Pranav Achar ff81428a9c fix(python): flatten_columns raises when flatten=False (#3629) ...

### Summary

`flatten_columns` raises `ValueError` when called with `flatten=False`,
even though `False` should mean "do not flatten". This is reachable from
the public API — `Query.to_pandas(flatten=...)` and
`to_batches(flatten=...)` type their `flatten` param as
`Optional[Union[int, bool]]` and pass it straight to `flatten_columns`.

### Cause

`bool` is a subclass of `int`, so `isinstance(False, int)` is `True`.
`flatten=False` skips the `flatten is True` check, falls into the
integer branch, and `False <= 0` evaluates to `True`, raising:

```
ValueError: Please specify a positive integer for flatten or the boolean value `True`
```

### Reproduction

```python
import lancedb
db = lancedb.connect("/tmp/db")
t = db.create_table("t", data=[{"id": 1, "vector": [0.1, 0.2]}])
t.search([0.1, 0.2]).to_pandas(flatten=False)   # -> ValueError
```

### Fix

Guard the integer branch with `not isinstance(flatten, bool)` so that
`flatten=False` (and `None`) mean "do not flatten". Behavior is
otherwise unchanged:

- `flatten=True` → flatten all nested levels
- positive `int` → flatten to that depth
- non-positive `int` (e.g. `0`) → still rejected with `ValueError`

Added a regression test in `tests/test_util.py` covering `None`,
`False`, `True`, a positive depth, and `0`.

2026-07-09 11:07:26 -07:00

..

lancedb

fix(python): flatten_columns raises when flatten=False (#3629)

2026-07-09 11:07:26 -07:00

tests

fix(python): flatten_columns raises when flatten=False (#3629)

2026-07-09 11:07:26 -07:00