LeonSGP
1e313d3c0d
Decimal literals such as Decimal("1E-7") and Decimal("1E+3") currently
raise ValueError while building an expression. Parse the coefficient and
exponent exactly, and normalize representable negative scales to zero so
both typed filters and predicate.to_sql() queries preserve the value.
Checked arithmetic bounds the Decimal128 coefficient to 38 digits,
preserves existing scale limits, and rejects nonfinite or overflowing
values. This does not add Decimal256 literal support.
Added 21 cases covering actual Arrow-backed table queries, SQL queries,
zero, signed exponents, precision boundaries, and errors. Both Python
3.11 and 3.13 expression suites pass 123 tests; the baseline fails 10 of
the new cases. Python binding Rust tests pass 13; official make doctest
passes 77 with 6 skips; Ruff, Rustfmt, hooks, Pyright and
workspace/tests/all-features Clippy with -D warnings pass. A fresh
environment restored from the original dependency freeze passes the full
required suite: 1528 passed, 37 skipped, 68 deselected (143.51s); while
optional Torch suites have the same baseline remote mock-server ordering
failure.
Tested against f4544628; observed official main d864e719 contains one
Catalog API commit without expr or Cargo.lock changes. AI assistance:
gpt-6.1-sol assisted implementation and local validation; all reported
checks were actually executed.
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.