Add py.typed to comply with PEP-561 ...

src/slickml/classification/_xgboost.py

@@ -137,6 +137,8 @@ class XGBoostClassifier(BaseEstimator, ClassifierMixin):
  References
  ----------
  .. [1] https://xgboost.readthedocs.io/en/latest/python/python_api.html
+ .. [2] https://matplotlib.org/stable/api/markers_api.html
+ .. [3] https://shap-lrjball.readthedocs.io/en/latest/generated/shap.summary_plot.html
  """
 
  num_boost_round: Optional[int] = 200
@@ -355,7 +357,7 @@ def plot_feature_importance(
  Color of the horizontal lines of lollipops, by default "#87CEEB"
 
  marker : str, optional
- Marker style of the lollipops. More valid marker styles can be found at [1]_, by default "o"
+ Marker style of the lollipops. More valid marker styles can be found at [2]_, by default "o"
 
  markersize : Union[int, float], optional
  Markersize, by default 10
@@ -382,10 +384,6 @@ def plot_feature_importance(
  return_fig : bool, optional
  Whether to return figure object, by default False
 
- References
- ----------
- .. [1] https://matplotlib.org/stable/api/markers_api.html
-
  Returns
  -------
  Figure, optional
@@ -431,7 +429,7 @@ def plot_shap_summary(
  This is a helper function to plot the ``shap`` summary plot based on all types of
  ``shap.Explainer`` including ``shap.LinearExplainer`` for linear models, ``shap.TreeExplainer``
  for tree-based models, and ``shap.DeepExplainer`` deep neural network models. More on details
- are available at [1]_. Note that this function should be ran after the ``predict_proba()``
+ are available at [3]_. Note that this function should be ran after the ``predict_proba()``
  to make sure the ``X_test`` is being instansiated or set ``validation=False``.
 
  Parameters
@@ -493,10 +491,6 @@ def plot_shap_summary(
  display_plot : bool, optional
  Whether to show the plot, by default True
 
- References
- ----------
- .. [1] https://shap-lrjball.readthedocs.io/en/latest/generated/shap.summary_plot.html
-
  Returns
  -------
  None
@@ -585,7 +579,7 @@ def plot_shap_waterfall(
  Color of the line plot, by default "purple"
 
  marker : str, optional
- Marker style of the lollipops. More valid marker styles can be found at [1]_, by default "o"
+ Marker style of the lollipops. More valid marker styles can be found at [2]_, by default "o"
 
  markersize : Union[int, float], optional
  Markersize, by default 7
@@ -618,10 +612,6 @@ def plot_shap_waterfall(
  return_fig : bool, optional
  Whether to return figure object, by default False
 
- References
- ----------
- .. [1] https://matplotlib.org/stable/api/markers_api.html
-
  Returns
  -------
  Figure, optional

src/slickml/py.typed

@@ -0,0 +1 @@
+# Comply with PEP-561 https://peps.python.org/pep-0561/