feat: automatically suggest related keywords

pysr/sr.py

@@ -1,6 +1,8 @@
 """Define the PySRRegressor scikit-learn interface."""
 
 import copy
+import difflib
+import inspect
 import os
 import pickle as pkl
 import re
@@ -907,9 +909,11 @@ def __init__(
                         FutureWarning,
                     )
                 else:
-                    raise TypeError(
-                        f"{k} is not a valid keyword argument for PySRRegressor."
-                    )
+                    suggested_keywords = self._suggest_keywords(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)}?"
+                    raise TypeError(err_msg)
 
     @classmethod
     def from_file(
@@ -1991,6 +1995,15 @@ def fit(
 
         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.

pysr/test/test.py

@@ -804,6 +804,26 @@ def test_bad_kwargs(self):
                 model.get_best()
                 print("Failed", opt["kwargs"])
 
+    def test_suggest_keywords(self):
+        model = PySRRegressor()
+        # Easy
+        self.assertEqual(model._suggest_keywords("loss_function"), ["loss_function"])
+
+        # More complex, and with error
+        with self.assertRaises(TypeError) as cm:
+            model = PySRRegressor(ncyclesperiterationn=5)
+
+        self.assertIn("ncyclesperiterationn is not a valid keyword", str(cm.exception))
+        self.assertIn("Did you mean", str(cm.exception))
+        self.assertIn("ncycles_per_iteration or", str(cm.exception))
+        self.assertIn("niteration", str(cm.exception))
+
+        # Farther matches (this might need to be changed)
+        with self.assertRaises(TypeError) as cm:
+            model = PySRRegressor(operators=["+", "-"])
+
+        self.assertIn("unary_operators or binary_operators", str(cm.exception))
+
 
 TRUE_PREAMBLE = "\n".join(
     [