Spenserrrr commented on code in PR #58000:
URL: https://github.com/apache/spark/pull/58000#discussion_r3786382080
##########
python/pyspark/testing/goldenutils.py:
##########
@@ -311,12 +311,33 @@ def repr_type(t: Any) -> str:
# "halffloat" -> "float16", "float" -> "float32", "double" ->
"float64"
return _ARROW_FLOAT_ALIASES.get(s, s)
+ @staticmethod
+ def _scalar_str(scalar: Any) -> str:
+ """
+ Render one PyArrow scalar for a golden cell via PyArrow's own
``str(scalar)``.
+
+ A temporal value can be valid in Arrow yet outside Python's
``datetime`` range
+ (e.g. a date32 past year 9999), where ``str`` builds a Python datetime
and
+ raises ``OverflowError``. For those, record the raw stored count as
+ ``raw=<value>`` (its unit is in the type suffix) instead of failing. A
+ non-temporal ``OverflowError`` is unexpected, so it propagates.
+ """
+ try:
+ return str(scalar).replace("\x00", "\\0")
+ except OverflowError:
+ # No Python datetime exists for this value; record the raw stored
count as
+ # ``raw=<value>``. A non-temporal overflow is unexpected, so
re-raise.
+ if pa.types.is_temporal(scalar.type):
+ return f"raw={scalar.value}"
Review Comment:
Yeah, that makes sense. I went with temporal overflow, and the cell now
renders `[temporal overflow, temporal overflow, None]@date32[day]`.
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