Make .arrow() from relation return record batch reader

duckdb/__init__.pyi

@@ -415,7 +415,7 @@ class DuckDBPyRelation:
     def variance(self, column: str, groups: str = ..., window_spec: str = ..., projected_columns: str = ...) -> DuckDBPyRelation: ...
     def list(self, column: str, groups: str = ..., window_spec: str = ..., projected_columns: str = ...) -> DuckDBPyRelation: ...
 
-    def arrow(self, batch_size: int = ...) -> pyarrow.lib.Table: ...
+    def arrow(self, batch_size: int = ...) -> pyarrow.lib.RecordBatchReader: ...
     def __arrow_c_stream__(self, requested_schema: Optional[object] = None) -> object: ...
     def create(self, table_name: str) -> None: ...
     def create_view(self, view_name: str, replace: bool = ...) -> DuckDBPyRelation: ...
@@ -448,6 +448,7 @@ class DuckDBPyRelation:
     def pl(self, rows_per_batch: int = ..., connection: DuckDBPyConnection = ...) -> polars.DataFrame: ...
     def query(self, virtual_table_name: str, sql_query: str) -> DuckDBPyRelation: ...
     def record_batch(self, batch_size: int = ...) -> pyarrow.lib.RecordBatchReader: ...
+    def fetch_record_batch(self, rows_per_batch: int = 1000000, *, connection: DuckDBPyConnection = ...) -> pyarrow.lib.RecordBatchReader: ...
     def select_types(self, types: List[Union[str, DuckDBPyType]]) -> DuckDBPyRelation: ...
     def select_dtypes(self, types: List[Union[str, DuckDBPyType]]) -> DuckDBPyRelation: ...
     def set_alias(self, alias: str) -> DuckDBPyRelation: ...

duckdb/experimental/spark/sql/dataframe.py

@@ -75,7 +75,7 @@ def toArrow(self) -> "pa.Table":
         age: [[2,5]]
         name: [["Alice","Bob"]]
         """
-        return self.relation.arrow()
+        return self.relation.to_arrow_table()
 
     def createOrReplaceTempView(self, name: str) -> None:
         """Creates or replaces a local temporary view with this :class:`DataFrame`.

src/duckdb_py/pyrelation/initialize.cpp

@@ -61,7 +61,7 @@ static void InitializeConsumers(py::class_<DuckDBPyRelation> &m) {
 	         py::arg("date_as_object") = false)
 	    .def("fetch_df_chunk", &DuckDBPyRelation::FetchDFChunk, "Execute and fetch a chunk of the rows",
 	         py::arg("vectors_per_chunk") = 1, py::kw_only(), py::arg("date_as_object") = false)
-	    .def("arrow", &DuckDBPyRelation::ToArrowTable, "Execute and fetch all rows as an Arrow Table",
+	    .def("arrow", &DuckDBPyRelation::ToRecordBatch, "Execute and return an Arrow Record Batch Reader that yields all rows",
 	         py::arg("batch_size") = 1000000)
 	    .def("fetch_arrow_table", &DuckDBPyRelation::ToArrowTable, "Execute and fetch all rows as an Arrow Table",
 	         py::arg("batch_size") = 1000000)
@@ -78,10 +78,18 @@ static void InitializeConsumers(py::class_<DuckDBPyRelation> &m) {
 		)";
 	m.def("__arrow_c_stream__", &DuckDBPyRelation::ToArrowCapsule, capsule_docs,
 	      py::arg("requested_schema") = py::none());
-	m.def("record_batch", &DuckDBPyRelation::ToRecordBatch,
-	      "Execute and return an Arrow Record Batch Reader that yields all rows", py::arg("batch_size") = 1000000)
-	    .def("fetch_arrow_reader", &DuckDBPyRelation::ToRecordBatch,
-	         "Execute and return an Arrow Record Batch Reader that yields all rows", py::arg("batch_size") = 1000000);
+	m.def("fetch_record_batch", &DuckDBPyRelation::ToRecordBatch,
+	      "Execute and return an Arrow Record Batch Reader that yields all rows", py::arg("rows_per_batch") = 1000000)
+	.def("fetch_arrow_reader", &DuckDBPyRelation::ToRecordBatch,
+	         "Execute and return an Arrow Record Batch Reader that yields all rows", py::arg("batch_size") = 1000000)
+	.def("record_batch",
+			 [](pybind11::object &self, idx_t rows_per_batch)
+			 {
+			 	PyErr_WarnEx(PyExc_DeprecationWarning,
+			 		"record_batch() is deprecated, use fetch_record_batch() instead.",
+			 		0);
+			 	return self.attr("fetch_record_batch")(rows_per_batch);
+			 }, py::arg("batch_size") = 1000000);
 }
 
 static void InitializeAggregates(py::class_<DuckDBPyRelation> &m) {

tests/pytest.ini

@@ -3,6 +3,7 @@
 filterwarnings =
     error
     ignore::UserWarning
+    ignore::DeprecationWarning
     # Jupyter is throwing DeprecationWarnings
     ignore:function ham\(\) is deprecated:DeprecationWarning
     # Pyspark is throwing these warnings