LeonSGP
554dc01f4d
`SourceField(json_schema_extra={...})` and
`VectorField(json_schema_extra={...})` currently raise `TypeError`
because the helper supplies the same `Field` keyword twice. Explicit
`None` also fails. This prevents users from adding ordinary Pydantic
JSON schema metadata to embedding fields.
Copy and merge the supplied dictionary before attaching the helper's
internal embedding identity. Caller dictionaries remain unchanged, and
reserved embedding keys retain the real function. Other `Field`
arguments keep their existing behavior. This change covers dictionaries
and `None`; callable `json_schema_extra` remains unsupported by the
existing embedding metadata reader and is outside this fix.
The 11 regression cases exercise both helpers, empty/custom/None
metadata, reserved-key collisions, other Field arguments, and a
deterministic local embedding model through JSON schema generation,
table creation, reopening, and search. On the original source, 9 fail
and 2 controls pass; the candidate passes all 11 on Python 3.11 and
3.13.
Validation uses read-only reused environments and the native extension
built for d864e719. The production helper is byte-identical to current
main bbc4aebe before this fix; no current-main native rebuild was
performed. The branch contains only this helper fix and its regression
test, independently based on d864e719.
Reproducible checkout commands below assume the documented environment
is installed as `.venv`; the actual local runs used existing
interpreters through absolute paths and isolated generated-data working
directories:
```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)
git diff --check
.venv/bin/ruff check .
.venv/bin/ruff format --check .
.venv/bin/python -m pre_commit run --files python/python/lancedb/embeddings/base.py python/python/tests/test_embedding_field_metadata.py
```
Doctests require the repository's tests/dev/embeddings dependencies,
including mlx on this platform. All checks below ran against frozen head
3fa6820.
Implemented with assistance from gpt-6.1-sol; the final diff was
reviewed locally.
Frozen-head validation (all exit 0):
- Python 3.11 full: 1535 passed, 36 skipped, 68 deselected; 190.272415
seconds wall time.
- Python 3.13 full: 1532 passed, 37 skipped, 68 deselected; 249.289778
seconds wall time.
- Python 3.13 doctests: 71 passed, 6 skipped; 10.391002 seconds wall
time.
- Pyright: 0 errors, 0 warnings; 4.884641 seconds wall time.
- pre-commit: 4 passed, 2 skipped; 0.747764 seconds wall time.
- Repository Ruff check: passed; 0.078177 seconds wall time.
- Repository Ruff format: 157 files already formatted; 0.034561 seconds
wall time.
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.