the method `Regression.predict()` requires 'x' or 'y' as keyword argument only

linear_regression.py

@@ -19,13 +19,13 @@ class Regression:
     def r2(self) -> float:
         return self.score
 
-    def predict(self, x: int | float = None, y: int | float = None) -> float:
+    def predict(self, *, x: int | float = None, y: int | float = None) -> float:
         """predict a value if x or y is given"""
         if x is not None:
             return self.intercept + x * self.coefficient
         if y is not None:
             return (y - self.intercept) / self.coefficient
-        msg = "predict() expects 1 argument, got 0"
+        msg = "predict() expects a keyword argument 'x' or 'y'"
         raise TypeError(msg)
 
     def to_dict(self):
@@ -65,14 +65,21 @@ def test_linear_regression(example_data):
 def test_regression_predict(example_data):
     regression = linear_regression(example_data, x="A", y="B")
 
-    prediction = regression.predict(10)
+    prediction = regression.predict(x=10)
 
     assert pytest.approx(30.7) == prediction
     assert pytest.approx(10) == regression.predict(y=prediction)
 
-    with pytest.raises(TypeError, match="expects 1 argument"):
+
+def test_regression_predict_exceptions(example_data):
+    regression = linear_regression(example_data, x="A", y="B")
+
+    with pytest.raises(TypeError, match="expects a keyword"):
         regression.predict()
 
+    with pytest.raises(TypeError, match="takes 1 positional argument but"):
+        regression.predict(1)
+
 
 def test_regression_to_dict(example_data):
     regression = linear_regression(example_data, x="A", y="B")