Rahul-cs50 opened a new pull request, #4199:
URL: https://github.com/apache/iceberg-python/pull/4199
Closes #4186
# Rationale for this change
`column_sizes` is an optional field of a data file, but `inspect.entries()`
builds it with `dict(entry.data_file.column_sizes)`, so an entry without it
raises `TypeError: 'NoneType' object is not iterable`. DuckDB writes data files
without `column_sizes`, so `entries()` fails on tables it wrote. #1902 already
added `or {}` to the three count maps next to it (`value_counts`,
`null_value_counts`, `nan_value_counts`); this applies the same to
`column_sizes`. The `readable_metrics` part of `entries()` and `files()`
already handle a missing `column_sizes`.
Note: with this, `entries()` reports a missing map as an empty map, like the
three count maps, while `files()` reports `null`. I kept `entries()` consistent
with its neighbours; happy to switch all four to `null` instead if you'd prefer.
## Are these changes tested?
Yes. `test_inspect_entries_and_files_with_data_file_without_metrics` in
`tests/table/test_inspect.py` appends a data file that has no metrics (as in
the issue's repro) and reads `entries()` and `files()`. It fails on `main` with
the `TypeError` above and passes with this change. `tests/table` and
`tests/catalog/test_base.py` unit tests: 545 passed. `ruff check` and `ruff
format --check` are clean.
## Are there any user-facing changes?
`inspect.entries()` no longer raises on data files without `column_sizes`.
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