Add filename_pattern to to_parquet Python API

_duckdb-stubs/__init__.pyi

@@ -720,6 +720,7 @@ class DuckDBPyRelation:
         partition_by: pytyping.List[str] | None = None,
         write_partition_columns: bool | None = None,
         append: bool | None = None,
+        filename_pattern: str | None = None,
     ) -> None: ...
     def to_table(self, table_name: str) -> None: ...
     def to_view(self, view_name: str, replace: bool = True) -> DuckDBPyRelation: ...
@@ -772,6 +773,7 @@ class DuckDBPyRelation:
         partition_by: pytyping.List[str] | None = None,
         write_partition_columns: bool | None = None,
         append: bool | None = None,
+        filename_pattern: str | None = None,
     ) -> None: ...
     @property
     def alias(self) -> str: ...

src/duckdb_py/include/duckdb_python/pyrelation.hpp

@@ -214,7 +214,7 @@ struct DuckDBPyRelation {
 	               const py::object &row_group_size = py::none(), const py::object &overwrite = py::none(),
 	               const py::object &per_thread_output = py::none(), const py::object &use_tmp_file = py::none(),
 	               const py::object &partition_by = py::none(), const py::object &write_partition_columns = py::none(),
-	               const py::object &append = py::none());
+	               const py::object &append = py::none(), const py::object &filename_pattern = py::none());
 
 	void ToCSV(const string &filename, const py::object &sep = py::none(), const py::object &na_rep = py::none(),
 	           const py::object &header = py::none(), const py::object &quotechar = py::none(),

src/duckdb_py/pyrelation.cpp

@@ -1213,7 +1213,8 @@ void DuckDBPyRelation::ToParquet(const string &filename, const py::object &compr
                                  const py::object &row_group_size_bytes, const py::object &row_group_size,
                                  const py::object &overwrite, const py::object &per_thread_output,
                                  const py::object &use_tmp_file, const py::object &partition_by,
-                                 const py::object &write_partition_columns, const py::object &append) {
+                                 const py::object &write_partition_columns, const py::object &append,
+                                 const py::object &filename_pattern) {
 	case_insensitive_map_t<vector<Value>> options;
 
 	if (!py::none().is(compression)) {
@@ -1304,6 +1305,13 @@ void DuckDBPyRelation::ToParquet(const string &filename, const py::object &compr
 		options["use_tmp_file"] = {Value::BOOLEAN(py::bool_(use_tmp_file))};
 	}
 
+	if (!py::none().is(filename_pattern)) {
+		if (!py::isinstance<py::str>(filename_pattern)) {
+			throw InvalidInputException("to_parquet only accepts 'filename_pattern' as a string");
+		}
+		options["filename_pattern"] = {Value(py::str(filename_pattern))};
+	}
+
 	auto write_parquet = rel->WriteParquetRel(filename, std::move(options));
 	PyExecuteRelation(write_parquet);
 }

src/duckdb_py/pyrelation/initialize.cpp

@@ -36,7 +36,8 @@ static void InitializeConsumers(py::class_<DuckDBPyRelation> &m) {
 	             py::arg("row_group_size_bytes") = py::none(), py::arg("row_group_size") = py::none(),
 	             py::arg("overwrite") = py::none(), py::arg("per_thread_output") = py::none(),
 	             py::arg("use_tmp_file") = py::none(), py::arg("partition_by") = py::none(),
-	             py::arg("write_partition_columns") = py::none(), py::arg("append") = py::none());
+	             py::arg("write_partition_columns") = py::none(), py::arg("append") = py::none(),
+	             py::arg("filename_pattern") = py::none());
 
 	DefineMethod(
 	    {"to_csv", "write_csv"}, m, &DuckDBPyRelation::ToCSV, "Write the relation object to a CSV file in 'file_name'",

tests/fast/api/test_to_parquet.py

@@ -1,4 +1,6 @@
 import os
+import pathlib
+import re
 import tempfile
 
 import pytest
@@ -170,3 +172,56 @@ def test_append(self, pd):
             ("shinji", 123.0, "a"),
         ]
         assert result.execute().fetchall() == expected
+
+    @pytest.mark.parametrize("pd", [NumpyPandas(), ArrowPandas()])
+    def test_filename_pattern_with_index(self, pd):
+        temp_file_name = os.path.join(tempfile.mkdtemp(), next(tempfile._get_candidate_names()))  # noqa: PTH118
+        df = pd.DataFrame(
+            {
+                "name": ["rei", "shinji", "asuka", "kaworu"],
+                "float": [321.0, 123.0, 23.0, 340.0],
+                "category": ["a", "a", "b", "c"],
+            }
+        )
+        rel = duckdb.from_df(df)
+        rel.to_parquet(temp_file_name, partition_by=["category"], filename_pattern="orders_{i}")
+        # Check that files follow the pattern with {i}
+        files_a = list(pathlib.Path(f"{temp_file_name}/category=a").iterdir())
+        files_b = list(pathlib.Path(f"{temp_file_name}/category=b").iterdir())
+        files_c = list(pathlib.Path(f"{temp_file_name}/category=c").iterdir())
+        filename_pattern = re.compile(r"^orders_[09]+\.parquet$")
+        assert all(filename_pattern.search(str(f.name)) for f in files_a)
+        assert all(filename_pattern.search(str(f.name)) for f in files_b)
+        assert all(filename_pattern.search(str(f.name)) for f in files_c)
+
+        # Verify data integrity
+        result = duckdb.sql(f"FROM read_parquet('{temp_file_name}/*/*.parquet', hive_partitioning=TRUE)")
+        expected = [("rei", 321.0, "a"), ("shinji", 123.0, "a"), ("asuka", 23.0, "b"), ("kaworu", 340.0, "c")]
+        assert result.execute().fetchall() == expected
+
+    @pytest.mark.parametrize("pd", [NumpyPandas(), ArrowPandas()])
+    def test_filename_pattern_with_uuid(self, pd):
+        temp_file_name = os.path.join(tempfile.mkdtemp(), next(tempfile._get_candidate_names()))  # noqa: PTH118
+        df = pd.DataFrame(
+            {
+                "name": ["rei", "shinji", "asuka", "kaworu"],
+                "float": [321.0, 123.0, 23.0, 340.0],
+                "category": ["a", "a", "b", "c"],
+            }
+        )
+        rel = duckdb.from_df(df)
+        rel.to_parquet(temp_file_name, partition_by=["category"], filename_pattern="file_{uuid}")
+        # Check that files follow the pattern with {uuid}
+        files_a = list(pathlib.Path(f"{temp_file_name}/category=a").iterdir())
+        files_b = list(pathlib.Path(f"{temp_file_name}/category=b").iterdir())
+        files_c = list(pathlib.Path(f"{temp_file_name}/category=c").iterdir())
+        filename_pattern = re.compile(r"^file_[a-z0-9]{8}-[a-z0-9]{4}-[a-z0-9]{4}-[a-z0-9]{4}-[a-z0-9]{12}\.parquet$")
+        print(files_a)
+        assert all(filename_pattern.search(str(f.name)) for f in files_a)
+        assert all(filename_pattern.search(str(f.name)) for f in files_b)
+        assert all(filename_pattern.search(str(f.name)) for f in files_c)
+
+        # Verify data integrity
+        result = duckdb.sql(f"FROM read_parquet('{temp_file_name}/*/*.parquet', hive_partitioning=TRUE)")
+        expected = [("rei", 321.0, "a"), ("shinji", 123.0, "a"), ("asuka", 23.0, "b"), ("kaworu", 340.0, "c")]
+        assert result.execute().fetchall() == expected