lancedb-gatefixer[bot]
dd5cb4d805
## Summary - exercise float16 sanitization through the reported direct Arrow-data table creation path - assert that the inferred fixed-size vector schema remains float16 - retain end-to-end index creation and vector search coverage ## Root cause and fix PyArrow 16 does not provide an is_nan kernel for half-float arrays, so passing float16 vector values directly to that kernel raises ArrowNotImplementedError. LanceDB's sanitizer already carries the compatibility fix from #837: it casts float16 values to float32 only for NaN detection while preserving the stored vector type. The existing end-to-end regression created an empty schema-defined table and added data afterward. This change aligns that regression with the issue reproduction by creating a table directly from a FixedSizeList<float16> Arrow table and verifying the persisted schema. ## Validation - uv run --extra tests pytest python/tests/test_table.py::test_create_f16_table_from_arrow_data -q - direct 1,000-row by 128-dimension float16 Arrow-table reproduction - PyArrow 16.1 half-float is_nan kernel reproduction - uvx ruff@0.15.20 format --check python/python/tests/test_table.py - uvx ruff@0.15.20 check . Fixes #835 <!-- lance-gatekeeper-fix:v1 agent=dd0a32a959f691f49de958d4333fb29d generation=1 --> --------- Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com>
LanceDB Python SDK
A Python library for LanceDB.
Installation
pip install lancedb
Pre-Haswell x86_64 hosts: lancedb-compat
The default lancedb wheel targets x86-64-haswell (AVX2 + FMA + F16C) for full performance on modern hardware. Pre-Haswell hosts — Intel Sandy Bridge / Ivy Bridge / Westmere; AMD Bulldozer / Piledriver / Steamroller — don't have AVX2 and crash with Illegal instruction at import lancedb.
For those hosts, install the lancedb-compat package instead:
pip install lancedb-compat
Same Python API (import lancedb works as usual). The compat wheel is compiled at the x86-64-v2 baseline (Nehalem-class) and uses runtime SIMD dispatch in the embedded lance crate to pick the right kernel tier (scalar / AVX / AVX+FMA / AVX2+FMA / AVX-512) at load time, so it still goes fast on modern hardware while running cleanly on the pre-Haswell silicon. Use lance.simd_info() from Python to verify which tier was selected.
lancedb and lancedb-compat install to the same lancedb/ namespace and conflict at install time. Pick one. To switch, pip uninstall lancedb first, then pip install lancedb-compat (or vice-versa).
If you need a custom baseline (or lancedb-compat isn't yet published for your platform), build from source with the override:
RUSTFLAGS="-C target-cpu=x86-64-v2" maturin build --release
pip install ./target/wheels/lancedb-*.whl
Preview Releases
Stable releases are created about every 2 weeks. For the latest features and bug fixes, you can install the preview release. These releases receive the same level of testing as stable releases, but are not guaranteed to be available for more than 6 months after they are released. Once your application is stable, we recommend switching to stable releases.
pip install --pre --extra-index-url https://pypi.fury.io/lancedb/ lancedb
Usage
Basic Example
import lancedb
db = lancedb.connect('<PATH_TO_LANCEDB_DATASET>')
table = db.open_table('my_table')
results = table.search([0.1, 0.3]).limit(20).to_list()
print(results)
Development
See CONTRIBUTING.md for information on how to contribute to LanceDB.