Yang Cen
2dedde9b6c
Remote SQL failures currently become generic runtime errors, and HTTP table lookup can discard server error metadata. Preserve transport status, current request ID, SQL job ID and worker request ID across Rust and Python. Select typed column, table, reference and schema exceptions only when an explicit server code matches the transport status. Remote `HttpError` and `RuntimeError` handlers remain compatible. Failed SQL jobs retain `JobFailedError` with a typed SQL cause when available. Missing metadata stays absent; message text never determines the exception class. Local missing-column errors retain their type and qualified-field suggestions, and `JobFailure.source` documents structured remote Flight SQL failures. This branch integrates main at `a9ad4997`, including its released Lance 15.0.0-beta.9 dependency update and remote optimize support. The only textual conflict was two independent additions to `test_remote_db.py`; both test groups and all original assertions are retained. The feature has no dependency or lockfile delta against current main. SDK runtime validation on `03ee633a` (runtime source unchanged in `f3f2d0b8`), macOS ARM64, pinned Rust 1.97.0 and the frozen uv Python 3.14 environment: - Rebuilt the native extension from the integrated source. All 22 targeted Python tests passed: native local errors, HTTP/Flight metadata, legacy sync/async table-not-found behavior, and the three main remote-optimize regressions. - All 52 Rust SQL, metadata/source and nested-field tests passed, including the new main optimize cases. - Root and Python-binding Rust Clippy with `-D warnings`, Rust formatting, Python package Ruff and conflict-file formatting passed. - Repository-wide Ruff reports 59 existing documentation findings, and its format check identifies six documentation files. Every affected file is byte-identical to current main; these checks are not reported as passing. - Direct integration review and AST comparison confirm both conflicting test groups were preserved. Earlier exception-constructor/pickling evidence remains applicable to the unchanged Python error modules. The unlocked build exhausted disk again on a runner with the same label but only 9.4 GiB free on a 72 GiB root filesystem. Keep the existing runner and dependency caches, serialize Cargo compilation, and remove only completed test/bench executables reported by Cargo. This job never runs those binaries; normal binaries, libraries and build-script outputs remain available. Fresh resolution, the ci profile, all features, and test/bench compilation and linking are retained. Three probes using Cargo and target-path validation pass with `-D warnings`: all fixture targets link while ordinary outputs remain usable; an undefined symbol still produces Cargo exit 101 and its linker diagnostic; files outside the target directory are never removed. The [current-head build-no-lock job](https://github.com/lancedb/lancedb/actions/runs/41911613851/job/126860364065) passed on `f3f2d0b8`: all compilation/linking completed, 20 completed test executables were removed, and `target` retained about 7.3 GiB. This successful run had a 145 GiB root with about 78 GiB free afterward; it was not an identical rerun of the failed 72 GiB image. The driver tests also passed in this job. All previous-head jobs ended naturally before the push; new-head CI and review gates still apply. Typed remote input exceptions require the server metadata contract. Older servers retain generic transport errors and existing missing-table compatibility. The optimize tests use mock servers and do not establish downstream server acceptance. BREAKING CHANGE: Rust callers with exhaustive matches on `lancedb::Error` must handle the new `FieldNotFound` and `Sql` variants. Local `Error::ColumnNotFound` failures now raise `lancedb.exceptions.ColumnNotFoundError`, a `ValueError` subclass. Python callers that previously caught only `RuntimeError` for this local failure must catch `ColumnNotFoundError` or `ValueError`.
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 (if pylance is installed, lance.simd_info() reports 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
Most applications only need lancedb. Install the optional pylance extra and
include the Lance preview index only when building query engines or connectors,
calling format-level lance APIs directly, or converting plain-scan lazy or
legacy blob columns with to_pandas():
pip install --pre \
--extra-index-url https://pypi.fury.io/lancedb/ \
--extra-index-url https://pypi.fury.io/lance-format/ \
"lancedb[pylance]"
With uv, also select the best matching version across the indexes:
uv pip install --prerelease allow \
--index https://pypi.fury.io/lancedb/ \
--index https://pypi.fury.io/lance-format/ \
--index-strategy unsafe-best-match \
"lancedb[pylance]"
The LanceDB preview index contains old pylance releases; current Lance previews
are published to the lance-format index. By default, uv only considers versions
from the first index containing a package, which can select an old pylance or
backtrack to an older LanceDB release. unsafe-best-match searches all configured
indexes, like pip; use it only with indexes you trust. Install the extra rather
than an unconstrained pylance so LanceDB's minimum supported version is enforced.
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.
Opening SQL blob descriptors
A SQL blob_descriptor(video) result keeps the Blob V2 storage metadata and a
source struct containing its table URI, version, commit timestamp, branch,
column and row identity. This example uses a remote SQL connection whose SQL
service produces those source-bearing descriptors. Open the reference on the
source table to read incrementally:
rows = db.execute_query("""
SELECT f.timestamp, blob_descriptor(v.video) AS video
FROM videos v JOIN frames f ON v.id = f.video_id
""").read_all()
videos = db.open_table("videos")
for row in rows.to_pylist():
if row["video"] is not None:
with videos.open_blob_file(row["video"]) as video:
frame = extract_frame(video, row["timestamp"])
open_blob_file accepts the dictionary or an Arrow struct scalar directly. It
keeps the query's version and branch without changing the table handle's checkout.
Payload bytes load on reads. An external blob with an unspecified size may need a
metadata-only HEAD request to open.
videos.open_blob_files(rows["video"]) returns an iterator over the same handles,
preserving order, duplicates and nulls (None). It accepts Arrow arrays/chunked
arrays or another iterable and opens each handle as iteration advances. Close each
non-null handle after use. Async tables offer await videos.open_blob_file(...)
and async for video in videos.open_blob_files(...).
for video in videos.open_blob_files(rows["video"]):
if video is not None:
with video:
header = video.read(4096)
To extract a frame while retaining each row's timestamp, iterate over the handles and rows together:
for row, video in zip(rows.to_pylist(), videos.open_blob_files(rows["video"])):
if video is not None:
with video:
frame = extract_frame(video, row["timestamp"])