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4 Commits

Author SHA1 Message Date
Gatefixer 05fce57841 Merge origin/main into gatekeeper/fix-3759-1 2026-08-28 01:19:19 +00:00
Gatefixer 43465f06d5 fix(python): support blob lists in dict appends 2026-08-26 23:47:47 +00:00
Gatefixer bc762926ab fix(python): preserve nested extension carriers 2026-08-26 23:21:40 +00:00
Gatefixer 2426f275cd fix(python): accept null extension column batches 2026-08-26 22:55:54 +00:00
60 changed files with 11986 additions and 3156 deletions
+1 -1
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@@ -1,5 +1,5 @@
[tool.bumpversion]
current_version = "0.38.0"
current_version = "0.38.0-beta.12"
parse = """(?x)
(?P<major>0|[1-9]\\d*)\\.
(?P<minor>0|[1-9]\\d*)\\.
-24
View File
@@ -44,27 +44,3 @@ updates:
python-deps:
patterns:
- "*"
# The npm ecosystem covers pnpm lockfiles. There are two separate installs:
# the bindings themselves and the examples, which have their own lockfile.
# As with cargo and pip above, only bump the lockfile — the version ranges
# in package.json are our consumers' constraints, not ours.
- package-ecosystem: npm
directory: /nodejs
schedule:
interval: weekly
versioning-strategy: lockfile-only
groups:
nodejs-deps:
patterns:
- "*"
- package-ecosystem: npm
directory: /nodejs/examples
schedule:
interval: weekly
versioning-strategy: lockfile-only
groups:
nodejs-examples-deps:
patterns:
- "*"
+4 -10
View File
@@ -29,14 +29,12 @@ jobs:
steps:
- uses: actions/setup-node@v6
with:
node-version: "24"
- uses: pnpm/action-setup@v6
with:
version: 11.1.1
node-version: "18"
# These rules are disabled because Github will always ensure there
# is a blank line between the title and the body and Github will
# word wrap the description field to ensure a reasonable max line
# length.
- run: npm install @commitlint/config-conventional
- run: >
echo 'module.exports = {
"rules": {
@@ -45,11 +43,7 @@ jobs:
"body-leading-blank": [0, "always"]
}
}' > .commitlintrc.js
- run: >
pnpm dlx
--package @commitlint/cli@21.2.2
--package @commitlint/config-conventional@21.2.2
commitlint --extends @commitlint/config-conventional --verbose <<< $COMMIT_MSG
- run: npx commitlint --extends @commitlint/config-conventional --verbose <<< $COMMIT_MSG
env:
COMMIT_MSG: >
${{ github.event.pull_request.title }}
@@ -60,7 +54,7 @@ jobs:
with:
script: |
const message = `**ACTION NEEDED**
Lance follows the [Conventional Commits specification](https://www.conventionalcommits.org/en/v1.0.0/) for release automation.
The PR title and description are used as the merge commit message.\
+1 -1
View File
@@ -56,7 +56,7 @@ jobs:
uses: lycheeverse/lychee-action@e7477775783ea5526144ba13e8db5eec57747ce8 # v2.9.0
with:
# Restricted to http(s) on purpose. Much of docs/src is generated
# API reference (the js/ tree comes from `pnpm run docs` in nodejs)
# API reference (the js/ tree comes from `npm run docs` in nodejs)
# and the hand-written pages use mkdocstrings cross-references and
# nav-relative paths that only resolve in the site mkdocs builds,
# not in this checkout, so relative links would be reported as
+3 -1
View File
@@ -55,7 +55,9 @@ jobs:
- name: Set up node
uses: actions/setup-node@v6
with:
node-version: 24
node-version: 20
cache: 'npm'
cache-dependency-path: docs/package-lock.json
- name: Install node dependencies
working-directory: nodejs
run: |
+13 -11
View File
@@ -47,8 +47,9 @@ jobs:
version: 11.1.1
- uses: actions/setup-node@v6
with:
# Build on a supported LTS; the matrix job below covers every
# Node version the library claims to support.
# pnpm 11 requires Node >= 22.13; use 24 since 22 hits EOL
# in October. The library itself still supports Node >= 18
# (see test matrix below).
node-version: 24
cache: 'pnpm'
cache-dependency-path: nodejs/pnpm-lock.yaml
@@ -83,7 +84,7 @@ jobs:
timeout-minutes: 30
strategy:
matrix:
node-version: [ "22", "24", "26" ]
node-version: [ "18", "20" ]
runs-on: "ubuntu-22.04"
defaults:
run:
@@ -100,9 +101,9 @@ jobs:
- uses: actions/setup-node@v6
name: Setup Node.js 24 for build
with:
# Build and install once on a fixed version so the generated docs
# are identical across matrix legs; the tests below then run on each
# supported Node version.
# pnpm 11 requires Node >= 22.13; use 24 since 22 hits EOL
# in October. Build/install runs on Node 24; tests run on the
# matrix version below using direct jest invocation.
node-version: 24
cache: 'pnpm'
cache-dependency-path: nodejs/pnpm-lock.yaml
@@ -151,9 +152,9 @@ jobs:
S3_TEST: "1"
# Newer @smithy/core uses dynamic ESM imports.
NODE_OPTIONS: "--experimental-vm-modules"
# Invoke the installed jest binary directly; the pnpm shim is set up
# against the build-phase Node, not the version selected above.
run: node_modules/.bin/jest --verbose
# Invoke jest directly because pnpm 11 itself requires Node 22+
# while the matrix tests on older Node versions.
run: npx jest --verbose
- name: Test examples
working-directory: ./
env:
@@ -163,7 +164,7 @@ jobs:
run: |
python ci/mock_openai.py &
cd nodejs/examples
node_modules/.bin/jest --testEnvironment jest-environment-node-single-context --verbose
npx jest --testEnvironment jest-environment-node-single-context --verbose
macos:
timeout-minutes: 30
# macos-15 ships a newer linker; the older macos-14 linker fails to insert
@@ -184,7 +185,8 @@ jobs:
version: 11.1.1
- uses: actions/setup-node@v6
with:
# pnpm 11 requires Node >= 22.13.
# pnpm 11 requires Node >= 22.13; use 24 since 22 hits EOL
# in October.
node-version: 24
cache: 'pnpm'
cache-dependency-path: nodejs/pnpm-lock.yaml
+8 -7
View File
@@ -168,7 +168,8 @@ jobs:
- name: Setup node
uses: actions/setup-node@v6
with:
# pnpm 11 requires Node >= 22.13.
# pnpm 11 requires Node >= 22.13; use 24 since 22 hits EOL
# in October.
node-version: 24
cache: pnpm
cache-dependency-path: nodejs/pnpm-lock.yaml
@@ -250,7 +251,7 @@ jobs:
run: |
set -e
${{ matrix.settings.pre_build }}
node_modules/.bin/napi build --platform --release \
npx napi build --platform --release \
--features ${{ matrix.settings.features }} \
--target ${{ matrix.settings.target }} \
--dts ../lancedb/native.d.ts \
@@ -270,7 +271,7 @@ jobs:
- name: Build
run: |
${{ matrix.settings.pre_build }}
node_modules/.bin/napi build --platform --release \
npx napi build --platform --release \
--features ${{ matrix.settings.features }} \
--target ${{ matrix.settings.target }} \
--dts ../lancedb/native.d.ts \
@@ -338,7 +339,7 @@ jobs:
- target: aarch64-unknown-linux-gnu
host: ubuntu-2404-8x-arm64
node:
- '22'
- '20'
runs-on: ${{ matrix.settings.host }}
defaults:
run:
@@ -384,9 +385,9 @@ jobs:
- name: Move built files
run: cp dist/native.d.ts dist/native.js dist/*.node lancedb/
- name: Test bindings
# Invoke the installed jest binary directly; the pnpm shim is set up
# against the install-phase Node, not the version selected above.
run: node_modules/.bin/jest --verbose
# Invoke jest directly because pnpm 11 itself requires Node 22+
# while the matrix tests on older Node versions.
run: npx jest --verbose
publish:
name: Publish
runs-on: ubuntu-latest
@@ -0,0 +1,22 @@
name: Update package-lock.json
on:
workflow_dispatch:
permissions:
contents: read
jobs:
publish:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v6
with:
ref: main
persist-credentials: false
fetch-depth: 0
lfs: true
- uses: ./.github/workflows/update_package_lock
with:
github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
@@ -0,0 +1,22 @@
name: Update NodeJs package-lock.json
on:
workflow_dispatch:
permissions:
contents: read
jobs:
publish:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v6
with:
ref: main
persist-credentials: false
fetch-depth: 0
lfs: true
- uses: ./.github/workflows/update_package_lock_nodejs
with:
github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
+1 -4
View File
@@ -20,10 +20,7 @@ repos:
hooks:
- id: local-biome-check
name: biome check
# Use the biome from nodejs/package.json rather than a separately
# pinned one: the two drifted apart and disagreed on formatting, so
# this hook rejected code that `pnpm lint` accepted.
entry: nodejs/node_modules/.bin/biome check --config-path nodejs/biome.json nodejs/
entry: npx @biomejs/biome@1.8.3 check --config-path nodejs/biome.json nodejs/
language: system
types: [text]
files: "nodejs/.*"
+3 -3
View File
@@ -38,7 +38,7 @@ Before committing changes, run formatting for every language you touched. At min
* Rust changes: run `cargo fmt --all`.
* Python changes: run `ruff format .` and `ruff check .` from the repository root,
and run targeted tests through `cd python && uv run ...`.
* TypeScript changes: run the relevant `pnpm` lint, format, build, and docs commands in `nodejs`.
* TypeScript changes: run the relevant `npm`/`pnpm` lint, format, build, and docs commands in `nodejs`.
Before creating a PR, the exact value passed to `gh pr create --title` must follow
Conventional Commits, such as `fix: support nested field paths in native index creation`
@@ -101,12 +101,12 @@ Python bindings changes:
TypeScript bindings changes:
1. Add napi-rs method binding on `Table` in `nodejs/src/table.rs`.
2. Run `pnpm build` to generate TypeScript definitions.
2. Run `npm run build` to generate TypeScript definitions.
3. Add typescript method on abstract class `Table` in `nodejs/src/table.ts`.
4. Add concrete method on `LocalTable` class in `nodejs/src/native_table.ts`.
* Note: despite the name, this class is also used for remote tables.
5. Add test in `nodejs/__test__/table.test.ts`.
6. Run `pnpm run docs` to generate TypeScript documentation.
6. Run `npm run docs` to generate TypeScript documentation.
## Python API reference
Generated
+71 -73
View File
@@ -535,9 +535,9 @@ dependencies = [
[[package]]
name = "async-trait"
version = "0.1.92"
version = "0.1.91"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "82f6aeea286b8eb4dd3431a1be1b59d290ace00f5bfd8e2a159bc2a05e2c1667"
checksum = "ae36dc4177970ef04fde5178d3e2429882def40e57a451f919c098f72baa6cec"
dependencies = [
"proc-macro2",
"quote",
@@ -1443,9 +1443,9 @@ checksum = "175812e0be2bccb6abe50bb8d566126198344f707e304f45c648fd8f2cc0365e"
[[package]]
name = "bytemuck"
version = "1.25.2"
version = "1.25.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "95832e849adfb21180ccb6826a99da14e5d266ae5c2e668e1602cf234f153797"
checksum = "c8efb64bd706a16a1bdde310ae86b351e4d21550d98d056f22f8a7f7a2183fec"
dependencies = [
"bytemuck_derive",
]
@@ -1597,9 +1597,9 @@ checksum = "613afe47fcd5fac7ccf1db93babcb082c5994d996f20b8b159f2ad1658eb5724"
[[package]]
name = "chacha20"
version = "0.10.2"
version = "0.10.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "65c35e4b699c7e15ccbe7ee35c005e4fc0a278d22238a2857e6ce2dadeda1b06"
checksum = "6f8d983286843e49675a4b7a2d174efe136dc93a18d69130dd18198a6c167601"
dependencies = [
"cfg-if 1.0.4",
"cpufeatures 0.3.0",
@@ -3455,8 +3455,8 @@ checksum = "42703706b716c37f96a77aea830392ad231f44c9e9a67872fa5548707e11b11c"
[[package]]
name = "fsst"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"rand 0.9.5",
@@ -4815,8 +4815,8 @@ checksum = "e037a2e1d8d5fdbd49b16a4ea09d5d6401c1f29eca5ff29d03d3824dba16256a"
[[package]]
name = "lance"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arc-swap",
"arrow",
@@ -4888,8 +4888,8 @@ dependencies = [
[[package]]
name = "lance-arrow"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"arrow-buffer",
@@ -4911,7 +4911,7 @@ dependencies = [
[[package]]
name = "lance-arrow-scalar"
version = "58.0.0"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"arrow-buffer",
@@ -4925,7 +4925,7 @@ dependencies = [
[[package]]
name = "lance-arrow-stats"
version = "58.0.0"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"arrow-schema",
@@ -4934,8 +4934,8 @@ dependencies = [
[[package]]
name = "lance-bitpacking"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrayref",
"crunchy",
@@ -4945,8 +4945,8 @@ dependencies = [
[[package]]
name = "lance-core"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"arrow-buffer",
@@ -4983,8 +4983,8 @@ dependencies = [
[[package]]
name = "lance-datafusion"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow",
"arrow-array",
@@ -5013,8 +5013,8 @@ dependencies = [
[[package]]
name = "lance-datagen"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow",
"arrow-array",
@@ -5031,8 +5031,8 @@ dependencies = [
[[package]]
name = "lance-derive"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"proc-macro2",
"quote",
@@ -5041,8 +5041,8 @@ dependencies = [
[[package]]
name = "lance-encoding"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-arith",
"arrow-array",
@@ -5075,8 +5075,8 @@ dependencies = [
[[package]]
name = "lance-file"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-arith",
"arrow-array",
@@ -5107,8 +5107,8 @@ dependencies = [
[[package]]
name = "lance-index"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arc-swap",
"arrow",
@@ -5172,8 +5172,8 @@ dependencies = [
[[package]]
name = "lance-index-core"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"arrow-schema",
@@ -5195,8 +5195,8 @@ dependencies = [
[[package]]
name = "lance-io"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow",
"arrow-array",
@@ -5236,8 +5236,8 @@ dependencies = [
[[package]]
name = "lance-linalg"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"arrow-schema",
@@ -5251,8 +5251,8 @@ dependencies = [
[[package]]
name = "lance-namespace"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow",
"async-trait",
@@ -5264,8 +5264,8 @@ dependencies = [
[[package]]
name = "lance-namespace-impls"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow",
"arrow-ipc",
@@ -5318,8 +5318,8 @@ dependencies = [
[[package]]
name = "lance-select"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"arrow-buffer",
@@ -5333,8 +5333,8 @@ dependencies = [
[[package]]
name = "lance-table"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow",
"arrow-array",
@@ -5374,8 +5374,8 @@ dependencies = [
[[package]]
name = "lance-testing"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"arrow-array",
"arrow-schema",
@@ -5388,8 +5388,8 @@ dependencies = [
[[package]]
name = "lance-tokenizer"
version = "12.0.0-beta.5"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
version = "12.0.0-beta.2"
source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
dependencies = [
"frostem",
"icu_segmenter",
@@ -5402,7 +5402,7 @@ dependencies = [
[[package]]
name = "lancedb"
version = "0.38.0"
version = "0.38.0-beta.12"
dependencies = [
"ahash",
"anyhow",
@@ -5490,7 +5490,7 @@ dependencies = [
[[package]]
name = "lancedb-nodejs"
version = "0.38.0"
version = "0.38.0-beta.12"
dependencies = [
"arrow-array",
"arrow-buffer",
@@ -5515,7 +5515,7 @@ dependencies = [
[[package]]
name = "lancedb-python"
version = "0.38.0"
version = "0.38.0-beta.12"
dependencies = [
"arrow",
"async-trait",
@@ -5748,9 +5748,9 @@ dependencies = [
[[package]]
name = "log"
version = "0.4.34"
version = "0.4.33"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "f9f8bd3e56ce4dfc153cf470fffbfa98c7620958b312ca5c3a4b8d5181fd13c6"
checksum = "0ceec5bc11778974d1bcb055b18002eba7f4b3518b6a0081b3af5f21666da9ad"
[[package]]
name = "loom"
@@ -6001,9 +6001,9 @@ dependencies = [
[[package]]
name = "moka"
version = "0.12.16"
version = "0.12.15"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "4293f18e7567a1caf3c584855554377025c65e0aa445344d04171f5ad63d19b9"
checksum = "957228ad12042ee839f93c8f257b62b4c0ab5eaae1d4fa60de53b27c9d7c5046"
dependencies = [
"async-lock",
"crossbeam-channel",
@@ -6097,15 +6097,14 @@ dependencies = [
[[package]]
name = "napi"
version = "3.12.2"
version = "3.11.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "58c5f4d5375213fdb7be2655e152386e82f026f9a5ba36a75556e11359aafe09"
checksum = "de33522036981030a75c231829566bc63414e08101a6f5ff4ac6cef19c8e0941"
dependencies = [
"bitflags 2.11.1",
"chrono",
"ctor 1.0.12",
"futures",
"libc",
"napi-build",
"napi-sys",
"nohash-hasher",
@@ -6117,15 +6116,15 @@ dependencies = [
[[package]]
name = "napi-build"
version = "2.4.1"
version = "2.4.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "60fdf9b392c50e7c4170fa633bd909490ed7835cea4c046776d1a4dd8d2ae0ab"
checksum = "5282704fbe8d49b0cf8b08e3f33233416a528658f205c7e5ace63b582de0b11c"
[[package]]
name = "napi-derive"
version = "3.6.3"
version = "3.6.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "0fa55ea69990c90b888e9e77044410e304ce7f35de599dc6d0b5c1923d2e59af"
checksum = "4d5c9c02556ea6dc99dffd36c1ce60141411657438501a125b675776d011ce92"
dependencies = [
"convert_case",
"ctor 1.0.12",
@@ -6137,9 +6136,9 @@ dependencies = [
[[package]]
name = "napi-derive-backend"
version = "6.1.2"
version = "6.1.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "df4056ac7c18e4438ccf0edaed4340ca0d269278c8ec19284f7b23cb039fd0ae"
checksum = "d60b5d773ad46c698c8cc2cd9fde0b283d39cbb7f71c04bee633c7bdba4423bd"
dependencies = [
"convert_case",
"proc-macro2",
@@ -8602,9 +8601,9 @@ dependencies = [
[[package]]
name = "roaring"
version = "0.11.5"
version = "0.11.4"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "18bd8a37d17a58532776dcdf6041ce64929adca78e8489d5cacbafe99229d3e1"
checksum = "1dedc5658c6ecb3bdb5ef5f3295bb9253f42dcf3fd1402c03f6b1f7659c3c4a9"
dependencies = [
"bytemuck",
"byteorder",
@@ -9064,9 +9063,9 @@ dependencies = [
[[package]]
name = "serde_with"
version = "3.22.0"
version = "3.21.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "ee78f1fbe43ac4a0e47aadb3dbd357b69eb0d3793e948624cd03dd2750ab1c0a"
checksum = "76a5c54c7310e7b8b9577c286d7e399ddd876c3e12b3ed917a8aabc4b96e9e8c"
dependencies = [
"base64 0.22.1",
"bs58",
@@ -9074,7 +9073,6 @@ dependencies = [
"hex",
"indexmap 1.9.3",
"indexmap 2.14.0",
"jiff",
"schemars 0.9.0",
"schemars 1.2.1",
"serde_core",
@@ -9085,9 +9083,9 @@ dependencies = [
[[package]]
name = "serde_with_macros"
version = "3.22.0"
version = "3.21.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "8705578779c2b6bd90d84d66eb2e206b708b1a4d7b9f17641b293545bf1c7e46"
checksum = "84d57bc0c8b9a17920c178daa6bb924850d54a9c97ab45194bb8c17ad66bb660"
dependencies = [
"darling 0.23.0",
"proc-macro2",
@@ -10454,9 +10452,9 @@ checksum = "06abde3611657adf66d383f00b093d7faecc7fa57071cce2578660c9f1010821"
[[package]]
name = "uuid"
version = "1.26.0"
version = "1.24.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "b5772d71c9be8a8a6ac2117d949c5b224c1b72241bb611d9a3012edcf8af7812"
checksum = "bf3923a6f5c4c6382e0b653c4117f48d631ea17f38ed86e2a828e6f7412f5239"
dependencies = [
"getrandom 0.4.2",
"js-sys",
+14 -14
View File
@@ -13,20 +13,20 @@ categories = ["database-implementations"]
rust-version = "1.91.0"
[workspace.dependencies]
lance = { "version" = "=12.0.0-beta.5", default-features = false, "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-core = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-datagen = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-file = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-io = { "version" = "=12.0.0-beta.5", default-features = false, "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-index = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-linalg = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace-impls = { "version" = "=12.0.0-beta.5", default-features = false, "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-table = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-testing = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-datafusion = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-encoding = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-arrow = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance = { "version" = "=12.0.0-beta.2", default-features = false, "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-core = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-datagen = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-file = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-io = { "version" = "=12.0.0-beta.2", default-features = false, "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-index = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-linalg = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace-impls = { "version" = "=12.0.0-beta.2", default-features = false, "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-table = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-testing = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-datafusion = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-encoding = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lance-arrow = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
lancedb = { path = "rust/lancedb", default-features = false }
ahash = "0.8"
# Note that this one does not include pyarrow
+1 -1
View File
@@ -5,5 +5,5 @@ licenses:
cd python && cargo about generate ../about.hbs -o RUST_THIRD_PARTY_LICENSES.html -c ../about.toml
cd python && uv sync --all-extras && uv tool run pip-licenses --python .venv/bin/python --format=markdown --with-urls --output-file=PYTHON_THIRD_PARTY_LICENSES.md
cd nodejs && cargo about generate ../about.hbs -o RUST_THIRD_PARTY_LICENSES.html -c ../about.toml
cd nodejs && pnpm dlx license-checker@25 --markdown --out NODEJS_THIRD_PARTY_LICENSES.md
cd nodejs && npx license-checker --markdown --out NODEJS_THIRD_PARTY_LICENSES.md
cd java && ./mvnw license:aggregate-add-third-party -q
+6 -2
View File
@@ -12,12 +12,16 @@ done
# This updates the lockfile without building
cargo metadata --quiet > /dev/null
pushd nodejs || exit 1
npm install --package-lock-only --silent
popd
if git diff --quiet --exit-code; then
echo "No lockfile changes to commit; skipping amend."
elif $AMEND; then
git add Cargo.lock
git add Cargo.lock nodejs/package-lock.json
git commit --amend --no-edit
else
git add Cargo.lock
git add Cargo.lock nodejs/package-lock.json
git commit -m "Update lockfiles"
fi
+11 -1
View File
@@ -131,13 +131,18 @@ allow = [
"BSD-3-Clause",
"ISC",
"Unicode-3.0",
"Unicode-DFS-2016",
"Zlib",
"CC0-1.0",
"MPL-2.0",
"BSL-1.0",
"OpenSSL",
# 0BSD ("BSD Zero Clause") is effectively public domain — no attribution
# required. Pulled in by `mock_instant`.
"0BSD",
# bzip2-1.0.6 is the permissive upstream bzip2 license (BSD-like). Pulled
# in by `libbz2-rs-sys`, the pure-Rust bzip2 implementation.
"bzip2-1.0.6",
# CDLA-Permissive-2.0 is a permissive data license used by `webpki-roots`
# for the Mozilla CA root bundle. Data-only, distribution-compatible.
"CDLA-Permissive-2.0",
@@ -145,7 +150,12 @@ allow = [
confidence-threshold = 0.8
# Per-crate license exceptions: allow a license for a specific crate only,
# rather than globally via the `allow` list above.
exceptions = []
exceptions = [
# CDDL-1.0 (copyleft) is pulled in only as a dev/profiling dependency via
# `inferno` -> `pprof` -> `lance-testing`; it is a test dependency that we
# do not distribute, so scope the allowance to `inferno` alone.
{ allow = ["CDDL-1.0"], crate = "inferno" },
]
# Crates whose license cannot be determined from Cargo metadata but whose
# license we've manually confirmed from upstream. Keep this list minimal.
[[licenses.clarify]]
+8 -11
View File
@@ -47,24 +47,22 @@ 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](../nodejs/CONTRIBUTING.md) for the toolchain setup.
The `@lancedb/lancedb` package must be built before running the tests:
```shell
pushd nodejs
pnpm install
pnpm build
npm ci
npm run 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:
Then you can run the examples by going to the `nodejs/examples` directory and
running the tests like a normal npm package:
```shell
pushd nodejs/examples
pnpm install
pnpm test
npm ci
npm test
popd
```
@@ -86,7 +84,6 @@ The new files should be checked into the repository.
```shell
pushd nodejs
# `pnpm docs` would invoke pnpm's built-in `docs` command, not the script.
pnpm run docs
npm run docs
popd
```
+135
View File
@@ -0,0 +1,135 @@
{
"name": "lancedb-docs-test",
"version": "1.0.0",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "lancedb-docs-test",
"version": "1.0.0",
"license": "Apache 2",
"dependencies": {
"apache-arrow": "file:../node/node_modules/apache-arrow",
"vectordb": "file:../node"
},
"devDependencies": {
"@types/node": "^20.11.8",
"typescript": "^5.3.3"
}
},
"../node": {
"name": "vectordb",
"version": "0.21.2-beta.0",
"cpu": [
"x64",
"arm64"
],
"license": "Apache-2.0",
"os": [
"darwin",
"linux",
"win32"
],
"dependencies": {
"@neon-rs/load": "^0.0.74",
"axios": "^1.4.0"
},
"devDependencies": {
"@neon-rs/cli": "^0.0.160",
"@types/chai": "^4.3.4",
"@types/chai-as-promised": "^7.1.5",
"@types/mocha": "^10.0.1",
"@types/node": "^18.16.2",
"@types/sinon": "^10.0.15",
"@types/temp": "^0.9.1",
"@types/uuid": "^9.0.3",
"@typescript-eslint/eslint-plugin": "^5.59.1",
"apache-arrow-old": "npm:apache-arrow@13.0.0",
"cargo-cp-artifact": "^0.1",
"chai": "^4.3.7",
"chai-as-promised": "^7.1.1",
"eslint": "^8.39.0",
"eslint-config-standard-with-typescript": "^34.0.1",
"eslint-plugin-import": "^2.26.0",
"eslint-plugin-n": "^15.7.0",
"eslint-plugin-promise": "^6.1.1",
"mocha": "^10.2.0",
"openai": "^4.24.1",
"sinon": "^15.1.0",
"temp": "^0.9.4",
"ts-node": "^10.9.1",
"ts-node-dev": "^2.0.0",
"typedoc": "^0.24.7",
"typedoc-plugin-markdown": "^3.15.3",
"typescript": "^5.1.0",
"uuid": "^9.0.0"
},
"optionalDependencies": {
"@lancedb/vectordb-darwin-arm64": "0.21.2-beta.0",
"@lancedb/vectordb-darwin-x64": "0.21.2-beta.0",
"@lancedb/vectordb-linux-arm64-gnu": "0.21.2-beta.0",
"@lancedb/vectordb-linux-x64-gnu": "0.21.2-beta.0",
"@lancedb/vectordb-win32-x64-msvc": "0.21.2-beta.0"
},
"peerDependencies": {
"@apache-arrow/ts": "^14.0.2",
"apache-arrow": "^14.0.2"
}
},
"../node/node_modules/apache-arrow": {
"version": "14.0.2",
"license": "Apache-2.0",
"dependencies": {
"@types/command-line-args": "5.2.0",
"@types/command-line-usage": "5.0.2",
"@types/node": "20.3.0",
"@types/pad-left": "2.1.1",
"command-line-args": "5.2.1",
"command-line-usage": "7.0.1",
"flatbuffers": "23.5.26",
"json-bignum": "^0.0.3",
"pad-left": "^2.1.0",
"tslib": "^2.5.3"
},
"bin": {
"arrow2csv": "bin/arrow2csv.js"
}
},
"node_modules/@types/node": {
"version": "20.11.8",
"resolved": "https://registry.npmjs.org/@types/node/-/node-20.11.8.tgz",
"integrity": "sha512-i7omyekpPTNdv4Jb/Rgqg0RU8YqLcNsI12quKSDkRXNfx7Wxdm6HhK1awT3xTgEkgxPn3bvnSpiEAc7a7Lpyow==",
"dev": true,
"dependencies": {
"undici-types": "~5.26.4"
}
},
"node_modules/apache-arrow": {
"resolved": "../node/node_modules/apache-arrow",
"link": true
},
"node_modules/typescript": {
"version": "5.3.3",
"resolved": "https://registry.npmjs.org/typescript/-/typescript-5.3.3.tgz",
"integrity": "sha512-pXWcraxM0uxAS+tN0AG/BF2TyqmHO014Z070UsJ+pFvYuRSq8KH8DmWpnbXe0pEPDHXZV3FcAbJkijJ5oNEnWw==",
"dev": true,
"bin": {
"tsc": "bin/tsc",
"tsserver": "bin/tsserver"
},
"engines": {
"node": ">=14.17"
}
},
"node_modules/undici-types": {
"version": "5.26.5",
"resolved": "https://registry.npmjs.org/undici-types/-/undici-types-5.26.5.tgz",
"integrity": "sha512-JlCMO+ehdEIKqlFxk6IfVoAUVmgz7cU7zD/h9XZ0qzeosSHmUJVOzSQvvYSYWXkFXC+IfLKSIffhv0sVZup6pA==",
"dev": true
},
"node_modules/vectordb": {
"resolved": "../node",
"link": true
}
}
}
+20
View File
@@ -0,0 +1,20 @@
{
"name": "lancedb-docs-test",
"version": "1.0.0",
"description": "auto-generated tests from doc",
"author": "dev@lancedb.com",
"license": "Apache 2",
"dependencies": {
"apache-arrow": "file:../node/node_modules/apache-arrow",
"vectordb": "file:../node"
},
"scripts": {
"build": "tsc -b && cd ../node && npm run build-release",
"example": "npm run build && node",
"test": "npm run build && ls dist/*.js | xargs -n 1 node"
},
"devDependencies": {
"@types/node": "^20.11.8",
"typescript": "^5.3.3"
}
}
+1 -1
View File
@@ -14,7 +14,7 @@ Add the following dependency to your `pom.xml`:
<dependency>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-core</artifactId>
<version>0.38.0</version>
<version>0.38.0-beta.12</version>
</dependency>
```
+17
View File
@@ -0,0 +1,17 @@
{
"include": [
"src/*.ts",
],
"compilerOptions": {
"target": "es2022",
"module": "nodenext",
"declaration": true,
"outDir": "./dist",
"strict": true,
"allowJs": true,
"resolveJsonModule": true,
},
"exclude": [
"./dist/*",
]
}
+1 -1
View File
@@ -8,7 +8,7 @@
<parent>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.38.0-final.0</version>
<version>0.38.0-beta.12</version>
<relativePath>../pom.xml</relativePath>
</parent>
+2 -2
View File
@@ -6,7 +6,7 @@
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.38.0-final.0</version>
<version>0.38.0-beta.12</version>
<packaging>pom</packaging>
<name>${project.artifactId}</name>
<description>LanceDB Java SDK Parent POM</description>
@@ -28,7 +28,7 @@
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<arrow.version>15.0.0</arrow.version>
<lance-core.version>12.0.0-beta.5</lance-core.version>
<lance-core.version>12.0.0-beta.2</lance-core.version>
<spotless.skip>false</spotless.skip>
<spotless.version>2.30.0</spotless.version>
<spotless.java.googlejavaformat.version>1.7</spotless.java.googlejavaformat.version>
+1 -1
View File
@@ -1,7 +1,7 @@
[package]
name = "lancedb-nodejs"
edition.workspace = true
version = "0.38.0"
version = "0.38.0-beta.12"
publish = false
license.workspace = true
description.workspace = true
+2 -2
View File
@@ -5,8 +5,8 @@ import packageJson = require("../package.json");
describe("package metadata", () => {
it("requires Node.js type declarations compatible with the runtime", () => {
expect(packageJson.engines.node).toBe(">= 22");
expect(packageJson.peerDependencies["@types/node"]).toBe(">=22");
expect(packageJson.engines.node).toBe(">= 18");
expect(packageJson.peerDependencies["@types/node"]).toBe(">=18");
expect(packageJson.peerDependenciesMeta["@types/node"]).toEqual({
optional: true,
});
+2 -9
View File
@@ -3,7 +3,6 @@
import * as http from "http";
import { RequestListener } from "http";
import packageJson = require("../package.json");
import {
ClientConfig,
Connection,
@@ -71,13 +70,7 @@ async function withMockDatabase(
try {
await callback(db);
} finally {
// `close()` alone leaves the port bound until keep-alive sockets drain, so
// a single failing test would cascade into EADDRINUSE for every test after
// it. Destroy the connections and wait for the port to actually be free.
await new Promise<void>((resolve) => {
server.closeAllConnections();
server.close(() => resolve());
});
server.close();
}
}
@@ -138,7 +131,7 @@ describe("remote connection", () => {
(req, res) => {
expect(req.headers["x-api-key"]).toEqual("fake");
expect(req.headers["user-agent"]).toEqual(
`LanceDB-Node-Client/${packageJson.version}`,
`LanceDB-Node-Client/${process.env.npm_package_version}`,
);
const body = JSON.stringify({ tables: [] });
+1 -2
View File
@@ -8,8 +8,7 @@
"//1": "--experimental-vm-modules is needed to run jest with sentence-transformers",
"//2": "--testEnvironment is needed to run jest with sentence-transformers",
"//3": "See: https://github.com/huggingface/transformers.js/issues/57",
"//4": "jest is invoked by its JS entry, not node_modules/.bin/jest: under pnpm that path is a shell shim, which `node` cannot execute",
"test": "node --experimental-vm-modules node_modules/jest/bin/jest.js --testEnvironment jest-environment-node-single-context --verbose",
"test": "node --experimental-vm-modules node_modules/.bin/jest --testEnvironment jest-environment-node-single-context --verbose",
"lint": "biome check *.ts && biome format *.ts",
"lint-ci": "biome ci .",
"lint-fix": "biome check --write *.ts && pnpm format",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-darwin-arm64",
"version": "0.38.0",
"version": "0.38.0-beta.12",
"os": ["darwin"],
"cpu": ["arm64"],
"main": "lancedb.darwin-arm64.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-arm64-gnu",
"version": "0.38.0",
"version": "0.38.0-beta.12",
"os": ["linux"],
"cpu": ["arm64"],
"main": "lancedb.linux-arm64-gnu.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-arm64-musl",
"version": "0.38.0",
"version": "0.38.0-beta.12",
"os": ["linux"],
"cpu": ["arm64"],
"main": "lancedb.linux-arm64-musl.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-x64-gnu",
"version": "0.38.0",
"version": "0.38.0-beta.12",
"os": ["linux"],
"cpu": ["x64"],
"main": "lancedb.linux-x64-gnu.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-x64-musl",
"version": "0.38.0",
"version": "0.38.0-beta.12",
"os": ["linux"],
"cpu": ["x64"],
"main": "lancedb.linux-x64-musl.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-win32-arm64-msvc",
"version": "0.38.0",
"version": "0.38.0-beta.12",
"os": [
"win32"
],
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-win32-x64-msvc",
"version": "0.38.0",
"version": "0.38.0-beta.12",
"os": ["win32"],
"cpu": ["x64"],
"main": "lancedb.win32-x64-msvc.node",
+11106
View File
File diff suppressed because it is too large Load Diff
+3 -3
View File
@@ -11,7 +11,7 @@
"ann"
],
"private": false,
"version": "0.38.0",
"version": "0.38.0-beta.12",
"main": "dist/index.js",
"exports": {
".": "./dist/index.js",
@@ -67,7 +67,7 @@
"timeout": "3m"
},
"engines": {
"node": ">= 22"
"node": ">= 18"
},
"packageManager": "pnpm@11.1.1",
"cpu": ["x64", "arm64"],
@@ -101,7 +101,7 @@
"openai": "4.29.2"
},
"peerDependencies": {
"@types/node": ">=22",
"@types/node": ">=18",
"apache-arrow": ">=15.0.0 <=18.1.0"
},
"peerDependenciesMeta": {
+1 -5
View File
@@ -664,11 +664,7 @@ impl JsFullTextQuery {
}
fn parse_fts_query(query: Object) -> napi::Result<FullTextSearchQuery> {
// `&JsFullTextQuery` recovers a native class reference through napi's borrow-tracked
// path, which is only usable from generated `#[napi]` argument conversion. This is a
// manual lookup on a nested `Object` property instead, so use `ClassInstance`, which
// unwraps the class without requiring a borrow scope.
if let Ok(Some(query)) = query.get::<ClassInstance<JsFullTextQuery>>("query") {
if let Ok(Some(query)) = query.get::<&JsFullTextQuery>("query") {
Ok(FullTextSearchQuery::new_query(query.inner.clone()))
} else if let Ok(Some(query_text)) = query.get::<String>("query") {
let mut query_text = query_text;
+1 -1
View File
@@ -1,6 +1,6 @@
[package]
name = "lancedb-python"
version = "0.38.0"
version = "0.38.0-beta.12"
publish = false
edition.workspace = true
description = "Python bindings for LanceDB"
-1
View File
@@ -150,7 +150,6 @@ class Connection(object):
def job(self, job_id: str) -> Job: ...
async def create_function_async(self, request_json: str) -> Job: ...
async def get_function(self, name: str, version: str) -> str: ...
async def drop_function(self, name: str, version: str) -> bool: ...
async def list_jobs(self) -> List[JobInfo]: ...
async def get_job(self, job_id: str) -> Optional[JobDescription]: ...
async def cancel_job(self, job_id: str) -> bool: ...
-18
View File
@@ -712,16 +712,6 @@ class DBConnection(EnforceOverrides):
"Function catalog operations are not supported for this connection type"
)
def drop_function(self, name: str, *, version: str) -> bool:
"""Drop one exact immutable Function version from the remote catalog.
Returns True when the version changed to Dropped and False for an
idempotent replay. Local connections raise NotImplementedError.
"""
raise NotImplementedError(
"Function catalog operations are not supported for this connection type"
)
def job(self, job_id: str) -> Job:
"""A [Job][lancedb.job.Job] handle for a server-side job by id.
@@ -1423,10 +1413,6 @@ class LanceDBConnection(DBConnection):
def get_function(self, name: str, *, version: str) -> FunctionVersion:
return LOOP.run(self._conn.get_function(name, version=version))
@override
def drop_function(self, name: str, *, version: str) -> bool:
return LOOP.run(self._conn.drop_function(name, version=version))
@override
def list_jobs(self) -> List[JobInfo]:
"""List server-side jobs across the database's tables."""
@@ -2257,10 +2243,6 @@ class AsyncConnection(object):
"""Open one exact immutable Function version from the remote catalog."""
return FunctionVersion.from_json(await self._inner.get_function(name, version))
async def drop_function(self, name: str, *, version: str) -> bool:
"""Drop one exact immutable Function version from the remote catalog."""
return await self._inner.drop_function(name, version)
async def list_jobs(self) -> List[JobInfo]:
"""List server-side jobs across the database's tables."""
return await self._inner.list_jobs()
+20 -327
View File
@@ -49,25 +49,11 @@ from pydantic import (
model_validator,
)
from .schema import is_blob_v2_field as _is_blob_v2_field
_Int32 = conint(strict=True, ge=-(2**31), le=2**31 - 1)
_UInt32 = conint(strict=True, ge=0, le=2**32 - 1)
_UInt64 = conint(strict=True, ge=0, le=2**64 - 1)
def _validate_gpu_wire_marker(value: Any) -> bool:
if value is not True:
raise ValueError("runtime.gpu must be true")
return True
def _normalize_gpu_marker(value: bool) -> Optional[bool]:
if not isinstance(value, bool):
raise ValueError("gpu must be a boolean")
return True if value else None
class _FrozenDict(dict):
def _immutable(self, *args, **kwargs):
raise TypeError("remote canonical values are immutable")
@@ -253,23 +239,6 @@ class PythonRuntimeSpec(_RemoteValue):
python_version: Optional[str] = None
environment: Optional[PythonEnvironmentSpec] = None
env: Optional[Mapping[str, str]] = None
gpu: Optional[bool] = None
@model_validator(mode="before")
@classmethod
def _discard_unknown_runtime_payload(cls, value):
if isinstance(value, Mapping):
kind = value.get("kind")
if isinstance(kind, str) and kind not in {"python", "python_v2"}:
return {"kind": kind}
return value
@field_validator("gpu", mode="before")
@classmethod
def _validate_gpu_marker(cls, value):
if value is None:
return None
return _validate_gpu_wire_marker(value)
@model_validator(mode="after")
def _validate_runtime_kind(self):
@@ -278,28 +247,18 @@ class PythonRuntimeSpec(_RemoteValue):
raise ValueError("python runtime requires python_version")
if self.environment is None:
raise ValueError("python runtime requires environment")
if self.gpu is not None:
raise ValueError("python runtime with gpu requires kind='python_v2'")
elif self.kind == "python_v2":
if self.python_version is None:
raise ValueError("python_v2 runtime requires python_version")
if self.environment is None:
raise ValueError("python_v2 runtime requires environment")
if self.gpu is None:
raise ValueError("python_v2 runtime requires gpu")
else:
object.__setattr__(self, "python_version", None)
object.__setattr__(self, "environment", None)
object.__setattr__(self, "env", None)
object.__setattr__(self, "gpu", None)
return self
class FunctionVersion(_RemoteValue):
"""An exact immutable Function version returned by Enterprise.
The GPU execution requirement is part of this identity. CPU and memory sizing,
priority, concurrency, and retry policy belong to the execution platform.
Scheduling resources, priority, concurrency, and retry policy belong to
the submitting Job and are not part of this identity.
"""
name: str
@@ -520,13 +479,6 @@ class RefreshColumnResult(_RemoteValue):
_FUNCTION_NAME = re.compile(r"^[A-Za-z_][A-Za-z0-9_.-]*$")
_FUNCTION_BLOB_V2_TYPE = "blob_v2"
_ARROW_EXTENSION_NAME_KEY = "ARROW:extension:name"
_BLOB_V2_EXTENSION_NAME = "lance.blob.v2"
_NESTED_BLOB_COLLECTION_ERROR = (
"unsupported Arrow type for Function signature: Blob v2 fields nested under "
"collection types are not supported"
)
_GRAMMAR_PRIMITIVES = (
@@ -543,7 +495,6 @@ _GRAMMAR_PRIMITIVES = (
(pa.float32(), "float32"),
(pa.float64(), "float64"),
(pa.string(), "utf8"),
(pa.large_string(), "large_utf8"),
(pa.binary(), "binary"),
(pa.date32(), "date32"),
(pa.date64(), "date64"),
@@ -551,258 +502,31 @@ _GRAMMAR_PRIMITIVES = (
def _canonical_arrow_type(data_type: pa.DataType) -> str:
"""The compact Function grammar, or canonical exact JSON for nested types."""
grammar = _grammar_arrow_type(data_type)
if grammar is not None:
return grammar
exact = _exact_arrow_type(data_type)
return json.dumps(exact, ensure_ascii=False, sort_keys=True, separators=(",", ":"))
def _grammar_arrow_type(data_type: pa.DataType) -> Optional[str]:
"""The server's V1 Function type grammar. Anything outside it is rejected
here rather than at registration."""
for candidate, name in _GRAMMAR_PRIMITIVES:
if data_type == candidate:
return name
if pa.types.is_list(data_type) or pa.types.is_large_list(data_type):
item = _grammar_list_item(data_type)
if item is None:
return None
prefix = "list" if pa.types.is_list(data_type) else "large_list"
return f"{prefix}<{item}>"
return f"{prefix}<{_canonical_list_item(data_type)}>"
if pa.types.is_fixed_size_list(data_type) and data_type.list_size > 0:
item = _grammar_list_item(data_type)
if item is not None:
return f"fixed_size_list<{item}, {data_type.list_size}>"
return None
return (
f"fixed_size_list<{_canonical_list_item(data_type)}, {data_type.list_size}>"
)
raise TypeError(f"unsupported Arrow type for Function signature: {data_type}")
def _grammar_list_item(data_type: pa.DataType) -> Optional[str]:
def _canonical_list_item(data_type: pa.DataType) -> str:
"""The grammar names only the item type; it always means a non-nullable
child called `item`, so other child properties require exact JSON."""
child called `item`, so any other child metadata cannot be represented."""
child = data_type.value_field
if child.name != "item" or child.nullable or child.metadata:
return None
return _grammar_arrow_type(child.type)
def _validate_exact_arrow_field(field: pa.Field) -> None:
if not field.name:
raise TypeError(
"unsupported Arrow type for Function signature: field names "
"must not be empty"
"unsupported Arrow type for Function signature: list items must be a "
f"non-nullable field named 'item', got {child}"
)
if _is_blob_v2_field(field):
if not _has_supported_blob_v2_layout(field):
raise TypeError(
"unsupported Arrow type for Function signature: lance.blob.v2 "
f"requires a supported Blob storage layout, got {field}"
)
metadata = {
(key.decode() if isinstance(key, bytes) else key): (
value.decode() if isinstance(value, bytes) else value
)
for key, value in (field.metadata or {}).items()
}
if metadata and metadata != {
_ARROW_EXTENSION_NAME_KEY: _BLOB_V2_EXTENSION_NAME
}:
raise TypeError(
"unsupported Arrow type for Function signature: lance.blob.v2 "
"field metadata must contain only its canonical extension marker"
)
elif field.metadata:
raise TypeError(
"unsupported Arrow type for Function signature: field metadata "
f"is not supported, got {field}"
)
def _has_supported_blob_v2_layout(field: pa.Field) -> bool:
data_type = field.type
if isinstance(data_type, pa.ExtensionType):
data_type = data_type.storage_type
if not pa.types.is_struct(data_type):
return False
fields = tuple(data_type)
def matches(spec, compare_nullable) -> bool:
return len(fields) == len(spec) and all(
actual.name == name
and actual.type == expected_type
and (not check_nullable or actual.nullable == nullable)
for actual, (name, expected_type, nullable), check_nullable in zip(
fields, spec, compare_nullable
)
)
logical_minimal = (
("data", pa.large_binary(), True),
("uri", pa.utf8(), True),
)
logical_full = logical_minimal + (
("position", pa.uint64(), True),
("size", pa.uint64(), True),
)
prepared = (
("kind", pa.uint8(), True),
("data", pa.large_binary(), True),
("uri", pa.utf8(), True),
("blob_id", pa.uint32(), True),
("blob_size", pa.uint64(), True),
("position", pa.uint64(), True),
)
descriptor = (
("kind", pa.uint8(), False),
("position", pa.uint64(), False),
("size", pa.uint64(), False),
("blob_id", pa.uint32(), False),
("blob_uri", pa.utf8(), False),
)
return (
matches(logical_minimal, (True, True))
or matches(logical_full, (True, True, False, False))
or matches(prepared, (True,) * len(prepared))
or matches(descriptor, (False,) * len(descriptor))
)
def _canonical_arrow_field(field: pa.Field) -> str:
_validate_exact_arrow_field(field)
if _is_blob_v2_field(field):
return _FUNCTION_BLOB_V2_TYPE
return _canonical_arrow_type(field.type)
def _blob_storage_type(field: pa.Field) -> pa.DataType:
data_type = field.type
if isinstance(data_type, pa.ExtensionType):
return data_type.storage_type
return data_type
def _exact_blob_storage_type(field: pa.Field) -> dict[str, Any]:
storage = _blob_storage_type(field)
if not pa.types.is_struct(storage):
raise TypeError(
"unsupported Arrow type for Function signature: lance.blob.v2 "
"requires struct storage"
)
return {
"type": "struct",
"fields": [
{
"name": child.name,
"nullable": child.nullable,
"type": (
{"type": "large_binary"}
if pa.types.is_large_binary(child.type)
else _exact_arrow_type(child.type)
),
}
for child in storage
],
}
def _data_type_has_blob_v2(data_type: pa.DataType) -> bool:
if pa.types.is_struct(data_type):
return any(
_is_blob_v2_field(field) or _data_type_has_blob_v2(field.type)
for field in data_type
)
if (
pa.types.is_list(data_type)
or pa.types.is_large_list(data_type)
or pa.types.is_fixed_size_list(data_type)
):
field = data_type.value_field
return _is_blob_v2_field(field) or _data_type_has_blob_v2(field.type)
if pa.types.is_map(data_type):
return any(
_is_blob_v2_field(field) or _data_type_has_blob_v2(field.type)
for field in (data_type.key_field, data_type.item_field)
)
return False
def _exact_arrow_field(
field: pa.Field, *, inside_collection: bool = False
) -> dict[str, Any]:
_validate_exact_arrow_field(field)
if _is_blob_v2_field(field):
if inside_collection:
raise TypeError(_NESTED_BLOB_COLLECTION_ERROR)
return {
"name": field.name,
"nullable": field.nullable,
"type": _exact_blob_storage_type(field),
"metadata": {
_ARROW_EXTENSION_NAME_KEY: _BLOB_V2_EXTENSION_NAME,
},
}
value = {
"name": field.name,
"nullable": field.nullable,
"type": _exact_arrow_type(field.type, inside_collection=inside_collection),
}
return value
def _exact_arrow_type(
data_type: pa.DataType, *, inside_collection: bool = False
) -> dict[str, Any]:
for candidate, name in _GRAMMAR_PRIMITIVES:
if data_type == candidate:
return {"type": name}
if pa.types.is_struct(data_type):
fields = list(data_type)
names = [field.name for field in fields]
if not fields or len(set(names)) != len(names):
raise TypeError(
"unsupported Arrow type for Function signature: structs must have "
"non-empty, uniquely named fields"
)
return {
"type": "struct",
"fields": [
_exact_arrow_field(field, inside_collection=inside_collection)
for field in fields
],
}
if (
pa.types.is_list(data_type)
or pa.types.is_large_list(data_type)
or pa.types.is_fixed_size_list(data_type)
):
if pa.types.is_fixed_size_list(data_type):
if data_type.value_field.name != "item":
raise TypeError(
"unsupported Arrow type for Function signature: fixed-size list "
"items must be named 'item'"
)
if data_type.list_size <= 0:
raise TypeError(
f"unsupported Arrow type for Function signature: {data_type}"
)
value: dict[str, Any] = {
"type": (
"list"
if pa.types.is_list(data_type)
else "large_list"
if pa.types.is_large_list(data_type)
else "fixed_size_list"
),
"fields": [
_exact_arrow_field(data_type.value_field, inside_collection=True)
],
}
if pa.types.is_fixed_size_list(data_type):
value["length"] = data_type.list_size
return value
if pa.types.is_map(data_type) and _data_type_has_blob_v2(data_type):
raise TypeError(_NESTED_BLOB_COLLECTION_ERROR)
raise TypeError(f"unsupported Arrow type for Function signature: {data_type}")
return _canonical_arrow_type(child.type)
def _list_of(item: pa.DataType) -> pa.DataType:
@@ -876,15 +600,8 @@ def _callable_parameters(function: Callable[..., Any]) -> tuple[inspect.Paramete
def _function_output(output: pa.DataType | pa.Field | pa.Schema) -> FunctionOutput:
if isinstance(output, pa.Schema):
if output.metadata:
raise TypeError("Function output schema metadata is not supported")
fields = tuple(output)
elif (
isinstance(output, pa.Field)
and not _is_blob_v2_field(output)
and pa.types.is_struct(output.type)
):
_validate_exact_arrow_field(output)
elif isinstance(output, pa.Field) and pa.types.is_struct(output.type):
if output.nullable:
raise ValueError("Function output must be non-nullable")
fields = tuple(output.type)
@@ -900,12 +617,11 @@ def _function_output(output: pa.DataType | pa.Field | pa.Schema) -> FunctionOutp
raise TypeError(
"output_schema must be a PyArrow DataType, Field, or Schema"
)
_validate_exact_arrow_field(field)
if field.nullable:
raise ValueError("Function output must be non-nullable")
return FunctionOutput(
kind="scalar",
arrow_type=_canonical_arrow_field(field),
arrow_type=_canonical_arrow_type(field.type),
nullable=False,
)
@@ -913,8 +629,6 @@ def _function_output(output: pa.DataType | pa.Field | pa.Schema) -> FunctionOutp
raise ValueError("named-struct Function output must contain at least one field")
if any(field.nullable for field in fields):
raise ValueError("Function output fields must be non-nullable")
for field in fields:
_validate_exact_arrow_field(field)
names = [field.name for field in fields]
if len(set(names)) != len(names):
raise ValueError("Function output field names must be unique")
@@ -923,7 +637,7 @@ def _function_output(output: pa.DataType | pa.Field | pa.Schema) -> FunctionOutp
fields=tuple(
FunctionResultField(
name=field.name,
arrow_type=_canonical_arrow_field(field),
arrow_type=_canonical_arrow_type(field.type),
nullable=False,
)
for field in fields
@@ -943,10 +657,6 @@ def _infer_signature(
if input_schema is not None:
if not isinstance(input_schema, pa.Schema):
raise TypeError("input_schema must be a PyArrow Schema")
if input_schema.metadata:
raise TypeError("Function input schema metadata is not supported")
for field in input_schema:
_validate_exact_arrow_field(field)
expected = tuple(parameter.name for parameter in parameters)
actual = tuple(input_schema.names)
if actual != expected:
@@ -957,7 +667,7 @@ def _infer_signature(
inputs = tuple(
FunctionParameter(
name=field.name,
arrow_type=_canonical_arrow_field(field),
arrow_type=_canonical_arrow_type(field.type),
nullable=field.nullable,
)
for field in input_schema
@@ -980,9 +690,7 @@ def _infer_signature(
inputs.append(
FunctionParameter(
name=parameter.name,
arrow_type=_canonical_arrow_field(
pa.field(parameter.name, data_type, nullable=nullable)
),
arrow_type=_canonical_arrow_type(data_type),
nullable=nullable,
)
)
@@ -1202,7 +910,6 @@ class UdfDefinition:
pip: tuple[str, ...],
env: Mapping[str, str],
python_version: Optional[str],
gpu: bool = False,
conda: tuple[str, ...] = (),
conda_channels: tuple[str, ...] = (),
):
@@ -1231,14 +938,12 @@ class UdfDefinition:
signature = _infer_signature(function, input_schema, output_schema)
source = _package_source(function)
digest = f"sha256:{hashlib.sha256(source).hexdigest()}"
gpu_marker = _normalize_gpu_marker(gpu)
runtime = PythonRuntimeSpec(
kind="python_v2" if gpu_marker is not None else "python",
kind="python",
python_version=python_version
or f"{sys.version_info.major}.{sys.version_info.minor}",
environment=environment_spec,
env=environment,
gpu=gpu_marker,
)
self._function = function
self._request = FunctionRegistrationRequest(
@@ -1284,7 +989,6 @@ def udf(
pip: tuple[str, ...] | list[str] = (),
env: Optional[Mapping[str, str]] = None,
python_version: Optional[str] = None,
gpu: bool = False,
conda: tuple[str, ...] | list[str] = (),
conda_channels: tuple[str, ...] | list[str] = (),
) -> Callable[[Callable[..., Any]], UdfDefinition]: ...
@@ -1299,7 +1003,6 @@ def udf(
pip: tuple[str, ...] | list[str] = (),
env: Optional[Mapping[str, str]] = None,
python_version: Optional[str] = None,
gpu: bool = False,
conda: tuple[str, ...] | list[str] = (),
conda_channels: tuple[str, ...] | list[str] = (),
):
@@ -1332,10 +1035,6 @@ def udf(
Environment variables included in the Function definition.
python_version : str, optional
Remote Python major/minor version. Defaults to the client version.
gpu : bool, default False
Whether every remote execution requires a GPU. The execution platform
selects one compatible GPU for each worker. The requirement is part of
the immutable Function version.
The packaged artifact is a snapshot: the function source plus exactly
the module-level names it references (modules as imports, importable
@@ -1360,11 +1059,6 @@ def udf(
... return value * 2
>>> score(1.5)
3.0
>>> @udf(pip=["cupy-cuda12x"], gpu=True)
... def gpu_score(value: int) -> int:
... return value * 2
>>> gpu_score.registration_request.runtime.gpu
True
"""
def decorate(target: Callable[..., Any]) -> UdfDefinition:
@@ -1376,7 +1070,6 @@ def udf(
pip=tuple(pip),
env={} if env is None else env,
python_version=python_version,
gpu=gpu,
conda=tuple(conda),
conda_channels=tuple(conda_channels),
)
-4
View File
@@ -749,10 +749,6 @@ class RemoteDBConnection(DBConnection):
def get_function(self, name: str, *, version: str) -> FunctionVersion:
return LOOP.run(self._conn.get_function(name, version=version))
@override
def drop_function(self, name: str, *, version: str) -> bool:
return LOOP.run(self._conn.drop_function(name, version=version))
@override
def list_jobs(self) -> List["JobInfo"]:
"""List server-side jobs across the database's tables."""
+1 -9
View File
@@ -67,15 +67,7 @@ from ..query import (
LanceTakeQueryBuilder,
LanceVectorQueryBuilder,
)
from ..table import (
AsyncTable,
BlobMode,
Branches,
IndexStatistics,
Query,
Table,
Tags,
)
from ..table import AsyncTable, BlobMode, Branches, IndexStatistics, Query, Table, Tags
from ..types import BaseTokenizerType
+215 -17
View File
@@ -559,12 +559,18 @@ def _coerce_blob_list_values(
def _coerce_value_to_blob(values: pa.Array, target_field: pa.Field) -> pa.Array:
if pa.types.is_null(values.type):
data = pa.nulls(len(values), type=pa.large_binary())
if _is_string_like(values.type):
carrier_name = "uri"
carrier = values
elif pa.types.is_null(values.type):
carrier_name = None
carrier = None
elif pa.types.is_large_binary(values.type):
data = values
carrier_name = "data"
carrier = values
else:
data = values.cast(pa.large_binary())
carrier_name = "data"
carrier = values.cast(pa.large_binary())
length = len(values)
storage_type = target_field.type
if isinstance(storage_type, pa.ExtensionType):
@@ -572,8 +578,8 @@ def _coerce_value_to_blob(values: pa.Array, target_field: pa.Field) -> pa.Array:
storage_fields = list(storage_type)
children = []
for storage_field in storage_fields:
if storage_field.name == "data":
children.append(data)
if storage_field.name == carrier_name:
children.append(carrier.cast(storage_field.type))
else:
children.append(pa.nulls(length, type=storage_field.type))
storage = pa.StructArray.from_arrays(
@@ -593,7 +599,11 @@ def _physical_array_and_type(array: pa.Array) -> tuple[pa.Array, pa.DataType]:
def _can_coerce_to_blob(data_type: pa.DataType) -> bool:
return _is_binary_like(data_type) or pa.types.is_null(data_type)
return (
_is_binary_like(data_type)
or _is_string_like(data_type)
or pa.types.is_null(data_type)
)
def _is_binary_like(data_type: pa.DataType) -> bool:
@@ -604,6 +614,15 @@ def _is_binary_like(data_type: pa.DataType) -> bool:
)
def _is_string_like(data_type: pa.DataType) -> bool:
predicates = ("is_string", "is_large_string", "is_string_view")
return any(
predicate(data_type)
for name in predicates
if (predicate := getattr(pa.types, name, None)) is not None
)
def _field_extension_name(field: pa.Field) -> Optional[str]:
extension_name = getattr(field.type, "extension_name", None)
if extension_name is not None:
@@ -618,6 +637,187 @@ def _field_extension_name(field: pa.Field) -> Optional[str]:
return extension_name
_JSON_EXTENSION_NAMES = {"arrow.json", "lance.json"}
_BLOB_EXTENSION_NAME = "lance.blob.v2"
def _field_contains_write_extension(field: pa.Field) -> bool:
extension_name = _field_extension_name(field)
if (
extension_name in _JSON_EXTENSION_NAMES
or extension_name == _BLOB_EXTENSION_NAME
):
return True
if pa.types.is_struct(field.type):
return any(_field_contains_write_extension(child) for child in field.type)
if (
pa.types.is_list(field.type)
or pa.types.is_large_list(field.type)
or pa.types.is_fixed_size_list(field.type)
):
return _field_contains_write_extension(field.type.value_field)
return False
def _with_field_type(
field: pa.Field,
data_type: pa.DataType,
*,
name: Optional[str] = None,
metadata: Optional[dict] = None,
) -> pa.Field:
return pa.field(
name or field.name,
data_type,
nullable=field.nullable,
metadata=field.metadata if metadata is None else metadata,
)
def _with_list_value_field(
data_type: pa.DataType, value_field: pa.Field
) -> pa.DataType:
if pa.types.is_list(data_type):
return pa.list_(value_field)
if pa.types.is_large_list(data_type):
return pa.large_list(value_field)
return pa.list_(value_field, data_type.list_size)
def _extension_storage_field(field: pa.Field) -> pa.Field:
"""Return a from-pylist-compatible field for nested write extensions."""
extension_name = _field_extension_name(field)
if extension_name in _JSON_EXTENSION_NAMES:
metadata = dict(field.metadata or {})
metadata[b"ARROW:extension:name"] = b"arrow.json"
return _with_field_type(field, pa.string(), metadata=metadata)
if extension_name == _BLOB_EXTENSION_NAME:
metadata = dict(field.metadata or {})
metadata[b"ARROW:extension:name"] = _BLOB_EXTENSION_NAME.encode()
metadata[b"ARROW:extension:metadata"] = b""
storage_type = getattr(field.type, "storage_type", field.type)
return _with_field_type(field, storage_type, metadata=metadata)
if pa.types.is_struct(field.type):
children = [_extension_storage_field(child) for child in field.type]
return _with_field_type(field, pa.struct(children))
if _is_list_like(field.type):
value_field = _extension_storage_field(field.type.value_field)
return _with_field_type(field, _with_list_value_field(field.type, value_field))
return field
def _prepare_extension_field(
field: pa.Field, target_field: pa.Field
) -> Tuple[pa.Field, bool]:
extension_name = _field_extension_name(target_field)
if extension_name in _JSON_EXTENSION_NAMES:
metadata = dict(field.metadata or {})
metadata[b"ARROW:extension:name"] = b"arrow.json"
return _with_field_type(field, pa.string(), metadata=metadata), True
if extension_name == _BLOB_EXTENSION_NAME and pa.types.is_null(field.type):
return _with_field_type(field, pa.large_binary()), True
if pa.types.is_struct(field.type) and pa.types.is_struct(target_field.type):
target_children = {child.name: child for child in target_field.type}
children = []
changed = False
for child in field.type:
target_child = target_children.get(child.name)
if target_child is None:
children.append(child)
continue
prepared, child_changed = _prepare_extension_field(child, target_child)
children.append(prepared)
changed = changed or child_changed
if changed:
return _with_field_type(field, pa.struct(children)), True
if _is_list_like(field.type) and _is_list_like(target_field.type):
target_value_field = target_field.type.value_field
if _field_contains_write_extension(target_value_field):
prepared = _extension_storage_field(target_value_field)
data_type = _with_list_value_field(target_field.type, prepared)
return _with_field_type(field, data_type), True
return field, False
def _prepare_extension_value(
value: Any, target_field: pa.Field, *, within_list: bool = False
) -> Any:
"""Shape raw nested blob values for PyArrow's struct construction."""
if value is None:
return None
extension_name = _field_extension_name(target_field)
if extension_name == _BLOB_EXTENSION_NAME and within_list:
if isinstance(value, (bytes, bytearray, memoryview)):
return {"data": value}
if isinstance(value, str):
return {"uri": value}
return value
if pa.types.is_struct(target_field.type) and isinstance(value, dict):
target_children = {child.name: child for child in target_field.type}
return {
name: _prepare_extension_value(
child_value, target_children[name], within_list=within_list
)
if name in target_children
else child_value
for name, child_value in value.items()
}
if _is_list_like(target_field.type) and isinstance(value, (list, tuple)):
return [
_prepare_extension_value(
item, target_field.type.value_field, within_list=True
)
for item in value
]
return value
def _prepare_extension_list(data: DATA, target_schema: pa.Schema) -> DATA:
"""Give inferred list columns the logical type required by extensions."""
if not isinstance(data, list) or not data or not isinstance(data[0], dict):
return data
target_fields = {field.name: field for field in target_schema}
if not any(
_field_contains_write_extension(field) for field in target_fields.values()
):
return data
inferred = pa.Table.from_pylist(data)
fields = []
changed = False
for field in inferred.schema:
target_field = target_fields.get(field.name)
if target_field is None:
fields.append(field)
continue
prepared, field_changed = _prepare_extension_field(field, target_field)
fields.append(prepared)
changed = changed or field_changed
if not changed:
return inferred
insert_schema = pa.schema(fields, metadata=inferred.schema.metadata)
prepared_data = [
{
name: _prepare_extension_value(value, target_fields[name])
if name in target_fields
else value
for name, value in row.items()
}
for row in data
]
return pa.Table.from_pylist(prepared_data, schema=insert_schema)
def _align_field_types(
fields: List[pa.Field],
target_fields: List[pa.Field],
@@ -2165,11 +2365,9 @@ class Table(ABC):
Function columns are supported only on LanceDB Cloud and
Enterprise.
computed: Dict[str, str], optional
A mapping from output column names to SQL expressions derives each
output field from its expression. A direct projection of a Blob v2
field inherits Blob v2 semantics; other expressions derive their
ordinary Arrow type. Mapping order is declaration and dependency
order.
A map of column name to a SQL expression defining the column. The
column's type and inputs are derived from the expression, so no
data type is supplied.
Unlike ``transforms``, the expression is stored rather than
evaluated now: the column is committed with no values, and rows get
@@ -5626,6 +5824,9 @@ class AsyncTable:
if fill_value is None:
fill_value = 0.0
if mode != "overwrite":
data = _prepare_extension_list(data, schema)
# _santitize_data is an old code path, but we will use it until the
# new code path is ready.
if mode == "overwrite":
@@ -6270,11 +6471,8 @@ class AsyncTable:
Function columns are supported only on LanceDB Cloud and
Enterprise.
computed: Dict[str, str], optional
A mapping from output column names to SQL expressions derives each
output field from its expression. A direct projection of a Blob v2
field inherits Blob v2 semantics; other expressions derive their
ordinary Arrow type. Mapping order is declaration and dependency
order.
A map of column name to a SQL expression defining the column. The
column's type and inputs are derived from the expression.
Unlike ``transforms``, the expression is stored rather than
evaluated now: the column is committed with no values, and rows get
+75
View File
@@ -710,6 +710,80 @@ def test_fetch_blobs_preserves_null_and_empty_values():
assert blobs[3].as_py() == b"present"
def test_add_all_null_list_to_blob_column():
table = _blob_table("all_null_add", [{"id": 1, "image": None}])
hits = table.search().to_arrow()
blobs = table.fetch_blobs("image", hits)
assert len(blobs) == 1
assert blobs[0].as_py() is None
def test_add_all_null_list_to_blob_column_with_sanitizer():
db = lancedb.connect("memory:///")
schema = pa.schema([pa.field("id", pa.int64()), lancedb.blob("image")])
table = db.create_table("all_null_sanitized_add", schema=schema)
table.add([{"id": 1, "image": None}], on_bad_vectors="fill")
hits = table.search().to_arrow()
blobs = table.fetch_blobs("image", hits)
assert len(blobs) == 1
assert blobs[0].as_py() is None
def test_add_all_null_list_to_nested_blob_column():
db = lancedb.connect("memory:///")
blob_field = lancedb.blob("image")
info_field = pa.field("info", pa.struct([blob_field]))
info = pa.StructArray.from_arrays(
[_blob_array("image", [b"seed"])], fields=[blob_field]
)
seed = pa.Table.from_arrays(
[pa.array([0], type=pa.int64()), info],
schema=pa.schema([pa.field("id", pa.int64()), info_field]),
)
table = db.create_table("nested_null_add", data=seed)
table.add([{"id": 1, "info": {"image": None}}])
table.add([{"id": 2, "info": {"image": None}}], on_bad_vectors="fill")
hits = table.search().where("id > 0").to_arrow()
blobs = table.fetch_blobs("info.image", hits)
assert len(blobs) == 2
assert all(blob.as_py() is None for blob in blobs)
@pytest.mark.parametrize("large_list", [False, True], ids=["list", "large_list"])
def test_add_list_of_dicts_to_blob_list_column(large_list):
db = lancedb.connect("memory:///")
blob_field = lancedb.blob("image")
blob_values = _blob_array("image", [b"seed"])
if large_list:
items_field = pa.field("items", pa.large_list(blob_field))
items = pa.LargeListArray.from_arrays(
pa.array([0, 1], type=pa.int64()), blob_values
)
else:
items_field = pa.field("items", pa.list_(blob_field))
items = pa.ListArray.from_arrays(pa.array([0, 1], type=pa.int32()), blob_values)
seed = pa.Table.from_arrays(
[pa.array([0], type=pa.int64()), items],
schema=pa.schema([pa.field("id", pa.int64()), items_field]),
)
table = db.create_table(f"blob_{large_list}_list_add", data=seed)
table.add([{"id": 1, "items": [None]}])
table.add(
[{"id": 2, "items": [b"a", None]}],
on_bad_vectors="fill",
)
ids = table.search().select(["id"]).to_arrow()["id"].to_pylist()
assert sorted(ids) == [0, 1, 2]
assert pa.types.is_large_list(table.schema.field("items").type) is large_list
def test_fetch_blob_ranges_aligns_repeated_ranges_and_nulls():
table = _blob_table(
"range_alignment",
@@ -1230,6 +1304,7 @@ def test_add_external_uri_string_round_trips_with_flag(tmp_path):
table = db.create_table("external_string", schema=schema)
table.add(
[{"id": 1, "image": blob_path.as_uri()}],
on_bad_vectors="fill",
allow_external_blob_outside_bases=True,
)
@@ -12,8 +12,6 @@ from datetime import date
import http.server
import json
from pathlib import Path
import subprocess
import sys
import threading
from typing import Optional
@@ -21,13 +19,7 @@ import pyarrow as pa
import pytest
import lancedb
from lancedb.functions import (
PythonRuntimeSpec,
UdfDefinition,
_canonical_arrow_type,
_GRAMMAR_PRIMITIVES,
udf,
)
from lancedb.functions import UdfDefinition, udf
THRESHOLD = 20
_CACHE = None
@@ -69,80 +61,6 @@ def test_scalar_udf_matches_shared_registration_golden_and_remains_callable():
}
def _main_udf_source(
*, threshold: int = 20, input_annotation: str = "int", comparison: str = ">="
) -> str:
return (
"from __future__ import annotations\n"
"from lancedb.functions import udf\n"
f"THRESHOLD = {threshold}\n"
"\n"
"@udf\n"
f"def label(value: {input_annotation}) -> str:\n"
f" return 'big' if value {comparison} THRESHOLD else 'small'\n"
"\n"
"assert label.__module__ == '__main__'\n"
"print(label.registration_request.to_canonical_json())\n"
)
def _run_main_udf(path: Path, source: str) -> dict:
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(source)
result = subprocess.run(
[sys.executable, str(path)],
check=True,
capture_output=True,
text=True,
)
return json.loads(result.stdout)
def test_main_udf_registration_identity_is_stable_across_processes_and_paths(
tmp_path,
):
source = _main_udf_source()
original_path = tmp_path / "original" / "job.py"
moved_path = tmp_path / "moved" / "renamed_job.py"
original_runs = [_run_main_udf(original_path, source) for _ in range(2)]
moved_run = _run_main_udf(moved_path, source)
assert len({run["artifact"]["digest"] for run in [*original_runs, moved_run]}) == 1
assert all(
run["signature"] == original_runs[0]["signature"]
for run in [original_runs[1], moved_run]
)
assert original_runs[0] == original_runs[1] == moved_run
body_change = _run_main_udf(
tmp_path / "changes" / "body.py", _main_udf_source(comparison=">")
)
global_change = _run_main_udf(
tmp_path / "changes" / "global.py", _main_udf_source(threshold=21)
)
annotation_change = _run_main_udf(
tmp_path / "changes" / "annotation.py",
_main_udf_source(input_annotation="float"),
)
baseline = original_runs[0]
assert baseline["signature"] == body_change["signature"]
assert baseline["signature"] == global_change["signature"]
assert baseline["signature"] != annotation_change["signature"]
assert (
len(
{
baseline["artifact"]["digest"],
body_change["artifact"]["digest"],
global_change["artifact"]["digest"],
annotation_change["artifact"]["digest"],
}
)
== 4
)
def _run_packaged(definition, *args):
"""Execute the shipped artifact in a fresh namespace, as a worker would."""
source = base64.b64decode(definition.registration_request.artifact.content.data)
@@ -171,58 +89,6 @@ def test_udf_conda_environment():
udf(name="channels", conda_channels=["conda-forge"])(lambda value: value)
def test_udf_gpu_marker_uses_gpu_runtime():
@udf(pip=["cupy-cuda12x"], gpu=True)
def double_on_gpu(value: int) -> int:
return value * 2
request = json.loads(double_on_gpu.registration_request.to_canonical_json())
assert request["runtime"]["kind"] == "python_v2"
assert request["runtime"]["gpu"] is True
@udf(pip=["pyarrow"])
def cpu_function(value: int) -> int:
return value
cpu_runtime = json.loads(cpu_function.registration_request.to_canonical_json())[
"runtime"
]
assert cpu_runtime["kind"] == "python"
assert "gpu" not in cpu_runtime
def identity(value: int) -> int:
return value
for invalid in [None, 0, 1, -1, 1.5, "", "true", "1", "H100"]:
with pytest.raises(ValueError, match="gpu must be a boolean"):
udf(name="invalid_gpu", gpu=invalid)(identity)
base_runtime = {
"kind": "python_v2",
"python_version": "3.12",
"environment": {"kind": "pip"},
}
runtime = PythonRuntimeSpec.model_validate({**base_runtime, "gpu": True})
assert runtime.gpu is True
for invalid in [False, 1, 0, "", "true", "1", "H100"]:
with pytest.raises(ValueError, match="runtime.gpu must be true"):
PythonRuntimeSpec.model_validate({**base_runtime, "gpu": invalid})
def test_unknown_runtime_discards_payload_before_known_field_validation():
for payload in [
{"kind": "python_v3", "gpu": {"model": "H100"}},
{"kind": "python_v3", "resources": []},
{
"kind": "python_v3",
"environment": {"kind": []},
"python_version": 3.15,
},
]:
runtime = PythonRuntimeSpec.model_validate(payload)
assert runtime.to_canonical_json() == '{"kind":"python_v3"}'
def test_udf_packages_attribute_access_and_body_imports():
@udf
def word_norm(body: str) -> float:
@@ -302,7 +168,9 @@ def test_udf_resolves_module_globals_before_builtins(tmp_path):
udf(module.uses_callable_shadow)
def test_canonical_arrow_type_prefers_the_compact_grammar():
def test_canonical_arrow_type_is_exactly_the_grammar():
from lancedb.functions import _GRAMMAR_PRIMITIVES, _canonical_arrow_type
golden = json.loads(
(
Path(__file__).parents[3]
@@ -313,19 +181,14 @@ def test_canonical_arrow_type_prefers_the_compact_grammar():
case["arrow_type"] for case in golden["valid"] if "<" not in case["arrow_type"]
]
assert [name for _, name in _GRAMMAR_PRIMITIVES] == primitives
assert _canonical_arrow_type(pa.list_(pa.field("item", pa.float32(), False))) == (
"list<float32>"
)
assert (
_canonical_arrow_type(pa.large_list(pa.field("item", pa.float32(), False)))
== "large_list<float32>"
)
for outside in [
pa.timestamp("us"),
pa.decimal128(10, 2),
pa.large_string(),
pa.large_binary(),
pa.binary(4),
pa.duration("s"),
pa.struct([pa.field("a", pa.int32())]),
pa.list_(pa.float32(), 0),
pa.list_(pa.timestamp("us")),
]:
@@ -515,27 +378,14 @@ def test_udf_recursion_versus_a_rebound_module_name(tmp_path):
udf(raw_fact)
def test_canonical_arrow_type_uses_exact_json_for_list_child_properties():
nullable = pa.list_(pa.float32())
assert json.loads(_canonical_arrow_type(nullable)) == {
"type": "list",
"fields": [
{
"name": "item",
"nullable": True,
"type": {"type": "float32"},
}
],
}
named = pa.list_(pa.field("custom", pa.float32(), nullable=False))
assert json.loads(_canonical_arrow_type(named))["fields"][0]["name"] == "custom"
def test_canonical_arrow_type_rejects_unrepresentable_list_children():
from lancedb.functions import _canonical_arrow_type
for outside in [
pa.list_(pa.float32()), # pyarrow default: nullable child
pa.list_(pa.field("custom", pa.float32(), nullable=False)),
pa.list_(pa.field("item", pa.float32(), nullable=False, metadata={"k": "v"})),
pa.list_(pa.field("item", pa.float32(), nullable=False), 0),
pa.list_(
pa.field("item", pa.float32(), nullable=False, metadata={"k": "v"}), 3
),
pa.list_(pa.field("custom", pa.float32(), nullable=False), 3),
]:
with pytest.raises(TypeError, match="unsupported Arrow type"):
_canonical_arrow_type(outside)
@@ -545,29 +395,6 @@ def test_canonical_arrow_type_uses_exact_json_for_list_child_properties():
)
== "fixed_size_list<float32, 3>"
)
fixed = json.loads(_canonical_arrow_type(pa.list_(pa.float32(), 3)))
assert fixed == {
"type": "fixed_size_list",
"fields": [
{
"name": "item",
"nullable": True,
"type": {"type": "float32"},
}
],
"length": 3,
}
large = json.loads(_canonical_arrow_type(pa.large_list(pa.float32())))
assert large["type"] == "large_list"
assert large["fields"][0]["nullable"] is True
for invalid_struct in [
pa.struct([]),
pa.struct([pa.field("a", pa.int32()), pa.field("a", pa.int64())]),
pa.struct([pa.field("", pa.int32())]),
]:
with pytest.raises(TypeError, match="unsupported Arrow type"):
_canonical_arrow_type(invalid_struct)
def _calls_missing(value: int) -> int:
@@ -605,7 +432,6 @@ def _arrow_type_from_golden(spec: dict) -> pa.DataType:
"null": pa.null(),
"bool": pa.bool_(),
"utf8": pa.string(),
"large_utf8": pa.large_string(),
"binary": pa.binary(),
"float16": pa.float16(),
"float32": pa.float32(),
@@ -622,6 +448,8 @@ def test_arrow_type_grammar_matches_the_shared_golden():
/ "rust/lancedb/tests/fixtures/first_class_functions/v1/arrow_types.json"
).read_text()
)
from lancedb.functions import _canonical_arrow_type
emitted = {
case["arrow_type"]: _canonical_arrow_type(_arrow_type_from_golden(case["json"]))
for case in golden["valid"]
@@ -654,395 +482,6 @@ def test_explicit_arrow_schema_is_deterministic():
assert signature.output.nullable is False
def test_blob_fields_use_the_scalar_function_semantic_type():
@udf(
input_schema=pa.schema([lancedb.blob("image", nullable=False)]),
output_schema=lancedb.blob("result", nullable=False),
)
def copy_blob(image):
return image
signature = copy_blob.registration_request.signature
assert signature.inputs[0].arrow_type == "blob_v2"
assert signature.output.kind == "scalar"
assert signature.output.arrow_type == "blob_v2"
def test_whole_named_struct_function_can_include_a_blob_result_field():
@udf(
input_schema=pa.schema([lancedb.blob("image", nullable=False)]),
output_schema=pa.field(
"payload",
pa.struct(
[
pa.field("mime_type", pa.string(), nullable=False),
lancedb.blob("image", nullable=False),
]
),
nullable=False,
),
)
def inspect_blob(image):
return {"mime_type": "image/png", "image": image}
output = inspect_blob.registration_request.signature.output
assert output.kind == "named_struct"
assert [(field.name, field.arrow_type) for field in output.fields] == [
("mime_type", "utf8"),
("image", "blob_v2"),
]
def test_struct_blob_signature_fields_preserve_exact_metadata_and_nullability():
nested_input = pa.field(
"payload",
pa.struct(
[
pa.field("mime_type", pa.string(), nullable=False),
pa.field(
"nested",
pa.struct([lancedb.blob("image", nullable=True)]),
nullable=True,
),
]
),
nullable=True,
)
nested_output = pa.field(
"result",
pa.struct(
[
pa.field("mime_type", pa.string(), nullable=False),
pa.field(
"nested",
pa.struct([lancedb.blob("image", nullable=True)]),
nullable=False,
),
]
),
nullable=False,
)
@udf(input_schema=pa.schema([nested_input]), output_schema=nested_output)
def copy_payload(payload):
return payload
signature = copy_payload.registration_request.signature
input_type = json.loads(signature.inputs[0].arrow_type)
assert input_type["fields"][1]["nullable"] is True
input_blob = input_type["fields"][1]["type"]["fields"][0]
assert input_blob["nullable"] is True
assert input_blob["metadata"] == {"ARROW:extension:name": "lance.blob.v2"}
assert signature.output.kind == "named_struct"
nested_result = next(
field for field in signature.output.fields if field.name == "nested"
)
output_type = json.loads(nested_result.arrow_type)
output_blob = output_type["fields"][0]
assert output_blob["nullable"] is True
assert output_blob["metadata"] == {"ARROW:extension:name": "lance.blob.v2"}
def test_struct_blob_signature_supports_multiple_struct_levels():
recursive = pa.field(
"value",
pa.struct(
[
pa.field(
"level_1",
pa.struct(
[
pa.field(
"level_2",
pa.struct([lancedb.blob("image", nullable=False)]),
nullable=False,
)
]
),
nullable=False,
)
]
),
nullable=False,
)
@udf(
input_schema=pa.schema([recursive]),
output_schema=pa.field("size", pa.int64(), nullable=False),
)
def blob_size(value):
return len(value["level_1"]["level_2"]["image"])
encoded = json.loads(blob_size.registration_request.signature.inputs[0].arrow_type)
blob = encoded["fields"][0]["type"]["fields"][0]["type"]["fields"][0]
assert blob["metadata"]["ARROW:extension:name"] == "lance.blob.v2"
@pytest.mark.parametrize(
"data_type",
[
pa.list_(lancedb.blob("item", nullable=False)),
pa.large_list(lancedb.blob("item", nullable=False)),
pa.list_(lancedb.blob("item", nullable=False), 2),
pa.map_(pa.string(), lancedb.blob("value", nullable=False).type),
],
)
def test_blob_signature_rejects_collection_ancestors(data_type):
with pytest.raises(
TypeError,
match="Blob v2 fields nested under collection types are not supported",
):
@udf(
input_schema=pa.schema([pa.field("value", data_type, nullable=False)]),
output_schema=pa.field("size", pa.int64(), nullable=False),
)
def blob_size(value):
return len(value)
def test_blob_signature_rejects_collection_below_a_struct():
nested = pa.field(
"value",
pa.struct(
[
pa.field(
"images",
pa.list_(lancedb.blob("item", nullable=False)),
nullable=False,
)
]
),
nullable=False,
)
with pytest.raises(
TypeError,
match="Blob v2 fields nested under collection types are not supported",
):
@udf(
input_schema=pa.schema([nested]),
output_schema=pa.field("size", pa.int64(), nullable=False),
)
def blob_size(value):
return len(value["images"])
def test_named_struct_function_can_include_a_blob_result_field():
@udf(
input_schema=pa.schema([lancedb.blob("image", nullable=False)]),
output_schema=pa.schema(
[
lancedb.blob("thumbnail", nullable=False),
pa.field("width", pa.int32(), nullable=False),
]
),
)
def inspect_blob(image):
return {"thumbnail": image, "width": 1}
output = inspect_blob.registration_request.signature.output
assert output.kind == "named_struct"
assert [(field.name, field.arrow_type) for field in output.fields] == [
("thumbnail", "blob_v2"),
("width", "int32"),
]
def test_metadata_marked_blob_field_uses_the_semantic_type():
extension = lancedb.blob("image", nullable=False).type
storage = (
extension.storage_type if isinstance(extension, pa.ExtensionType) else extension
)
metadata_blob = pa.field(
"image",
storage,
nullable=False,
metadata={"ARROW:extension:name": "lance.blob.v2"},
)
@udf(
input_schema=pa.schema([metadata_blob]),
output_schema=pa.field("size", pa.int64(), nullable=False),
)
def blob_size(image):
return len(image)
assert blob_size.registration_request.signature.inputs[0].arrow_type == "blob_v2"
def test_blob_marker_rejects_invalid_storage_layout():
malformed = pa.field(
"image",
pa.int64(),
nullable=False,
metadata={"ARROW:extension:name": "lance.blob.v2"},
)
with pytest.raises(TypeError, match="requires a supported Blob storage layout"):
@udf(
input_schema=pa.schema([malformed]),
output_schema=pa.field("size", pa.int64(), nullable=False),
)
def blob_size(image):
return len(image)
def test_nested_non_blob_extension_is_not_silently_unwrapped():
class TestExtension(pa.ExtensionType):
def __init__(self):
super().__init__(pa.int64(), "test.function.extension")
def __arrow_ext_serialize__(self):
return b""
@classmethod
def __arrow_ext_deserialize__(cls, storage_type, serialized):
return cls()
nested = pa.field(
"value",
pa.struct([pa.field("extended", TestExtension(), nullable=False)]),
nullable=False,
)
with pytest.raises(TypeError, match="unsupported Arrow type"):
@udf(
input_schema=pa.schema([nested]),
output_schema=pa.field("result", pa.int64(), nullable=False),
)
def extension_value(value):
return value["extended"]
def test_explicit_large_utf8_schemas_use_the_canonical_function_name():
input_schema = pa.schema([pa.field("text", pa.large_string(), nullable=True)])
output_schema = pa.field("result", pa.large_string(), nullable=False)
@udf(input_schema=input_schema, output_schema=output_schema)
def preserve(text):
return text
signature = preserve.registration_request.signature
assert signature.inputs[0].arrow_type == "large_utf8"
assert signature.inputs[0].nullable is True
assert signature.output.arrow_type == "large_utf8"
assert signature.output.nullable is False
nested = pa.struct([pa.field("text", pa.large_string(), nullable=True)])
assert json.loads(_canonical_arrow_type(nested)) == {
"type": "struct",
"fields": [
{
"name": "text",
"nullable": True,
"type": {"type": "large_utf8"},
}
],
}
def test_nested_struct_output_uses_canonical_exact_json():
token = pa.struct(
[
pa.field("position", pa.int32(), nullable=False),
pa.field("value", pa.string(), nullable=False),
pa.field("length", pa.int32(), nullable=False),
]
)
analysis = pa.struct(
[
pa.field("normalized_text", pa.string(), nullable=False),
pa.field("has_content", pa.bool_(), nullable=False),
pa.field(
"metrics",
pa.struct(
[
pa.field("character_count", pa.int64(), nullable=False),
pa.field("word_count", pa.int32(), nullable=False),
pa.field("average_word_length", pa.float64(), nullable=False),
]
),
nullable=False,
),
pa.field(
"diagnostics",
pa.struct(
[
pa.field("status", pa.string(), nullable=False),
pa.field(
"normalization",
pa.struct(
[
pa.field("changed", pa.bool_(), nullable=False),
pa.field(
"original_length", pa.int64(), nullable=False
),
]
),
nullable=False,
),
]
),
nullable=False,
),
pa.field(
"token_preview",
pa.list_(pa.field("item", token, nullable=False)),
nullable=False,
),
]
)
@udf(
input_schema=pa.schema([pa.field("text", pa.string(), nullable=False)]),
output_schema=pa.field("analysis", analysis, nullable=False),
)
def analyze(text):
return {"normalized_text": text}
output = analyze.registration_request.signature.output
assert output.kind == "named_struct"
assert [field.name for field in output.fields] == [
"normalized_text",
"has_content",
"metrics",
"diagnostics",
"token_preview",
]
metrics = json.loads(output.fields[2].arrow_type)
assert metrics == {
"type": "struct",
"fields": [
{
"name": "character_count",
"nullable": False,
"type": {"type": "int64"},
},
{
"name": "word_count",
"nullable": False,
"type": {"type": "int32"},
},
{
"name": "average_word_length",
"nullable": False,
"type": {"type": "float64"},
},
],
}
preview = json.loads(output.fields[4].arrow_type)
assert preview["type"] == "list"
assert preview["fields"][0]["type"]["type"] == "struct"
assert [field["name"] for field in preview["fields"][0]["type"]["fields"]] == [
"position",
"value",
"length",
]
def test_annotation_and_explicit_schema_validation_fail_closed():
with pytest.raises(TypeError, match="missing Function annotations"):
@@ -1086,72 +525,6 @@ def test_annotation_and_explicit_schema_validation_fail_closed():
def nullable_explicit(value):
return value
for invalid_field in [
pa.field("", pa.int32(), nullable=False),
pa.field("result", pa.int32(), nullable=False, metadata={"k": "v"}),
]:
with pytest.raises(TypeError, match="unsupported Arrow type"):
@udf(
input_schema=pa.schema([pa.field("value", pa.int64())]),
output_schema=pa.schema([invalid_field]),
)
def invalid_explicit_field(value):
return value
with pytest.raises(TypeError, match="unsupported Arrow type"):
@udf(
input_schema=pa.schema(
[pa.field("value", pa.int64(), metadata={"k": "v"})]
),
output_schema=pa.int64(),
)
def input_field_metadata(value):
return value
with pytest.raises(TypeError, match="unsupported Arrow type"):
@udf(
input_schema=pa.schema([pa.field("value", pa.int64())]),
output_schema=pa.field(
"result", pa.int64(), nullable=False, metadata={"k": "v"}
),
)
def scalar_output_field_metadata(value):
return value
struct_type = pa.struct([pa.field("value", pa.int64(), nullable=False)])
with pytest.raises(TypeError, match="unsupported Arrow type"):
@udf(
input_schema=pa.schema([pa.field("value", pa.int64())]),
output_schema=pa.field(
"result", struct_type, nullable=False, metadata={"k": "v"}
),
)
def struct_output_field_metadata(value):
return {"value": value}
for input_schema, output_schema in [
(
pa.schema([pa.field("value", pa.int64())], metadata={"k": "v"}),
pa.int64(),
),
(
pa.schema([pa.field("value", pa.int64())]),
pa.schema(
[pa.field("result", pa.int64(), nullable=False)],
metadata={"k": "v"},
),
),
]:
with pytest.raises(TypeError, match="schema metadata"):
@udf(input_schema=input_schema, output_schema=output_schema)
def schema_metadata(value):
return value
def test_local_function_catalog_operations_are_not_supported(tmp_path):
db = lancedb.connect(tmp_path)
@@ -1162,8 +535,6 @@ def test_local_function_catalog_operations_are_not_supported(tmp_path):
db.create_function_async(normalize_score)
with pytest.raises(NotImplementedError, match=message):
db.get_function("normalize_score", version="fv_exact")
with pytest.raises(NotImplementedError, match=message):
db.drop_function("normalize_score", version="fv_exact")
@contextlib.contextmanager
@@ -1209,12 +580,6 @@ def _mock_remote_function_catalog():
"version": "fv_exact",
}
response = state["version"]
elif self.path == "/v1/functions/drop":
assert body == {
"name": "normalize_score",
"version": "fv_exact",
}
response = {"dropped": True}
else:
status = 404
response = {"error": "not found"}
@@ -1273,40 +638,3 @@ def test_blocking_remote_registration_returns_function_version():
"/v1/functions/create",
"/v1/jobs/describe",
]
def test_remote_drop_function_sends_exact_version():
with _mock_remote_function_catalog() as (host, state):
db = lancedb.connect(
"db://dev",
api_key="fake",
host_override=host,
client_config={"retry_config": {"retries": 0}},
)
assert db.drop_function("normalize_score", version="fv_exact") is True
assert state["requests"] == [
(
"/v1/functions/drop",
{"name": "normalize_score", "version": "fv_exact"},
)
]
@pytest.mark.asyncio
async def test_async_remote_drop_function_sends_exact_version():
with _mock_remote_function_catalog() as (host, state):
db = await lancedb.connect_async(
"db://dev",
api_key="fake",
host_override=host,
client_config={"retry_config": {"retries": 0}},
)
assert await db.drop_function("normalize_score", version="fv_exact") is True
assert state["requests"] == [
(
"/v1/functions/drop",
{"name": "normalize_score", "version": "fv_exact"},
)
]
+49 -23
View File
@@ -786,6 +786,55 @@ async def test_add_async(mem_db_async: AsyncConnection):
assert await table.count_rows() == 3
@pytest.mark.skipif(not hasattr(pa, "json_"), reason="requires PyArrow JSON type")
@pytest.mark.asyncio
@pytest.mark.parametrize(
("values", "expected"),
[
([None], [None]),
([None, '{"k": 1}'], [None, '{"k":1}']),
(['{"k": 2}'], ['{"k":2}']),
],
)
async def test_add_list_of_dicts_to_json_column(
mem_db_async: AsyncConnection, values, expected
):
schema = pa.schema([pa.field("id", pa.int64()), pa.field("value", pa.json_())])
table = await mem_db_async.create_table("json_list_add", schema=schema)
await table.add([{"id": idx, "value": value} for idx, value in enumerate(values)])
rows = (await table.to_arrow()).sort_by("id").to_pylist()
assert [row["value"] for row in rows] == expected
@pytest.mark.skipif(not hasattr(pa, "json_"), reason="requires PyArrow JSON type")
@pytest.mark.asyncio
async def test_add_list_of_dicts_to_nested_json_column(
mem_db_async: AsyncConnection,
):
json_field = pa.field("value", pa.json_())
info_field = pa.field("info", pa.struct([json_field]))
info = pa.StructArray.from_arrays(
[pa.array(['{"seed": 0}'], type=pa.json_())], fields=[json_field]
)
seed = pa.Table.from_arrays(
[pa.array([0], type=pa.int64()), info],
schema=pa.schema([pa.field("id", pa.int64()), info_field]),
)
table = await mem_db_async.create_table("nested_json_list_add", data=seed)
await table.add([{"id": 1, "info": {"value": '{"k": 1}'}}])
await table.add([{"id": 2, "info": {"value": '{"k": 2}'}}], on_bad_vectors="fill")
rows = (await table.to_arrow()).sort_by("id").to_pylist()
assert rows == [
{"id": 0, "info": {"value": '{"seed":0}'}},
{"id": 1, "info": {"value": '{"k":1}'}},
{"id": 2, "info": {"value": '{"k":2}'}},
]
def test_add_overwrite_infers_vector_schema(mem_db: DBConnection):
"""Overwrite should infer vector columns the same way create_table does.
@@ -4087,29 +4136,6 @@ def test_computed_column_rejects_transforms_and_computed_together(tmp_path):
table.add_columns({"a": "x + 1"}, computed={"b": "x * 2"})
def test_computed_column_blob_projection_inherits_semantics(tmp_path):
schema = pa.schema([pa.field("id", pa.int64()), lancedb.blob("image")])
db = lancedb.connect(tmp_path)
table = db.create_table("computed_column_blob", schema=schema)
table.add(
[
{"id": 1, "image": b"hello"},
{"id": 2, "image": b""},
{"id": 3, "image": None},
]
)
table.add_columns(computed={"image_copy": "image", "second_copy": "image_copy"})
assert table.refresh_column("image_copy").rows_filled == 2
assert table.refresh_column("second_copy").rows_filled == 2
assert table.blob_columns() == ["image", "image_copy", "second_copy"]
hits = table.search().with_row_id(True).limit(10).to_arrow()
rows = sorted(zip(hits["id"].to_pylist(), hits["_rowid"].to_pylist()))
copied = table.fetch_blobs("second_copy", [row_id for _, row_id in rows])
assert copied.to_pylist() == [b"hello", b"", None]
@pytest.mark.asyncio
async def test_computed_column_async(tmp_path):
db = await lancedb.connect_async(tmp_path)
-11
View File
@@ -629,17 +629,6 @@ impl Connection {
})
}
pub fn drop_function(
self_: PyRef<'_, Self>,
name: String,
version: String,
) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.get_inner()?.clone();
future_into_py(self_.py(), async move {
inner.drop_function(name, version).await.infer_error()
})
}
pub fn list_jobs(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.get_inner()?.clone();
future_into_py(self_.py(), async move {
+1 -1
View File
@@ -1,6 +1,6 @@
[package]
name = "lancedb"
version = "0.38.0"
version = "0.38.0-beta.12"
edition.workspace = true
description = "LanceDB: A serverless, low-latency vector database for AI applications"
license.workspace = true
-15
View File
@@ -523,21 +523,6 @@ impl Connection {
.await
}
/// Drop one exact immutable Function version from the remote catalog.
///
/// Returns `true` when the server appended a Dropped transition and
/// `false` for an idempotent replay. Local databases return
/// [`Error::NotSupported`].
pub async fn drop_function(
&self,
name: impl AsRef<str>,
version: impl AsRef<str>,
) -> Result<bool> {
self.internal
.drop_function(name.as_ref(), version.as_ref())
.await
}
/// Rename a table in the database.
///
/// This is only supported in LanceDB Cloud.
-4
View File
@@ -307,10 +307,6 @@ pub trait Database:
) -> Result<crate::function::FunctionVersion> {
function_catalog_not_supported()
}
/// Drop one exact immutable Function version from the remote catalog.
async fn drop_function(&self, _name: &str, _version: &str) -> Result<bool> {
function_catalog_not_supported()
}
/// A [`crate::job::Job`] handle for a server-side job by id, suitable for
/// waiting on or cancelling the job. The handle is constructed without a
/// server round trip; an unknown id surfaces when the handle is used.
+3 -10
View File
@@ -539,7 +539,9 @@ impl Database for LanceNamespaceDatabase {
self.namespace
.drop_table(drop_request)
.await
.map_err(|e| map_namespace_lance_error(e, name))?;
.map_err(|e| Error::Runtime {
message: format!("Failed to drop table: {}", e),
})?;
Ok(())
}
@@ -1493,15 +1495,6 @@ mod tests {
.expect("Failed to list tables");
assert!(!table_names_after.contains(&"drop_test".to_string()));
let error = conn
.drop_table("drop_test", &["test_ns".into()])
.await
.expect_err("dropping a missing table should fail");
assert!(
matches!(error, Error::TableNotFound { ref name, .. } if name == "drop_test"),
"expected TableNotFound, got: {error:?}"
);
// Verify: Cannot open dropped table
let open_result = conn.open_table("drop_test").execute().await;
assert!(open_result.is_err());
+27 -153
View File
@@ -15,9 +15,6 @@ use serde_json::Value;
use crate::{Error, Result};
/// Semantic Function type for a Blob v2 value.
pub const FUNCTION_BLOB_V2_TYPE: &str = "blob_v2";
fn invalid_json(error: impl std::fmt::Display) -> Error {
Error::InvalidInput {
message: format!("invalid remote Function JSON: {error}"),
@@ -210,33 +207,6 @@ pub enum PythonRuntimeSpec {
environment: PythonEnvironmentSpec,
env: BTreeMap<String, String>,
},
/// The GPU-enabled Sophon-managed Python runtime.
///
/// # Examples
///
/// ```
/// use std::collections::BTreeMap;
/// use lancedb::function::{PythonEnvironmentSpec, PythonRuntimeSpec};
///
/// let runtime = PythonRuntimeSpec::PythonV2 {
/// python_version: "3.12".to_string(),
/// environment: PythonEnvironmentSpec {
/// kind: "pip".to_string(),
/// packages: vec!["cupy-cuda12x".to_string()],
/// channels: Vec::new(),
/// path: None,
/// modules: Vec::new(),
/// image: None,
/// },
/// env: BTreeMap::new(),
/// };
/// assert!(runtime.requires_gpu());
/// ```
PythonV2 {
python_version: String,
environment: PythonEnvironmentSpec,
env: BTreeMap<String, String>,
},
/// A runtime kind introduced by a newer server.
///
/// Unknown payload fields are intentionally not retained because the
@@ -249,27 +219,22 @@ impl PythonRuntimeSpec {
pub fn kind(&self) -> &str {
match self {
Self::Python { .. } => "python",
Self::PythonV2 { .. } => "python_v2",
Self::Unrecognized { kind } => kind,
}
}
/// The Python version for a known Python runtime, or `None` for an unknown kind.
/// The Python version for the V1 runtime, or `None` for an unknown kind.
pub fn python_version(&self) -> Option<&str> {
match self {
Self::Python { python_version, .. } | Self::PythonV2 { python_version, .. } => {
Some(python_version)
}
Self::Python { python_version, .. } => Some(python_version),
Self::Unrecognized { .. } => None,
}
}
/// The Python environment for a known Python runtime, or `None` for an unknown kind.
/// The Python environment for the V1 runtime, or `None` for an unknown kind.
pub fn environment(&self) -> Option<&PythonEnvironmentSpec> {
match self {
Self::Python { environment, .. } | Self::PythonV2 { environment, .. } => {
Some(environment)
}
Self::Python { environment, .. } => Some(environment),
Self::Unrecognized { .. } => None,
}
}
@@ -277,73 +242,38 @@ impl PythonRuntimeSpec {
/// Environment variables, or `None` for an unknown kind.
pub fn env(&self) -> Option<&BTreeMap<String, String>> {
match self {
Self::Python { env, .. } | Self::PythonV2 { env, .. } => Some(env),
Self::Python { env, .. } => Some(env),
Self::Unrecognized { .. } => None,
}
}
/// Whether the runtime requires a GPU selected by the execution platform.
pub fn requires_gpu(&self) -> bool {
matches!(self, Self::PythonV2 { .. })
}
}
#[derive(Deserialize)]
struct PythonRuntimeV1Wire {
python_version: String,
environment: PythonEnvironmentSpec,
struct PythonRuntimeWire {
kind: String,
#[serde(default)]
python_version: Option<String>,
#[serde(default)]
environment: Option<PythonEnvironmentSpec>,
#[serde(default)]
env: BTreeMap<String, String>,
#[serde(default)]
gpu: Option<Value>,
}
#[derive(Deserialize)]
struct PythonRuntimeV2Wire {
python_version: String,
environment: PythonEnvironmentSpec,
#[serde(default)]
env: BTreeMap<String, String>,
gpu: bool,
}
impl<'de> Deserialize<'de> for PythonRuntimeSpec {
fn deserialize<D: Deserializer<'de>>(deserializer: D) -> std::result::Result<Self, D::Error> {
let value = Value::deserialize(deserializer)?;
let kind = value
.get("kind")
.ok_or_else(|| de::Error::missing_field("kind"))?
.as_str()
.ok_or_else(|| de::Error::custom("runtime.kind must be a string"))?
.to_string();
match kind.as_str() {
"python" => {
let wire: PythonRuntimeV1Wire =
serde_json::from_value(value).map_err(de::Error::custom)?;
if wire.gpu.is_some() {
return Err(de::Error::custom(
"python runtime with gpu requires kind='python_v2'",
));
}
Ok(Self::Python {
python_version: wire.python_version,
environment: wire.environment,
env: wire.env,
})
}
"python_v2" => {
let wire: PythonRuntimeV2Wire =
serde_json::from_value(value).map_err(de::Error::custom)?;
if !wire.gpu {
return Err(de::Error::custom("runtime.gpu must be true"));
}
Ok(Self::PythonV2 {
python_version: wire.python_version,
environment: wire.environment,
env: wire.env,
})
}
_ => Ok(Self::Unrecognized { kind }),
let wire = PythonRuntimeWire::deserialize(deserializer)?;
if wire.kind == "python" {
Ok(Self::Python {
python_version: wire
.python_version
.ok_or_else(|| de::Error::missing_field("python_version"))?,
environment: wire
.environment
.ok_or_else(|| de::Error::missing_field("environment"))?,
env: wire.env,
})
} else {
Ok(Self::Unrecognized { kind: wire.kind })
}
}
}
@@ -357,8 +287,6 @@ impl Serialize for PythonRuntimeSpec {
environment: &'a PythonEnvironmentSpec,
#[serde(skip_serializing_if = "BTreeMap::is_empty")]
env: &'a BTreeMap<String, String>,
#[serde(skip_serializing_if = "Option::is_none")]
gpu: Option<bool>,
}
#[derive(Serialize)]
@@ -376,19 +304,6 @@ impl Serialize for PythonRuntimeSpec {
python_version,
environment,
env,
gpu: None,
}
.serialize(serializer),
Self::PythonV2 {
python_version,
environment,
env,
} => PythonRuntimeRef {
kind: "python_v2",
python_version,
environment,
env,
gpu: Some(true),
}
.serialize(serializer),
Self::Unrecognized { kind } => UnrecognizedRuntimeRef { kind }.serialize(serializer),
@@ -398,8 +313,8 @@ impl Serialize for PythonRuntimeSpec {
/// Immutable Function version returned by the Enterprise catalog.
///
/// The GPU execution requirement is part of this identity. CPU and memory sizing,
/// priority, concurrency, and retry policy belong to the execution platform.
/// Scheduling resources, priority, concurrency, and retry policy belong to
/// the submitting Job and are not part of this identity.
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub struct FunctionVersion {
name: String,
@@ -674,7 +589,7 @@ impl_json!(RefreshColumnResult);
#[cfg(test)]
mod conda_environment_tests {
use super::{PythonEnvironmentSpec, PythonRuntimeSpec};
use super::PythonEnvironmentSpec;
#[test]
fn conda_channels_round_trip_and_pip_stays_bare() {
@@ -693,45 +608,4 @@ mod conda_environment_tests {
serde_json::from_str(r#"{"kind":"pip","packages":["numpy"]}"#).unwrap();
assert!(!serde_json::to_string(&pip).unwrap().contains("channels"));
}
#[test]
fn gpu_python_runtime_marker_round_trips_and_validates() {
let runtime: PythonRuntimeSpec = serde_json::from_str(
r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"},"gpu":true}"#,
)
.unwrap();
assert_eq!(runtime.kind(), "python_v2");
assert!(runtime.requires_gpu());
assert_eq!(
super::canonical_json(&runtime).unwrap(),
r#"{"environment":{"kind":"pip"},"gpu":true,"kind":"python_v2","python_version":"3.12"}"#
);
for invalid in [
r#"{"kind":"python","python_version":"3.12","environment":{"kind":"pip"},"gpu":true}"#,
r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"}}"#,
r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"},"gpu":1}"#,
r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"},"gpu":false}"#,
r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"},"gpu":"true"}"#,
r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"},"gpu":"H100"}"#,
] {
assert!(serde_json::from_str::<PythonRuntimeSpec>(invalid).is_err());
}
}
#[test]
fn unknown_runtime_discards_payload_before_known_field_validation() {
for encoded in [
r#"{"kind":"python_v3","gpu":{"model":"H100"}}"#,
r#"{"kind":"python_v3","resources":[]}"#,
r#"{"kind":"python_v3","python_version":3.15,"environment":{"kind":[]}}"#,
] {
let runtime: PythonRuntimeSpec = serde_json::from_str(encoded).unwrap();
assert_eq!(runtime.kind(), "python_v3");
assert_eq!(
super::canonical_json(&runtime).unwrap(),
r#"{"kind":"python_v3"}"#
);
}
}
}
-38
View File
@@ -533,11 +533,6 @@ struct RemoteListJobsResponse {
page_token: Option<String>,
}
#[derive(serde::Deserialize)]
struct RemoteDropFunctionResponse {
dropped: bool,
}
/// Bound on `list_jobs` page walking; a warning is logged when the listing
/// is truncated at this many pages.
const MAX_LIST_JOBS_PAGES: usize = 100;
@@ -588,20 +583,6 @@ impl<S: HttpSend> Database for RemoteDatabase<S> {
response.json().await.err_to_http(request_id)
}
async fn drop_function(&self, name: &str, version: &str) -> Result<bool> {
let req = self
.client
.post("/v1/functions/drop")
.json(&serde_json::json!({
"name": name,
"version": version,
}));
let (request_id, response) = self.client.send(req).await?;
let response = self.client.check_response(&request_id, response).await?;
let response: RemoteDropFunctionResponse = response.json().await.err_to_http(request_id)?;
Ok(response.dropped)
}
fn job(&self, job_id: &str) -> Result<crate::job::Job> {
Ok(crate::job::Job::new(Box::new(super::job::RemoteJob::new(
self.client.clone(),
@@ -2708,25 +2689,6 @@ mod tests {
assert_eq!(version.version(), "fv_01K3EXACT");
}
#[tokio::test]
async fn test_drop_function_sends_exact_version_and_decodes_replay() {
let conn = Connection::new_with_handler(|request| {
assert_eq!(request.method(), &reqwest::Method::POST);
assert_eq!(request.url().path(), "/v1/functions/drop");
let body: serde_json::Value =
serde_json::from_slice(request.body().unwrap().as_bytes().unwrap()).unwrap();
assert_eq!(
body,
serde_json::json!({"name": "embed", "version": "fv_01K3EXACT"})
);
http::Response::builder()
.status(200)
.body(r#"{"dropped":false}"#)
.unwrap()
});
assert!(!conn.drop_function("embed", "fv_01K3EXACT").await.unwrap());
}
#[tokio::test]
async fn test_conn_job_waits_to_done() {
let polls = Arc::new(AtomicUsize::new(0));
+7 -93
View File
@@ -3180,8 +3180,8 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
self.schema().await?.as_ref(),
"schema evolution",
)?;
// The server plans the declaration against its table schema, including
// Blob v2 semantics inherited by a direct field projection.
// The server plans the declaration: expression validation, type
// inference and the persisted binding all happen there.
let entries = columns
.iter()
.map(
@@ -5734,8 +5734,9 @@ mod tests {
))
.execute()
.await;
let Err(err) = result else {
panic!("legacy remote query unexpectedly succeeded")
let err = match result {
Ok(_) => panic!("legacy remote query unexpectedly succeeded"),
Err(err) => err,
};
assert!(
@@ -7387,8 +7388,8 @@ mod tests {
assert_eq!(result.version, if old_server { 0 } else { 43 });
}
/// A declaration is sent as `{name, computed}` for the server to plan; the
/// client never types the expression itself.
/// A declaration is sent as `{name, computed}` entries for the server to
/// plan; the client never types the expression itself.
#[tokio::test]
async fn test_add_computed_columns_sends_the_expression() {
let table = Table::new_with_handler("my_table", |request| match request.url().path() {
@@ -7464,93 +7465,6 @@ mod tests {
assert_eq!(result.version, 8);
}
#[tokio::test]
async fn test_add_function_column_allows_an_existing_binding() {
let binding = crate::function::FunctionBinding::from_json(include_str!(
"../../tests/fixtures/first_class_functions/v1/remote_function_binding.json"
))
.unwrap();
let binding_metadata = crate::table::computed_columns::function_bindings_metadata(
std::slice::from_ref(&binding),
)
.unwrap();
let mut fields = vec![
Field::new("title", DataType::Utf8, true),
Field::new("body", DataType::Utf8, true),
];
fields.extend(binding.outputs().iter().map(|output| {
let data_type = match output.arrow_type.as_str() {
"utf8" => DataType::Utf8,
"int64" => DataType::Int64,
other => panic!("unexpected fixture output type {other}"),
};
Field::new(&output.output_name, data_type, true).with_metadata(
crate::table::computed_columns::function_computed_column_metadata(
binding.binding_id(),
output.output_ordinal,
&["title".into(), "body".into()],
),
)
}));
let schema = Schema::new_with_metadata(
fields,
HashMap::from([(
crate::table::computed_columns::FUNCTION_BINDINGS_META_KEY.to_string(),
binding_metadata,
)]),
);
let table =
Table::new_with_handler("my_table", move |request| match request.url().path() {
"/v1/table/my_table/describe/" => http::Response::builder()
.status(200)
.body(describe_response(&schema))
.unwrap(),
"/v1/table/my_table/add_columns/" => {
let actual: serde_json::Value =
serde_json::from_slice(request.body().unwrap().as_bytes().unwrap())
.unwrap();
assert_eq!(
actual["new_columns"],
serde_json::json!([
{"name":"secondary_text","all_null":true},
{"name":"secondary_token_count","all_null":true}
])
);
http::Response::builder()
.status(200)
.body(r#"{"version":10}"#.to_string())
.unwrap()
}
path => panic!("Unexpected path: {path}"),
});
let application = crate::function::FunctionApplication::from_json(
r#"{
"function":{"name":"text_features","version":"fv_01K3TEXT"},
"inputs":[
{"parameter":"title","kind":"column","value":{"path":"title"}},
{"parameter":"body","kind":"column","value":{"path":"body"}}
],
"output":{"kind":"named_struct","fields":[
{"name":"normalized_text","arrow_type":"utf8","nullable":false},
{"name":"token_count","arrow_type":"int64","nullable":false}
]},
"columns":{
"normalized_text":"secondary_text",
"token_count":"secondary_token_count"
}
}"#,
)
.unwrap();
let result = table
.add_columns()
.function(application)
.execute()
.await
.unwrap();
assert_eq!(result.version, 10);
}
#[tokio::test]
async fn test_add_fixed_size_list_function_column_declares_the_vector_type() {
let table = Table::new_with_handler("my_table", |request| {
+2 -9
View File
@@ -750,8 +750,8 @@ pub trait BaseTable: std::fmt::Display + std::fmt::Debug + Send + Sync {
/// Declare computed columns, each defined by a SQL expression.
///
/// Where the declaration is planned depends on the backend: a local table
/// validates and types the expression itself, while a remote one sends the
/// expression for the server to plan.
/// validates and types the expression itself, a remote one sends the text
/// for the server to plan.
async fn add_computed_columns(
&self,
_columns: &[(String, String)],
@@ -5763,13 +5763,6 @@ mod tests {
assert!(index_bytes > 0);
assert_eq!(with_index, data_only + index_bytes);
// Release builds reject unstable overlay datasets unless explicitly opted in.
if !lance_table::feature_flags::can_read_dataset(
lance_table::feature_flags::FLAG_UNSTABLE_DATA_OVERLAY_FILES,
) {
return;
}
// Commit an overlay file supplying new `foo` values for the first three
// rows of fragment 0. There is no high-level API that writes overlays
// yet, so write the overlay's data file and commit the `DataOverlay`
File diff suppressed because it is too large Load Diff
+7 -515
View File
@@ -29,14 +29,10 @@
//! inputs masked to null first, so a poison value in a row nobody is filling
//! cannot fail the refresh.
use std::collections::HashSet;
use std::sync::Arc;
use arrow_array::{
Array, ArrayRef, BooleanArray, LargeBinaryArray, RecordBatch, RecordBatchOptions, StructArray,
new_null_array,
};
use arrow_schema::{DataType, Field as ArrowField, Schema as ArrowSchema};
use arrow_array::{ArrayRef, BooleanArray, RecordBatch, RecordBatchOptions};
use arrow_schema::Schema as ArrowSchema;
use datafusion_expr::ColumnarValue;
use futures::{Stream, StreamExt, TryStreamExt};
use lance::Dataset;
@@ -44,7 +40,7 @@ use lance::dataset::WriteDestination;
use lance::dataset::fragment::FileFragment;
use lance::dataset::transaction::Operation;
use lance_core::ROW_ID;
use lance_core::datatypes::{BlobHandling, Schema as LanceSchema};
use lance_core::datatypes::Schema as LanceSchema;
use serde::{Deserialize, Serialize};
use super::computed_columns::{BoundExpression, ComputedColumnKind, computed_column_from_field};
@@ -108,7 +104,6 @@ async fn execute_refresh_column_with_source(
fields: vec![field.clone()],
metadata: Default::default(),
};
let output_is_blob = field.is_blob_v2();
let mut rows_filled = 0u64;
let mut replacements = Vec::new();
@@ -118,8 +113,7 @@ async fn execute_refresh_column_with_source(
continue;
}
rows_filled += gained;
let values =
fill_stream(&dataset, &fragment, bound.clone(), column, output_is_blob).await?;
let values = fill_stream(&dataset, &fragment, bound.clone(), column).await?;
replacements.push(fragment.write_columns(values, &column_schema).await?);
}
@@ -300,15 +294,12 @@ fn evaluation_batch(
mask_out: Option<&BooleanArray>,
) -> lance_core::Result<RecordBatch> {
let mut columns = Vec::with_capacity(bound.roots.len());
let mut fields = Vec::with_capacity(bound.roots.len());
for name in &bound.roots {
let index = batch.schema_ref().index_of(name).map_err(|_| {
let column = batch.column_by_name(name).ok_or_else(|| {
lance_core::Error::invalid_input(format!(
"refreshing a computed column read no {name} column"
))
})?;
let column = batch.column(index);
fields.push(batch.schema_ref().field(index).clone());
// Rows outside the mask must not reach the expression: a value in a
// deleted or already-filled row can be one it would choke on.
columns.push(match mask_out {
@@ -317,7 +308,7 @@ fn evaluation_batch(
});
}
Ok(RecordBatch::try_new_with_options(
Arc::new(ArrowSchema::new(fields)),
bound.read_schema.clone(),
columns,
&RecordBatchOptions::new().with_row_count(Some(batch.num_rows())),
)?)
@@ -338,99 +329,6 @@ fn evaluate(bound: &BoundExpression, batch: &RecordBatch) -> lance_core::Result<
}
}
fn materialized_blob_ids(schema: &LanceSchema, paths: &[String]) -> Result<HashSet<u32>> {
paths
.iter()
.map(|path| {
let field = schema
.resolve(path)
.and_then(|fields| fields.last().copied())
.ok_or_else(|| Error::InvalidInput {
message: format!("computed Blob input '{path}' no longer exists"),
})?;
if !field.is_blob_v2() {
return Err(Error::InvalidInput {
message: format!("computed Blob input '{path}' is no longer Blob v2"),
});
}
u32::try_from(field.id).map_err(|_| Error::InvalidInput {
message: format!(
"computed Blob input '{path}' has invalid field id {}",
field.id
),
})
})
.collect()
}
fn configure_blob_inputs(
scanner: &mut lance::dataset::scanner::Scanner,
schema: &LanceSchema,
bound: &BoundExpression,
extra_blob_id: Option<u32>,
) -> Result<()> {
let mut ids = materialized_blob_ids(schema, &bound.blob_paths)?;
ids.extend(extra_blob_id);
scanner.blob_handling(BlobHandling::SomeBlobsBinary(ids));
Ok(())
}
fn blob_array_from_binary(
array: &ArrayRef,
target_field: &ArrowField,
) -> lance_core::Result<ArrayRef> {
let values = array
.as_any()
.downcast_ref::<LargeBinaryArray>()
.ok_or_else(|| {
lance_core::Error::invalid_input(format!(
"a Blob v2 computed output produced {}, expected LargeBinary",
array.data_type()
))
})?;
let mut builder = lance::blob::BlobArrayBuilder::new(values.len());
for index in 0..values.len() {
if values.is_null(index) {
builder.push_null()?;
} else {
builder.push_bytes(values.value(index))?;
}
}
let minimal = builder.finish()?;
let minimal = minimal
.as_any()
.downcast_ref::<StructArray>()
.ok_or_else(|| lance_core::Error::internal("Blob builder returned a non-struct array"))?;
let DataType::Struct(target_fields) = target_field.data_type() else {
return Err(lance_core::Error::invalid_input(format!(
"Blob v2 output field '{}' has non-struct type {}",
target_field.name(),
target_field.data_type()
)));
};
let columns = target_fields
.iter()
.map(|field| match field.name().as_str() {
"data" | "uri" => minimal
.column_by_name(field.name())
.cloned()
.ok_or_else(|| {
lance_core::Error::internal(format!("Blob builder omitted '{}'", field.name()))
}),
"position" | "size" => Ok(new_null_array(field.data_type(), minimal.len())),
name => Err(lance_core::Error::invalid_input(format!(
"Blob v2 output field '{}' has unsupported logical child '{name}'",
target_field.name()
))),
})
.collect::<lance_core::Result<Vec<_>>>()?;
Ok(Arc::new(StructArray::try_new(
target_fields.clone(),
columns,
minimal.nulls().cloned(),
)?))
}
/// How many rows of one fragment would gain a value.
///
/// Scans only the unfilled live rows -- deleted rows never reach the
@@ -449,7 +347,6 @@ async fn count_fragment_gains(
.with_row_id()
.filter(&format!("{} IS NULL", quote_identifier(column)))?
.project(&bound.roots)?;
configure_blob_inputs(&mut scanner, dataset.schema(), bound, None)?;
let mut gained = 0u64;
let mut batches = scanner.try_into_stream().await?;
@@ -471,7 +368,6 @@ async fn fill_stream(
fragment: &FileFragment,
bound: Arc<BoundExpression>,
column: &str,
output_is_blob: bool,
) -> Result<impl Stream<Item = lance_core::Result<RecordBatch>> + Send + use<>> {
let mut projection: Vec<String> = bound.roots.clone();
projection.push(column.to_string());
@@ -481,20 +377,6 @@ async fn fill_stream(
.with_row_id()
.include_deleted_rows()
.project(&projection)?;
let output_blob_id = output_is_blob
.then(|| {
dataset
.schema()
.field(column)
.and_then(|field| u32::try_from(field.id).ok())
})
.flatten();
configure_blob_inputs(
&mut scanner,
dataset.schema(),
bound.as_ref(),
output_blob_id,
)?;
let projected = Arc::new(ArrowSchema::new(vec![
ArrowSchema::from(dataset.schema())
@@ -530,11 +412,6 @@ async fn fill_stream(
let computed = evaluate(&bound, &evaluation_batch(&batch, &bound, Some(&keep))?)?;
let merged = arrow_select::zip::zip(&fill, &computed, existing)?;
let merged = if output_is_blob {
blob_array_from_binary(&merged, projected.field(0))?
} else {
merged
};
Ok(RecordBatch::try_new(projected.clone(), vec![merged])?)
}))
}
@@ -543,12 +420,8 @@ async fn fill_stream(
mod tests {
use std::sync::Arc;
use arrow_array::{
Array, ArrayRef, Int32Array, LargeBinaryArray, RecordBatch, StructArray, record_batch,
};
use arrow_schema::Field as ArrowField;
use arrow_array::{Int32Array, record_batch};
use futures::TryStreamExt;
use lance_core::ROW_ID;
use crate::connect;
use crate::query::{ExecutableQuery, QueryBase, Select};
@@ -604,25 +477,6 @@ mod tests {
table.add(batch).execute().await.unwrap();
}
#[test]
fn test_blob_output_matches_complete_logical_field() {
let values: ArrayRef = Arc::new(LargeBinaryArray::from(vec![
Some(b"hello".as_slice()),
None,
]));
let field = ArrowField::new(
"image",
lance_core::datatypes::BLOB_V2_LOGICAL_TYPE.clone(),
true,
);
let output = super::blob_array_from_binary(&values, &field).unwrap();
assert_eq!(output.data_type(), field.data_type());
let output = output.as_any().downcast_ref::<StructArray>().unwrap();
assert_eq!(output.column_by_name("position").unwrap().null_count(), 2);
assert_eq!(output.column_by_name("size").unwrap().null_count(), 2);
}
/// The gate's reproducer: `b = coalesce(a, 0)` refreshed before `a`
/// must not bake zeros from `a`'s placeholder null. It is refused, and
/// names the input, until `a` is filled -- after every append too.
@@ -1310,366 +1164,4 @@ mod tests {
let err = table.refresh_column("embedding").await.unwrap_err();
assert!(matches!(err, Error::NotSupported { message } if message.contains("udf")));
}
fn blob_batch(ids: Vec<i32>, payloads: Vec<Option<&[u8]>>) -> RecordBatch {
use arrow_array::Int32Array;
use arrow_schema::{Field, Schema};
let mut builder = lance::blob::BlobArrayBuilder::new(payloads.len());
for payload in payloads {
match payload {
Some(payload) => builder.push_bytes(payload).unwrap(),
None => builder.push_null().unwrap(),
}
}
RecordBatch::try_new(
Arc::new(Schema::new(vec![
Field::new("id", arrow_schema::DataType::Int32, false),
crate::blob("image", true),
])),
vec![Arc::new(Int32Array::from(ids)), builder.finish().unwrap()],
)
.unwrap()
}
async fn create_blob_table(path: &std::path::Path, batch: RecordBatch) -> Table {
let conn = connect(path.to_str().unwrap()).execute().await.unwrap();
conn.create_table("blobs", batch).execute().await.unwrap()
}
#[tokio::test]
async fn test_refresh_inherits_and_publishes_blob_output() {
use arrow_array::UInt64Array;
use lance_arrow::{
BLOB_DEDICATED_SIZE_THRESHOLD_META_KEY, BLOB_INLINE_SIZE_THRESHOLD_META_KEY,
};
use lance_core::datatypes::BlobKind;
use crate::table::schema_evolution::FieldMetadataUpdate;
let tmp = tempfile::tempdir().unwrap();
let table = create_blob_table(
tmp.path(),
blob_batch(
vec![1, 2, 3, 4],
vec![Some(b"hello"), Some(b"ab"), Some(b""), None],
),
)
.await;
table
.add_columns()
.computed("image_copy", "image")
.execute()
.await
.unwrap();
table
.update_field_metadata(&[FieldMetadataUpdate::new("image_copy")
.set(BLOB_INLINE_SIZE_THRESHOLD_META_KEY, "1")
.set(BLOB_DEDICATED_SIZE_THRESHOLD_META_KEY, "4")])
.await
.unwrap();
let first_refresh = table.refresh_column("image_copy").await.unwrap();
assert_eq!(first_refresh.rows_filled, 3);
assert_eq!(
table.blob_columns().await.unwrap(),
vec!["image".to_string(), "image_copy".to_string()]
);
let batches = table
.query()
.with_row_id()
.execute()
.await
.unwrap()
.try_collect::<Vec<_>>()
.await
.unwrap();
let batch = arrow_select::concat::concat_batches(&batches[0].schema(), &batches).unwrap();
assert!(
batch
.column_by_name("image_copy")
.unwrap()
.as_any()
.is::<arrow_array::StructArray>()
);
let row_ids = batch
.column_by_name(ROW_ID)
.unwrap()
.as_any()
.downcast_ref::<UInt64Array>()
.unwrap()
.values()
.to_vec();
let original = table.fetch_blobs("image", &row_ids).await.unwrap();
let copied = table.fetch_blobs("image_copy", &row_ids).await.unwrap();
assert_eq!(original, copied);
let ids = batch
.column_by_name("id")
.unwrap()
.as_any()
.downcast_ref::<Int32Array>()
.unwrap();
let files = table
.fetch_blob_files("image_copy", &row_ids)
.await
.unwrap();
let mut layouts = ids
.values()
.iter()
.copied()
.zip(files)
.map(|(id, file)| (id, file.and_then(|file| file.kind())))
.collect::<Vec<_>>();
layouts.sort_by_key(|(id, _)| *id);
assert_eq!(
layouts,
vec![
(1, Some(BlobKind::Dedicated)),
(2, Some(BlobKind::Packed)),
(3, Some(BlobKind::Inline)),
(4, None),
]
);
table
.add(blob_batch(vec![5], vec![Some(b"appended")]))
.execute()
.await
.unwrap();
table
.optimize(crate::table::OptimizeAction::Compact {
options: crate::table::CompactionOptions::default(),
remap_options: None,
})
.await
.unwrap();
assert_eq!(
table
.refresh_column("image_copy")
.await
.unwrap()
.rows_filled,
1
);
assert_eq!(
table
.refresh_column("image_copy")
.await
.unwrap()
.rows_filled,
0
);
table.checkout(first_refresh.version).await.unwrap();
assert_eq!(table.count_rows(None).await.unwrap(), 4);
assert_eq!(
table.blob_columns().await.unwrap(),
vec!["image".to_string(), "image_copy".to_string()]
);
table.checkout_latest().await.unwrap();
}
#[tokio::test]
async fn test_refresh_inherits_nested_struct_blob_input() {
use arrow_array::{Int32Array, StructArray, UInt64Array};
use arrow_schema::{DataType, Field, Fields, Schema};
let tmp = tempfile::tempdir().unwrap();
let mut blob_builder = lance::blob::BlobArrayBuilder::new(2);
blob_builder.push_bytes(b"nested").unwrap();
blob_builder.push_null().unwrap();
let blob_field = crate::blob("image", true);
let metadata_fields = Fields::from(vec![blob_field.clone()]);
let metadata = StructArray::new(
metadata_fields.clone(),
vec![blob_builder.finish().unwrap()],
None,
);
let batch = RecordBatch::try_new(
Arc::new(Schema::new(vec![
Field::new("id", DataType::Int32, false),
Field::new("metadata", DataType::Struct(metadata_fields), true),
])),
vec![Arc::new(Int32Array::from(vec![1, 2])), Arc::new(metadata)],
)
.unwrap();
let table = create_blob_table(tmp.path(), batch).await;
table
.add_columns()
.computed("payload_copy", "metadata.image")
.execute()
.await
.unwrap();
assert_eq!(
table
.refresh_column("payload_copy")
.await
.unwrap()
.rows_filled,
1
);
assert_eq!(
table.blob_columns().await.unwrap(),
vec!["metadata.image".to_string(), "payload_copy".to_string()]
);
let batches = table
.query()
.with_row_id()
.execute()
.await
.unwrap()
.try_collect::<Vec<_>>()
.await
.unwrap();
let row_ids = batches[0]
.column_by_name(ROW_ID)
.unwrap()
.as_any()
.downcast_ref::<UInt64Array>()
.unwrap()
.values();
let payloads = table.fetch_blobs("payload_copy", row_ids).await.unwrap();
assert_eq!(payloads.value(0), b"nested");
assert!(payloads.is_null(1));
}
#[tokio::test]
async fn test_refresh_preserves_list_shape_when_materializing_blob_input() {
use arrow_array::{Int32Array, ListArray};
use arrow_buffer::{OffsetBuffer, ScalarBuffer};
use arrow_schema::{DataType, Field, Schema};
let tmp = tempfile::tempdir().unwrap();
let mut blob_builder = lance::blob::BlobArrayBuilder::new(3);
blob_builder.push_bytes(b"a").unwrap();
blob_builder.push_bytes(b"bb").unwrap();
blob_builder.push_null().unwrap();
let item = Arc::new(crate::blob("item", true));
let images = ListArray::new(
item.clone(),
OffsetBuffer::new(ScalarBuffer::from(vec![0, 2, 3])),
blob_builder.finish().unwrap(),
None,
);
let batch = RecordBatch::try_new(
Arc::new(Schema::new(vec![
Field::new("id", DataType::Int32, false),
Field::new("images", DataType::List(item), true),
])),
vec![Arc::new(Int32Array::from(vec![1, 2])), Arc::new(images)],
)
.unwrap();
let table = create_blob_table(tmp.path(), batch).await;
table
.add_columns()
.computed("image_payloads", "images")
.execute()
.await
.unwrap();
assert_eq!(
table
.refresh_column("image_payloads")
.await
.unwrap()
.rows_filled,
2
);
let batches = table
.query()
.select(Select::columns(&["image_payloads"]))
.execute()
.await
.unwrap()
.try_collect::<Vec<_>>()
.await
.unwrap();
let output = batches[0]
.column_by_name("image_payloads")
.unwrap()
.as_any()
.downcast_ref::<ListArray>()
.unwrap();
assert_eq!(output.value_offsets(), &[0, 2, 3]);
assert!(output.values().as_any().is::<LargeBinaryArray>());
}
#[tokio::test]
async fn test_refresh_inherits_external_blob_input() {
use arrow_array::{Int32Array, StringArray, UInt64Array};
use arrow_schema::{DataType, Field, Schema};
let tmp = tempfile::tempdir().unwrap();
let payload = b"external-payload";
let path = tmp.path().join("payload.bin");
std::fs::write(&path, payload).unwrap();
let uri = url::Url::from_file_path(path).unwrap().to_string();
let conn = connect(tmp.path().join("db").to_str().unwrap())
.execute()
.await
.unwrap();
let table = conn
.create_empty_table(
"external",
Arc::new(Schema::new(vec![
Field::new("id", DataType::Int32, false),
crate::blob("image", true),
])),
)
.execute()
.await
.unwrap();
let batch = RecordBatch::try_new(
Arc::new(Schema::new(vec![
Field::new("id", DataType::Int32, false),
Field::new("image", DataType::Utf8, true),
])),
vec![
Arc::new(Int32Array::from(vec![1])),
Arc::new(StringArray::from(vec![Some(uri)])),
],
)
.unwrap();
table
.add(batch)
.allow_external_blob_outside_bases(true)
.execute()
.await
.unwrap();
table
.add_columns()
.computed("payload_copy", "image")
.execute()
.await
.unwrap();
assert_eq!(
table
.refresh_column("payload_copy")
.await
.unwrap()
.rows_filled,
1
);
let batches = table
.query()
.with_row_id()
.execute()
.await
.unwrap()
.try_collect::<Vec<_>>()
.await
.unwrap();
let row_ids = batches[0]
.column_by_name(ROW_ID)
.unwrap()
.as_any()
.downcast_ref::<UInt64Array>()
.unwrap()
.values();
let payloads = table.fetch_blobs("payload_copy", row_ids).await.unwrap();
assert_eq!(payloads.value(0), payload);
}
}
@@ -45,11 +45,7 @@ async fn local_function_catalog_operations_return_stable_not_supported() {
.get_function("normalize_score", "fv_exact")
.await
.unwrap_err();
let drop_error = connection
.drop_function("normalize_score", "fv_exact")
.await
.unwrap_err();
for error in [create_error, lookup_error, drop_error] {
for error in [create_error, lookup_error] {
assert!(matches!(
error,
Error::NotSupported { message }
@@ -78,12 +78,6 @@
"type": "utf8"
}
},
{
"arrow_type": "large_utf8",
"json": {
"type": "large_utf8"
}
},
{
"arrow_type": "binary",
"json": {
@@ -177,21 +171,6 @@
]
}
},
{
"arrow_type": "list<large_utf8>",
"json": {
"type": "list",
"fields": [
{
"name": "item",
"nullable": false,
"type": {
"type": "large_utf8"
}
}
]
}
},
{
"arrow_type": "large_list<utf8>",
"json": {
@@ -207,21 +186,6 @@
]
}
},
{
"arrow_type": "large_list<large_utf8>",
"json": {
"type": "large_list",
"fields": [
{
"name": "item",
"nullable": false,
"type": {
"type": "large_utf8"
}
}
]
}
},
{
"arrow_type": "fixed_size_list<float32, 384>",
"json": {
@@ -366,4 +330,4 @@
"timestamp[us]",
"struct<a: int32>"
]
}
}