refactor: clean up use of `__init__` in keyword suggestion

pysr/sr.py

@@ -909,7 +909,7 @@ class PySRRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
                         FutureWarning,
                     )
                 else:
-                    suggested_keywords = self._suggest_keywords(k)
+                    suggested_keywords = _suggest_keywords(PySRRegressor, k)
                     err_msg = f"{k} is not a valid keyword argument for PySRRegressor."
                     if len(suggested_keywords) > 0:
                         err_msg += f" Did you mean {' or '.join(suggested_keywords)}?"
@@ -1995,15 +1995,6 @@ class PySRRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
 
         return self
 
-    def _suggest_keywords(self, k: str) -> List[str]:
-        valid_keywords = [
-            param
-            for param in inspect.signature(self.__init__).parameters
-            if param not in ["self", "kwargs"]
-        ]
-        suggestions = difflib.get_close_matches(k, valid_keywords, n=3)
-        return suggestions
-
     def refresh(self, checkpoint_file=None) -> None:
         """
         Update self.equations_ with any new options passed.
@@ -2455,6 +2446,16 @@ class PySRRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
         return with_preamble(table_string)
 
 
+def _suggest_keywords(cls, k: str) -> List[str]:
+    valid_keywords = [
+        param
+        for param in inspect.signature(cls.__init__).parameters
+        if param not in ["self", "kwargs"]
+    ]
+    suggestions = difflib.get_close_matches(k, valid_keywords, n=3)
+    return suggestions
+
+
 def idx_model_selection(equations: pd.DataFrame, model_selection: str):
     """Select an expression and return its index."""
     if model_selection == "accuracy":

pysr/test/test.py

@@ -15,7 +15,12 @@ from .. import PySRRegressor, install, jl
 from ..export_latex import sympy2latex
 from ..feature_selection import _handle_feature_selection, run_feature_selection
 from ..julia_helpers import init_julia
-from ..sr import _check_assertions, _process_constraints, idx_model_selection
+from ..sr import (
+    _check_assertions,
+    _process_constraints,
+    _suggest_keywords,
+    idx_model_selection,
+)
 from ..utils import _csv_filename_to_pkl_filename
 from .params import (
     DEFAULT_NCYCLES,
@@ -805,9 +810,10 @@ class TestHelpMessages(unittest.TestCase):
                 print("Failed", opt["kwargs"])
 
     def test_suggest_keywords(self):
-        model = PySRRegressor()
         # Easy
-        self.assertEqual(model._suggest_keywords("loss_function"), ["loss_function"])
+        self.assertEqual(
+            _suggest_keywords(PySRRegressor, "loss_function"), ["loss_function"]
+        )
 
         # More complex, and with error
         with self.assertRaises(TypeError) as cm: