhf.infer.hypotest with the
     addition of the return_expected keyword arg is as expected
@@ -309,7 +316,8 @@ def test_hypotest_return_expected(tmp_path, hypotest_args, test_stat):
 
 
 @pytest.mark.parametrize("test_stat", ["q0", "q", "qtilde"])
-def test_hypotest_return_expected_set(tmp_path, hypotest_args, test_stat):
+@pytest.mark.usefixtures("tmp_path")
+def test_hypotest_return_expected_set(hypotest_args, test_stat):
     """
     Check that the return structure of pyhf.infer.hypotest with the
     addition of the return_expected_set keyword arg is as expected
@@ -343,8 +351,8 @@ def test_hypotest_return_expected_set(tmp_path, hypotest_args, test_stat):
 @pytest.mark.parametrize("return_tail_probs", [True, False])
 @pytest.mark.parametrize("return_expected", [True, False])
 @pytest.mark.parametrize("return_expected_set", [True, False])
+@pytest.mark.usefixtures("tmp_path")
 def test_hypotest_return_calculator(
-    tmp_path,
     hypotest_args,
     calctype,
     kwargs,
@@ -391,7 +399,8 @@ def test_hypotest_return_calculator(
     [{"calctype": "asymptotics"}, {"calctype": "toybased", "ntoys": 5}],
     ids=lambda x: x["calctype"],
 )
-def test_hypotest_backends(backend, kwargs):
+@pytest.mark.usefixtures("backend")
+def test_hypotest_backends(kwargs):
     """
     Check that hypotest runs fully across all backends for all calculator types.
     """
@@ -535,7 +544,8 @@ def test_significance_to_pvalue_roundtrip(backend):
     assert np.allclose(sigma, back_to_sigma, atol=0, rtol=rtol)
 
 
-def test_emperical_distribution(tmp_path, hypotest_args):
+@pytest.mark.usefixtures("tmp_path")
+def test_emperical_distribution(hypotest_args):
     """
     Check that the empirical distribution of the test statistic gives
     expected results
@@ -581,7 +591,8 @@ def test_emperical_distribution(tmp_path, hypotest_args):
     )
 
 
-def test_toy_calculator(tmp_path, hypotest_args):
+@pytest.mark.usefixtures("tmp_path")
+def test_toy_calculator(hypotest_args):
     """
     Check that the toy calculator is performing as expected
     """

tests/test_init.py

@@ -19,7 +19,8 @@
     ],
     ids=["numpy", "jax"],
 )
-def test_missing_backends(isolate_modules, param):
+@pytest.mark.usefixtures("isolate_modules")
+def test_missing_backends(param):
     backend_name, module_name, import_name, expectation = param
 
     # hide
@@ -57,7 +58,8 @@ def test_missing_backends(isolate_modules, param):
     ],
     ids=["scipy", "minuit"],
 )
-def test_missing_optimizer(isolate_modules, param):
+@pytest.mark.usefixtures("isolate_modules")
+def test_missing_optimizer(param):
     backend_name, module_name, import_name, expectation = param
 
     # hide