Add Parquet Reader options classes to pylibcudf

cpp/include/cudf/io/parquet.hpp

@@ -410,6 +410,7 @@ class parquet_reader_options_builder {
    *
    * @param val Boolean value whether to read matching projected and filter columns from mismatched
    * Parquet sources.
+   *
    * @return this for chaining.
    */
   parquet_reader_options_builder& allow_mismatched_pq_schemas(bool val)

python/cudf/cudf/_lib/parquet.pyx

@@ -219,7 +219,7 @@ cdef object _process_metadata(object df,
             else:
                 start = range_index_meta["start"] + skip_rows
                 stop = range_index_meta["stop"]
-                if nrows != -1:
+                if nrows > -1:
                     stop = start + nrows
                 idx = cudf.RangeIndex(
                     start=start,
@@ -270,16 +270,27 @@ def read_parquet_chunked(
     # (see read_parquet)
     allow_range_index = columns is not None and len(columns) != 0
 
+    options = (
+        plc.io.parquet.ParquetReaderOptions.builder(
+            plc.io.SourceInfo(filepaths_or_buffers)
+        )
+        .use_pandas_metadata(use_pandas_metadata)
+        .allow_mismatched_pq_schemas(allow_mismatched_pq_schemas)
+        .build()
+    )
+    if row_groups is not None:
+        options.set_row_groups(row_groups)
+    if nrows > -1:
+        options.set_num_rows(nrows)
+    if skip_rows != 0:
+        options.set_skip_rows(skip_rows)
+    if columns is not None:
+        options.set_columns(columns)
+
     reader = ChunkedParquetReader(
-        plc.io.SourceInfo(filepaths_or_buffers),
-        columns,
-        row_groups,
-        use_pandas_metadata=use_pandas_metadata,
+        options,
         chunk_read_limit=chunk_read_limit,
         pass_read_limit=pass_read_limit,
-        skip_rows=skip_rows,
-        nrows=nrows,
-        allow_mismatched_pq_schemas=allow_mismatched_pq_schemas,
     )
 
     tbl_w_meta = reader.read_chunk()
@@ -339,19 +350,26 @@ cpdef read_parquet(filepaths_or_buffers, columns=None, row_groups=None,
     if columns is not None and len(columns) == 0 or filters:
         allow_range_index = False
 
-    # Read Parquet
-
-    tbl_w_meta = plc.io.parquet.read_parquet(
-        plc.io.SourceInfo(filepaths_or_buffers),
-        columns,
-        row_groups,
-        filters,
-        convert_strings_to_categories = False,
-        use_pandas_metadata = use_pandas_metadata,
-        skip_rows = skip_rows,
-        nrows = nrows,
-        allow_mismatched_pq_schemas=allow_mismatched_pq_schemas,
+    options = (
+        plc.io.parquet.ParquetReaderOptions.builder(
+            plc.io.SourceInfo(filepaths_or_buffers)
+        )
+        .use_pandas_metadata(use_pandas_metadata)
+        .allow_mismatched_pq_schemas(allow_mismatched_pq_schemas)
+        .build()
     )
+    if row_groups is not None:
+        options.set_row_groups(row_groups)
+    if nrows > -1:
+        options.set_num_rows(nrows)
+    if skip_rows != 0:
+        options.set_skip_rows(skip_rows)
+    if columns is not None:
+        options.set_columns(columns)
+    if filters is not None:
+        options.set_filter(filters)
+
+    tbl_w_meta = plc.io.parquet.read_parquet(options)
 
     df = cudf.DataFrame._from_data(
         *data_from_pylibcudf_io(tbl_w_meta)

python/cudf_polars/cudf_polars/dsl/ir.py

@@ -517,17 +517,22 @@ def do_evaluate(
         elif typ == "parquet":
             parquet_options = config_options.get("parquet_options", {})
             if parquet_options.get("chunked", True):
+                options = plc.io.parquet.ParquetReaderOptions.builder(
+                    plc.io.SourceInfo(paths)
+                ).build()
+                # We handle skip_rows != 0 by reading from the
+                # up to n_rows + skip_rows and slicing off the
+                # first skip_rows entries.
+                # TODO: Remove this workaround once
+                # https://github.com/rapidsai/cudf/issues/16186
+                # is fixed
+                nrows = n_rows + skip_rows
+                if nrows > -1:
+                    options.set_num_rows(nrows)
+                if with_columns is not None:
+                    options.set_columns(with_columns)
                 reader = plc.io.parquet.ChunkedParquetReader(
-                    plc.io.SourceInfo(paths),
-                    columns=with_columns,
-                    # We handle skip_rows != 0 by reading from the
-                    # up to n_rows + skip_rows and slicing off the
-                    # first skip_rows entries.
-                    # TODO: Remove this workaround once
-                    # https://github.com/rapidsai/cudf/issues/16186
-                    # is fixed
-                    nrows=n_rows + skip_rows,
-                    skip_rows=0,
+                    options,
                     chunk_read_limit=parquet_options.get(
                         "chunk_read_limit", cls.PARQUET_DEFAULT_CHUNK_SIZE
                     ),
@@ -573,13 +578,18 @@ def slice_skip(tbl: plc.Table):
                 if predicate is not None and row_index is None:
                     # Can't apply filters during read if we have a row index.
                     filters = to_parquet_filter(predicate.value)
-                tbl_w_meta = plc.io.parquet.read_parquet(
-                    plc.io.SourceInfo(paths),
-                    columns=with_columns,
-                    filters=filters,
-                    nrows=n_rows,
-                    skip_rows=skip_rows,
-                )
+                options = plc.io.parquet.ParquetReaderOptions.builder(
+                    plc.io.SourceInfo(paths)
+                ).build()
+                if n_rows != -1:
+                    options.set_num_rows(n_rows)
+                if skip_rows != 0:
+                    options.set_skip_rows(skip_rows)
+                if with_columns is not None:
+                    options.set_columns(with_columns)
+                if filters is not None:
+                    options.set_filter(filters)
+                tbl_w_meta = plc.io.parquet.read_parquet(options)
                 df = DataFrame.from_table(
                     tbl_w_meta.tbl,
                     # TODO: consider nested column names?

python/pylibcudf/pylibcudf/io/parquet.pxd

@@ -18,33 +18,41 @@ from pylibcudf.libcudf.io.parquet cimport (
     chunked_parquet_reader as cpp_chunked_parquet_reader,
     parquet_writer_options,
     parquet_writer_options_builder,
+    parquet_reader_options,
+    parquet_reader_options_builder,
 )
 from pylibcudf.libcudf.types cimport size_type
 from pylibcudf.table cimport Table
 from pylibcudf.types cimport DataType
 
 
+cdef class ParquetReaderOptions:
+    cdef parquet_reader_options c_obj
+    cdef SourceInfo source
+    cpdef void set_row_groups(self, list row_groups)
+    cpdef void set_num_rows(self, size_type nrows)
+    cpdef void set_skip_rows(self, int64_t skip_rows)
+    cpdef void set_columns(self, list col_names)
+    cpdef void set_filter(self, Expression filter)
+
+cdef class ParquetReaderOptionsBuilder:
+    cdef parquet_reader_options_builder c_obj
+    cdef SourceInfo source
+    cpdef ParquetReaderOptionsBuilder convert_strings_to_categories(self, bool val)
+    cpdef ParquetReaderOptionsBuilder use_pandas_metadata(self, bool val)
+    cpdef ParquetReaderOptionsBuilder allow_mismatched_pq_schemas(self, bool val)
+    cpdef ParquetReaderOptionsBuilder use_arrow_schema(self, bool val)
+    cpdef build(self)
+
+
 cdef class ChunkedParquetReader:
     cdef unique_ptr[cpp_chunked_parquet_reader] reader
 
     cpdef bool has_next(self)
     cpdef TableWithMetadata read_chunk(self)
 
 
-cpdef read_parquet(
-    SourceInfo source_info,
-    list columns = *,
-    list row_groups = *,
-    Expression filters = *,
-    bool convert_strings_to_categories = *,
-    bool use_pandas_metadata = *,
-    int64_t skip_rows = *,
-    size_type nrows = *,
-    bool allow_mismatched_pq_schemas = *,
-    # disabled see comment in parquet.pyx for more
-    # ReaderColumnSchema reader_column_schema = *,
-    # DataType timestamp_type = *
-)
+cpdef read_parquet(ParquetReaderOptions options)
 
 cdef class ParquetWriterOptions:
     cdef parquet_writer_options c_obj

python/pylibcudf/pylibcudf/io/parquet.pyi

@@ -1,7 +1,8 @@
 # Copyright (c) 2024, NVIDIA CORPORATION.
 
 from collections.abc import Mapping
-from typing import Self
+
+from typing_extensions import Self
 
 from pylibcudf.expressions import Expression
 from pylibcudf.io.types import (
@@ -16,6 +17,24 @@ from pylibcudf.io.types import (
 )
 from pylibcudf.table import Table
 
+class ParquetReaderOptions:
+    def __init__(self): ...
+    def set_row_groups(self, row_groups: list[list[int]]): ...
+    def set_num_rows(self, nrows: int): ...
+    def set_skip_rows(self, skip_rows: int): ...
+    def set_columns(self, col_names: list[str]): ...
+    def set_filter(self, filter: Expression): ...
+    @staticmethod
+    def builder(source: SourceInfo) -> ParquetReaderOptionsBuilder: ...
+
+class ParquetReaderOptionsBuilder:
+    def __init__(self): ...
+    def convert_strings_to_categories(self, val: bool) -> Self: ...
+    def use_pandas_metadata(self, val: bool) -> Self: ...
+    def allow_mismatched_pq_schemas(self, val: bool) -> Self: ...
+    def use_arrow_schema(self, val: bool) -> Self: ...
+    def build(self) -> ParquetReaderOptions: ...
+
 class ChunkedParquetReader:
     def __init__(
         self,