jorisvandenbossche commented on code in PR #42010:
URL: https://github.com/apache/arrow/pull/42010#discussion_r1636586472
##########
python/pyarrow/tests/test_cuda.py:
##########
@@ -792,3 +792,57 @@ def test_IPC(size):
p.start()
p.join()
assert p.exitcode == 0
+
+
+def test_print_array():
+ batch = make_recordbatch(10)
+ cbuf = cuda.serialize_record_batch(batch, global_context)
+ cbatch = cuda.read_record_batch(cbuf, batch.schema)
+ arr = batch["f0"]
+ carr = cbatch["f0"]
+ assert str(carr) == str(arr)
+
+ batch = make_recordbatch(100)
+ cbuf = cuda.serialize_record_batch(batch, global_context)
+ cbatch = cuda.read_record_batch(cbuf, batch.schema)
+ arr = batch["f0"]
+ carr = cbatch["f0"]
+ assert str(carr) == str(arr)
+
+
+def make_chunked_array(n_elements_per_chunk, n_chunks):
+ arrs = []
+ carrs = []
+ for _ in range(n_chunks):
+ batch = make_recordbatch(n_elements_per_chunk)
+ cbuf = cuda.serialize_record_batch(batch, global_context)
+ cbatch = cuda.read_record_batch(cbuf, batch.schema)
+ arrs.append(batch["f0"])
+ carrs.append(cbatch["f0"])
+
+ return pa.chunked_array(arrs), pa.chunked_array(carrs)
Review Comment:
This is still a bit verbose, but can be simplified once the "copy to device"
functionality is exposed (should maybe do that first now)
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