Fix validation against dataclasses (#212)

DanielRosenwasser · web-flow · commit 79cac6b49a32 · 2024-03-15T12:29:30.000-07:00
* Add failing test case for validating dataclasses.

* Serialize back to JSON before validating.

* Add newline.

* Remove `overload`.
diff --git a/python/pyproject.toml b/python/pyproject.toml
@@ -23,6 +23,7 @@ classifiers = [
 ]
 dependencies = [
   "pydantic>=2.5.2",
+  "pydantic_core>=2.16.3",
   "httpx>=0.27.0",
   "typing_extensions>=4.10.0",
 ]
@@ -64,7 +65,7 @@ cov = [
 ]
 
 [[tool.hatch.envs.all.matrix]]
-python = ["3.11"]
+python = ["3.11", "3.12"]
 
 [tool.hatch.envs.lint]
 detached = true
diff --git a/python/src/typechat/_internal/validator.py b/python/src/typechat/_internal/validator.py
@@ -2,6 +2,7 @@
 from typing_extensions import Generic, TypeVar
 
 import pydantic
+import pydantic_core
 
 from typechat._internal.result import Failure, Result, Success
 
@@ -26,14 +27,19 @@ def __init__(self, py_type: type[T]):
     def validate_object(self, obj: object) -> Result[T]:
         """
         Validates the given Python object according to the associated schema type.
-        
-        Useful for translators that may presume a non-JSON output.
 
         Returns a `Success[T]` object containing the object if validation was successful.
         Otherwise, returns a `Failure` object with a `message` property describing the error.
         """
         try:
-            typed_dict = self._adapted_type.validate_python(obj, strict=True)
+            # TODO: Switch to `validate_python` when validation modes are exposed.
+            # https://github.com/pydantic/pydantic-core/issues/712
+            # We'd prefer to keep `validate_object` as the core method and
+            # allow translators to concern themselves with the JSON instead.
+            # However, under Pydantic's `strict` mode, a `dict` isn't considered compatible
+            # with a dataclass. So for now, jump back to JSON and validate the string.
+            json_str = pydantic_core.to_json(obj)
+            typed_dict = self._adapted_type.validate_json(json_str, strict=True)
             return Success(typed_dict)
         except pydantic.ValidationError as validation_error:
             return _handle_error(validation_error)
diff --git a/python/tests/test_validator.py b/python/tests/test_validator.py
@@ -0,0 +1,16 @@
+
+from dataclasses import dataclass
+import typechat
+
+@dataclass
+class Example:
+    a: str
+    b: int
+    c: bool
+
+v = typechat.TypeChatValidator(Example)
+
+def test_dict_valid_as_dataclass():
+    r = v.validate_object({"a": "hello!", "b": 42, "c": True})
+    assert r == typechat.Success(Example(a="hello!", b=42, c=True))
+    

Original file line number	Diff line number	Diff line change
`@@ -23,6 +23,7 @@ classifiers = [`
`23`	`23`	`]`
`24`	`24`	`dependencies = [`
`25`	`25`	`"pydantic>=2.5.2",`
	`26`	`+ "pydantic_core>=2.16.3",`
`26`	`27`	`"httpx>=0.27.0",`
`27`	`28`	`"typing_extensions>=4.10.0",`
`28`	`29`	`]`
`@@ -64,7 +65,7 @@ cov = [`
`64`	`65`	`]`
`65`	`66`
`66`	`67`	`[[tool.hatch.envs.all.matrix]]`
`67`		`-python = ["3.11"]`
	`68`	`+python = ["3.11", "3.12"]`
`68`	`69`
`69`	`70`	`[tool.hatch.envs.lint]`
`70`	`71`	`detached = true`