367abe99d2
## Summary
- Add `@value_to_sql.register(dict)` handler that converts Python dicts
to DataFusion's `named_struct()` SQL syntax
- Enables updating struct-typed columns via `table.update(values={"col":
{"field_a": 1, "field_b": "hello"}})`
- Recursively handles nested structs, lists, nulls, and all existing
scalar types
Closes #1363
## Details
The `named_struct` function was introduced in DataFusion 38 and is now
available (LanceDB uses DataFusion 52.1). The implementation follows the
existing `singledispatch` pattern in `util.py`.
**Example conversion:**
```python
value_to_sql({"field_a": 1, "field_b": "hello"})
# => "named_struct('field_a', 1, 'field_b', 'hello')"
```
## Test plan
- [x] Unit tests for flat struct, nested struct, list inside struct,
mixed types, null values, and empty dict
- [ ] CI integration tests with actual table.update() on struct columns
🔗 [DataFusion named_struct
docs](https://datafusion.apache.org/user-guide/sql/scalar_functions.html#named-struct)
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LanceDB is designed for fast, scalable, and production-ready vector search. It is built on top of the Lance columnar format. You can store, index, and search over petabytes of multimodal data and vectors with ease. LanceDB is a central location where developers can build, train and analyze their AI workloads.
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| Interface | Documentation |
|---|---|
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| Typescript SDK | https://lancedb.github.io/lancedb/js/globals/ |
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