XXX: Implement test case with artificial time delay.

Author: ingomueller-net

experimental/iterators/test/python/dialects/iterators/arrow.py

@@ -2,7 +2,9 @@
 
 import ctypes
 import os
+import sys
 from tempfile import NamedTemporaryFile
+import time
 
 import numpy as np
 import pandas as pd
@@ -249,3 +251,46 @@ def testArrowCSVInput():
     # CHECK-NEXT: (10, 510, 1010, 1510, 2510, 3010)
     # CHECK-NEXT: (35, 535, 1035, 1535, 2535, 3035)
     sum_batches_elementwise_with_iterators(reader)
+
+
+# Test case: Read from a sequence of Arrow arrays/record batches (produced by a
+# Python generator).
+
+
+# Create a generator that produces single-row record batches with increasing
+# numbers with an artificial delay of one second after each of them. Since each
+# generated record batch immediately produces output, this visually demonstrate
+# that the consumption by the MLIR-based iterators interleaves with the
+# Python-based production of the record batches in the stream.
+def generate_batches_with_delay(schema: pa.Schema) -> None:
+  for i in range(5):
+    arrays = [
+        pa.array(np.array([i], field.type.to_pandas_dtype()))
+        for field in schema
+    ]
+    batch = pa.RecordBatch.from_arrays(arrays, schema=schema)
+    yield batch
+    # Sleep only when a TTY is attached (in order not to delay unit tests).
+    if sys.stdout.isatty():
+      time.sleep(1)
+
+
+# CHECK-LABEL: TEST: testGeneratorInput
+@run
+def testGeneratorInput():
+  # Use pyarrow to create an Arrow table in memory.
+  table = create_test_input()
+
+  # Make physically separate batches from the table. (This ensures offset=0).
+  generator = generate_batches_with_delay(table.schema)
+
+  # Create a RecordBatchReader and export it as a C struct.
+  reader = pa.RecordBatchReader.from_batches(table.schema, generator)
+
+  # Hand the reader as an Arrow array stream to the Iterators test program.
+  # CHECK-NEXT: (0, 0, 0, 0, 0, 0, 0)
+  # CHECK-NEXT: (1, 1, 1, 1, 1, 1, 1)
+  # CHECK-NEXT: (2, 2, 2, 2, 2, 2, 2)
+  # CHECK-NEXT: (3, 3, 3, 3, 3, 3, 3)
+  # CHECK-NEXT: (4, 4, 4, 4, 4, 4, 4)
+  sum_batches_elementwise_with_iterators(reader)