Ignore DeprecationWarning triggered by arviz

Author: ricardoV94

tests/backends/test_arviz.py

@@ -32,7 +32,11 @@
 from pymc.exceptions import ImputationWarning
 
 # Turn all warnings into errors for this module
-pytestmark = pytest.mark.filterwarnings("error")
+pytestmark = pytest.mark.filterwarnings(
+    "error",
+    # Related to https://github.com/arviz-devs/arviz/issues/2327
+    "ignore:datetime.datetime.utcnow():DeprecationWarning",
+)
 
 
 @pytest.fixture(scope="module")
@@ -672,13 +676,17 @@ def test_include_transformed(self):
             )
             assert "p_interval__" in inference_data.posterior
 
+    @pytest.mark.filterwarnings(
+        "error",
+        # Related to https://github.com/arviz-devs/arviz/issues/2327
+        "ignore:datetime.datetime.utcnow():DeprecationWarning",
+    )
     @pytest.mark.parametrize("chains", (1, 2))
     def test_single_chain(self, chains):
         # Test that no UserWarning is raised when sampling with NUTS defaults
 
         # When this test was added, a `UserWarning: More chains (500) than draws (1)` used to be issued
         # when sampling with a single chain
-        warnings.simplefilter("error")
         with pm.Model():
             pm.Normal("x")
             pm.sample(chains=chains, return_inferencedata=True)

tests/distributions/test_timeseries.py

@@ -48,7 +48,12 @@
 
 # Turn all warnings into errors for this module
 # Ignoring NumPy deprecation warning tracked in https://github.com/pymc-devs/pytensor/issues/146
-pytestmark = pytest.mark.filterwarnings("error", "ignore: NumPy will stop allowing conversion")
+pytestmark = pytest.mark.filterwarnings(
+    "error",
+    "ignore: NumPy will stop allowing conversion",
+    # Related to https://github.com/arviz-devs/arviz/issues/2327
+    "ignore:datetime.datetime.utcnow():DeprecationWarning",
+)
 
 
 class TestRandomWalk:

tests/sampling/test_mcmc_external.py

@@ -47,7 +47,7 @@ def test_external_nuts_sampler(recwarn, nuts_sampler):
     warns = {
         (warn.category, warn.message.args[0])
         for warn in recwarn
-        if warn.category is not FutureWarning
+        if warn.category not in (FutureWarning, DeprecationWarning)
     }
     expected = set()
     if nuts_sampler == "nutpie":

tests/variational/test_inference.py

@@ -172,7 +172,13 @@ def test_fit_oo(inference, fit_kwargs, simple_model_data):
         warn_ctxt = nullcontext()
 
     with warn_ctxt:
-        trace = inference.fit(**fit_kwargs).sample(10000)
+        with warnings.catch_warnings():
+            # Related to https://github.com/arviz-devs/arviz/issues/2327
+            warnings.filterwarnings(
+                "ignore", message="datetime.datetime.utcnow()", category=DeprecationWarning
+            )
+
+            trace = inference.fit(**fit_kwargs).sample(10000)
     mu_post = simple_model_data["mu_post"]
     d = simple_model_data["d"]
     np.testing.assert_allclose(np.mean(trace.posterior["mu"]), mu_post, rtol=0.05)
@@ -207,10 +213,16 @@ def test_fit_start(inference_spec, simple_model):
     expected_warning = observed_value.name.startswith("minibatch")
     with warnings.catch_warnings(record=True) as record:
         warnings.simplefilter("always")
-        try:
-            trace = inference.fit(n=0).sample(10000)
-        except NotImplementedInference as e:
-            pytest.skip(str(e))
+        with warnings.catch_warnings():
+            # Related to https://github.com/arviz-devs/arviz/issues/2327
+            warnings.filterwarnings(
+                "ignore", message="datetime.datetime.utcnow()", category=DeprecationWarning
+            )
+
+            try:
+                trace = inference.fit(n=0).sample(10000)
+            except NotImplementedInference as e:
+                pytest.skip(str(e))
 
     if expected_warning:
         assert len(record) > 0