add tests

Author: auderson

pandas/tests/apply/test_frame_apply.py

@@ -90,6 +90,16 @@ def test_apply_args(float_frame, axis, raw, engine, nopython):
     tm.assert_frame_equal(result, expected)
 
     if engine == "numba":
+        # py signature binding
+        with pytest.raises(TypeError, match="missing a required argument: 'a'"):
+            float_frame.apply(
+                lambda x, a: x + a,
+                b=2,
+                raw=raw,
+                engine=engine,
+                engine_kwargs=engine_kwargs,
+            )
+
         # keyword-only arguments are not supported in numba
         with pytest.raises(
             pd.errors.NumbaUtilError,

pandas/tests/groupby/aggregate/test_numba.py

@@ -35,18 +35,35 @@ def incorrect_function(x):
 def test_check_nopython_kwargs():
     pytest.importorskip("numba")
 
-    def incorrect_function(values, index):
-        return sum(values) * 2.7
+    def incorrect_function(values, index, *, a):
+        return sum(values) * 2.7 + a
+
+    def correct_function(values, index, a):
+        return sum(values) * 2.7 + a
 
     data = DataFrame(
         {"key": ["a", "a", "b", "b", "a"], "data": [1.0, 2.0, 3.0, 4.0, 5.0]},
         columns=["key", "data"],
     )
+    # py signature binding
+    with pytest.raises(TypeError, match="missing a required argument: 'a'"):
+        data.groupby("key").agg(incorrect_function, engine="numba", b=1)
+    with pytest.raises(TypeError, match="missing a required argument: 'a'"):
+        data.groupby("key").agg(correct_function, engine="numba", b=1)
+
+    with pytest.raises(TypeError, match="missing a required argument: 'a'"):
+        data.groupby("key")["data"].agg(incorrect_function, engine="numba", b=1)
+    with pytest.raises(TypeError, match="missing a required argument: 'a'"):
+        data.groupby("key")["data"].agg(correct_function, engine="numba", b=1)
+
+    # numba signature check after binding
     with pytest.raises(NumbaUtilError, match="numba does not support"):
         data.groupby("key").agg(incorrect_function, engine="numba", a=1)
+    data.groupby("key").agg(correct_function, engine="numba", a=1)
 
     with pytest.raises(NumbaUtilError, match="numba does not support"):
         data.groupby("key")["data"].agg(incorrect_function, engine="numba", a=1)
+    data.groupby("key")["data"].agg(correct_function, engine="numba", a=1)
 
 
 @pytest.mark.filterwarnings("ignore")

pandas/tests/groupby/transform/test_numba.py

@@ -33,18 +33,35 @@ def incorrect_function(x):
 def test_check_nopython_kwargs():
     pytest.importorskip("numba")
 
-    def incorrect_function(values, index):
-        return values + 1
+    def incorrect_function(values, index, *, a):
+        return values + a
+
+    def correct_function(values, index, a):
+        return values + a
 
     data = DataFrame(
         {"key": ["a", "a", "b", "b", "a"], "data": [1.0, 2.0, 3.0, 4.0, 5.0]},
         columns=["key", "data"],
     )
+    # py signature binding
+    with pytest.raises(TypeError, match="missing a required argument: 'a'"):
+        data.groupby("key").transform(incorrect_function, engine="numba", b=1)
+    with pytest.raises(TypeError, match="missing a required argument: 'a'"):
+        data.groupby("key").transform(correct_function, engine="numba", b=1)
+
+    with pytest.raises(TypeError, match="missing a required argument: 'a'"):
+        data.groupby("key")["data"].transform(incorrect_function, engine="numba", b=1)
+    with pytest.raises(TypeError, match="missing a required argument: 'a'"):
+        data.groupby("key")["data"].transform(correct_function, engine="numba", b=1)
+
+    # numba signature check after binding
     with pytest.raises(NumbaUtilError, match="numba does not support"):
         data.groupby("key").transform(incorrect_function, engine="numba", a=1)
+    data.groupby("key").transform(correct_function, engine="numba", a=1)
 
     with pytest.raises(NumbaUtilError, match="numba does not support"):
         data.groupby("key")["data"].transform(incorrect_function, engine="numba", a=1)
+    data.groupby("key")["data"].transform(correct_function, engine="numba", a=1)
 
 
 @pytest.mark.filterwarnings("ignore")

pandas/tests/window/test_numba.py

@@ -319,13 +319,24 @@ def f(x):
 
 @td.skip_if_no("numba")
 def test_invalid_kwargs_nopython():
+    with pytest.raises(TypeError, match="got an unexpected keyword argument 'a'"):
+        Series(range(1)).rolling(1).apply(
+            lambda x: x, kwargs={"a": 1}, engine="numba", raw=True
+        )
     with pytest.raises(
         NumbaUtilError, match="numba does not support keyword-only arguments"
     ):
         Series(range(1)).rolling(1).apply(
-            lambda x: x, kwargs={"a": 1}, engine="numba", raw=True
+            lambda x, *, a: x, kwargs={"a": 1}, engine="numba", raw=True
         )
 
+    tm.assert_series_equal(
+        Series(range(1), dtype=float) + 1,
+        Series(range(1))
+        .rolling(1)
+        .apply(lambda x, a: (x + a).sum(), kwargs={"a": 1}, engine="numba", raw=True),
+    )
+
 
 @td.skip_if_no("numba")
 @pytest.mark.slow