streamable: Fix default value assignments for dataclass_from_dict (#11732)

* streamable: Use constructor in `dataclass_from_dict`

This fixes default value assignments after #10561 but also leads to less perfomance due to `__post_init__` being called which at least gets mitigated by #11730.

* tests: Test default values with `from_json_dict`

* Convert to `str`, then compare.

Author: xdustinface

chia/util/streamable.py

@@ -132,7 +132,7 @@ def dataclass_from_dict(klass: Type[Any], item: Any) -> Any:
     """
     if type(item) == klass:
         return item
-    obj = object.__new__(klass)
+
     if klass not in CONVERT_FUNCTIONS_FOR_STREAMABLE_CLASS:
         # For non-streamable dataclasses we can't populate the cache on startup, so we do it here for convert
         # functions only.
@@ -144,9 +144,13 @@ def dataclass_from_dict(klass: Type[Any], item: Any) -> Any:
         fields = FIELDS_FOR_STREAMABLE_CLASS[klass]
         convert_funcs = CONVERT_FUNCTIONS_FOR_STREAMABLE_CLASS[klass]
 
-    for field, convert_func in zip(fields, convert_funcs):
-        object.__setattr__(obj, field.name, convert_func(item[field.name]))
-    return obj
+    return klass(
+        **{
+            field.name: convert_func(item[field.name])
+            for field, convert_func in zip(fields, convert_funcs)
+            if field.name in item
+        }
+    )
 
 
 def function_to_convert_one_item(f_type: Type[Any]) -> ConvertFunctionType:

tests/core/util/test_streamable.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 import io
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 from typing import Any, Dict, List, Optional, Tuple, Type
 
 import pytest
@@ -128,15 +128,15 @@ def test_pure_dataclasses_in_dataclass_from_dict() -> None:
     "test_class, input_dict, error",
     [
         [TestDataclassFromDict1, {"a": "asdf", "b": "2", "c": G1Element()}, ValueError],
-        [TestDataclassFromDict1, {"a": 1, "b": "2"}, KeyError],
+        [TestDataclassFromDict1, {"a": 1, "b": "2"}, TypeError],
         [TestDataclassFromDict1, {"a": 1, "b": "2", "c": "asd"}, ValueError],
         [TestDataclassFromDict1, {"a": 1, "b": "2", "c": "00" * G1Element.SIZE}, ValueError],
         [TestDataclassFromDict1, {"a": [], "b": "2", "c": G1Element()}, TypeError],
         [TestDataclassFromDict1, {"a": {}, "b": "2", "c": G1Element()}, TypeError],
         [TestDataclassFromDict2, {"a": "asdf", "b": 1.2345, "c": 1.2345}, TypeError],
         [TestDataclassFromDict2, {"a": 1.2345, "b": {"a": 1, "b": "2"}, "c": 1.2345}, TypeError],
-        [TestDataclassFromDict2, {"a": {"a": 1, "b": "2", "c": G1Element()}, "b": {"a": 1, "b": "2"}}, KeyError],
-        [TestDataclassFromDict2, {"a": {"a": 1, "b": "2"}, "b": {"a": 1, "b": "2"}, "c": 1.2345}, KeyError],
+        [TestDataclassFromDict2, {"a": {"a": 1, "b": "2", "c": G1Element()}, "b": {"a": 1, "b": "2"}}, TypeError],
+        [TestDataclassFromDict2, {"a": {"a": 1, "b": "2"}, "b": {"a": 1, "b": "2"}, "c": 1.2345}, TypeError],
     ],
 )
 def test_dataclass_from_dict_failures(test_class: Type[Any], input_dict: Dict[str, Any], error: Any) -> None:
@@ -145,6 +145,28 @@ def test_dataclass_from_dict_failures(test_class: Type[Any], input_dict: Dict[st
         dataclass_from_dict(test_class, input_dict)
 
 
+@streamable
+@dataclass(frozen=True)
+class TestFromJsonDictDefaultValues(Streamable):
+    a: uint64 = uint64(1)
+    b: str = "default"
+    c: List[uint64] = field(default_factory=list)
+
+
+@pytest.mark.parametrize(
+    "input_dict, output_dict",
+    [
+        [{}, {"a": 1, "b": "default", "c": []}],
+        [{"a": 2}, {"a": 2, "b": "default", "c": []}],
+        [{"b": "not_default"}, {"a": 1, "b": "not_default", "c": []}],
+        [{"c": [1, 2]}, {"a": 1, "b": "default", "c": [1, 2]}],
+        [{"a": 2, "b": "not_default", "c": [1, 2]}, {"a": 2, "b": "not_default", "c": [1, 2]}],
+    ],
+)
+def test_from_json_dict_default_values(input_dict: Dict[str, object], output_dict: Dict[str, object]) -> None:
+    assert str(TestFromJsonDictDefaultValues.from_json_dict(input_dict).to_json_dict()) == str(output_dict)
+
+
 def test_basic_list() -> None:
     a = [1, 2, 3]
     assert is_type_List(type(a))