Jonathan M HsiehandClaude Opus 5
404b91d4d6
`secret_env_bindings` took the general noun for one delivery mode. A binding is
the concept; how it arrives is a property of one. `secret_bindings` is a list of
`SecretBinding`, tagged by `kind`, so a later mode is a variant rather than a
sibling field -- and the rules that are per-Function, like how many Secrets it
may bind, stay answerable from one place.
The cost of one field is that an unknown kind is a decode error unless it is
caught. It is caught, the way `PythonRuntimeSpec` catches an unknown runtime:
`Unrecognized { kind }`, `#[non_exhaustive]`, and the payload dropped rather
than retained because the client does not proxy catalog values. A test pins it
-- a `file` binding from a newer server decodes, reports its kind, and
round-trips as its discriminator without failing the version around it.
A list has no key order to inherit, and the list is in the version hash, so
`bind_secrets` sorts it: a caller's argument order is not part of what a
Function is.
The Secret is named under `secret_ref`, not `secret`: the service scans Job
payloads for credential-shaped keys and refuses one called `secret` whatever it
holds. That guard is worth more blunt than argued with.
`create_secret` and `alter_secret` also stop sharing a request shape. They are
different operations to the service -- one refuses an existing name, the other
requires it -- and either may grow a field the other has no meaning for. What
they share is posting a body that must not be logged, which is a function.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01UfmeJ533rQDnPBkMtjerV6
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.