Implement read_csv in cudf-polars using pylibcudf

python/cudf_polars/cudf_polars/dsl/ir.py

@@ -242,10 +242,6 @@ def evaluate(self, *, cache: MutableMapping[int, DataFrame]) -> DataFrame:
         with_columns = options.with_columns
         row_index = options.row_index
         if self.typ == "csv":
-            dtype_map = {
-                name: cudf._lib.types.PYLIBCUDF_TO_SUPPORTED_NUMPY_TYPES[typ.id()]
-                for name, typ in self.schema.items()
-            }
             parse_options = self.reader_options["parse_options"]
             sep = chr(parse_options["separator"])
             quote = chr(parse_options["quote_char"])
@@ -278,33 +274,40 @@ def evaluate(self, *, cache: MutableMapping[int, DataFrame]) -> DataFrame:
 
             # polars skips blank lines at the beginning of the file
             pieces = []
+            colnames = None
             for p in self.paths:
                 skiprows = self.reader_options["skip_rows"]
-                # TODO: read_csv expands globs which we should not do,
-                # because polars will already have handled them.
                 path = Path(p)
                 with path.open() as f:
                     while f.readline() == "\n":
                         skiprows += 1
-                pieces.append(
-                    cudf.read_csv(
-                        path,
-                        sep=sep,
-                        quotechar=quote,
-                        lineterminator=eol,
-                        names=column_names,
-                        header=header,
-                        usecols=usecols,
-                        na_filter=True,
-                        na_values=null_values,
-                        keep_default_na=False,
-                        skiprows=skiprows,
-                        comment=comment,
-                        decimal=decimal,
-                        dtype=dtype_map,
-                    )
+                tbl_w_meta = plc.io.csv.read_csv(
+                    plc.io.SourceInfo([path]),
+                    delimiter=sep,
+                    quotechar=quote,
+                    lineterminator=eol,
+                    col_names=column_names,
+                    header=header,
+                    usecols=usecols,
+                    na_filter=True,
+                    na_values=null_values,
+                    keep_default_na=False,
+                    skiprows=skiprows,
+                    comment=comment,
+                    decimal=decimal,
+                    dtypes=self.schema,
+                )
+                pieces.append(tbl_w_meta)
+            tbls, colnames = zip(
+                *(
+                    (piece.tbl, piece.column_names(include_children=False))
+                    for piece in pieces
                 )
-            df = DataFrame.from_cudf(cudf.concat(pieces))
+            )
+            df = DataFrame.from_table(
+                plc.concatenate.concatenate(list(tbls)),
+                colnames[0],
+            )
         elif self.typ == "parquet":
             cdf = cudf.read_parquet(self.paths, columns=with_columns)
             assert isinstance(cdf, cudf.DataFrame)

python/cudf_polars/tests/test_scan.py

@@ -2,10 +2,13 @@
 # SPDX-License-Identifier: Apache-2.0
 from __future__ import annotations
 
+import os
+
 import pytest
 
 import polars as pl
 
+from cudf_polars.callback import execute_with_cudf
 from cudf_polars.testing.asserts import (
     assert_gpu_result_equal,
     assert_ir_translation_raises,
@@ -129,6 +132,30 @@ def test_scan_csv_column_renames_projection_schema(tmp_path):
     assert_gpu_result_equal(q)
 
 
+@pytest.mark.parametrize("filename", [["test1.csv", "test2.csv"], "test*.csv"])
+def test_scan_csv_multi(tmp_path, filename):
+    with (tmp_path / "test1.csv").open("w") as f:
+        f.write("""foo,bar,baz\n1,2\n3,4,5""")
+    with (tmp_path / "test2.csv").open("w") as f:
+        f.write("""foo,bar,baz\n1,2\n3,4,5""")
+    os.chdir(tmp_path)
+    q = pl.scan_csv(filename)
+
+    assert_gpu_result_equal(q)
+
+
+def test_scan_csv_multi_differing_colnames(tmp_path):
+    with (tmp_path / "test1.csv").open("w") as f:
+        f.write("""foo,bar,baz\n1,2\n3,4,5""")
+    with (tmp_path / "test2.csv").open("w") as f:
+        f.write("""abc,def,ghi\n1,2\n3,4,5""")
+    q = pl.scan_csv(
+        [tmp_path / "test1.csv", tmp_path / "test2.csv"],
+    )
+    with pytest.raises(pl.exceptions.ComputeError):
+        q.collect(post_opt_callback=execute_with_cudf)
+
+
 def test_scan_csv_skip_after_header_not_implemented(tmp_path):
     with (tmp_path / "test.csv").open("w") as f:
         f.write("""foo,bar,baz\n1,2,3\n3,4,5""")