flake8 compliant

src/model_experiential/__init__.py

@@ -1,24 +1 @@
 from .classes import VisualSyntaxModelOutput
-
-
-
-# CLASS_NAME_LIST = Literal[
-#     "non transactional action",
-#     "non transactional reaction",
-#     "unidirectional transactional action",
-#     "unidirectional transactional reaction",
-#     "bidirectional transactional action",
-#     "bidirectional transactional reaction",
-#     "conversion",
-#     "speech process",
-#     "classification overt taxonomy",
-#     "analytical exhaustive",
-#     "analytical disarranged",
-#     "analytical temporal",
-#     "analytical distributed",
-#     "anaytical topological",
-#     "analytical exploded",
-#     "analytical inclusive",
-#     "symbolic suggestive",
-#     "symbolic attributive"
-# ]

src/model_experiential/classes.py

@@ -6,6 +6,7 @@ import random
 class OptionNotSetException(Exception):
     pass
 
+
 class ModelOutput(BaseModel):
 
     @classmethod
@@ -17,13 +18,13 @@ class ModelOutput(BaseModel):
     def list_fields(cls) -> List[str]:
         """List options that are stored as attributes."""
         return list(cls.model_fields.keys())
-    
+
     @classmethod
     def from_random(cls):
         """Instantiate with random numbers."""
         kwargs = {field: random.random() for field in cls.list_fields()}
         return cls(**kwargs)
-    
+
     @classmethod
     def from_choice(cls, option: str):
         """Instantiate from choice."""
@@ -31,7 +32,8 @@ class ModelOutput(BaseModel):
             raise ValidationError()
         assert isinstance(option, str), "option is not a string"
         allowed_options_list = cls.list_fields()
-        assert option in allowed_options_list, f"{option} is not among allowed fields {allowed_options_list}"
+        assert option in allowed_options_list, \
+            f"{option} is not among allowed fields {allowed_options_list}"
         kwargs = {field: 0 for field in cls.list_fields()}
         kwargs[option] = 1
         return cls(**kwargs)
@@ -39,15 +41,19 @@ class ModelOutput(BaseModel):
     def __repr__(self) -> str:
         model_dict = self.model_dump()
         model_repr_str = f"{self.classname()}("
-        model_repr_str += ", ".join([f"{field}={value:.3f}" for field, value in model_dict.items()])
+        model_repr_str += ", ".join([
+            f"{field}={value:.3f}"
+            for field, value
+            in model_dict.items()
+        ])
         model_repr_str += ")"
         return model_repr_str
-    
+
     def highest_score_field(self) -> str:
         """Return name of field with highest score."""
         model_dict = self.model_dump()
         return max(model_dict, key=lambda k: model_dict[k])
-    
+
     def highest_score_value(self) -> float:
         """Return value of field with highest score."""
         model_dict = self.model_dump()