LeonSGP
8552fd2f5b
Registering a different embedding class under an existing alias silently replaced the original class. A deterministic real local SDK table reproduction changed the top result for the same query from alpha to beta after reopening the persisted table. Check the resolved key before inserting a class. Preserve repeated registration of the same class under the same nonempty explicit alias as idempotent, as existing SDK tests rely on it. Repeated implicit class-name registration, including an empty alias, still raises KeyError. Failed registration preserves the mapping and class metadata. Existing embedding tests receive isolated registry mappings; test_util.py remains unchanged. Eight regression cases cover different-class alias collisions, alias/class-name collisions, implicit and empty-alias duplicates, equal class names under distinct aliases, explicit-alias idempotence, and real local creation/reopening/search. This is independent of #4356, which fixes no-alias serialization. Validation on52a1ccee5a: - Original registry plus eight new cases: 4 failed, 4 passed; Python 3.11.14; exit 1; 2.902604 s. Candidate plus full utility module: 83 passed, 1 skipped; exit 0; 3.144414 s. - Python 3.11.14 full official non-slow/non-S3 suite: 1532 passed, 36 skipped, 68 deselected; exit 0; 152.631543 s. - Python 3.13.11 full official non-slow/non-S3 suite: 1529 passed, 37 skipped, 68 deselected; exit 0; 163.970571 s. - Official Python 3.13 doctest with existing compatible embeddings/torch/mlx dependencies: 71 passed, 6 skipped; exit 0; 9.635034 s. - Pyright with matching interpreter/source path: 0 errors, 0 warnings; exit 0; 4.299743 s. - Repository Ruff 0.9.9 check and format: exit 0; 157 files already formatted; 0.047418 s and 0.016815 s. Pre-commit changed files: four hooks passed, two inapplicable skipped; exit 0; 0.406136 s. git diff --check passed. Base is officiald864e7198fwith its verified matching native extension reused read-only. All 174 native/config paths are unchanged from that base. Latest mainbbc4aebe55has byte-identical registry production code; its complete native build was not run. Verification was macOS arm64, with optional dependency/service skips above; Linux/Windows CI remains remote verification. Exact commands, cwd, identities, raw logs and intermediate failures are in the local manifest. The earlier strict same-class check caused 13 utility failures and was corrected in production; it is not described as a baseline failure. Reproduction commands after preparing the repository's declared environment (from repository root unless noted): ```sh PYTHONPATH=python/python .venv/bin/python -m pytest python/python/tests -m 'not slow and not s3_test' -q -rs -p no:cacheprovider PYTHONPATH=python/python .venv/bin/python -m pytest --doctest-modules python/python/lancedb -q --tb=short (cd python && PYTHONPATH=python ../.venv/bin/pyright --pythonpath ../.venv/bin/python) .venv/bin/ruff check . .venv/bin/ruff format --check . .venv/bin/python -m pre_commit run --files python/python/lancedb/embeddings/registry.py python/python/tests/test_embedding_registry.py python/python/tests/test_embeddings.py git diff --check ``` These relative commands describe reproducible source/cwd equivalents. The recorded local runs used absolute paths to existing Python 3.11.14/3.13.11 environments, a verified matching reused native extension, and read-only compatible optional-dependency cache paths for the 3.13 doctest, rather than a newly installed `.venv`. Full tests used separate task-private working directories and `--basetemp` directories to avoid cross-run database collisions. Implemented with assistance from gpt-6.1-sol; the final diff was reviewed locally by the collaborating agents.
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.