chore(jambo): Remove redundant comments and docstrings (#8)

* Remove redundant comments in type parsers and tests

* Clean up redundant comments in `test_oneof_type_parser.py`

* Remove redundant comments across parsers and tests

jambo/parser/__init__.py

@@ -29,4 +29,4 @@ __all__ = [
     "OneOfTypeParser",
     "StringTypeParser",
     "RefTypeParser",
-]
+]

jambo/parser/_type_parser.py

@@ -127,23 +127,9 @@ class GenericTypeParser(ABC, Generic[T]):
 
     @staticmethod
     def _has_meaningful_constraints(field_props):
-        """
-        Check if field properties contain meaningful constraints that require Field wrapping.
-
-        Returns False if:
-        - field_props is None or empty
-        - field_props only contains {'default': None}
-
-        Returns True if:
-        - field_props contains a non-None default value
-        - field_props contains other constraint properties (min_length, max_length, pattern, etc.)
-        """
         if not field_props:
             return False
 
-        # If only default is set and it's None, no meaningful constraints
         if field_props == {"default": None}:
             return False
-
-        # If there are multiple properties or non-None default, that's meaningful
         return True

jambo/parser/array_type_parser.py

@@ -35,17 +35,14 @@ class ArrayTypeParser(GenericTypeParser):
 
         mapped_properties = self.mappings_properties_builder(properties, **kwargs)
 
-        # Only set default_factory if the field is not required OR if there's an actual default
         if not kwargs.get("required", False) and "default" not in mapped_properties:
             mapped_properties["default_factory"] = self._build_default_factory(
                 properties.get("default"), wrapper_type
             )
         elif "default" in properties:
-            # If there's a default value specified, set the default_factory
             mapped_properties["default_factory"] = self._build_default_factory(
                 properties["default"], wrapper_type
             )
-            # Remove the regular default since we're using default_factory
             mapped_properties.pop("default", None)
 
         return field_type, mapped_properties

jambo/parser/const_type_parser.py

@@ -33,14 +33,10 @@ class ConstTypeParser(GenericTypeParser):
         return const_type, parsed_properties
 
     def _build_const_type(self, const_value):
-        # Try to use Literal for hashable types (required for discriminated unions)
-        # Fall back to validator approach for non-hashable types
         try:
-            # Test if the value is hashable (can be used in Literal)
             hash(const_value)
             return Literal[const_value]
         except TypeError:
-            # Non-hashable type (like list, dict), use validator approach
             def _validate_const_value(value: Any) -> Any:
                 if value != const_value:
                     raise ValueError(
@@ -48,4 +44,4 @@ class ConstTypeParser(GenericTypeParser):
                     )
                 return value
 
-            return Annotated[type(const_value), AfterValidator(_validate_const_value)]
+            return Annotated[type(const_value), AfterValidator(_validate_const_value)]

jambo/parser/string_type_parser.py

@@ -28,7 +28,7 @@ class StringTypeParser(GenericTypeParser):
         "time": time,
         "date-time": datetime,
         "binary": bytes,
-        "file-path": FilePath,  # Added file-path format
+        "file-path": FilePath,
     }
 
     format_pattern_mapping = {
@@ -57,4 +57,4 @@ class StringTypeParser(GenericTypeParser):
             mapped_properties["json_schema_extra"] = {}
         mapped_properties["json_schema_extra"]["format"] = format_type
 
-        return mapped_type, mapped_properties
+        return mapped_type, mapped_properties

tests/parser/test_array_type_parser.py

@@ -99,16 +99,13 @@ class TestArrayTypeParser(TestCase):
             parser.from_properties("placeholder", properties)
 
     def test_array_parser_required_without_default(self):
-        """Regression test: Required array fields without defaults should be required"""
         parser = ArrayTypeParser()
 
         properties = {"items": {"type": "string"}}
 
-        # Test with required=True (should be required)
         type_parsing, type_validator = parser.from_properties(
             "test_array", properties, required=True
         )
 
-        # Should NOT have default_factory when required and no default specified
         self.assertNotIn("default_factory", type_validator)
         self.assertNotIn("default", type_validator)

tests/parser/test_const_type_parser.py

@@ -7,7 +7,6 @@ from unittest import TestCase
 
 class TestConstTypeParser(TestCase):
     def test_const_type_parser_hashable_value(self):
-        """Test const parser with hashable values (uses Literal)"""
         parser = ConstTypeParser()
 
         expected_const_value = "United States of America"
@@ -17,31 +16,27 @@ class TestConstTypeParser(TestCase):
             "country", properties
         )
 
-        # Check that we get a Literal type for hashable values
         self.assertEqual(get_origin(parsed_type), Literal)
         self.assertEqual(get_args(parsed_type), (expected_const_value,))
 
         self.assertEqual(parsed_properties["default"], expected_const_value)
 
     def test_const_type_parser_non_hashable_value(self):
-        """Test const parser with non-hashable values (uses Annotated with validator)"""
         parser = ConstTypeParser()
 
-        expected_const_value = [1, 2, 3]  # Lists are not hashable
+        expected_const_value = [1, 2, 3]
         properties = {"const": expected_const_value}
 
         parsed_type, parsed_properties = parser.from_properties_impl(
             "list_const", properties
         )
 
-        # Check that we get an Annotated type for non-hashable values
         self.assertEqual(get_origin(parsed_type), Annotated)
         self.assertIn(list, get_args(parsed_type))
 
         self.assertEqual(parsed_properties["default"], expected_const_value)
 
     def test_const_type_parser_integer_value(self):
-        """Test const parser with integer values (uses Literal)"""
         parser = ConstTypeParser()
 
         expected_const_value = 42
@@ -51,14 +46,12 @@ class TestConstTypeParser(TestCase):
             "int_const", properties
         )
 
-        # Check that we get a Literal type for hashable values
         self.assertEqual(get_origin(parsed_type), Literal)
         self.assertEqual(get_args(parsed_type), (expected_const_value,))
 
         self.assertEqual(parsed_properties["default"], expected_const_value)
 
     def test_const_type_parser_boolean_value(self):
-        """Test const parser with boolean values (uses Literal)"""
         parser = ConstTypeParser()
 
         expected_const_value = True
@@ -68,7 +61,6 @@ class TestConstTypeParser(TestCase):
             "bool_const", properties
         )
 
-        # Check that we get a Literal type for hashable values
         self.assertEqual(get_origin(parsed_type), Literal)
         self.assertEqual(get_args(parsed_type), (expected_const_value,))
 
@@ -99,4 +91,4 @@ class TestConstTypeParser(TestCase):
         self.assertIn(
             "Const type invalid_country must have 'const' value of allowed types",
             str(context.exception),
-        )
+        )

tests/parser/test_oneof_type_parser.py

@@ -351,32 +351,26 @@ class TestOneOfTypeParser(TestCase):
                             }
                         }
                     ],
-                    "discriminator": {}  # discriminator without propertyName
+                    "discriminator": {}
                 }
             }
         }
 
         Model = SchemaConverter.build(schema)
 
-        # Should succeed because input matches exactly one schema (the first one)
-        # The first schema matches: type="a" matches const("a"), value="test" is a string
-        # The second schema doesn't match: type="a" does not match const("b")
         obj = Model(value={"type": "a", "value": "test", "extra": "invalid"})
         self.assertEqual(obj.value.type, "a")
         self.assertEqual(obj.value.value, "test")
 
-        # Test with input that matches the second schema
         obj2 = Model(value={"type": "b", "value": 42})
         self.assertEqual(obj2.value.type, "b")
         self.assertEqual(obj2.value.value, 42)
 
-        # Test with input that matches neither schema (should fail)
         with self.assertRaises(ValueError) as cm:
             Model(value={"type": "c", "value": "test"})
         self.assertIn("does not match any of the oneOf schemas", str(cm.exception))
 
     def test_oneof_multiple_matches_without_discriminator(self):
-        """Test case where input genuinely matches multiple oneOf schemas"""
         schema = {
             "title": "Test",
             "type": "object",
@@ -397,21 +391,18 @@ class TestOneOfTypeParser(TestCase):
                             }
                         }
                     ],
-                    "discriminator": {}  # discriminator without propertyName
+                    "discriminator": {}
                 }
             }
         }
 
         Model = SchemaConverter.build(schema)
 
-        # This input matches both schemas since both accept data as string
-        # and neither requires specific additional properties
         with self.assertRaises(ValueError) as cm:
             Model(value={"data": "test"})
         self.assertIn("matches multiple oneOf schemas", str(cm.exception))
 
         def test_oneof_overlapping_strings_from_docs(self):
-            """Test the overlapping strings example from documentation"""
             schema = {
                 "title": "SimpleExample",
                 "type": "object",
@@ -428,21 +419,17 @@ class TestOneOfTypeParser(TestCase):
 
             Model = SchemaConverter.build(schema)
 
-            # Valid: Short string (matches first schema only)
             obj1 = Model(value="hi")
             self.assertEqual(obj1.value, "hi")
 
-            # Valid: Long string (matches second schema only)
             obj2 = Model(value="very long string")
             self.assertEqual(obj2.value, "very long string")
 
-            # Invalid: Medium string (matches BOTH schemas - violates oneOf)
             with self.assertRaises(ValueError) as cm:
                 Model(value="hello")  # 5 chars: matches maxLength=6 AND minLength=4
             self.assertIn("matches multiple oneOf schemas", str(cm.exception))
 
         def test_oneof_shapes_discriminator_from_docs(self):
-            """Test the shapes discriminator example from documentation"""
             schema = {
                 "title": "Shape",
                 "type": "object",
@@ -477,17 +464,14 @@ class TestOneOfTypeParser(TestCase):
 
             Model = SchemaConverter.build(schema)
 
-            # Valid: Circle
             circle = Model(shape={"type": "circle", "radius": 5.0})
             self.assertEqual(circle.shape.type, "circle")
             self.assertEqual(circle.shape.radius, 5.0)
 
-            # Valid: Rectangle
             rectangle = Model(shape={"type": "rectangle", "width": 10, "height": 20})
             self.assertEqual(rectangle.shape.type, "rectangle")
             self.assertEqual(rectangle.shape.width, 10)
             self.assertEqual(rectangle.shape.height, 20)
 
-            # Invalid: Wrong properties for the type
             with self.assertRaises(ValueError):
                 Model(shape={"type": "circle", "width": 10})