Files
lancedb/python
Weston Pace 1f1d03f306 feat(python): add backpressure to StreamingDataset post-transform queue (#3897)
Rename prefetch_batches → io_queue_depth and introduce
transform_queue_depth as a symmetric pair: both express "number of
batches to buffer per split at this pipeline stage." The old names are
still accepted as keyword arguments but log a deprecation warning
redirecting callers to the new names.

transform_queue_depth caps how many transform-result batches can
accumulate per split in the post-transform queue. Without this limit a
slow consumer (e.g. a GPU training step) causes cooked rows to pile up
unboundedly. The backpressure check in _try_submit_tx counts both
already-cooked rows and rows expected from in-flight transforms; it
skips proactive transform submission when the combined total reaches the
limit. The reactive _ensure_cooked path bypasses the check so the
consumer never stalls.

---------

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-08-23 15:28:07 +08:00
..
2025-01-29 08:27:07 -08:00
2024-04-05 16:22:59 -07:00

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

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_THREADS overrides the number of compute workers. One worker is the appropriate setting for a two-CPU container when an explicit override is needed.
  • LANCE_IO_THREADS controls 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.