feat(core): implement get_params() API for steps

ibis_ml/core.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import copy
+import inspect
 import os
 import pprint
 from collections import defaultdict
@@ -306,6 +307,69 @@ def categorize(df: pd.DataFrame, categories: dict[str, list[Any]]) -> pd.DataFra
 
 
 class Step:
+    @classmethod
+    def _get_param_names(cls) -> list[str]:
+        """Get parameter names for the estimator.
+
+        Notes
+        -----
+        Copied from [1]_.
+
+        References
+        ----------
+        .. [1] https://github.com/scikit-learn/scikit-learn/blob/ab2f539/sklearn/base.py#L148-L173
+        """
+        # fetch the constructor or the original constructor before
+        # deprecation wrapping if any
+        init = getattr(cls.__init__, "deprecated_original", cls.__init__)
+        if init is object.__init__:
+            # No explicit constructor to introspect
+            return []
+
+        # introspect the constructor arguments to find the model parameters
+        # to represent
+        init_signature = inspect.signature(init)
+        # Consider the constructor parameters excluding 'self'
+        parameters = [
+            p
+            for p in init_signature.parameters.values()
+            if p.name != "self" and p.kind != p.VAR_KEYWORD
+        ]
+        for p in parameters:
+            if p.kind == p.VAR_POSITIONAL:
+                raise RuntimeError(
+                    "scikit-learn estimators should always "
+                    "specify their parameters in the signature"
+                    " of their __init__ (no varargs)."
+                    f" {cls} with constructor {init_signature} doesn't "
+                    " follow this convention."
+                )
+        # Extract and sort argument names excluding 'self'
+        return sorted([p.name for p in parameters])
+
+    def get_params(self, deep=True) -> dict[str, Any]:
+        """Get parameters for this estimator.
+
+        Parameters
+        ----------
+        deep : bool, default=True
+            Has no effect, because steps cannot contain nested substeps.
+
+        Returns
+        -------
+        params : dict
+            Parameter names mapped to their values.
+
+        Notes
+        -----
+        Derived from [1]_.
+
+        References
+        ----------
+        .. [1] https://github.com/scikit-learn/scikit-learn/blob/626b460/sklearn/base.py#L145-L167
+        """
+        return {key: getattr(self, key) for key in self._get_param_names()}
+
     def __repr__(self) -> str:
         return pprint.pformat(self)
 
@@ -449,8 +513,6 @@ def set_output(
     ) -> Recipe:
         """Set output type returned by `transform`.
 
-        This is part of the standard Scikit-Learn API.
-
         Parameters
         ----------
         transform : {"default", "pandas"}, default=None

ibis_ml/steps/_common.py

@@ -135,6 +135,11 @@ def __init__(
         self.expr = expr
         self.named_exprs = named_exprs
 
+    @classmethod
+    def _get_param_names(cls) -> list[str]:
+        """Get parameter names for the estimator."""
+        return ["expr", "inputs", "named_exprs"]
+
     def _repr(self) -> Iterable[tuple[str, Any]]:
         yield ("", self.inputs)
         if self.expr is not None:
@@ -191,11 +196,15 @@ def __init__(
         self.exprs = exprs
         self.named_exprs = named_exprs
 
+    @classmethod
+    def _get_param_names(cls) -> list[str]:
+        """Get parameter names for the estimator."""
+        return ["exprs", "named_exprs"]
+
     def _repr(self) -> Iterable[tuple[str, Any]]:
         for expr in self.exprs:
             yield "", expr
-        for name, expr in self.named_exprs.items():
-            yield name, expr
+        yield from self.named_exprs.items()
 
     def is_fitted(self):
         return True

tests/test_common.py

@@ -34,6 +34,7 @@ def test_mutate_at_expr():
     res = step.transform_table(t)
     sol = t.mutate(x=_.x.abs(), y=_.y.abs())
     assert res.equals(sol)
+    assert list(step.get_params()) == ["expr", "inputs", "named_exprs"]
 
 
 def test_mutate_at_named_exprs():
@@ -44,6 +45,7 @@ def test_mutate_at_named_exprs():
     res = step.transform_table(t)
     sol = t.mutate(x=_.x.abs(), y=_.y.abs(), x_log=_.x.log(), y_log=_.y.log())
     assert res.equals(sol)
+    assert list(step.get_params()) == ["expr", "inputs", "named_exprs"]
 
 
 def test_mutate():
@@ -54,3 +56,4 @@ def test_mutate():
     res = step.transform_table(t)
     sol = t.mutate(_.x.abs().name("x_abs"), y_log=lambda t: t.y.log())
     assert res.equals(sol)
+    assert list(step.get_params()) == ["exprs", "named_exprs"]

tests/test_core.py

@@ -365,6 +365,13 @@ def test_errors_nicely_if_not_fitted(table, method):
         getattr(r, method)(table)
 
 
+def test_get_params():
+    rec = ml.Recipe(ml.ExpandDateTime(ml.timestamp()))
+
+    assert "expanddatetime__components" in rec.get_params(deep=True)
+    assert "expanddatetime__components" not in rec.get_params(deep=False)
+
+
 @pytest.mark.parametrize(
     ("step", "url"),
     [