Srijan Keshri
118e606e8e
Arrow's `flatten()` skips child values hidden under null list parents, but `list_parent_indices()` can retain their indices. This makes `has_nan_values()` raise `ArrowInvalid` because the parent indices and NaN mask have different lengths. Filter out indices belonging to null parents before applying the mask. The regression test covers `ListArray` and `LargeListArray`, float16/32/64, and chunked inputs: 12 cases. NaN and null-component policies stay the same. The crash also affects #4503. This patch fixes it separately from that PR's changes to bad-vector policies. Validation: - All 12 regression cases failed before the fix. The utility suite now passes with 87 passed and 1 skipped. - Ruff lint and formatting pass for both changed files, as does `git diff --check`. - The patch applies cleanly to main at `ca275b6d`. The patched helper from that revision also passes all 12 cases. - A separate AI reviewer checked commit `343082a6` and found no blocking issues. They reran the utility suite and compared 4,059 generated cases plus 12 explicit null-parent cases with a row-by-row reference implementation. Those checks include slices, chunked inputs, and fixed-size lists. SDK tests used base `07e626ec` with the existing compiled extension. The broader Python run stopped after 474 passed and 23 skipped at `test_local_module_outside_code_warns_at_registration` with `ModuleNotFoundError`. That test also fails with the original vector helper restored. Repository-wide Ruff reports 49 lint errors and 11 files needing formatting, all in untouched documentation examples. Full SDK integration tests against current main require a newer native build and have not been run.
LanceDB Python SDK
A Python library for LanceDB.
Installation
pip install lancedb
If no wheel is published for your platform, pip builds lancedb from the source distribution. That build needs a Rust toolchain and protoc (the Protocol Buffers compiler) on your PATH, and can take a while.
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
Threading in CPU-limited containers
LanceDB uses separate pools for compute work and storage I/O. On a container with two visible CPUs, current releases intentionally use one compute worker by default; no manual configuration is needed. If every query logs an I/O core reservation warning on a two-CPU container, upgrade from LanceDB 0.21.1 or earlier.
The two commonly tuned environment variables control different resources:
LANCE_CPU_THREADSoverrides the number of compute workers. One worker is the appropriate setting for a two-CPU container when an explicit override is needed.LANCE_IO_THREADScontrols concurrent storage operations, not reserved CPU cores. Its default can be greater than the number of CPUs because I/O workers spend much of their time waiting for storage.
Keep the defaults unless measurements show that the workload benefits from an override. See the Lance threading model for the current defaults and tuning guidance.
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.