The Python bindings route every async call through a single, lazily created Tokio runtime, stored behind a raw pointer so it can survive being reset (not dropped) across fork() -- dropping it there would hang joining now-dead worker threads. That leak-on-fork path is deliberate and documented, but normal process exit had no equivalent handling at all: nothing ever tells the runtime to shut down, so its worker threads keep running, completely uncoordinated with the interpreter, until the process ends. If a worker thread is mid-task exactly as Py_Finalize begins tearing down interpreter state, it can panic on state that's already gone. That panic happens on a background thread with no PyO3-wrapped call frame to catch it -- and if it lands while another unwind is already in progress, Rust aborts the whole process outright rather than merely failing that one call. This reproduces as an intermittent SIGABRT on otherwise-successful short-lived processes that open a connection, do a handful of operations, and exit normally. Give the runtime a coordinated, bounded shutdown at the one point it was missing one: register a Python atexit callback that calls runtime::shutdown(), which takes the runtime through the same atomic slot the fork handler uses and calls shutdown_timeout() rather than a bare drop -- bounded, so a wedged background task can never hang process exit, but real in-flight work gets a genuine chance to finish first. Runs with the GIL released (Python::detach), since the wait would otherwise be able to deadlock against any in-flight task that itself needs the GIL to complete. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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_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.