anxkhn opened a new pull request, #3601:
URL: https://github.com/apache/iceberg-python/pull/3601
# Rationale for this change
`NameMappingProjectionVisitor.field` (the visitor behind
`apply_name_mapping`)
rebuilds each `NestedField`, but it passed the field's write default under
the
keyword `initial_write=`:
```python
return NestedField(
field_id=field_partner.field_id,
name=field.name,
field_type=field_result,
required=field.required,
doc=field.doc,
initial_default=field.initial_default,
initial_write=field.write_default, # <- no such parameter
)
```
`NestedField.__init__` has no `initial_write` parameter; its write-default
keyword is `write_default`. Because `NestedField` is a Pydantic model, the
unknown `initial_write` key is absorbed by the `**data` catch-all and
silently
ignored, so `apply_name_mapping` dropped every field's `write_default` to
`None` (while `initial_default` was preserved). Every other place that
rebuilds
a `NestedField` (for example in `pyiceberg/table/update/schema.py`) already
uses
`write_default=`; this was the one call site out of step with the
constructor.
The fix passes `write_default=field.write_default` to match the constructor
contract.
## Are these changes tested?
Yes. Added `test_mapping_preserves_field_defaults` in
`tests/table/test_name_mapping.py`, which builds a schema whose field carries
both `initial_default` and `write_default`, runs it through
`apply_name_mapping`, and asserts both values survive on the mapped field. It
fails before the change (`write_default` comes back `None`) and passes after.
- `tests/table/test_name_mapping.py`: 13 passed
- `tests/io/test_pyarrow_visitor.py` and `tests/test_schema.py`: 388 passed
(the PyArrow name-mapping visitor and schema, the current caller surface)
Integration tests (Docker + Spark) were not run in this environment; the
change
is pure Python type-plumbing fully exercised by the unit tests above.
## Are there any user-facing changes?
No observable change in the current code paths. The only caller today is
`pyarrow_to_schema` -> `apply_name_mapping` (`pyiceberg/io/pyarrow.py`),
which
feeds a PyArrow-derived schema whose fields never carry an Iceberg
`write_default`, so nothing is dropped in practice right now. This is a
latent
correctness fix: it prevents `write_default` from being silently discarded
the
moment a name mapping is applied to any schema whose fields set a write
default.
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