add pre-commit changes

src/amltk/pipeline/parsers/optuna.py

@@ -115,6 +115,11 @@
 
 @dataclass
 class OptunaSearchSpace:
+    """A class to represent an Optuna search space.
+
+    Wraps a dictionary of hyperparameters and their Optuna distributions.
+    """
+
     distributions: dict[str, BaseDistribution] = field(default_factory=dict)
 
     def __repr__(self) -> str:
@@ -124,22 +129,29 @@ def __str__(self) -> str:
         return str(self.distributions)
 
     @classmethod
-    def parse(cls, *args, **kwargs) -> OptunaSearchSpace:
+    def parse(cls, *args: Any, **kwargs: Any) -> OptunaSearchSpace:
+        """Parse a Node into an Optuna search space."""
         return parser(*args, **kwargs)
 
     def sample_configuration(self) -> dict[str, Any]:
+        """Sample a configuration from the search space using a default Optuna Study."""
         study = optuna.create_study()
         trial = self.get_trial(study)
         return trial.params
 
-    def get_trial(self, study: Study) -> optuna.Trial:
+    def get_trial(self, study: optuna.Study) -> optuna.Trial:
+        """Get a trial from a given Optuna Study using this search space."""
+        optuna_trial: optuna.Trial
         if any("__choice__" in k for k in self.distributions):
-            optuna_trial: optuna.Trial = study.ask()
+            optuna_trial = study.ask()
             # do all __choice__ suggestions with suggest_categorical
             workspace = self.distributions.copy()
             filter_patterns = []
             for name, distribution in workspace.items():
-                if "__choice__" in name:
+                if "__choice__" in name and isinstance(
+                    distribution,
+                    CategoricalDistribution,
+                ):
                     possible_choices = distribution.choices
                     choice_made = optuna_trial.suggest_categorical(
                         name,
@@ -178,7 +190,7 @@ def get_trial(self, study: Study) -> optuna.Trial:
                     case _:
                         raise ValueError(f"Unknown distribution: {distribution}")
         else:
-            optuna_trial: optuna.Trial = study.ask(self.distributions)
+            optuna_trial = study.ask(self.distributions)
         return optuna_trial
 
 
@@ -274,7 +286,10 @@ def parser(
 
     for child in children:
         subspace = parser(
-            child, flat=flat, conditionals=conditionals, delim=delim
+            child,
+            flat=flat,
+            conditionals=conditionals,
+            delim=delim,
         ).distributions
         if not flat:
             subspace = prefix_keys(subspace, prefix=f"{node.name}{delim}")

tests/pipeline/parsing/test_optuna_parser.py

@@ -5,10 +5,9 @@
 
 import pytest
 from pytest_cases import case, parametrize_with_cases
-from src.amltk.pipeline.components import Split
 
 from amltk.pipeline import Component, Fixed, Node
-from amltk.pipeline.components import Choice
+from amltk.pipeline.components import Choice, Split
 
 try:
     from optuna.distributions import CategoricalDistribution, IntDistribution