chore: import upstream snapshot with attribution

python/ray/data/_internal/datasource_v2/scanners/scanner.py

@@ -0,0 +1,51 @@
+from abc import ABC, abstractmethod
+from typing import Generic
+
+import pyarrow as pa
+
+from ray.data._internal.datasource_v2 import InputSplit
+from ray.data._internal.datasource_v2.readers.base_reader import Reader
+from ray.util.annotations import DeveloperAPI
+
+
+@DeveloperAPI
+class Scanner(ABC, Generic[InputSplit]):
+    """Abstract base class for configured scanners.
+
+    A Scanner represents the logical result of reading data, including applied
+    filters, projections, limits, and other pushdown operations. It is an
+    immutable abstraction: each push operation returns a new Scanner instance
+    via cloning rather than mutation.
+
+    The Scanner is responsible for:
+    1. Determining the output schema after all projections
+    2. Creating Reader instances configured with all pushdowns
+
+    Splitting the input into parallel work units used to live here as a
+    ``plan()`` method. That responsibility now belongs to the listing-side
+    pipeline (``ListFiles`` + ``FilePartitioner``); scanners only
+    need to answer "what schema?" and "give me a reader."
+    """
+
+    @abstractmethod
+    def read_schema(self) -> pa.Schema:
+        """Return the schema that will be produced by this scanner.
+
+        This reflects the schema after all column pruning has been applied.
+
+        Returns:
+            PyArrow Schema describing the output data.
+        """
+        ...
+
+    @abstractmethod
+    def create_reader(self) -> Reader[InputSplit]:
+        """Create a Reader configured for this scanner.
+
+        The returned Reader will have all pushdowns (columns, predicates, limits)
+        applied and is ready to execute on workers.
+
+        Returns:
+            Configured Reader instance.
+        """
+        ...