Adds namespace addressing to Functions, matching what Secrets already have (#4150). ## API `create_function` / `create_function_async`, `get_function`, `list_functions`, `drop_function` / `drop_function_async` take `namespace_path` — keyword-only in Python (sync, async and remote connections) and a trailing `&[String]` in Rust — defaulting to the root. The namespace is addressed in the route identifier (`/v1/function/analytics$features$embed/describe`, `/v1/namespace/analytics$features/function/list`); no body carries it. `FunctionVersion` and `FunctionVersionRef` name their Function **by parts** — a short `name` plus `namespace_path` — the same shape as `SecretReference`, so a returned version reopens from its own fields: ```python fv = db.create_function(embed, namespace_path=["analytics", "features"]) fv.name, fv.namespace_path # "embed", ("analytics", "features") db.get_function(fv.name, version=fv.version, namespace_path=list(fv.namespace_path)) ``` An empty path is omitted from the wire, so root documents keep their shape. `namespace_path` is passed straight to the binding, so a bare string (`namespace_path="prod"`) is a `TypeError` rather than four one-character segments; segments are checked for addressability before a request is built. The binding and application allow-lists now share one field list, `FUNCTION_VERSION_REF_FIELDS`, which admits `namespace_path` — without it a namespaced binding or application read as coming from a newer contract. ## Service side The Sophon half serves and persists FunctionVersion / FunctionVersionRef documents in this split form, keeping the joined id as its internal catalog key. It lands in sophon with the submodule bump. ## Tests - Rust: every Function verb addresses a namespace in the path; an unaddressable segment never reaches the transport; `FunctionVersion` round-trips a namespace and `reference()` carries it; a namespaced binding and application are known shapes. - Python: sync and async verbs address the namespace; a created Function reopens from its own `name`/`namespace_path`; a bare-string path is refused before any request. Draft: compiles, `cargo fmt --check` and clippy `-D warnings` clean; lancedb lib Function tests (116) and `first_class_function_slice2` pass on this base. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-authored-by: Claude Opus 5.5 <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.