From d7f869cb3ca2ff57b1ac5ee56e8163d851fe0afe Mon Sep 17 00:00:00 2001
From: rafa-be <raphael@noisycamp.com>
Date: Fri, 28 Feb 2025 15:28:18 +0100
Subject: [PATCH] Improves the error message when and/or/not operators are used
 with Pargraph functions.

---
 pargraph/graph/decorators.py   | 12 +++++++++++-
 tests/test_graph_generation.py | 15 +++++++++++++++
 2 files changed, 26 insertions(+), 1 deletion(-)

diff --git a/pargraph/graph/decorators.py b/pargraph/graph/decorators.py
index b65ef17..286708d 100644
--- a/pargraph/graph/decorators.py
+++ b/pargraph/graph/decorators.py
@@ -84,6 +84,14 @@ def call(*args) -> Any:
 
         return call(self, len(args), *args, *itertools.chain(*kwargs.items()))
 
+    def __bool__(self) -> bool:
+        # As Python does not allow the overloading of its and/or/not operators, we cannot implement
+        # our graph deduction mechanism on these.
+        # This implementation of __bool__ provides a more insightful error message when these
+        # operators are used on Pargraph functions.
+        # More info: https://peps.python.org/pep-0335/
+        raise TypeError("Pargraph does not support the use of boolean (and/or/not) operators.")
+
 
 def external_input() -> GraphContext:
     """
@@ -345,8 +353,10 @@ def _generate_graph(func: Callable, /, *args, **kwargs):
 # __hash__() is not included because since Python 3.3 hash randomization is enabled by default yielding impure hashes
 # between isolated instances making it not suitable for out-of-core computations
 # More info: https://docs.python.org/3/reference/datamodel.html#object.__hash__
+#
+# __bool__() has a specific implementation, as Python does not support the overloading of its and/or operators (see
+# GraphContext.__bool__ here-above).
 for op in {
-    bool,
     int,
     float,
     complex,
diff --git a/tests/test_graph_generation.py b/tests/test_graph_generation.py
index 604afb6..0de6ce2 100644
--- a/tests/test_graph_generation.py
+++ b/tests/test_graph_generation.py
@@ -149,6 +149,21 @@ def sample_graph(df1: pd.DataFrame, df2: pd.DataFrame) -> pd.DataFrame:
             ),
         )
 
+    def test_boolean(self):
+        @delayed
+        def is_even(value: int) -> bool:
+            return value % 2 == 0
+
+        @delayed
+        def is_positive(value: int) -> bool:
+            return value >= 0
+
+        @graph
+        def invalid_graph(value: int) -> bool:
+            return is_even(value) or is_positive(value)
+
+        self.assertRaises(TypeError, invalid_graph.to_graph)
+
     def test_explode_subgraphs(self):
         @graph
         def sample_subgraph(x: int, y: int) -> int: