alexowens90 commented on issue #49309:
URL: https://github.com/apache/arrow/issues/49309#issuecomment-4004232240
Yes, I have a workaround to use `table.schema` like so:
```
if table.num_rows == 0:
pa_record_batches = [
pa.RecordBatch.from_arrays(
[chunked_array.chunk(0) for chunked_array in
table.itercolumns()], schema=table.schema
)
]
else:
pa_record_batches = table.to_batches()
```
I guess the unexepcted behaviour from my perspective was that the following
could does not work:
```
>>> import pyarrow as pa
>>> table = pa.table({"col": pa.array([], pa.int64())})
>>> new_table = pa.Table.from_batches(table.to_batches())
Traceback (most recent call last):
File "<python-input-4>", line 1, in <module>
new_table = pa.Table.from_batches(batches)
File "pyarrow/table.pxi", line 5032, in pyarrow.lib.Table.from_batches
ValueError: Must pass schema, or at least one RecordBatch
```
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