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`Table.update` and `AsyncTable.update` convert Python values into SQL literals. Tuple arrays and `numpy.datetime64` values currently raise `NotImplementedError`, even when the same values can be ingested into the corresponding local Arrow columns. Register tuples with the existing recursive list converter and format NumPy timestamps as complete nanosecond ISO strings with an explicit UTC offset. `NaT` becomes SQL NULL; subnanosecond units raise an explicit error rather than silently losing precision. Regression tests exercise local synchronous and asynchronous create/update/Arrow reads, date and timestamp units, nanosecond precision, NULL, and existing list/ndarray/Python datetime behavior. Nested and empty tuple arrays are compared with equivalent lists on the actual SDK: successful results must match, and the matching d864 native engine's existing list limitations must produce the same stable error without changing either table. This does not change SQL map handling. Implemented with assistance from gpt-6.1-sol; final diff reviewed locally. Local verification uses Python 3.11.14 and 3.13.11 in existing read-only development environments with the native extension matching based864e7198f. The current main `util.py` is byte-identical to that base; current-main native code has not been rebuilt. Slow tests, S3 tests, remote production services and other operating systems are not validated here. Reproducible commands after preparing the repository's documented development environment (these relative `.venv` examples describe equivalent commands; the local runs use absolute read-only environment paths and fresh task-private working directories): ```sh PYTHONPATH=python/python .venv/bin/python -m pytest python/python/tests/test_util_update_values.py -q -p no:cacheprovider PYTHONPATH=python/python .venv/bin/python -m pytest python/python/tests -m 'not slow and not s3_test' -q -rs -p no:cacheprovider PYTHONPATH=python/python .venv/bin/python -m pytest --doctest-modules python/python/lancedb -q --tb=short (cd python && PYTHONPATH=python ../.venv/bin/pyright --pythonpath ../.venv/bin/python) .venv/bin/ruff check . .venv/bin/ruff format --check . .venv/bin/python -m pre_commit run --files python/python/lancedb/util.py python/python/tests/test_util_update_values.py git diff --checkd864e7198fHEAD ``` Frozen commit `33e74d0ed3d90a20419816a3f1fc15ff038db452` passed all local gates: Python 3.11.14 full suite 1,590 passed / 36 skipped / 68 deselected; Python 3.13.11 full suite 1,587 passed / 37 skipped / 68 deselected. All 66 added SDK cases passed on both runtimes. Python 3.13 doctests: 71 passed / 6 skipped. Pyright: 0 errors / 0 warnings. Ruff, formatting, applicable pre-commit hooks, two-file syntax/import checks and the PR merge-base diff check exited 0. Exact local argv/runtime/wall metadata and raw logs are retained in the acceptance manifest. The follow-up addresses the non-UTC timestamp issue reported in review: an update previously changed the epoch ingested by Arrow (New York +5 hours, Tokyo -9 hours). On the published original head, 4 non-UTC sync/async SDK regressions failed and 12 naive/UTC/NaT controls passed (exit 1; wall 3.713 seconds). Formatting with `timezone="UTC"` emits a Z suffix and preserves the ingested nanosecond instant independently of the destination timezone. This is consistent with the Arrow-aligned epoch convention in merged #3775. The original 50 cases also remain green. Full-suite wall times were 158.619 seconds (3.11) and 163.631 seconds (3.13), both exit 0.
The Multimodal Lakehouse for AI
How to Install ✦ Detailed Documentation ✦ Tutorials and Recipes ✦ Contributors
The ultimate multimodal data platform for AI/ML applications.
LanceDB is designed for fast, scalable, and production-ready vector search. It is built on top of the Lance columnar format. You can store, index, and search over petabytes of multimodal data and vectors with ease. LanceDB is a central location where developers can build, train and analyze their AI workloads.
Demo: Multimodal Search by Keyword, Vector or with SQL
Star LanceDB to get updates!
⭐ Click here ⭐ to see how fast we're growing!
Key Features:
- Fast Vector Search: Search billions of vectors in milliseconds with state-of-the-art indexing.
- Comprehensive Search: Support for vector similarity search, full-text search and SQL.
- Multimodal Support: Store, query and filter vectors, metadata and multimodal data (text, images, videos, point clouds, and more).
- Advanced Features: Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure. GPU support in building vector index.
Products:
- Open Source & Local: 100% open source, runs locally or in your cloud. No vendor lock-in.
- Cloud and Enterprise: Production-scale vector search with no servers to manage. Complete data sovereignty and security.
Ecosystem:
- Columnar Storage: Built on the Lance columnar format for efficient storage and analytics.
- Seamless Integration: Python, Node.js, Rust, and REST APIs for easy integration. Native Python and Javascript/Typescript support.
- Rich Ecosystem: Integrations with LangChain 🦜️🔗, LlamaIndex 🦙, Apache-Arrow, Pandas, Polars, DuckDB and more on the way.
How to Install:
Follow the Quickstart doc to set up LanceDB locally.
API & SDK: We also support Python, Typescript and Rust SDKs
| Interface | Documentation |
|---|---|
| Python SDK | https://lancedb.github.io/lancedb/python/python/ |
| Typescript SDK | https://lancedb.github.io/lancedb/js/globals/ |
| Rust SDK | https://docs.rs/lancedb/latest/lancedb/index.html |
| REST API | https://docs.lancedb.com/api-reference/rest |
Join Us and Contribute
We welcome contributions from everyone! Whether you're a developer, researcher, or just someone who wants to help out.
If you have any suggestions or feature requests, please feel free to open an issue on GitHub or discuss it on our Discord server.
Check out the GitHub Issues if you would like to work on the features that are planned for the future. If you have any suggestions or feature requests, please feel free to open an issue on GitHub.
Contributors
Stay in Touch With Us