diff --git a/python/datafusion/tests/test_udaf.py b/python/datafusion/tests/test_udaf.py
index 76488e19b..6f2525b0f 100644
--- a/python/datafusion/tests/test_udaf.py
+++ b/python/datafusion/tests/test_udaf.py
@@ -21,7 +21,7 @@
 import pyarrow.compute as pc
 import pytest
 
-from datafusion import Accumulator, SessionContext, column, udaf
+from datafusion import Accumulator, column, udaf, udf
 
 
 class Summarize(Accumulator):
@@ -60,18 +60,15 @@ def state(self) -> List[pa.Scalar]:
 
 
 @pytest.fixture
-def df():
-    ctx = SessionContext()
-
+def df(ctx):
     # create a RecordBatch and a new DataFrame from it
     batch = pa.RecordBatch.from_arrays(
         [pa.array([1, 2, 3]), pa.array([4, 4, 6])],
         names=["a", "b"],
     )
-    return ctx.create_dataframe([[batch]])
+    return ctx.create_dataframe([[batch]], name="test_table")
 
 
-@pytest.mark.skip(reason="df.collect() will hang, need more investigations")
 def test_errors(df):
     with pytest.raises(TypeError):
         udaf(
@@ -92,8 +89,9 @@ def test_errors(df):
     df = df.aggregate([], [accum(column("a"))])
 
     msg = (
-        "Can't instantiate abstract class MissingMethods with abstract "
-        "methods evaluate, merge, update"
+        "Can't instantiate abstract class MissingMethods (without an implementation "
+        "for abstract methods 'evaluate', 'merge', 'update'|with abstract methods "
+        "evaluate, merge, update)"
     )
     with pytest.raises(Exception, match=msg):
         df.collect()
@@ -132,3 +130,36 @@ def test_group_by(df):
     arrays = [batch.column(1) for batch in batches]
     joined = pa.concat_arrays(arrays)
     assert joined == pa.array([1.0 + 2.0, 3.0])
+
+
+def test_register_udaf(ctx, df) -> None:
+    summarize = udaf(
+        Summarize,
+        pa.float64(),
+        pa.float64(),
+        [pa.float64()],
+        volatility="immutable",
+    )
+
+    ctx.register_udaf(summarize)
+
+    df_result = ctx.sql("select summarize(b) from test_table")
+
+    assert df_result.collect()[0][0][0].as_py() == 14.0
+
+
+def test_register_udf(ctx, df) -> None:
+    is_null = udf(
+        lambda x: x.is_null(),
+        [pa.float64()],
+        pa.bool_(),
+        volatility="immutable",
+        name="is_null",
+    )
+
+    ctx.register_udf(is_null)
+
+    df_result = ctx.sql("select is_null(a) from test_table")
+    result = df_result.collect()[0].column(0)
+
+    assert result == pa.array([False, False, False])
diff --git a/python/datafusion/udf.py b/python/datafusion/udf.py
index a3b74bb11..f74d675e3 100644
--- a/python/datafusion/udf.py
+++ b/python/datafusion/udf.py
@@ -192,7 +192,7 @@ def __init__(
         See :py:func:`udaf` for a convenience function and argument
         descriptions.
         """
-        self._udf = df_internal.AggregateUDF(
+        self._udaf = df_internal.AggregateUDF(
             name, accumulator, input_types, return_type, state_type, str(volatility)
         )
 
@@ -203,7 +203,7 @@ def __call__(self, *args: Expr) -> Expr:
         occur during the evaluation of the dataframe.
         """
         args = [arg.expr for arg in args]
-        return Expr(self._udf.__call__(*args))
+        return Expr(self._udaf.__call__(*args))
 
     @staticmethod
     def udaf(