Wyatt Alt
0e65123bd8
Registering a real (embedding) Function failed on the client for three
reasons:
- `_package_source` treated `inspect.getclosurevars().unbound` as
"unresolved globals"; CPython puts attribute names there, so any body
with `np.linalg.norm(...)` or `body.split()` was rejected. Module-scope
references now come from Python's own scope analysis (`symtable`) over
the function source, recursively, and each is resolved the way the
interpreter would: the function's globals first (a module global may
shadow a builtin), then builtins. Free variables of nested scopes stay
lexical; postponed annotations are not runtime loads. A genuinely
missing global still fails.
- `_canonical_arrow_type` emitted spellings the server's frozen grammar
rejects (`fixed_size_list<T>[n]`, `timestamp[us]`, `struct<...>`,
zero-sized lists). It now emits exactly the grammar, with the server's
`fixed_size_list<item, size>` form, and the Rust declaration planner
parses that form too.
A shared golden
(`tests/fixtures/first_class_functions/v1/arrow_types.json`)
enumerates every grammar type, nested forms and rejected spellings; the
Python emitter and Rust parser are tested against it, and the same file
is under test in sophon. Packaging tests execute the shipped artifact in
a fresh namespace.
Contract changes (hence `breaking-change`):
- `@udf` now rejects namespace acquisition structurally
(`globals()`/`eval`/... by name, plus `import
sys`/`builtins`/`importlib`/`inspect` inside the body), requires the
function's captured `__builtins__` to be the standard mapping itself
(identity, so neither lookups nor implicit hooks such as `__import__`
can differ), rejects module globals that are namespace-bearing modules
(`builtins`, `sys`, ...), and treats the function's own name as
recursion only when the module binds it to the function or to the exact
`UdfDefinition` the decorator produced; it resolves module globals
through the function's real namespace (a module global may shadow a
builtin) and ships importable classes/functions as imports.
- List outputs must declare a non-nullable, metadata-free child named
`item` (`pa.list_(pa.field("item", t, nullable=False))`); that is what
the grammar means, and pyarrow's default nullable child was being
silently collapsed into it.
Contract, stated in the `udf` docstring: the artifact is a snapshot of
the function source plus exactly the module names it references.
Reaching the module namespace by another route is rejected where a
static packager can see it and is otherwise unsupported; there is no
dynamic-access detection beyond that.
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.