fix: resolve CI/CD test and lint failures

dataforge/type_check.py

@@ -37,19 +37,17 @@ def parse_type_spec(type_spec: TypeSpec) -> Tuple[str, Optional[Dict[str, Any]]]
         return "unknown", None
 
 
-def check_type(
+def check_type(value: Any, expected_type: TypeSpec) -> Tuple[bool, Optional[str]]:
-    value: Any, expected_type: TypeSpec
-) -> Tuple[bool, Optional[str]]:
     """Check if a value matches the expected type specification."""
     actual_type = infer_type(value)
     type_name, type_info = parse_type_spec(expected_type)
-
+    
     if type_name == "any":
         return True, None
-
+    
     if actual_type != type_name:
         return False, f"Expected {type_name}, got {actual_type}"
-
+    
     if type_name == "object" and isinstance(type_info, dict):
         properties = type_info.get("properties", {})
         required = type_info.get("required", [])
@@ -58,12 +56,12 @@ def check_type(
                 prop_valid, error = check_type(value[prop_name], prop_type)
                 if not prop_valid:
                     return False, f"Property '{prop_name}': {error}"
-
+        
         if isinstance(required, list):
             for req_prop in required:
                 if req_prop not in value:
                     return False, f"Missing required property: '{req_prop}'"
-
+    
     if type_name == "array" and isinstance(type_info, dict):
         items = type_info.get("items")
         if items is not None:
@@ -71,13 +69,11 @@ def check_type(
                 item_valid, error = check_type(item, items)
                 if not item_valid:
                     return False, f"Array item {i}: {error}"
-
+    
     return True, None
 
 
-def validate_types(
+def validate_types(data: Any, type_spec: TypeSpec, path: str = "root") -> List[str]:
-    data: Any, type_spec: TypeSpec, path: str = "root"
-) -> List[str]:
     """Validate data against a type specification and return all errors."""
     errors = []
     valid, error = check_type(data, type_spec)
@@ -106,11 +102,11 @@ def validate_types(
 def infer_schema_from_data(data: Any) -> Dict[str, Any]:
     """Infer a JSON Schema from data."""
     schema: Dict[str, Any] = {}
-
+    
     def build_schema(value: Any, schema_obj: Dict[str, Any]) -> None:
         type_name = infer_type(value)
         schema_obj["type"] = type_name
-
+        
         if type_name == "object" and isinstance(value, dict):
             schema_obj["properties"] = {}
             required = []
@@ -122,10 +118,10 @@ def infer_schema_from_data(data: Any) -> Dict[str, Any]:
                     required.append(key)
             if required:
                 schema_obj["required"] = required
-
+        
         elif type_name == "array" and isinstance(value, list) and value:
             schema_obj["items"] = {}
             build_schema(value[0], schema_obj["items"])
-
+    
     build_schema(data, schema)
     return schema