Monkeypatch instructions for migrating away from the old rv.logp API

pymc3/distributions/distribution.py

@@ -122,6 +122,13 @@ def get_moment(op, rv, size, *rv_inputs):
         return new_cls
 
 
+def _make_nice_attr_error(oldcode: str, newcode: str):
+    def fn(*args, **kwargs):
+        raise AttributeError(f"The `{oldcode}` method was removed. Instead use `{newcode}`.`")
+
+    return fn
+
+
 class Distribution(metaclass=DistributionMeta):
     """Statistical distribution"""
 
@@ -243,6 +250,9 @@ def __new__(
             functools.partial(str_for_dist, formatting="latex"), rv_out
         )
 
+        rv_out.logp = _make_nice_attr_error("rv.logp(x)", "pm.logp(rv, x)")
+        rv_out.logcdf = _make_nice_attr_error("rv.logcdf(x)", "pm.logcdf(rv, x)")
+        rv_out.random = _make_nice_attr_error("rv.random()", "rv.eval()")
         return rv_out
 
     @classmethod
@@ -333,6 +343,9 @@ def dist(
             rv_out.update = (rng, new_rng)
             rng.default_update = new_rng
 
+        rv_out.logp = _make_nice_attr_error("rv.logp(x)", "pm.logp(rv, x)")
+        rv_out.logcdf = _make_nice_attr_error("rv.logcdf(x)", "pm.logcdf(rv, x)")
+        rv_out.random = _make_nice_attr_error("rv.random()", "rv.eval()")
         return rv_out
 
 

pymc3/tests/test_distributions.py

@@ -3262,3 +3262,28 @@ def test_distinct_rvs():
         pp_samples_2 = pm.sample_prior_predictive(samples=2)
 
     assert np.array_equal(pp_samples["y"], pp_samples_2["y"])
+
+
+@pytest.mark.parametrize(
+    "method,newcode",
+    [
+        ("logp", r"pm.logp\(rv, x\)"),
+        ("logcdf", r"pm.logcdf\(rv, x\)"),
+        ("random", r"rv.eval\(\)"),
+    ],
+)
+def test_logp_gives_migration_instructions(method, newcode):
+    rv = pm.Normal.dist()
+    f = getattr(rv, method)
+    with pytest.raises(AttributeError, match=rf"use `{newcode}`"):
+        f()
+
+    # A dim-induced resize of the rv created by the `.dist()` API,
+    # happening in Distribution.__new__ would make us loose the monkeypatches.
+    # So this triggers it to test if the monkeypatch still works.
+    with pm.Model(coords={"year": [2019, 2021, 2022]}):
+        rv = pm.Normal("n", dims="year")
+        f = getattr(rv, method)
+        with pytest.raises(AttributeError, match=rf"use `{newcode}`"):
+            f()
+    pass