chore(CrossValidationReport): Rename estimator_reports_ to reports_

examples/getting_started/plot_skore_getting_started.py

@@ -165,7 +165,7 @@
 # for example getting the report metrics for the first split only:
 
 # %%
-cv_report.estimator_reports_[0].metrics.summarize().frame()
+cv_report.reports_[0].metrics.summarize().frame()
 
 # %%
 # .. seealso::

examples/use_cases/plot_employee_salaries.py

@@ -165,7 +165,7 @@
 # :class:`skore.EstimatorReport` for each split.
 
 # %%
-hgbt_split_1 = hgbt_model_report.estimator_reports_[0]
+hgbt_split_1 = hgbt_model_report.reports_[0]
 hgbt_split_1.metrics.summarize(indicator_favorability=True).frame()
 
 # %%

skore/src/skore/_sklearn/_comparison/metrics_accessor.py

@@ -1272,7 +1272,7 @@ def _get_display(
 
             else:
                 for report_name, report in self._parent.reports_.items():
-                    for split, estimator_report in enumerate(report.estimator_reports_):
+                    for split, estimator_report in enumerate(report.reports_):
                         report_X, report_y, _ = (
                             estimator_report.metrics._get_X_y_and_data_source_hash(
                                 data_source=data_source,
@@ -1320,7 +1320,7 @@ def _get_display(
                     estimators=[
                         estimator_report.estimator_
                         for report in self._parent.reports_.values()
-                        for estimator_report in report.estimator_reports_
+                        for estimator_report in report.reports_
                     ],
                     ml_task=self._parent._ml_task,
                     data_source=data_source,

skore/src/skore/_sklearn/_cross_validation/feature_importance_accessor.py

@@ -50,7 +50,7 @@ def coefficients(self) -> FeatureImportanceDisplay:
                 for split, df in enumerate(
                     list(
                         report.feature_importance.coefficients().frame()
-                        for report in self._parent.estimator_reports_
+                        for report in self._parent.reports_
                     )
                 )
             },

skore/src/skore/_sklearn/_cross_validation/metrics_accessor.py

@@ -218,7 +218,7 @@ def _compute_metric_scores(
         progress = self._parent._progress_info["current_progress"]
         main_task = self._parent._progress_info["current_task"]
 
-        total_estimators = len(self._parent.estimator_reports_)
+        total_estimators = len(self._parent.reports_)
         progress.update(main_task, total=total_estimators)
 
         if cache_key in self._parent._cache:
@@ -233,7 +233,7 @@ def _compute_metric_scores(
                 delayed(getattr(report.metrics, report_metric_name))(
                     data_source=data_source, X=X, y=y, **metric_kwargs
                 )
-                for report in self._parent.estimator_reports_
+                for report in self._parent.reports_
             )
             results = []
             for result in generator:
@@ -315,10 +315,10 @@ def timings(
         timings: pd.DataFrame = pd.concat(
             [
                 pd.Series(report.metrics.timings())
-                for report in self._parent.estimator_reports_
+                for report in self._parent.reports_
             ],
             axis=1,
-            keys=[f"Split #{i}" for i in range(len(self._parent.estimator_reports_))],
+            keys=[f"Split #{i}" for i in range(len(self._parent.reports_))],
         )
         if aggregate:
             if isinstance(aggregate, str):
@@ -1128,15 +1128,15 @@ def _get_display(
         assert self._parent._progress_info is not None, "Progress info not set"
         progress = self._parent._progress_info["current_progress"]
         main_task = self._parent._progress_info["current_task"]
-        total_estimators = len(self._parent.estimator_reports_)
+        total_estimators = len(self._parent.reports_)
         progress.update(main_task, total=total_estimators)
 
         if cache_key in self._parent._cache:
             display = self._parent._cache[cache_key]
         else:
             y_true: list[YPlotData] = []
             y_pred: list[YPlotData] = []
-            for report_idx, report in enumerate(self._parent.estimator_reports_):
+            for report_idx, report in enumerate(self._parent.reports_):
                 if data_source != "X_y":
                     # only retrieve data stored in the reports when we don't want to
                     # use an external common X and y
@@ -1178,7 +1178,7 @@ def _get_display(
                 y_pred=y_pred,
                 report_type="cross-validation",
                 estimators=[
-                    report.estimator_ for report in self._parent.estimator_reports_
+                    report.estimator_ for report in self._parent.reports_
                 ],
                 ml_task=self._parent._ml_task,
                 data_source=data_source,

skore/src/skore/_sklearn/_cross_validation/report.py

@@ -120,7 +120,7 @@ class CrossValidationReport(_BaseReport, DirNamesMixin):
     estimator_name_ : str
         The name of the estimator.
 
-    estimator_reports_ : list of EstimatorReport
+    reports_ : list of EstimatorReport
         The estimator reports for each split.
 
     See Also
@@ -170,16 +170,14 @@ def __init__(
         self._split_indices = tuple(self._splitter.split(self._X, self._y))
         self.n_jobs = n_jobs
 
-        self.estimator_reports_: list[EstimatorReport] = self._fit_estimator_reports()
+        self.reports_: list[EstimatorReport] = self._fit_estimator_reports()
 
         self._rng = np.random.default_rng(time.time_ns())
         self._hash = self._rng.integers(
             low=np.iinfo(np.int64).min, high=np.iinfo(np.int64).max
         )
         self._cache: dict[tuple[Any, ...], Any] = {}
-        self._ml_task = _find_ml_task(
-            y, estimator=self.estimator_reports_[0]._estimator
-        )
+        self._ml_task = _find_ml_task(y, estimator=self.reports_[0]._estimator)
 
     @progress_decorator(
         description=lambda self: (
@@ -293,7 +291,7 @@ def clear_cache(self) -> None:
         >>> report._cache
         {}
         """
-        for report in self.estimator_reports_:
+        for report in self.reports_:
             report.clear_cache()
         self._cache = {}
 
@@ -336,10 +334,10 @@ def cache_predictions(
         progress = self._progress_info["current_progress"]
         main_task = self._progress_info["current_task"]
 
-        total_estimators = len(self.estimator_reports_)
+        total_estimators = len(self.reports_)
         progress.update(main_task, total=total_estimators)
 
-        for split_idx, estimator_report in enumerate(self.estimator_reports_, 1):
+        for split_idx, estimator_report in enumerate(self.reports_, 1):
             # Share the parent's progress bar with child report
             estimator_report._progress_info = {
                 "current_progress": progress,
@@ -439,7 +437,7 @@ def get_predictions(
                 X=X,
                 pos_label=pos_label,
             )
-            for report in self.estimator_reports_
+            for report in self.reports_
         ]
 
     @property
@@ -489,6 +487,17 @@ def pos_label(self, value: PositiveLabel | None) -> None:
             f"Call the constructor of {self.__class__.__name__} to create a new report."
         )
 
+    @property
+    def estimator_reports_(self) -> list[EstimatorReport]:
+        """
+        The estimator reports for each split.
+
+        .. deprecated
+          The ``report.estimator_reports_`` property will be removed in favor of
+          ``report.reports_`` in a near future.
+        """
+        return self.reports_
+
     ####################################################################################
     # Methods related to the help and repr
     ####################################################################################

skore/src/skore/_utils/_accessor.py

@@ -140,7 +140,7 @@ def _check_estimator_report_has_method(
     method_name: str,
 ) -> Callable:
     def check(accessor: Any) -> bool:
-        estimator_report = accessor._parent.estimator_reports_[0]
+        estimator_report = accessor._parent.reports_[0]
 
         if not hasattr(estimator_report, accessor_name):
             raise AttributeError(
@@ -163,7 +163,7 @@ def check(accessor: Any) -> bool:
 def _check_cross_validation_sub_estimator_has_coef() -> Callable:
     def check(accessor: Any) -> bool:
         """Check if the underlying estimator has a `coef_` attribute."""
-        return _check_has_coef(accessor._parent.estimator_reports_[0].estimator)
+        return _check_has_coef(accessor._parent.reports_[0].estimator)
 
     return check
 
@@ -183,7 +183,7 @@ def check(accessor: Any) -> bool:
         for parent_report in parent.reports_.values():
             if parent._reports_type == "CrossValidationReport":
                 parent_report = cast(CrossValidationReport, parent_report)
-                parent_estimators.append(parent_report.estimator_reports_[0].estimator_)
+                parent_estimators.append(parent_report.reports_[0].estimator_)
             elif parent._reports_type == "EstimatorReport":
                 parent_estimators.append(parent_report.estimator_)
             else:

skore/src/skore/_utils/_progress_bar.py

@@ -38,17 +38,23 @@ def progress_decorator(
     def decorator(func: Callable[..., T]) -> Callable[..., T]:
         @wraps(func)
         def wrapper(*args: Any, **kwargs: Any) -> T:
+            # Avoid circular import
+            from skore import ComparisonReport
+
+            # The object to which a `rich.Progress` instance will be attached.
+            # Expected to be a Report
+            # (EstimatorReport | CrossValidationReport | ComparisonReport)
             self_obj: Any = args[0]
 
+            # If the decorated method is in an Accessor (e.g. MetricsAccessor),
+            # then make sure `self_obj` is the Report, not the Accessor.
             if hasattr(self_obj, "_parent"):
                 # self_obj is an accessor
                 self_obj = self_obj._parent
 
-            desc = description(self_obj) if callable(description) else description
-
             created_progress = False
 
-            if getattr(self_obj, "_progress_info", None) is not None:
+            if self_obj._progress_info is not None:
                 progress = self_obj._progress_info["current_progress"]
             else:
                 progress = Progress(
@@ -67,15 +73,20 @@ def wrapper(*args: Any, **kwargs: Any) -> T:
                 progress.start()
                 created_progress = True
 
-            # assigning progress to child reports
+            # Make child reports share their parent's Progress instance
+            # so that there is only one Progress instance at any given point
             reports_to_cleanup: list[Any] = []
-            if hasattr(self_obj, "reports_"):
+            if isinstance(self_obj, ComparisonReport):
                 for report in self_obj.reports_.values():
-                    if hasattr(report, "_progress_info"):
-                        report._progress_info = {"current_progress": progress}
-                        reports_to_cleanup.append(report)
-
-            task = progress.add_task(desc, total=None)
+                    report._progress_info = {"current_progress": progress}
+                    reports_to_cleanup.append(report)
+
+            task = progress.add_task(
+                description=(
+                    description(self_obj) if callable(description) else description
+                ),
+                total=None,
+            )
             self_obj._progress_info = {
                 "current_progress": progress,
                 "current_task": task,

skore/tests/unit/displays/metrics_summary/test_cross_validation.py

@@ -56,7 +56,7 @@ def test_data_source_external(
     for split_idx in range(splitter):
         # check that it is equivalent to call the individual estimator report
         report_result = (
-            report.estimator_reports_[split_idx]
+            report.reports_[split_idx]
             .metrics.summarize(data_source="X_y", X=X, y=y)
             .frame()
         )
@@ -389,7 +389,7 @@ def test_scorer(linear_regression_data):
                 est_rep.y_test, est_rep.estimator_.predict(est_rep.X_test)
             ),
         ]
-        for est_rep in report.estimator_reports_
+        for est_rep in report.reports_
     ]
     np.testing.assert_allclose(
         result.to_numpy(),

skore/tests/unit/displays/precision_recall_curve/test_comparison_cross_validation.py

@@ -28,7 +28,7 @@ def test_binary_classification(
 
     pos_label = 1
     n_reports = len(report.reports_)
-    n_splits = len(list(report.reports_.values())[0].estimator_reports_)
+    n_splits = len(list(report.reports_.values())[0].reports_)
 
     display.plot()
     assert isinstance(display.lines_, list)
@@ -76,7 +76,7 @@ def test_multiclass_classification(
 
     labels = display.precision_recall["label"].cat.categories
     n_reports = len(report.reports_)
-    n_splits = len(list(report.reports_.values())[0].estimator_reports_)
+    n_splits = len(list(report.reports_.values())[0].reports_)
 
     display.plot()
     assert isinstance(display.lines_, list)

skore/tests/unit/displays/precision_recall_curve/test_cross_validation.py

@@ -32,7 +32,7 @@ def test_binary_classification(
 
     display.plot()
 
-    pos_label = report.estimator_reports_[0].estimator_.classes_[1]
+    pos_label = report.reports_[0].estimator_.classes_[1]
 
     assert hasattr(display, "ax_")
     assert hasattr(display, "figure_")
@@ -88,7 +88,7 @@ def test_multiclass_classification(
 
     display.plot()
 
-    class_labels = report.estimator_reports_[0].estimator_.classes_
+    class_labels = report.reports_[0].estimator_.classes_
 
     assert isinstance(display.lines_, list)
     assert len(display.lines_) == len(class_labels) * cv

skore/tests/unit/displays/roc_curve/test_cross_validation.py

@@ -27,7 +27,7 @@ def test_binary_classification(
     assert isinstance(display, RocCurveDisplay)
 
     check_display_data(display)
-    pos_label = report.estimator_reports_[0].estimator_.classes_[1]
+    pos_label = report.reports_[0].estimator_.classes_[1]
     assert (
         list(display.roc_curve["label"].unique())
         == list(display.roc_auc["label"].unique())
@@ -88,7 +88,7 @@ def test_multiclass_classification(
 
     # check the structure of the attributes
     check_display_data(display)
-    class_labels = report.estimator_reports_[0].estimator_.classes_
+    class_labels = report.reports_[0].estimator_.classes_
     assert (
         list(display.roc_curve["label"].unique())
         == list(display.roc_auc["label"].unique())

skore/tests/unit/reports/comparison/cross_validation/test_report.py

@@ -62,3 +62,9 @@ def test_get_predictions(
     assert len(predictions) == len(report.reports_)
     for i, cv_report in enumerate(report.reports_.values()):
         assert len(predictions[i]) == cv_report._splitter.n_splits
+
+
+def test_estimator_reports_(cross_validation_reports_regression):
+    cv, _ = cross_validation_reports_regression
+
+    assert id(cv.estimator_reports_) == id(cv.reports_)

skore/tests/unit/reports/cross_validation/test_report.py

@@ -74,13 +74,13 @@ def test_attributes(fixture_name, request, cv, n_jobs):
     estimator, X, y = request.getfixturevalue(fixture_name)
     report = CrossValidationReport(estimator, X, y, splitter=cv, n_jobs=n_jobs)
     assert isinstance(report, CrossValidationReport)
-    assert isinstance(report.estimator_reports_, list)
-    for estimator_report in report.estimator_reports_:
+    assert isinstance(report.reports_, list)
+    for estimator_report in report.reports_:
         assert isinstance(estimator_report, EstimatorReport)
     assert report.X is X
     assert report.y is y
     assert report.n_jobs == n_jobs
-    assert len(report.estimator_reports_) == cv
+    assert len(report.reports_) == cv
     if isinstance(estimator, Pipeline):
         assert report.estimator_name_ == estimator[-1].__class__.__name__
     else:
@@ -137,12 +137,12 @@ def test_cache_predictions(request, fixture_name, expected_n_keys, n_jobs):
     # underlying estimator reports
     assert report._cache == {}
 
-    for estimator_report in report.estimator_reports_:
+    for estimator_report in report.reports_:
         assert len(estimator_report._cache) == expected_n_keys
 
     report.clear_cache()
     assert report._cache == {}
-    for estimator_report in report.estimator_reports_:
+    for estimator_report in report.reports_:
         assert estimator_report._cache == {}
 
 
@@ -174,9 +174,9 @@ def test_get_predictions(
     assert len(predictions) == 2
     for split_idx, split_predictions in enumerate(predictions):
         if data_source == "train":
-            expected_shape = report.estimator_reports_[split_idx].y_train.shape
+            expected_shape = report.reports_[split_idx].y_train.shape
         elif data_source == "test":
-            expected_shape = report.estimator_reports_[split_idx].y_test.shape
+            expected_shape = report.reports_[split_idx].y_test.shape
         else:  # data_source == "X_y"
             expected_shape = (X.shape[0],)
         assert split_predictions.shape == expected_shape

skore/tests/unit/utils/test_accessors.py

@@ -130,7 +130,7 @@ def __init__(self, estimator):
 
     class MockParent:
         def __init__(self, estimator):
-            self.estimator_reports_ = [MockReport(estimator)]
+            self.reports_ = [MockReport(estimator)]
 
     class MockAccessor:
         def __init__(self, parent):