Jack Ye
dcfef7c5ab
SQL blob descriptors need pinned source identity to reopen a value after
the query finishes. Adds `open_blob_file(descriptor)` and
`open_blob_files(descriptors)` so Python can read the original blob
incrementally without materializing it in the SQL result.
### Python experience
```python
rows = db.execute_query("""
SELECT f.timestamp, blob_descriptor(v.video) AS video
FROM videos v JOIN frames f ON v.id = f.video_id
""").read_all()
videos = db.open_table("videos")
for row in rows.to_pylist():
if row["video"] is not None:
with videos.open_blob_file(row["video"]) as video:
frame = extract_frame(video, row["timestamp"])
```
The singular API accepts the descriptor dictionary or an Arrow struct
scalar directly and returns a seekable `BlobFile`.
`videos.open_blob_files(rows["video"])` accepts an Arrow array/chunked
array or another iterable, opens handles as iteration advances, and
preserves order, duplicates, and nulls as `None`. Async tables provide
`await videos.open_blob_file(...)` and `async for video in
videos.open_blob_files(...)`.
The iterable API can be used directly with the Arrow result column. Zip
it with the rows to keep each frame timestamp:
```python
for row, video in zip(rows.to_pylist(), videos.open_blob_files(rows["video"])):
if video is not None:
with video:
frame = extract_frame(video, row["timestamp"])
```
Each iteration opens one handle. Null descriptors yield `None`; handles
preserve input order and duplicates, and the `with` block closes each
non-null file.
For an async table:
```python
async for video in async_videos.open_blob_files(rows["video"]):
if video is not None:
with video:
payload = await video.aread()
```
### Execution
The descriptor retains the canonical `kind`, `position`, `size`,
`blob_id`, and `blob_uri` fields and carries a `source` struct with its
dataset URI, version, commit timestamp, branch, column, row reference,
and whether that reference is a physical address. Native opening
resolves that exact snapshot without changing the table handle's
checkout and rejects a descriptor belonging to another table. Remote
handles send authenticated byte-range requests with the captured
version/branch, commit timestamp, and source URI, so an old physical
address is never interpreted against the latest table.
Known-size remote descriptors open without a payload request. External
blobs with an unspecified size use a metadata-only HEAD request. Payload
bytes load only when the file is read; full reads still allocate the
full value. Existing row-ID-based `fetch_blob_files` remains available
when a descriptor is not already present.
Coverage includes native snapshot preservation after overwrite, both row
IDs and addresses, dictionary/Arrow inputs, null/empty values, reordered
and duplicate descriptors, lazy iterable behavior, async iteration, and
remote range pinning for all six storage kinds.
Descriptor reads isolate their pinned snapshot from the live table
handle's freshness state. Both native and remote reads verify the source
commit timestamp to reject a replaced snapshot after table recreation.
LanceDB Documentation
LanceDB docs are available at docs.lancedb.com.
The SDK docs are built and deployed automatically by Github Actions
whenever a commit is pushed to the main branch. So it is possible for the docs to show
unreleased features.
Building the docs
Setup
- Install LanceDB Python. See setup in Python contributing guide.
Run
make developto install the Python package. - Install documentation dependencies. From LanceDB repo root:
pip install -r docs/requirements.txt
Preview the docs
Run these commands from the LanceDB repository root. The subshell changes into
docs to load mkdocs.yml, while leaving your shell in the repository root.
(cd docs && PYTHONPATH=. mkdocs serve)
If you want to just generate the HTML files:
(cd docs && PYTHONPATH=. mkdocs build)
If successful, you should see a docs/site directory in the repository root that
you can verify locally.
Adding examples
To make sure examples are correct, we put examples in test files so they can be run as part of our test suites.
You can see the tests are at:
- Python:
python/python/tests/docs - Typescript:
nodejs/examples/
Checking python examples
cd python
pytest -vv python/tests/docs
Checking typescript examples
The examples depend on @lancedb/lancedb at file:../dist, so the package must be
built before running the tests. This uses pnpm; see the
Typescript contributing guide for the toolchain setup.
pushd nodejs
pnpm install
pnpm build
popd
Then you can run the examples by going to the nodejs/examples directory, which is a
separate pnpm package with its own lockfile:
pushd nodejs/examples
pnpm install
pnpm test
popd
API documentation
Python
The Python API documentation is organized based on the file docs/src/python/python.md.
We manually add entries there so we can control the organization of the reference page.
However, this means any new types must be manually added to the file. No additional
steps are needed to generate the API documentation.
Typescript
The typescript API documentation is generated from the typescript source code using typedoc.
When new APIs are added, you must manually re-run the typedoc command to update the API documentation. The new files should be checked into the repository.
pushd nodejs
# `pnpm docs` would invoke pnpm's built-in `docs` command, not the script.
pnpm run docs
popd