feat: make config fields optional

app/domain/common/optional_model.py

@@ -4,11 +4,15 @@
 
 
 class OptionalModel(BaseModel):
+    __non_optional_fields__ = set()
+
     @classmethod
     def __pydantic_init_subclass__(cls, **kwargs: Any) -> None:
         super().__pydantic_init_subclass__(**kwargs)
 
         for field in cls.model_fields.values():
+            if field in cls.__non_optional_fields__:
+                continue
             field.default = None
 
         cls.model_rebuild(force=True)

app/domain/task/afd/config.py

@@ -1,10 +1,14 @@
 from typing import Annotated, Literal, Union
-from pydantic import BaseModel, Field
+from pydantic import Field
 
+from app.domain.common.optional_model import OptionalModel
 from app.domain.task.afd.algo_name import AfdAlgoName
 
 
-class BaseAfdConfig(BaseModel): ...
+class BaseAfdConfig(OptionalModel):
+    __non_optional_fields__ = {
+        "algo_name",
+    }
 
 
 class PyroConfig(BaseAfdConfig):

app/domain/task/fd/config.py

@@ -1,11 +1,14 @@
-from pydantic import BaseModel, Field
+from pydantic import Field
 from typing import Annotated, Literal, Union
 
+from app.domain.common.optional_model import OptionalModel
 from app.domain.task.fd.algo_name import FdAlgoName
 
 
-# Should be OptionalModel with required field `algo_name`
-class BaseFdConfig(BaseModel): ...
+class BaseFdConfig(OptionalModel):
+    __non_optional_fields__ = {
+        "algo_name",
+    }
 
 
 class AidConfig(BaseFdConfig):

tests/domain/task/test_fd.py

@@ -4,14 +4,24 @@
 import logging
 from polyfactory.factories.pydantic_factory import ModelFactory
 
-# TODO: change when optional fields are suported
-# @pytest.mark.parametrize(
-#     "table", [pd.read_csv("tests/datasets/university_fd.csv", sep=",", header=0)]
-# )
-# def test_with_default_params(task_cls, table):
-#     task = FdTask()
-#     result = task.execute(table)
-#     logging.info(result)
+from app.domain.task.fd.algo_name import FdAlgoName
+from app.domain.task.primitive_name import PrimitiveName
+
+
+@pytest.mark.parametrize("algo_name", [algo_name.value for algo_name in FdAlgoName])
+@pytest.mark.parametrize(
+    "table",
+    [pd.read_csv("tests/datasets/university_fd.csv", sep=",", header=0)],
+)
+def test_with_default_params(algo_name, table):
+    task = FdTask()
+    config = FdTaskConfig(
+        primitive_name=PrimitiveName.fd,
+        config={"algo_name": algo_name},  # type: ignore
+    )
+    logging.info(config)
+    result = task.execute(table, config)
+    logging.info(result)
 
 
 @pytest.mark.parametrize(