chore: import upstream snapshot with attribution

tests/datalab/test_data_issues.py

@@ -0,0 +1,52 @@
+import pytest
+from cleanlab.datalab.internal.data import Data
+from cleanlab.datalab.internal.data_issues import DataIssues, _ClassificationInfoStrategy
+from cleanlab.datalab.internal.task import Task
+
+
+class TestDataIssues:
+    labels = ["B", "A", "B"]
+    label_name = "labels"
+    strategy = _ClassificationInfoStrategy
+
+    @pytest.fixture
+    def data_issues(self):
+        data = Data(
+            data={self.label_name: self.labels},
+            task=Task.CLASSIFICATION,
+            label_name=self.label_name,
+        )
+        data_issues = DataIssues(data=data, strategy=self.strategy)
+        yield data_issues
+
+    def test_data_issues_init(self, data_issues):
+        assert hasattr(data_issues, "issues")
+        assert hasattr(data_issues, "issue_summary")
+        assert hasattr(data_issues, "info")
+
+    def test_statistics(self, data_issues):
+        stats = data_issues.statistics
+
+        assert stats == data_issues.info["statistics"]
+        assert stats["num_examples"] == 3, f"Incorrect number of examples: {stats['num_examples']}"
+        assert stats["class_names"] == ["A", "B"], f"Incorrect class names: {stats['class_names']}"
+        assert stats["num_classes"] == 2, f"Incorrect number of classes: {stats['num_classes']}"
+        assert stats["multi_label"] is False
+        assert (
+            stats["health_score"] is None
+        ), f"Health score should initially be None, but is {stats['health_score']}"
+
+    def test_get_info(self, data_issues):
+        with pytest.raises(ValueError):
+            data_issues.get_info("nonexistent_issue")
+        assert data_issues.get_info("statistics") == data_issues.info["statistics"]
+
+    def test_get_info_label(self, data_issues):
+        data_issues.info["label"] = {"given_label": [0, 1, 1], "predicted_label": [1, 0, 1]}
+        info = data_issues.get_info("label")
+
+        label_format_error_message = (
+            "get_info('label') should return the given label formatted with the class names"
+        )
+        assert info.get("given_label").tolist() == ["A", "B", "B"], label_format_error_message
+        assert info.get("predicted_label").tolist() == self.labels, label_format_error_message