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@@ -1,5 +1,5 @@
|
||||
[tool.bumpversion]
|
||||
current_version = "0.13.0"
|
||||
current_version = "0.14.0-beta.2"
|
||||
parse = """(?x)
|
||||
(?P<major>0|[1-9]\\d*)\\.
|
||||
(?P<minor>0|[1-9]\\d*)\\.
|
||||
|
||||
4
.github/workflows/docs.yml
vendored
4
.github/workflows/docs.yml
vendored
@@ -72,9 +72,9 @@ jobs:
|
||||
- name: Setup Pages
|
||||
uses: actions/configure-pages@v2
|
||||
- name: Upload artifact
|
||||
uses: actions/upload-pages-artifact@v1
|
||||
uses: actions/upload-pages-artifact@v3
|
||||
with:
|
||||
path: "docs/site"
|
||||
- name: Deploy to GitHub Pages
|
||||
id: deployment
|
||||
uses: actions/deploy-pages@v1
|
||||
uses: actions/deploy-pages@v4
|
||||
|
||||
298
.github/workflows/npm-publish.yml
vendored
298
.github/workflows/npm-publish.yml
vendored
@@ -133,7 +133,7 @@ jobs:
|
||||
free -h
|
||||
- name: Build Linux Artifacts
|
||||
run: |
|
||||
bash ci/build_linux_artifacts.sh ${{ matrix.config.arch }}
|
||||
bash ci/build_linux_artifacts.sh ${{ matrix.config.arch }} ${{ matrix.config.arch }}-unknown-linux-gnu
|
||||
- name: Upload Linux Artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
@@ -185,7 +185,7 @@ jobs:
|
||||
- name: Build Linux Artifacts
|
||||
run: |
|
||||
source ./saved_env
|
||||
bash ci/manylinux_node/build_vectordb.sh ${{ matrix.config.arch }}
|
||||
bash ci/manylinux_node/build_vectordb.sh ${{ matrix.config.arch }} ${{ matrix.config.arch }}-unknown-linux-musl
|
||||
- name: Upload Linux Artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
@@ -334,109 +334,50 @@ jobs:
|
||||
path: |
|
||||
node/dist/lancedb-vectordb-win32*.tgz
|
||||
|
||||
# TODO: re-enable once working https://github.com/lancedb/lancedb/pull/1831
|
||||
# node-windows-arm64:
|
||||
# name: vectordb win32-arm64-msvc
|
||||
# runs-on: windows-4x-arm
|
||||
# if: startsWith(github.ref, 'refs/tags/v')
|
||||
# steps:
|
||||
# - uses: actions/checkout@v4
|
||||
# - name: Install Git
|
||||
# run: |
|
||||
# Invoke-WebRequest -Uri "https://github.com/git-for-windows/git/releases/download/v2.44.0.windows.1/Git-2.44.0-64-bit.exe" -OutFile "git-installer.exe"
|
||||
# Start-Process -FilePath "git-installer.exe" -ArgumentList "/VERYSILENT", "/NORESTART" -Wait
|
||||
# shell: powershell
|
||||
# - name: Add Git to PATH
|
||||
# run: |
|
||||
# Add-Content $env:GITHUB_PATH "C:\Program Files\Git\bin"
|
||||
# $env:Path = [System.Environment]::GetEnvironmentVariable("Path","Machine") + ";" + [System.Environment]::GetEnvironmentVariable("Path","User")
|
||||
# shell: powershell
|
||||
# - name: Configure Git symlinks
|
||||
# run: git config --global core.symlinks true
|
||||
# - uses: actions/checkout@v4
|
||||
# - uses: actions/setup-python@v5
|
||||
# with:
|
||||
# python-version: "3.13"
|
||||
# - name: Install Visual Studio Build Tools
|
||||
# run: |
|
||||
# Invoke-WebRequest -Uri "https://aka.ms/vs/17/release/vs_buildtools.exe" -OutFile "vs_buildtools.exe"
|
||||
# Start-Process -FilePath "vs_buildtools.exe" -ArgumentList "--quiet", "--wait", "--norestart", "--nocache", `
|
||||
# "--installPath", "C:\BuildTools", `
|
||||
# "--add", "Microsoft.VisualStudio.Component.VC.Tools.ARM64", `
|
||||
# "--add", "Microsoft.VisualStudio.Component.VC.Tools.x86.x64", `
|
||||
# "--add", "Microsoft.VisualStudio.Component.Windows11SDK.22621", `
|
||||
# "--add", "Microsoft.VisualStudio.Component.VC.ATL", `
|
||||
# "--add", "Microsoft.VisualStudio.Component.VC.ATLMFC", `
|
||||
# "--add", "Microsoft.VisualStudio.Component.VC.Llvm.Clang" -Wait
|
||||
# shell: powershell
|
||||
# - name: Add Visual Studio Build Tools to PATH
|
||||
# run: |
|
||||
# $vsPath = "C:\BuildTools\VC\Tools\MSVC"
|
||||
# $latestVersion = (Get-ChildItem $vsPath | Sort-Object {[version]$_.Name} -Descending)[0].Name
|
||||
# Add-Content $env:GITHUB_PATH "C:\BuildTools\VC\Tools\MSVC\$latestVersion\bin\Hostx64\arm64"
|
||||
# Add-Content $env:GITHUB_PATH "C:\BuildTools\VC\Tools\MSVC\$latestVersion\bin\Hostx64\x64"
|
||||
# Add-Content $env:GITHUB_PATH "C:\Program Files (x86)\Windows Kits\10\bin\10.0.22621.0\arm64"
|
||||
# Add-Content $env:GITHUB_PATH "C:\Program Files (x86)\Windows Kits\10\bin\10.0.22621.0\x64"
|
||||
# Add-Content $env:GITHUB_PATH "C:\BuildTools\VC\Tools\Llvm\x64\bin"
|
||||
|
||||
# # Add MSVC runtime libraries to LIB
|
||||
# $env:LIB = "C:\BuildTools\VC\Tools\MSVC\$latestVersion\lib\arm64;" +
|
||||
# "C:\Program Files (x86)\Windows Kits\10\Lib\10.0.22621.0\um\arm64;" +
|
||||
# "C:\Program Files (x86)\Windows Kits\10\Lib\10.0.22621.0\ucrt\arm64"
|
||||
# Add-Content $env:GITHUB_ENV "LIB=$env:LIB"
|
||||
|
||||
# # Add INCLUDE paths
|
||||
# $env:INCLUDE = "C:\BuildTools\VC\Tools\MSVC\$latestVersion\include;" +
|
||||
# "C:\Program Files (x86)\Windows Kits\10\Include\10.0.22621.0\ucrt;" +
|
||||
# "C:\Program Files (x86)\Windows Kits\10\Include\10.0.22621.0\um;" +
|
||||
# "C:\Program Files (x86)\Windows Kits\10\Include\10.0.22621.0\shared"
|
||||
# Add-Content $env:GITHUB_ENV "INCLUDE=$env:INCLUDE"
|
||||
# shell: powershell
|
||||
# - name: Install Rust
|
||||
# run: |
|
||||
# Invoke-WebRequest https://win.rustup.rs/x86_64 -OutFile rustup-init.exe
|
||||
# .\rustup-init.exe -y --default-host aarch64-pc-windows-msvc
|
||||
# shell: powershell
|
||||
# - name: Add Rust to PATH
|
||||
# run: |
|
||||
# Add-Content $env:GITHUB_PATH "$env:USERPROFILE\.cargo\bin"
|
||||
# shell: powershell
|
||||
|
||||
# - uses: Swatinem/rust-cache@v2
|
||||
# with:
|
||||
# workspaces: rust
|
||||
# - name: Install 7-Zip ARM
|
||||
# run: |
|
||||
# New-Item -Path 'C:\7zip' -ItemType Directory
|
||||
# Invoke-WebRequest https://7-zip.org/a/7z2408-arm64.exe -OutFile C:\7zip\7z-installer.exe
|
||||
# Start-Process -FilePath C:\7zip\7z-installer.exe -ArgumentList '/S' -Wait
|
||||
# shell: powershell
|
||||
# - name: Add 7-Zip to PATH
|
||||
# run: Add-Content $env:GITHUB_PATH "C:\Program Files\7-Zip"
|
||||
# shell: powershell
|
||||
# - name: Install Protoc v21.12
|
||||
# working-directory: C:\
|
||||
# run: |
|
||||
# if (Test-Path 'C:\protoc') {
|
||||
# Write-Host "Protoc directory exists, skipping installation"
|
||||
# return
|
||||
# }
|
||||
# New-Item -Path 'C:\protoc' -ItemType Directory
|
||||
# Set-Location C:\protoc
|
||||
# Invoke-WebRequest https://github.com/protocolbuffers/protobuf/releases/download/v21.12/protoc-21.12-win64.zip -OutFile C:\protoc\protoc.zip
|
||||
# & 'C:\Program Files\7-Zip\7z.exe' x protoc.zip
|
||||
# shell: powershell
|
||||
# - name: Add Protoc to PATH
|
||||
# run: Add-Content $env:GITHUB_PATH "C:\protoc\bin"
|
||||
# shell: powershell
|
||||
# - name: Build Windows native node modules
|
||||
# run: .\ci\build_windows_artifacts.ps1 aarch64-pc-windows-msvc
|
||||
# - name: Upload Windows ARM64 Artifacts
|
||||
# uses: actions/upload-artifact@v4
|
||||
# with:
|
||||
# name: node-native-windows-arm64
|
||||
# path: |
|
||||
# node/dist/*.node
|
||||
node-windows-arm64:
|
||||
name: vectordb ${{ matrix.config.arch }}-pc-windows-msvc
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
runs-on: ubuntu-latest
|
||||
container: alpine:edge
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
config:
|
||||
# - arch: x86_64
|
||||
- arch: aarch64
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
apk add protobuf-dev curl clang lld llvm19 grep npm bash msitools sed
|
||||
curl --proto '=https' --tlsv1.3 -sSf https://raw.githubusercontent.com/rust-lang/rustup/refs/heads/master/rustup-init.sh | sh -s -- -y --default-toolchain 1.80.0
|
||||
echo "source $HOME/.cargo/env" >> saved_env
|
||||
echo "export CC=clang" >> saved_env
|
||||
echo "export AR=llvm-ar" >> saved_env
|
||||
source "$HOME/.cargo/env"
|
||||
rustup target add ${{ matrix.config.arch }}-pc-windows-msvc --toolchain 1.80.0
|
||||
(mkdir -p sysroot && cd sysroot && sh ../ci/sysroot-${{ matrix.config.arch }}-pc-windows-msvc.sh)
|
||||
echo "export C_INCLUDE_PATH=/usr/${{ matrix.config.arch }}-pc-windows-msvc/usr/include" >> saved_env
|
||||
echo "export CARGO_BUILD_TARGET=${{ matrix.config.arch }}-pc-windows-msvc" >> saved_env
|
||||
- name: Configure x86_64 build
|
||||
if: ${{ matrix.config.arch == 'x86_64' }}
|
||||
run: |
|
||||
echo "export RUSTFLAGS='-Ctarget-cpu=haswell -Ctarget-feature=+crt-static,+avx2,+fma,+f16c -Clinker=lld -Clink-arg=/LIBPATH:/usr/x86_64-pc-windows-msvc/usr/lib'" >> saved_env
|
||||
- name: Configure aarch64 build
|
||||
if: ${{ matrix.config.arch == 'aarch64' }}
|
||||
run: |
|
||||
echo "export RUSTFLAGS='-Ctarget-feature=+crt-static,+neon,+fp16,+fhm,+dotprod -Clinker=lld -Clink-arg=/LIBPATH:/usr/aarch64-pc-windows-msvc/usr/lib -Clink-arg=arm64rt.lib'" >> saved_env
|
||||
- name: Build Windows Artifacts
|
||||
run: |
|
||||
source ./saved_env
|
||||
bash ci/manylinux_node/build_vectordb.sh ${{ matrix.config.arch }} ${{ matrix.config.arch }}-pc-windows-msvc
|
||||
- name: Upload Windows Artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: node-native-windows-${{ matrix.config.arch }}
|
||||
path: |
|
||||
node/dist/lancedb-vectordb-win32*.tgz
|
||||
|
||||
nodejs-windows:
|
||||
name: lancedb ${{ matrix.target }}
|
||||
@@ -472,103 +413,57 @@ jobs:
|
||||
path: |
|
||||
nodejs/dist/*.node
|
||||
|
||||
# TODO: re-enable once working https://github.com/lancedb/lancedb/pull/1831
|
||||
# nodejs-windows-arm64:
|
||||
# name: lancedb win32-arm64-msvc
|
||||
# runs-on: windows-4x-arm
|
||||
# if: startsWith(github.ref, 'refs/tags/v')
|
||||
# steps:
|
||||
# - uses: actions/checkout@v4
|
||||
# - name: Install Git
|
||||
# run: |
|
||||
# Invoke-WebRequest -Uri "https://github.com/git-for-windows/git/releases/download/v2.44.0.windows.1/Git-2.44.0-64-bit.exe" -OutFile "git-installer.exe"
|
||||
# Start-Process -FilePath "git-installer.exe" -ArgumentList "/VERYSILENT", "/NORESTART" -Wait
|
||||
# shell: powershell
|
||||
# - name: Add Git to PATH
|
||||
# run: |
|
||||
# Add-Content $env:GITHUB_PATH "C:\Program Files\Git\bin"
|
||||
# $env:Path = [System.Environment]::GetEnvironmentVariable("Path","Machine") + ";" + [System.Environment]::GetEnvironmentVariable("Path","User")
|
||||
# shell: powershell
|
||||
# - name: Configure Git symlinks
|
||||
# run: git config --global core.symlinks true
|
||||
# - uses: actions/checkout@v4
|
||||
# - uses: actions/setup-python@v5
|
||||
# with:
|
||||
# python-version: "3.13"
|
||||
# - name: Install Visual Studio Build Tools
|
||||
# run: |
|
||||
# Invoke-WebRequest -Uri "https://aka.ms/vs/17/release/vs_buildtools.exe" -OutFile "vs_buildtools.exe"
|
||||
# Start-Process -FilePath "vs_buildtools.exe" -ArgumentList "--quiet", "--wait", "--norestart", "--nocache", `
|
||||
# "--installPath", "C:\BuildTools", `
|
||||
# "--add", "Microsoft.VisualStudio.Component.VC.Tools.ARM64", `
|
||||
# "--add", "Microsoft.VisualStudio.Component.VC.Tools.x86.x64", `
|
||||
# "--add", "Microsoft.VisualStudio.Component.Windows11SDK.22621", `
|
||||
# "--add", "Microsoft.VisualStudio.Component.VC.ATL", `
|
||||
# "--add", "Microsoft.VisualStudio.Component.VC.ATLMFC", `
|
||||
# "--add", "Microsoft.VisualStudio.Component.VC.Llvm.Clang" -Wait
|
||||
# shell: powershell
|
||||
# - name: Add Visual Studio Build Tools to PATH
|
||||
# run: |
|
||||
# $vsPath = "C:\BuildTools\VC\Tools\MSVC"
|
||||
# $latestVersion = (Get-ChildItem $vsPath | Sort-Object {[version]$_.Name} -Descending)[0].Name
|
||||
# Add-Content $env:GITHUB_PATH "C:\BuildTools\VC\Tools\MSVC\$latestVersion\bin\Hostx64\arm64"
|
||||
# Add-Content $env:GITHUB_PATH "C:\BuildTools\VC\Tools\MSVC\$latestVersion\bin\Hostx64\x64"
|
||||
# Add-Content $env:GITHUB_PATH "C:\Program Files (x86)\Windows Kits\10\bin\10.0.22621.0\arm64"
|
||||
# Add-Content $env:GITHUB_PATH "C:\Program Files (x86)\Windows Kits\10\bin\10.0.22621.0\x64"
|
||||
# Add-Content $env:GITHUB_PATH "C:\BuildTools\VC\Tools\Llvm\x64\bin"
|
||||
|
||||
# $env:LIB = ""
|
||||
# Add-Content $env:GITHUB_ENV "LIB=C:\Program Files (x86)\Windows Kits\10\Lib\10.0.22621.0\um\arm64;C:\Program Files (x86)\Windows Kits\10\Lib\10.0.22621.0\ucrt\arm64"
|
||||
# shell: powershell
|
||||
# - name: Install Rust
|
||||
# run: |
|
||||
# Invoke-WebRequest https://win.rustup.rs/x86_64 -OutFile rustup-init.exe
|
||||
# .\rustup-init.exe -y --default-host aarch64-pc-windows-msvc
|
||||
# shell: powershell
|
||||
# - name: Add Rust to PATH
|
||||
# run: |
|
||||
# Add-Content $env:GITHUB_PATH "$env:USERPROFILE\.cargo\bin"
|
||||
# shell: powershell
|
||||
|
||||
# - uses: Swatinem/rust-cache@v2
|
||||
# with:
|
||||
# workspaces: rust
|
||||
# - name: Install 7-Zip ARM
|
||||
# run: |
|
||||
# New-Item -Path 'C:\7zip' -ItemType Directory
|
||||
# Invoke-WebRequest https://7-zip.org/a/7z2408-arm64.exe -OutFile C:\7zip\7z-installer.exe
|
||||
# Start-Process -FilePath C:\7zip\7z-installer.exe -ArgumentList '/S' -Wait
|
||||
# shell: powershell
|
||||
# - name: Add 7-Zip to PATH
|
||||
# run: Add-Content $env:GITHUB_PATH "C:\Program Files\7-Zip"
|
||||
# shell: powershell
|
||||
# - name: Install Protoc v21.12
|
||||
# working-directory: C:\
|
||||
# run: |
|
||||
# if (Test-Path 'C:\protoc') {
|
||||
# Write-Host "Protoc directory exists, skipping installation"
|
||||
# return
|
||||
# }
|
||||
# New-Item -Path 'C:\protoc' -ItemType Directory
|
||||
# Set-Location C:\protoc
|
||||
# Invoke-WebRequest https://github.com/protocolbuffers/protobuf/releases/download/v21.12/protoc-21.12-win64.zip -OutFile C:\protoc\protoc.zip
|
||||
# & 'C:\Program Files\7-Zip\7z.exe' x protoc.zip
|
||||
# shell: powershell
|
||||
# - name: Add Protoc to PATH
|
||||
# run: Add-Content $env:GITHUB_PATH "C:\protoc\bin"
|
||||
# shell: powershell
|
||||
# - name: Build Windows native node modules
|
||||
# run: .\ci\build_windows_artifacts_nodejs.ps1 aarch64-pc-windows-msvc
|
||||
# - name: Upload Windows ARM64 Artifacts
|
||||
# uses: actions/upload-artifact@v4
|
||||
# with:
|
||||
# name: nodejs-native-windows-arm64
|
||||
# path: |
|
||||
# nodejs/dist/*.node
|
||||
nodejs-windows-arm64:
|
||||
name: lancedb ${{ matrix.config.arch }}-pc-windows-msvc
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
runs-on: ubuntu-latest
|
||||
container: alpine:edge
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
config:
|
||||
# - arch: x86_64
|
||||
- arch: aarch64
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
apk add protobuf-dev curl clang lld llvm19 grep npm bash msitools sed
|
||||
curl --proto '=https' --tlsv1.3 -sSf https://raw.githubusercontent.com/rust-lang/rustup/refs/heads/master/rustup-init.sh | sh -s -- -y --default-toolchain 1.80.0
|
||||
echo "source $HOME/.cargo/env" >> saved_env
|
||||
echo "export CC=clang" >> saved_env
|
||||
echo "export AR=llvm-ar" >> saved_env
|
||||
source "$HOME/.cargo/env"
|
||||
rustup target add ${{ matrix.config.arch }}-pc-windows-msvc --toolchain 1.80.0
|
||||
(mkdir -p sysroot && cd sysroot && sh ../ci/sysroot-${{ matrix.config.arch }}-pc-windows-msvc.sh)
|
||||
echo "export C_INCLUDE_PATH=/usr/${{ matrix.config.arch }}-pc-windows-msvc/usr/include" >> saved_env
|
||||
echo "export CARGO_BUILD_TARGET=${{ matrix.config.arch }}-pc-windows-msvc" >> saved_env
|
||||
printf '#!/bin/sh\ncargo "$@"' > $HOME/.cargo/bin/cargo-xwin
|
||||
chmod u+x $HOME/.cargo/bin/cargo-xwin
|
||||
- name: Configure x86_64 build
|
||||
if: ${{ matrix.config.arch == 'x86_64' }}
|
||||
run: |
|
||||
echo "export RUSTFLAGS='-Ctarget-cpu=haswell -Ctarget-feature=+crt-static,+avx2,+fma,+f16c -Clinker=lld -Clink-arg=/LIBPATH:/usr/x86_64-pc-windows-msvc/usr/lib'" >> saved_env
|
||||
- name: Configure aarch64 build
|
||||
if: ${{ matrix.config.arch == 'aarch64' }}
|
||||
run: |
|
||||
echo "export RUSTFLAGS='-Ctarget-feature=+crt-static,+neon,+fp16,+fhm,+dotprod -Clinker=lld -Clink-arg=/LIBPATH:/usr/aarch64-pc-windows-msvc/usr/lib -Clink-arg=arm64rt.lib'" >> saved_env
|
||||
- name: Build Windows Artifacts
|
||||
run: |
|
||||
source ./saved_env
|
||||
bash ci/manylinux_node/build_lancedb.sh ${{ matrix.config.arch }}
|
||||
- name: Upload Windows Artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: nodejs-native-windows-${{ matrix.config.arch }}
|
||||
path: |
|
||||
nodejs/dist/*.node
|
||||
|
||||
release:
|
||||
name: vectordb NPM Publish
|
||||
needs: [node, node-macos, node-linux-gnu, node-linux-musl, node-windows]
|
||||
needs: [node, node-macos, node-linux-gnu, node-linux-musl, node-windows, node-windows-arm64]
|
||||
runs-on: ubuntu-latest
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
@@ -608,7 +503,7 @@ jobs:
|
||||
|
||||
release-nodejs:
|
||||
name: lancedb NPM Publish
|
||||
needs: [nodejs-macos, nodejs-linux-gnu, nodejs-linux-musl, nodejs-windows]
|
||||
needs: [nodejs-macos, nodejs-linux-gnu, nodejs-linux-musl, nodejs-windows, nodejs-windows-arm64]
|
||||
runs-on: ubuntu-latest
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
@@ -666,6 +561,7 @@ jobs:
|
||||
SLACK_WEBHOOK_URL: ${{ secrets.ACTION_MONITORING_SLACK }}
|
||||
|
||||
update-package-lock:
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
needs: [release]
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
@@ -683,6 +579,7 @@ jobs:
|
||||
github_token: ${{ secrets.GITHUB_TOKEN }}
|
||||
|
||||
update-package-lock-nodejs:
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
needs: [release-nodejs]
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
@@ -700,6 +597,7 @@ jobs:
|
||||
github_token: ${{ secrets.GITHUB_TOKEN }}
|
||||
|
||||
gh-release:
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
contents: write
|
||||
|
||||
2
.github/workflows/pypi-publish.yml
vendored
2
.github/workflows/pypi-publish.yml
vendored
@@ -83,7 +83,7 @@ jobs:
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v4
|
||||
with:
|
||||
python-version: 3.8
|
||||
python-version: 3.12
|
||||
- uses: ./.github/workflows/build_windows_wheel
|
||||
with:
|
||||
python-minor-version: 8
|
||||
|
||||
1
.github/workflows/upload_wheel/action.yml
vendored
1
.github/workflows/upload_wheel/action.yml
vendored
@@ -17,6 +17,7 @@ runs:
|
||||
run: |
|
||||
python -m pip install --upgrade pip
|
||||
pip install twine
|
||||
python3 -m pip install --upgrade pkginfo
|
||||
- name: Choose repo
|
||||
shell: bash
|
||||
id: choose_repo
|
||||
|
||||
35
Cargo.toml
35
Cargo.toml
@@ -23,26 +23,27 @@ rust-version = "1.80.0" # TO
|
||||
[workspace.dependencies]
|
||||
lance = { "version" = "=0.20.0", "features" = [
|
||||
"dynamodb",
|
||||
], git = "https://github.com/lancedb/lance.git", tag = "v0.20.0-beta.2" }
|
||||
lance-index = { version = "=0.20.0", git = "https://github.com/lancedb/lance.git", tag = "v0.20.0-beta.2" }
|
||||
lance-linalg = { version = "=0.20.0", git = "https://github.com/lancedb/lance.git", tag = "v0.20.0-beta.2" }
|
||||
lance-table = { version = "=0.20.0", git = "https://github.com/lancedb/lance.git", tag = "v0.20.0-beta.2" }
|
||||
lance-testing = { version = "=0.20.0", git = "https://github.com/lancedb/lance.git", tag = "v0.20.0-beta.2" }
|
||||
lance-datafusion = { version = "=0.20.0", git = "https://github.com/lancedb/lance.git", tag = "v0.20.0-beta.2" }
|
||||
lance-encoding = { version = "=0.20.0", git = "https://github.com/lancedb/lance.git", tag = "v0.20.0-beta.2" }
|
||||
] }
|
||||
lance-io = "0.20.0"
|
||||
lance-index = "0.20.0"
|
||||
lance-linalg = "0.20.0"
|
||||
lance-table = "0.20.0"
|
||||
lance-testing = "0.20.0"
|
||||
lance-datafusion = "0.20.0"
|
||||
lance-encoding = "0.20.0"
|
||||
# Note that this one does not include pyarrow
|
||||
arrow = { version = "52.2", optional = false }
|
||||
arrow-array = "52.2"
|
||||
arrow-data = "52.2"
|
||||
arrow-ipc = "52.2"
|
||||
arrow-ord = "52.2"
|
||||
arrow-schema = "52.2"
|
||||
arrow-arith = "52.2"
|
||||
arrow-cast = "52.2"
|
||||
arrow = { version = "53.2", optional = false }
|
||||
arrow-array = "53.2"
|
||||
arrow-data = "53.2"
|
||||
arrow-ipc = "53.2"
|
||||
arrow-ord = "53.2"
|
||||
arrow-schema = "53.2"
|
||||
arrow-arith = "53.2"
|
||||
arrow-cast = "53.2"
|
||||
async-trait = "0"
|
||||
chrono = "0.4.35"
|
||||
datafusion-common = "41.0"
|
||||
datafusion-physical-plan = "41.0"
|
||||
datafusion-common = "42.0"
|
||||
datafusion-physical-plan = "42.0"
|
||||
env_logger = "0.10"
|
||||
half = { "version" = "=2.4.1", default-features = false, features = [
|
||||
"num-traits",
|
||||
|
||||
@@ -1,8 +1,9 @@
|
||||
#!/bin/bash
|
||||
set -e
|
||||
ARCH=${1:-x86_64}
|
||||
TARGET_TRIPLE=${2:-x86_64-unknown-linux-gnu}
|
||||
|
||||
# We pass down the current user so that when we later mount the local files
|
||||
# We pass down the current user so that when we later mount the local files
|
||||
# into the container, the files are accessible by the current user.
|
||||
pushd ci/manylinux_node
|
||||
docker build \
|
||||
@@ -18,4 +19,4 @@ docker run \
|
||||
-v $(pwd):/io -w /io \
|
||||
--memory-swap=-1 \
|
||||
lancedb-node-manylinux \
|
||||
bash ci/manylinux_node/build_vectordb.sh $ARCH
|
||||
bash ci/manylinux_node/build_vectordb.sh $ARCH $TARGET_TRIPLE
|
||||
|
||||
@@ -2,6 +2,7 @@
|
||||
# Builds the node module for manylinux. Invoked by ci/build_linux_artifacts.sh.
|
||||
set -e
|
||||
ARCH=${1:-x86_64}
|
||||
TARGET_TRIPLE=${2:-x86_64-unknown-linux-gnu}
|
||||
|
||||
if [ "$ARCH" = "x86_64" ]; then
|
||||
export OPENSSL_LIB_DIR=/usr/local/lib64/
|
||||
@@ -17,4 +18,4 @@ FILE=$HOME/.bashrc && test -f $FILE && source $FILE
|
||||
cd node
|
||||
npm ci
|
||||
npm run build-release
|
||||
npm run pack-build
|
||||
npm run pack-build -- -t $TARGET_TRIPLE
|
||||
|
||||
105
ci/sysroot-aarch64-pc-windows-msvc.sh
Normal file
105
ci/sysroot-aarch64-pc-windows-msvc.sh
Normal file
@@ -0,0 +1,105 @@
|
||||
#!/bin/sh
|
||||
|
||||
# https://github.com/mstorsjo/msvc-wine/blob/master/vsdownload.py
|
||||
# https://github.com/mozilla/gecko-dev/blob/6027d1d91f2d3204a3992633b3ef730ff005fc64/build/vs/vs2022-car.yaml
|
||||
|
||||
# function dl() {
|
||||
# curl -O https://download.visualstudio.microsoft.com/download/pr/$1
|
||||
# }
|
||||
|
||||
# [[.h]]
|
||||
|
||||
# "id": "Win11SDK_10.0.26100"
|
||||
# "version": "10.0.26100.7"
|
||||
|
||||
# libucrt.lib
|
||||
|
||||
# example: <assert.h>
|
||||
# dir: ucrt/
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/2ee3a5fc6e9fc832af7295b138e93839/universal%20crt%20headers%20libraries%20and%20sources-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/b1aa09b90fe314aceb090f6ec7626624/16ab2ea2187acffa6435e334796c8c89.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/400609bb0ff5804e36dbe6dcd42a7f01/6ee7bbee8435130a869cf971694fd9e2.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/2ac327317abb865a0e3f56b2faefa918/78fa3c824c2c48bd4a49ab5969adaaf7.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/f034bc0b2680f67dccd4bfeea3d0f932/7afc7b670accd8e3cc94cfffd516f5cb.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/7ed5e12f9d50f80825a8b27838cf4c7f/96076045170fe5db6d5dcf14b6f6688e.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/764edc185a696bda9e07df8891dddbbb/a1e2a83aa8a71c48c742eeaff6e71928.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/66854bedc6dbd5ccb5dd82c8e2412231/b2f03f34ff83ec013b9e45c7cd8e8a73.cab
|
||||
|
||||
# example: <windows.h>
|
||||
# dir: um/
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/b286efac4d83a54fc49190bddef1edc9/windows%20sdk%20for%20windows%20store%20apps%20headers-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/e0dc3811d92ab96fcb72bf63d6c08d71/766c0ffd568bbb31bf7fb6793383e24a.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/613503da4b5628768497822826aed39f/8125ee239710f33ea485965f76fae646.cab
|
||||
|
||||
# example: <winapifamily.h>
|
||||
# dir: /shared
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/122979f0348d3a2a36b6aa1a111d5d0c/windows%20sdk%20for%20windows%20store%20apps%20headers%20onecoreuap-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/766e04beecdfccff39e91dd9eb32834a/e89e3dcbb016928c7e426238337d69eb.cab
|
||||
|
||||
|
||||
# "id": "Microsoft.VisualC.14.16.CRT.Headers"
|
||||
# "version": "14.16.27045"
|
||||
|
||||
# example: <vcruntime.h>
|
||||
# dir: MSVC/
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/bac0afd7-cc9e-4182-8a83-9898fa20e092/87bbe41e09a2f83711e72696f49681429327eb7a4b90618c35667a6ba2e2880e/Microsoft.VisualC.14.16.CRT.Headers.vsix
|
||||
|
||||
# [[.lib]]
|
||||
|
||||
# advapi32.lib bcrypt.lib kernel32.lib ntdll.lib user32.lib uuid.lib ws2_32.lib userenv.lib cfgmgr32.lib runtimeobject.lib
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/944c4153b849a1f7d0c0404a4f1c05ea/windows%20sdk%20for%20windows%20store%20apps%20libs-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/5306aed3e1a38d1e8bef5934edeb2a9b/05047a45609f311645eebcac2739fc4c.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/13c8a73a0f5a6474040b26d016a26fab/13d68b8a7b6678a368e2d13ff4027521.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/149578fb3b621cdb61ee1813b9b3e791/463ad1b0783ebda908fd6c16a4abfe93.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/5c986c4f393c6b09d5aec3b539e9fb4a/5a22e5cde814b041749fb271547f4dd5.cab
|
||||
|
||||
# fwpuclnt.lib arm64rt.lib
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/7a332420d812f7c1d41da865ae5a7c52/windows%20sdk%20desktop%20libs%20arm64-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/19de98ed4a79938d0045d19c047936b3/3e2f7be479e3679d700ce0782e4cc318.cab
|
||||
|
||||
# libcmt.lib libvcruntime.lib
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/bac0afd7-cc9e-4182-8a83-9898fa20e092/227f40682a88dc5fa0ccb9cadc9ad30af99ad1f1a75db63407587d079f60d035/Microsoft.VisualC.14.16.CRT.ARM64.Desktop.vsix
|
||||
|
||||
|
||||
msiextract universal%20crt%20headers%20libraries%20and%20sources-x86_en-us.msi
|
||||
msiextract windows%20sdk%20for%20windows%20store%20apps%20headers-x86_en-us.msi
|
||||
msiextract windows%20sdk%20for%20windows%20store%20apps%20headers%20onecoreuap-x86_en-us.msi
|
||||
msiextract windows%20sdk%20for%20windows%20store%20apps%20libs-x86_en-us.msi
|
||||
msiextract windows%20sdk%20desktop%20libs%20arm64-x86_en-us.msi
|
||||
unzip -o Microsoft.VisualC.14.16.CRT.Headers.vsix
|
||||
unzip -o Microsoft.VisualC.14.16.CRT.ARM64.Desktop.vsix
|
||||
|
||||
mkdir -p /usr/aarch64-pc-windows-msvc/usr/include
|
||||
mkdir -p /usr/aarch64-pc-windows-msvc/usr/lib
|
||||
|
||||
# lowercase folder/file names
|
||||
echo "$(find . -regex ".*/[^/]*[A-Z][^/]*")" | xargs -I{} sh -c 'mv "$(echo "{}" | sed -E '"'"'s/(.*\/)/\L\1/'"'"')" "$(echo "{}" | tr [A-Z] [a-z])"'
|
||||
|
||||
# .h
|
||||
(cd 'program files/windows kits/10/include/10.0.26100.0' && cp -r ucrt/* um/* shared/* -t /usr/aarch64-pc-windows-msvc/usr/include)
|
||||
|
||||
cp -r contents/vc/tools/msvc/14.16.27023/include/* /usr/aarch64-pc-windows-msvc/usr/include
|
||||
|
||||
# lowercase #include "" and #include <>
|
||||
find /usr/aarch64-pc-windows-msvc/usr/include -type f -exec sed -i -E 's/(#include <[^<>]*?[A-Z][^<>]*?>)|(#include "[^"]*?[A-Z][^"]*?")/\L\1\2/' "{}" ';'
|
||||
|
||||
# ARM intrinsics
|
||||
# original dir: MSVC/
|
||||
|
||||
# '__n128x4' redefined in arm_neon.h
|
||||
# "arm64_neon.h" included from intrin.h
|
||||
|
||||
(cd /usr/lib/llvm19/lib/clang/19/include && cp arm_neon.h intrin.h -t /usr/aarch64-pc-windows-msvc/usr/include)
|
||||
|
||||
# .lib
|
||||
|
||||
# _Interlocked intrinsics
|
||||
# must always link with arm64rt.lib
|
||||
# reason: https://developercommunity.visualstudio.com/t/libucrtlibstreamobj-error-lnk2001-unresolved-exter/1544787#T-ND1599818
|
||||
# I don't understand the 'correct' fix for this, arm64rt.lib is supposed to be the workaround
|
||||
|
||||
(cd 'program files/windows kits/10/lib/10.0.26100.0/um/arm64' && cp advapi32.lib bcrypt.lib kernel32.lib ntdll.lib user32.lib uuid.lib ws2_32.lib userenv.lib cfgmgr32.lib runtimeobject.lib fwpuclnt.lib arm64rt.lib -t /usr/aarch64-pc-windows-msvc/usr/lib)
|
||||
|
||||
(cd 'contents/vc/tools/msvc/14.16.27023/lib/arm64' && cp libcmt.lib libvcruntime.lib -t /usr/aarch64-pc-windows-msvc/usr/lib)
|
||||
|
||||
cp 'program files/windows kits/10/lib/10.0.26100.0/ucrt/arm64/libucrt.lib' /usr/aarch64-pc-windows-msvc/usr/lib
|
||||
105
ci/sysroot-x86_64-pc-windows-msvc.sh
Normal file
105
ci/sysroot-x86_64-pc-windows-msvc.sh
Normal file
@@ -0,0 +1,105 @@
|
||||
#!/bin/sh
|
||||
|
||||
# https://github.com/mstorsjo/msvc-wine/blob/master/vsdownload.py
|
||||
# https://github.com/mozilla/gecko-dev/blob/6027d1d91f2d3204a3992633b3ef730ff005fc64/build/vs/vs2022-car.yaml
|
||||
|
||||
# function dl() {
|
||||
# curl -O https://download.visualstudio.microsoft.com/download/pr/$1
|
||||
# }
|
||||
|
||||
# [[.h]]
|
||||
|
||||
# "id": "Win11SDK_10.0.26100"
|
||||
# "version": "10.0.26100.7"
|
||||
|
||||
# libucrt.lib
|
||||
|
||||
# example: <assert.h>
|
||||
# dir: ucrt/
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/2ee3a5fc6e9fc832af7295b138e93839/universal%20crt%20headers%20libraries%20and%20sources-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/b1aa09b90fe314aceb090f6ec7626624/16ab2ea2187acffa6435e334796c8c89.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/400609bb0ff5804e36dbe6dcd42a7f01/6ee7bbee8435130a869cf971694fd9e2.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/2ac327317abb865a0e3f56b2faefa918/78fa3c824c2c48bd4a49ab5969adaaf7.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/f034bc0b2680f67dccd4bfeea3d0f932/7afc7b670accd8e3cc94cfffd516f5cb.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/7ed5e12f9d50f80825a8b27838cf4c7f/96076045170fe5db6d5dcf14b6f6688e.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/764edc185a696bda9e07df8891dddbbb/a1e2a83aa8a71c48c742eeaff6e71928.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/66854bedc6dbd5ccb5dd82c8e2412231/b2f03f34ff83ec013b9e45c7cd8e8a73.cab
|
||||
|
||||
# example: <windows.h>
|
||||
# dir: um/
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/b286efac4d83a54fc49190bddef1edc9/windows%20sdk%20for%20windows%20store%20apps%20headers-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/e0dc3811d92ab96fcb72bf63d6c08d71/766c0ffd568bbb31bf7fb6793383e24a.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/613503da4b5628768497822826aed39f/8125ee239710f33ea485965f76fae646.cab
|
||||
|
||||
# example: <winapifamily.h>
|
||||
# dir: /shared
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/122979f0348d3a2a36b6aa1a111d5d0c/windows%20sdk%20for%20windows%20store%20apps%20headers%20onecoreuap-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/766e04beecdfccff39e91dd9eb32834a/e89e3dcbb016928c7e426238337d69eb.cab
|
||||
|
||||
|
||||
# "id": "Microsoft.VisualC.14.16.CRT.Headers"
|
||||
# "version": "14.16.27045"
|
||||
|
||||
# example: <vcruntime.h>
|
||||
# dir: MSVC/
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/bac0afd7-cc9e-4182-8a83-9898fa20e092/87bbe41e09a2f83711e72696f49681429327eb7a4b90618c35667a6ba2e2880e/Microsoft.VisualC.14.16.CRT.Headers.vsix
|
||||
|
||||
# [[.lib]]
|
||||
|
||||
# advapi32.lib bcrypt.lib kernel32.lib ntdll.lib user32.lib uuid.lib ws2_32.lib userenv.lib cfgmgr32.lib
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/944c4153b849a1f7d0c0404a4f1c05ea/windows%20sdk%20for%20windows%20store%20apps%20libs-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/5306aed3e1a38d1e8bef5934edeb2a9b/05047a45609f311645eebcac2739fc4c.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/13c8a73a0f5a6474040b26d016a26fab/13d68b8a7b6678a368e2d13ff4027521.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/149578fb3b621cdb61ee1813b9b3e791/463ad1b0783ebda908fd6c16a4abfe93.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/5c986c4f393c6b09d5aec3b539e9fb4a/5a22e5cde814b041749fb271547f4dd5.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/bfc3904a0195453419ae4dfea7abd6fb/e10768bb6e9d0ea730280336b697da66.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/637f9f3be880c71f9e3ca07b4d67345c/f9b24c8280986c0683fbceca5326d806.cab
|
||||
|
||||
# dbghelp.lib fwpuclnt.lib
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/9f51690d5aa804b1340ce12d1ec80f89/windows%20sdk%20desktop%20libs%20x64-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/d3a7df4ca3303a698640a29e558a5e5b/58314d0646d7e1a25e97c902166c3155.cab
|
||||
|
||||
# libcmt.lib libvcruntime.lib
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/bac0afd7-cc9e-4182-8a83-9898fa20e092/8728f21ae09940f1f4b4ee47b4a596be2509e2a47d2f0c83bbec0ea37d69644b/Microsoft.VisualC.14.16.CRT.x64.Desktop.vsix
|
||||
|
||||
|
||||
msiextract universal%20crt%20headers%20libraries%20and%20sources-x86_en-us.msi
|
||||
msiextract windows%20sdk%20for%20windows%20store%20apps%20headers-x86_en-us.msi
|
||||
msiextract windows%20sdk%20for%20windows%20store%20apps%20headers%20onecoreuap-x86_en-us.msi
|
||||
msiextract windows%20sdk%20for%20windows%20store%20apps%20libs-x86_en-us.msi
|
||||
msiextract windows%20sdk%20desktop%20libs%20x64-x86_en-us.msi
|
||||
unzip -o Microsoft.VisualC.14.16.CRT.Headers.vsix
|
||||
unzip -o Microsoft.VisualC.14.16.CRT.x64.Desktop.vsix
|
||||
|
||||
mkdir -p /usr/x86_64-pc-windows-msvc/usr/include
|
||||
mkdir -p /usr/x86_64-pc-windows-msvc/usr/lib
|
||||
|
||||
# lowercase folder/file names
|
||||
echo "$(find . -regex ".*/[^/]*[A-Z][^/]*")" | xargs -I{} sh -c 'mv "$(echo "{}" | sed -E '"'"'s/(.*\/)/\L\1/'"'"')" "$(echo "{}" | tr [A-Z] [a-z])"'
|
||||
|
||||
# .h
|
||||
(cd 'program files/windows kits/10/include/10.0.26100.0' && cp -r ucrt/* um/* shared/* -t /usr/x86_64-pc-windows-msvc/usr/include)
|
||||
|
||||
cp -r contents/vc/tools/msvc/14.16.27023/include/* /usr/x86_64-pc-windows-msvc/usr/include
|
||||
|
||||
# lowercase #include "" and #include <>
|
||||
find /usr/x86_64-pc-windows-msvc/usr/include -type f -exec sed -i -E 's/(#include <[^<>]*?[A-Z][^<>]*?>)|(#include "[^"]*?[A-Z][^"]*?")/\L\1\2/' "{}" ';'
|
||||
|
||||
# x86 intrinsics
|
||||
# original dir: MSVC/
|
||||
|
||||
# '_mm_movemask_epi8' defined in emmintrin.h
|
||||
# '__v4sf' defined in xmmintrin.h
|
||||
# '__v2si' defined in mmintrin.h
|
||||
# '__m128d' redefined in immintrin.h
|
||||
# '__m128i' redefined in intrin.h
|
||||
# '_mm_comlt_epu8' defined in ammintrin.h
|
||||
|
||||
(cd /usr/lib/llvm19/lib/clang/19/include && cp emmintrin.h xmmintrin.h mmintrin.h immintrin.h intrin.h ammintrin.h -t /usr/x86_64-pc-windows-msvc/usr/include)
|
||||
|
||||
# .lib
|
||||
(cd 'program files/windows kits/10/lib/10.0.26100.0/um/x64' && cp advapi32.lib bcrypt.lib kernel32.lib ntdll.lib user32.lib uuid.lib ws2_32.lib userenv.lib cfgmgr32.lib dbghelp.lib fwpuclnt.lib -t /usr/x86_64-pc-windows-msvc/usr/lib)
|
||||
|
||||
(cd 'contents/vc/tools/msvc/14.16.27023/lib/x64' && cp libcmt.lib libvcruntime.lib -t /usr/x86_64-pc-windows-msvc/usr/lib)
|
||||
|
||||
cp 'program files/windows kits/10/lib/10.0.26100.0/ucrt/x64/libucrt.lib' /usr/x86_64-pc-windows-msvc/usr/lib
|
||||
@@ -55,6 +55,9 @@ plugins:
|
||||
show_signature_annotations: true
|
||||
show_root_heading: true
|
||||
members_order: source
|
||||
docstring_section_style: list
|
||||
signature_crossrefs: true
|
||||
separate_signature: true
|
||||
import:
|
||||
# for cross references
|
||||
- https://arrow.apache.org/docs/objects.inv
|
||||
|
||||
@@ -6,6 +6,7 @@ LanceDB registers the OpenAI embeddings function in the registry by default, as
|
||||
|---|---|---|---|
|
||||
| `name` | `str` | `"text-embedding-ada-002"` | The name of the model. |
|
||||
| `dim` | `int` | Model default | For OpenAI's newer text-embedding-3 model, we can specify a dimensionality that is smaller than the 1536 size. This feature supports it |
|
||||
| `use_azure` | bool | `False` | Set true to use Azure OpenAPI SDK |
|
||||
|
||||
|
||||
```python
|
||||
|
||||
@@ -1,23 +1,35 @@
|
||||
# Building Scalar Index
|
||||
# Building a Scalar Index
|
||||
|
||||
Similar to many SQL databases, LanceDB supports several types of Scalar indices to accelerate search
|
||||
Scalar indices organize data by scalar attributes (e.g. numbers, categorical values), enabling fast filtering of vector data. In vector databases, scalar indices accelerate the retrieval of scalar data associated with vectors, thus enhancing the query performance when searching for vectors that meet certain scalar criteria.
|
||||
|
||||
Similar to many SQL databases, LanceDB supports several types of scalar indices to accelerate search
|
||||
over scalar columns.
|
||||
|
||||
- `BTREE`: The most common type is BTREE. This index is inspired by the btree data structure
|
||||
although only the first few layers of the btree are cached in memory.
|
||||
It will perform well on columns with a large number of unique values and few rows per value.
|
||||
- `BITMAP`: this index stores a bitmap for each unique value in the column.
|
||||
This index is useful for columns with a finite number of unique values and many rows per value.
|
||||
For example, columns that represent "categories", "labels", or "tags"
|
||||
- `LABEL_LIST`: a special index that is used to index list columns whose values have a finite set of possibilities.
|
||||
- `BTREE`: The most common type is BTREE. The index stores a copy of the
|
||||
column in sorted order. This sorted copy allows a binary search to be used to
|
||||
satisfy queries.
|
||||
- `BITMAP`: this index stores a bitmap for each unique value in the column. It
|
||||
uses a series of bits to indicate whether a value is present in a row of a table
|
||||
- `LABEL_LIST`: a special index that can be used on `List<T>` columns to
|
||||
support queries with `array_contains_all` and `array_contains_any`
|
||||
using an underlying bitmap index.
|
||||
For example, a column that contains lists of tags (e.g. `["tag1", "tag2", "tag3"]`) can be indexed with a `LABEL_LIST` index.
|
||||
|
||||
!!! tips "How to choose the right scalar index type"
|
||||
|
||||
`BTREE`: This index is good for scalar columns with mostly distinct values and does best when the query is highly selective.
|
||||
|
||||
`BITMAP`: This index works best for low-cardinality numeric or string columns, where the number of unique values is small (i.e., less than a few thousands).
|
||||
|
||||
`LABEL_LIST`: This index should be used for columns containing list-type data.
|
||||
|
||||
| Data Type | Filter | Index Type |
|
||||
| --------------------------------------------------------------- | ----------------------------------------- | ------------ |
|
||||
| Numeric, String, Temporal | `<`, `=`, `>`, `in`, `between`, `is null` | `BTREE` |
|
||||
| Boolean, numbers or strings with fewer than 1,000 unique values | `<`, `=`, `>`, `in`, `between`, `is null` | `BITMAP` |
|
||||
| List of low cardinality of numbers or strings | `array_has_any`, `array_has_all` | `LABEL_LIST` |
|
||||
|
||||
### Create a scalar index
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
@@ -46,7 +58,7 @@ over scalar columns.
|
||||
await tlb.create_index("publisher", { config: lancedb.Index.bitmap() })
|
||||
```
|
||||
|
||||
For example, the following scan will be faster if the column `my_col` has a scalar index:
|
||||
The following scan will be faster if the column `book_id` has a scalar index:
|
||||
|
||||
=== "Python"
|
||||
|
||||
@@ -106,3 +118,30 @@ Scalar indices can also speed up scans containing a vector search or full text s
|
||||
.limit(10)
|
||||
.toArray();
|
||||
```
|
||||
### Update a scalar index
|
||||
Updating the table data (adding, deleting, or modifying records) requires that you also update the scalar index. This can be done by calling `optimize`, which will trigger an update to the existing scalar index.
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
table.add([{"vector": [7, 8], "book_id": 4}])
|
||||
table.optimize()
|
||||
```
|
||||
|
||||
=== "TypeScript"
|
||||
|
||||
```typescript
|
||||
await tbl.add([{ vector: [7, 8], book_id: 4 }]);
|
||||
await tbl.optimize();
|
||||
```
|
||||
|
||||
=== "Rust"
|
||||
|
||||
```rust
|
||||
let more_data: Box<dyn RecordBatchReader + Send> = create_some_records()?;
|
||||
tbl.add(more_data).execute().await?;
|
||||
tbl.optimize(OptimizeAction::All).execute().await?;
|
||||
```
|
||||
|
||||
!!! note
|
||||
|
||||
New data added after creating the scalar index will still appear in search results if optimize is not used, but with increased latency due to a flat search on the unindexed portion. LanceDB Cloud automates the optimize process, minimizing the impact on search speed.
|
||||
@@ -27,10 +27,13 @@ LanceDB OSS supports object stores such as AWS S3 (and compatible stores), Azure
|
||||
|
||||
Azure Blob Storage:
|
||||
|
||||
<!-- skip-test -->
|
||||
```python
|
||||
import lancedb
|
||||
db = lancedb.connect("az://bucket/path")
|
||||
```
|
||||
Note that for Azure, storage credentials must be configured. See [below](#azure-blob-storage) for more details.
|
||||
|
||||
|
||||
=== "TypeScript"
|
||||
|
||||
@@ -87,11 +90,6 @@ In most cases, when running in the respective cloud and permissions are set up c
|
||||
export TIMEOUT=60s
|
||||
```
|
||||
|
||||
!!! note "`storage_options` availability"
|
||||
|
||||
The `storage_options` parameter is only available in Python *async* API and JavaScript API.
|
||||
It is not yet supported in the Python synchronous API.
|
||||
|
||||
If you only want this to apply to one particular connection, you can pass the `storage_options` argument when opening the connection:
|
||||
|
||||
=== "Python"
|
||||
|
||||
@@ -790,6 +790,101 @@ Use the `drop_table()` method on the database to remove a table.
|
||||
This permanently removes the table and is not recoverable, unlike deleting rows.
|
||||
If the table does not exist an exception is raised.
|
||||
|
||||
## Changing schemas
|
||||
|
||||
While tables must have a schema specified when they are created, you can
|
||||
change the schema over time. There's three methods to alter the schema of
|
||||
a table:
|
||||
|
||||
* `add_columns`: Add new columns to the table
|
||||
* `alter_columns`: Alter the name, nullability, or data type of a column
|
||||
* `drop_columns`: Drop columns from the table
|
||||
|
||||
### Adding new columns
|
||||
|
||||
You can add new columns to the table with the `add_columns` method. New columns
|
||||
are filled with values based on a SQL expression. For example, you can add a new
|
||||
column `y` to the table and fill it with the value of `x + 1`.
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
table.add_columns({"double_price": "price * 2"})
|
||||
```
|
||||
**API Reference:** [lancedb.table.Table.add_columns][]
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
```typescript
|
||||
--8<-- "nodejs/examples/basic.test.ts:add_columns"
|
||||
```
|
||||
**API Reference:** [lancedb.Table.addColumns](../js/classes/Table.md/#addcolumns)
|
||||
|
||||
If you want to fill it with null, you can use `cast(NULL as <data_type>)` as
|
||||
the SQL expression to fill the column with nulls, while controlling the data
|
||||
type of the column. Available data types are base on the
|
||||
[DataFusion data types](https://datafusion.apache.org/user-guide/sql/data_types.html).
|
||||
You can use any of the SQL types, such as `BIGINT`:
|
||||
|
||||
```sql
|
||||
cast(NULL as BIGINT)
|
||||
```
|
||||
|
||||
Using Arrow data types and the `arrow_typeof` function is not yet supported.
|
||||
|
||||
<!-- TODO: we could provide a better formula for filling with nulls:
|
||||
https://github.com/lancedb/lance/issues/3175
|
||||
-->
|
||||
|
||||
### Altering existing columns
|
||||
|
||||
You can alter the name, nullability, or data type of a column with the `alter_columns`
|
||||
method.
|
||||
|
||||
Changing the name or nullability of a column just updates the metadata. Because
|
||||
of this, it's a fast operation. Changing the data type of a column requires
|
||||
rewriting the column, which can be a heavy operation.
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
import pyarrow as pa
|
||||
table.alter_column({"path": "double_price", "rename": "dbl_price",
|
||||
"data_type": pa.float32(), "nullable": False})
|
||||
```
|
||||
**API Reference:** [lancedb.table.Table.alter_columns][]
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
```typescript
|
||||
--8<-- "nodejs/examples/basic.test.ts:alter_columns"
|
||||
```
|
||||
**API Reference:** [lancedb.Table.alterColumns](../js/classes/Table.md/#altercolumns)
|
||||
|
||||
### Dropping columns
|
||||
|
||||
You can drop columns from the table with the `drop_columns` method. This will
|
||||
will remove the column from the schema.
|
||||
|
||||
<!-- TODO: Provide guidance on how to reduce disk usage once optimize helps here
|
||||
waiting on: https://github.com/lancedb/lance/issues/3177
|
||||
-->
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
table.drop_columns(["dbl_price"])
|
||||
```
|
||||
**API Reference:** [lancedb.table.Table.drop_columns][]
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
```typescript
|
||||
--8<-- "nodejs/examples/basic.test.ts:drop_columns"
|
||||
```
|
||||
**API Reference:** [lancedb.Table.dropColumns](../js/classes/Table.md/#altercolumns)
|
||||
|
||||
|
||||
## Handling bad vectors
|
||||
|
||||
In LanceDB Python, you can use the `on_bad_vectors` parameter to choose how
|
||||
|
||||
@@ -1,6 +1,16 @@
|
||||
# Python API Reference
|
||||
|
||||
This section contains the API reference for the OSS Python API.
|
||||
This section contains the API reference for the Python API. There is a
|
||||
synchronous and an asynchronous API client.
|
||||
|
||||
The general flow of using the API is:
|
||||
|
||||
1. Use [lancedb.connect][] or [lancedb.connect_async][] to connect to a database.
|
||||
2. Use the returned [lancedb.DBConnection][] or [lancedb.AsyncConnection][] to
|
||||
create or open tables.
|
||||
3. Use the returned [lancedb.table.Table][] or [lancedb.AsyncTable][] to query
|
||||
or modify tables.
|
||||
|
||||
|
||||
## Installation
|
||||
|
||||
|
||||
@@ -7,6 +7,10 @@ performed on the top-k results returned by the vector search. However, pre-filte
|
||||
option that performs the filter prior to vector search. This can be useful to narrow down on
|
||||
the search space on a very large dataset to reduce query latency.
|
||||
|
||||
Note that both pre-filtering and post-filtering can yield false positives. For pre-filtering, if the filter is too selective, it might eliminate relevant items that the vector search would have otherwise identified as a good match. In this case, increasing `nprobes` parameter will help reduce such false positives. It is recommended to set `use_index=false` if you know that the filter is highly selective.
|
||||
|
||||
Similarly, a highly selective post-filter can lead to false positives. Increasing both `nprobes` and `refine_factor` can mitigate this issue. When deciding between pre-filtering and post-filtering, pre-filtering is generally the safer choice if you're uncertain.
|
||||
|
||||
<!-- Setup Code
|
||||
```python
|
||||
import lancedb
|
||||
@@ -57,6 +61,9 @@ const tbl = await db.createTable('myVectors', data)
|
||||
```ts
|
||||
--8<-- "docs/src/sql_legacy.ts:search"
|
||||
```
|
||||
!!! note
|
||||
|
||||
Creating a [scalar index](guides/scalar_index.md) accelerates filtering
|
||||
|
||||
## SQL filters
|
||||
|
||||
|
||||
@@ -8,7 +8,7 @@
|
||||
<parent>
|
||||
<groupId>com.lancedb</groupId>
|
||||
<artifactId>lancedb-parent</artifactId>
|
||||
<version>0.13.0-final.0</version>
|
||||
<version>0.14.0-beta.2</version>
|
||||
<relativePath>../pom.xml</relativePath>
|
||||
</parent>
|
||||
|
||||
|
||||
@@ -6,7 +6,7 @@
|
||||
|
||||
<groupId>com.lancedb</groupId>
|
||||
<artifactId>lancedb-parent</artifactId>
|
||||
<version>0.13.0-final.0</version>
|
||||
<version>0.14.0-beta.2</version>
|
||||
<packaging>pom</packaging>
|
||||
|
||||
<name>LanceDB Parent</name>
|
||||
|
||||
78
node/package-lock.json
generated
78
node/package-lock.json
generated
@@ -1,12 +1,12 @@
|
||||
{
|
||||
"name": "vectordb",
|
||||
"version": "0.13.0",
|
||||
"version": "0.14.0-beta.2",
|
||||
"lockfileVersion": 3,
|
||||
"requires": true,
|
||||
"packages": {
|
||||
"": {
|
||||
"name": "vectordb",
|
||||
"version": "0.13.0",
|
||||
"version": "0.14.0-beta.2",
|
||||
"cpu": [
|
||||
"x64",
|
||||
"arm64"
|
||||
@@ -52,12 +52,14 @@
|
||||
"uuid": "^9.0.0"
|
||||
},
|
||||
"optionalDependencies": {
|
||||
"@lancedb/vectordb-darwin-arm64": "0.13.0",
|
||||
"@lancedb/vectordb-darwin-x64": "0.13.0",
|
||||
"@lancedb/vectordb-linux-arm64-gnu": "0.13.0",
|
||||
"@lancedb/vectordb-linux-x64-gnu": "0.13.0",
|
||||
"@lancedb/vectordb-win32-arm64-msvc": "0.13.0",
|
||||
"@lancedb/vectordb-win32-x64-msvc": "0.13.0"
|
||||
"@lancedb/vectordb-darwin-arm64": "0.14.0-beta.2",
|
||||
"@lancedb/vectordb-darwin-x64": "0.14.0-beta.2",
|
||||
"@lancedb/vectordb-linux-arm64-gnu": "0.14.0-beta.2",
|
||||
"@lancedb/vectordb-linux-arm64-musl": "0.14.0-beta.2",
|
||||
"@lancedb/vectordb-linux-x64-gnu": "0.14.0-beta.2",
|
||||
"@lancedb/vectordb-linux-x64-musl": "0.14.0-beta.2",
|
||||
"@lancedb/vectordb-win32-arm64-msvc": "0.14.0-beta.2",
|
||||
"@lancedb/vectordb-win32-x64-msvc": "0.14.0-beta.2"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"@apache-arrow/ts": "^14.0.2",
|
||||
@@ -327,66 +329,6 @@
|
||||
"@jridgewell/sourcemap-codec": "^1.4.10"
|
||||
}
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-darwin-arm64": {
|
||||
"version": "0.13.0",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-arm64/-/vectordb-darwin-arm64-0.13.0.tgz",
|
||||
"integrity": "sha512-8hdcjkRmgrdQYf1jN+DyZae40LIv8UUfnWy70Uid5qy63sSvRW/+MvIdqIPFr9QlLUXmpyyQuX0y3bZhUR99cQ==",
|
||||
"cpu": [
|
||||
"arm64"
|
||||
],
|
||||
"optional": true,
|
||||
"os": [
|
||||
"darwin"
|
||||
]
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-darwin-x64": {
|
||||
"version": "0.13.0",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-x64/-/vectordb-darwin-x64-0.13.0.tgz",
|
||||
"integrity": "sha512-fWzAY4l5SQtNfMYh80v+M66ugZHhdxbkpk5mNEv6Zsug3DL6kRj3Uv31/i0wgzY6F5G3LUlbjZerN+eTnDLwOw==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
"optional": true,
|
||||
"os": [
|
||||
"darwin"
|
||||
]
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-linux-arm64-gnu": {
|
||||
"version": "0.13.0",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-arm64-gnu/-/vectordb-linux-arm64-gnu-0.13.0.tgz",
|
||||
"integrity": "sha512-ltwAT9baOSuR5YiGykQXPC8/HGYF13vpI47qxhP9yfgiz9pA8EUn8p8YrBRzq7J4DIZ4b8JSVDXQnMIqEtB4Kg==",
|
||||
"cpu": [
|
||||
"arm64"
|
||||
],
|
||||
"optional": true,
|
||||
"os": [
|
||||
"linux"
|
||||
]
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-linux-x64-gnu": {
|
||||
"version": "0.13.0",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-x64-gnu/-/vectordb-linux-x64-gnu-0.13.0.tgz",
|
||||
"integrity": "sha512-MiT/RBlMPGGRh7BX+MXwRuNiiUnKmuDcHH8nm88IH28T7TQxXIbA9w6UpSg5m9f3DgKQI2K8oLi29oKIB8ZwDQ==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
"optional": true,
|
||||
"os": [
|
||||
"linux"
|
||||
]
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-win32-x64-msvc": {
|
||||
"version": "0.13.0",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-win32-x64-msvc/-/vectordb-win32-x64-msvc-0.13.0.tgz",
|
||||
"integrity": "sha512-SovP/hwWYLJIy65DKbVuXlBPTb/nwvVpTO6dh9zRch+L5ek6JmVAkwsfeTS2p5bMa8VPujsCXYUAVuCDEJU8wg==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
"optional": true,
|
||||
"os": [
|
||||
"win32"
|
||||
]
|
||||
},
|
||||
"node_modules/@neon-rs/cli": {
|
||||
"version": "0.0.160",
|
||||
"resolved": "https://registry.npmjs.org/@neon-rs/cli/-/cli-0.0.160.tgz",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "vectordb",
|
||||
"version": "0.13.0",
|
||||
"version": "0.14.0-beta.2",
|
||||
"description": " Serverless, low-latency vector database for AI applications",
|
||||
"main": "dist/index.js",
|
||||
"types": "dist/index.d.ts",
|
||||
@@ -84,18 +84,20 @@
|
||||
"aarch64-apple-darwin": "@lancedb/vectordb-darwin-arm64",
|
||||
"x86_64-unknown-linux-gnu": "@lancedb/vectordb-linux-x64-gnu",
|
||||
"aarch64-unknown-linux-gnu": "@lancedb/vectordb-linux-arm64-gnu",
|
||||
"x86_64-unknown-linux-musl": "@lancedb/vectordb-linux-x64-musl",
|
||||
"aarch64-unknown-linux-musl": "@lancedb/vectordb-linux-arm64-musl",
|
||||
"x86_64-pc-windows-msvc": "@lancedb/vectordb-win32-x64-msvc",
|
||||
"aarch64-pc-windows-msvc": "@lancedb/vectordb-win32-arm64-msvc"
|
||||
}
|
||||
},
|
||||
"optionalDependencies": {
|
||||
"@lancedb/vectordb-darwin-x64": "0.13.0",
|
||||
"@lancedb/vectordb-darwin-arm64": "0.13.0",
|
||||
"@lancedb/vectordb-linux-x64-gnu": "0.13.0",
|
||||
"@lancedb/vectordb-linux-arm64-gnu": "0.13.0",
|
||||
"@lancedb/vectordb-linux-x64-musl": "0.13.0",
|
||||
"@lancedb/vectordb-linux-arm64-musl": "0.13.0",
|
||||
"@lancedb/vectordb-win32-x64-msvc": "0.13.0",
|
||||
"@lancedb/vectordb-win32-arm64-msvc": "0.13.0"
|
||||
"@lancedb/vectordb-darwin-x64": "0.14.0-beta.2",
|
||||
"@lancedb/vectordb-darwin-arm64": "0.14.0-beta.2",
|
||||
"@lancedb/vectordb-linux-x64-gnu": "0.14.0-beta.2",
|
||||
"@lancedb/vectordb-linux-arm64-gnu": "0.14.0-beta.2",
|
||||
"@lancedb/vectordb-linux-x64-musl": "0.14.0-beta.2",
|
||||
"@lancedb/vectordb-linux-arm64-musl": "0.14.0-beta.2",
|
||||
"@lancedb/vectordb-win32-x64-msvc": "0.14.0-beta.2",
|
||||
"@lancedb/vectordb-win32-arm64-msvc": "0.14.0-beta.2"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
[package]
|
||||
name = "lancedb-nodejs"
|
||||
edition.workspace = true
|
||||
version = "0.13.0"
|
||||
version = "0.14.0-beta.2"
|
||||
license.workspace = true
|
||||
description.workspace = true
|
||||
repository.workspace = true
|
||||
|
||||
@@ -110,7 +110,10 @@ describe("given a connection", () => {
|
||||
let table = await db.createTable("test", data, { useLegacyFormat: true });
|
||||
|
||||
const isV2 = async (table: Table) => {
|
||||
const data = await table.query().toArrow({ maxBatchLength: 100000 });
|
||||
const data = await table
|
||||
.query()
|
||||
.limit(10000)
|
||||
.toArrow({ maxBatchLength: 100000 });
|
||||
console.log(data.batches.length);
|
||||
return data.batches.length < 5;
|
||||
};
|
||||
|
||||
@@ -585,11 +585,11 @@ describe("When creating an index", () => {
|
||||
expect(fs.readdirSync(indexDir)).toHaveLength(1);
|
||||
|
||||
for await (const r of tbl.query().where("id > 1").select(["id"])) {
|
||||
expect(r.numRows).toBe(298);
|
||||
expect(r.numRows).toBe(10);
|
||||
}
|
||||
// should also work with 'filter' alias
|
||||
for await (const r of tbl.query().filter("id > 1").select(["id"])) {
|
||||
expect(r.numRows).toBe(298);
|
||||
expect(r.numRows).toBe(10);
|
||||
}
|
||||
});
|
||||
|
||||
@@ -825,6 +825,18 @@ describe("schema evolution", function () {
|
||||
new Field("price", new Float64(), true),
|
||||
]);
|
||||
expect(await table.schema()).toEqual(expectedSchema);
|
||||
|
||||
await table.alterColumns([{ path: "new_id", dataType: "int32" }]);
|
||||
const expectedSchema2 = new Schema([
|
||||
new Field("new_id", new Int32(), true),
|
||||
new Field(
|
||||
"vector",
|
||||
new FixedSizeList(2, new Field("item", new Float32(), true)),
|
||||
true,
|
||||
),
|
||||
new Field("price", new Float64(), true),
|
||||
]);
|
||||
expect(await table.schema()).toEqual(expectedSchema2);
|
||||
});
|
||||
|
||||
it("can drop a column from the schema", async function () {
|
||||
|
||||
@@ -116,6 +116,26 @@ test("basic table examples", async () => {
|
||||
await tbl.add(data);
|
||||
// --8<-- [end:add_data]
|
||||
}
|
||||
|
||||
{
|
||||
// --8<-- [start:add_columns]
|
||||
await tbl.addColumns([{ name: "double_price", valueSql: "price * 2" }]);
|
||||
// --8<-- [end:add_columns]
|
||||
// --8<-- [start:alter_columns]
|
||||
await tbl.alterColumns([
|
||||
{
|
||||
path: "double_price",
|
||||
rename: "dbl_price",
|
||||
dataType: "float",
|
||||
nullable: true,
|
||||
},
|
||||
]);
|
||||
// --8<-- [end:alter_columns]
|
||||
// --8<-- [start:drop_columns]
|
||||
await tbl.dropColumns(["dbl_price"]);
|
||||
// --8<-- [end:drop_columns]
|
||||
}
|
||||
|
||||
{
|
||||
// --8<-- [start:vector_search]
|
||||
const res = await tbl.search([100, 100]).limit(2).toArray();
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-darwin-arm64",
|
||||
"version": "0.13.0",
|
||||
"version": "0.14.0-beta.2",
|
||||
"os": ["darwin"],
|
||||
"cpu": ["arm64"],
|
||||
"main": "lancedb.darwin-arm64.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-darwin-x64",
|
||||
"version": "0.13.0",
|
||||
"version": "0.14.0-beta.2",
|
||||
"os": ["darwin"],
|
||||
"cpu": ["x64"],
|
||||
"main": "lancedb.darwin-x64.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-arm64-gnu",
|
||||
"version": "0.13.0",
|
||||
"version": "0.14.0-beta.2",
|
||||
"os": ["linux"],
|
||||
"cpu": ["arm64"],
|
||||
"main": "lancedb.linux-arm64-gnu.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-arm64-musl",
|
||||
"version": "0.13.0",
|
||||
"version": "0.14.0-beta.2",
|
||||
"os": ["linux"],
|
||||
"cpu": ["arm64"],
|
||||
"main": "lancedb.linux-arm64-musl.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-x64-gnu",
|
||||
"version": "0.13.0",
|
||||
"version": "0.14.0-beta.2",
|
||||
"os": ["linux"],
|
||||
"cpu": ["x64"],
|
||||
"main": "lancedb.linux-x64-gnu.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-x64-musl",
|
||||
"version": "0.13.0",
|
||||
"version": "0.14.0-beta.2",
|
||||
"os": ["linux"],
|
||||
"cpu": ["x64"],
|
||||
"main": "lancedb.linux-x64-musl.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-win32-arm64-msvc",
|
||||
"version": "0.13.0",
|
||||
"version": "0.14.0-beta.2",
|
||||
"os": [
|
||||
"win32"
|
||||
],
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-win32-x64-msvc",
|
||||
"version": "0.13.0",
|
||||
"version": "0.14.0-beta.2",
|
||||
"os": ["win32"],
|
||||
"cpu": ["x64"],
|
||||
"main": "lancedb.win32-x64-msvc.node",
|
||||
|
||||
@@ -10,7 +10,7 @@
|
||||
"vector database",
|
||||
"ann"
|
||||
],
|
||||
"version": "0.13.0",
|
||||
"version": "0.14.0-beta.2",
|
||||
"main": "dist/index.js",
|
||||
"exports": {
|
||||
".": "./dist/index.js",
|
||||
|
||||
@@ -178,16 +178,20 @@ impl Table {
|
||||
#[napi(catch_unwind)]
|
||||
pub async fn alter_columns(&self, alterations: Vec<ColumnAlteration>) -> napi::Result<()> {
|
||||
for alteration in &alterations {
|
||||
if alteration.rename.is_none() && alteration.nullable.is_none() {
|
||||
if alteration.rename.is_none()
|
||||
&& alteration.nullable.is_none()
|
||||
&& alteration.data_type.is_none()
|
||||
{
|
||||
return Err(napi::Error::from_reason(
|
||||
"Alteration must have a 'rename' or 'nullable' field.",
|
||||
"Alteration must have a 'rename', 'dataType', or 'nullable' field.",
|
||||
));
|
||||
}
|
||||
}
|
||||
let alterations = alterations
|
||||
.into_iter()
|
||||
.map(LanceColumnAlteration::from)
|
||||
.collect::<Vec<_>>();
|
||||
.map(LanceColumnAlteration::try_from)
|
||||
.collect::<std::result::Result<Vec<_>, String>>()
|
||||
.map_err(napi::Error::from_reason)?;
|
||||
|
||||
self.inner_ref()?
|
||||
.alter_columns(&alterations)
|
||||
@@ -433,24 +437,43 @@ pub struct ColumnAlteration {
|
||||
/// The new name of the column. If not provided then the name will not be changed.
|
||||
/// This must be distinct from the names of all other columns in the table.
|
||||
pub rename: Option<String>,
|
||||
/// A new data type for the column. If not provided then the data type will not be changed.
|
||||
/// Changing data types is limited to casting to the same general type. For example, these
|
||||
/// changes are valid:
|
||||
/// * `int32` -> `int64` (integers)
|
||||
/// * `double` -> `float` (floats)
|
||||
/// * `string` -> `large_string` (strings)
|
||||
/// But these changes are not:
|
||||
/// * `int32` -> `double` (mix integers and floats)
|
||||
/// * `string` -> `int32` (mix strings and integers)
|
||||
pub data_type: Option<String>,
|
||||
/// Set the new nullability. Note that a nullable column cannot be made non-nullable.
|
||||
pub nullable: Option<bool>,
|
||||
}
|
||||
|
||||
impl From<ColumnAlteration> for LanceColumnAlteration {
|
||||
fn from(js: ColumnAlteration) -> Self {
|
||||
impl TryFrom<ColumnAlteration> for LanceColumnAlteration {
|
||||
type Error = String;
|
||||
fn try_from(js: ColumnAlteration) -> std::result::Result<Self, Self::Error> {
|
||||
let ColumnAlteration {
|
||||
path,
|
||||
rename,
|
||||
nullable,
|
||||
data_type,
|
||||
} = js;
|
||||
Self {
|
||||
let data_type = if let Some(data_type) = data_type {
|
||||
Some(
|
||||
lancedb::utils::string_to_datatype(&data_type)
|
||||
.ok_or_else(|| format!("Invalid data type: {}", data_type))?,
|
||||
)
|
||||
} else {
|
||||
None
|
||||
};
|
||||
Ok(Self {
|
||||
path,
|
||||
rename,
|
||||
nullable,
|
||||
// TODO: wire up this field
|
||||
data_type: None,
|
||||
}
|
||||
data_type,
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
[tool.bumpversion]
|
||||
current_version = "0.16.1-beta.0"
|
||||
current_version = "0.17.0"
|
||||
parse = """(?x)
|
||||
(?P<major>0|[1-9]\\d*)\\.
|
||||
(?P<minor>0|[1-9]\\d*)\\.
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "lancedb-python"
|
||||
version = "0.16.1-beta.0"
|
||||
version = "0.17.0"
|
||||
edition.workspace = true
|
||||
description = "Python bindings for LanceDB"
|
||||
license.workspace = true
|
||||
@@ -14,29 +14,29 @@ name = "_lancedb"
|
||||
crate-type = ["cdylib"]
|
||||
|
||||
[dependencies]
|
||||
arrow = { version = "52.1", features = ["pyarrow"] }
|
||||
arrow = { version = "53.2", features = ["pyarrow"] }
|
||||
lancedb = { path = "../rust/lancedb", default-features = false }
|
||||
env_logger.workspace = true
|
||||
pyo3 = { version = "0.21", features = ["extension-module", "abi3-py38", "gil-refs"] }
|
||||
# Using this fork for now: https://github.com/awestlake87/pyo3-asyncio/issues/119
|
||||
# pyo3-asyncio = { version = "0.20", features = ["attributes", "tokio-runtime"] }
|
||||
pyo3-asyncio-0-21 = { version = "0.21.0", features = ["attributes", "tokio-runtime"] }
|
||||
|
||||
pyo3 = { version = "0.22.2", features = [
|
||||
"extension-module",
|
||||
"abi3-py39",
|
||||
"gil-refs"
|
||||
] }
|
||||
pyo3-async-runtimes = { version = "0.22", features = ["attributes", "tokio-runtime"] }
|
||||
pin-project = "1.1.5"
|
||||
futures.workspace = true
|
||||
tokio = { version = "1.36.0", features = ["sync"] }
|
||||
tokio = { version = "1.40", features = ["sync"] }
|
||||
|
||||
[build-dependencies]
|
||||
pyo3-build-config = { version = "0.20.3", features = [
|
||||
"extension-module",
|
||||
"abi3-py38",
|
||||
"abi3-py39",
|
||||
] }
|
||||
|
||||
[features]
|
||||
default = ["default-tls", "remote"]
|
||||
fp16kernels = ["lancedb/fp16kernels"]
|
||||
remote = ["lancedb/remote"]
|
||||
|
||||
# TLS
|
||||
default-tls = ["lancedb/default-tls"]
|
||||
native-tls = ["lancedb/native-tls"]
|
||||
|
||||
@@ -3,8 +3,7 @@ name = "lancedb"
|
||||
# version in Cargo.toml
|
||||
dependencies = [
|
||||
"deprecation",
|
||||
"nest-asyncio~=1.0",
|
||||
"pylance==0.20.0b2",
|
||||
"pylance==0.20.0",
|
||||
"tqdm>=4.27.0",
|
||||
"pydantic>=1.10",
|
||||
"packaging",
|
||||
@@ -31,7 +30,6 @@ classifiers = [
|
||||
"Programming Language :: Python",
|
||||
"Programming Language :: Python :: 3",
|
||||
"Programming Language :: Python :: 3 :: Only",
|
||||
"Programming Language :: Python :: 3.8",
|
||||
"Programming Language :: Python :: 3.9",
|
||||
"Programming Language :: Python :: 3.10",
|
||||
"Programming Language :: Python :: 3.11",
|
||||
|
||||
@@ -36,6 +36,7 @@ def connect(
|
||||
read_consistency_interval: Optional[timedelta] = None,
|
||||
request_thread_pool: Optional[Union[int, ThreadPoolExecutor]] = None,
|
||||
client_config: Union[ClientConfig, Dict[str, Any], None] = None,
|
||||
storage_options: Optional[Dict[str, str]] = None,
|
||||
**kwargs: Any,
|
||||
) -> DBConnection:
|
||||
"""Connect to a LanceDB database.
|
||||
@@ -67,6 +68,9 @@ def connect(
|
||||
Configuration options for the LanceDB Cloud HTTP client. If a dict, then
|
||||
the keys are the attributes of the ClientConfig class. If None, then the
|
||||
default configuration is used.
|
||||
storage_options: dict, optional
|
||||
Additional options for the storage backend. See available options at
|
||||
https://lancedb.github.io/lancedb/guides/storage/
|
||||
|
||||
Examples
|
||||
--------
|
||||
@@ -111,7 +115,11 @@ def connect(
|
||||
|
||||
if kwargs:
|
||||
raise ValueError(f"Unknown keyword arguments: {kwargs}")
|
||||
return LanceDBConnection(uri, read_consistency_interval=read_consistency_interval)
|
||||
return LanceDBConnection(
|
||||
uri,
|
||||
read_consistency_interval=read_consistency_interval,
|
||||
storage_options=storage_options,
|
||||
)
|
||||
|
||||
|
||||
async def connect_async(
|
||||
|
||||
25
python/python/lancedb/background_loop.py
Normal file
25
python/python/lancedb/background_loop.py
Normal file
@@ -0,0 +1,25 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
# SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
import asyncio
|
||||
import threading
|
||||
|
||||
|
||||
class BackgroundEventLoop:
|
||||
"""
|
||||
A background event loop that can run futures.
|
||||
|
||||
Used to bridge sync and async code, without messing with users event loops.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
self.loop = asyncio.new_event_loop()
|
||||
self.thread = threading.Thread(
|
||||
target=self.loop.run_forever,
|
||||
name="LanceDBBackgroundEventLoop",
|
||||
daemon=True,
|
||||
)
|
||||
self.thread.start()
|
||||
|
||||
def run(self, future):
|
||||
return asyncio.run_coroutine_threadsafe(future, self.loop).result()
|
||||
@@ -13,34 +13,29 @@
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import os
|
||||
from abc import abstractmethod
|
||||
from pathlib import Path
|
||||
from typing import TYPE_CHECKING, Dict, Iterable, List, Literal, Optional, Union
|
||||
|
||||
import pyarrow as pa
|
||||
from overrides import EnforceOverrides, override
|
||||
from pyarrow import fs
|
||||
|
||||
from lancedb.common import data_to_reader, validate_schema
|
||||
from lancedb.common import data_to_reader, sanitize_uri, validate_schema
|
||||
from lancedb.background_loop import BackgroundEventLoop
|
||||
|
||||
from ._lancedb import connect as lancedb_connect
|
||||
from .table import (
|
||||
AsyncTable,
|
||||
LanceTable,
|
||||
Table,
|
||||
_table_path,
|
||||
sanitize_create_table,
|
||||
)
|
||||
from .util import (
|
||||
fs_from_uri,
|
||||
get_uri_location,
|
||||
get_uri_scheme,
|
||||
validate_table_name,
|
||||
)
|
||||
|
||||
if TYPE_CHECKING:
|
||||
import pyarrow as pa
|
||||
from .pydantic import LanceModel
|
||||
from datetime import timedelta
|
||||
|
||||
@@ -48,6 +43,8 @@ if TYPE_CHECKING:
|
||||
from .common import DATA, URI
|
||||
from .embeddings import EmbeddingFunctionConfig
|
||||
|
||||
LOOP = BackgroundEventLoop()
|
||||
|
||||
|
||||
class DBConnection(EnforceOverrides):
|
||||
"""An active LanceDB connection interface."""
|
||||
@@ -180,6 +177,7 @@ class DBConnection(EnforceOverrides):
|
||||
control over how data is saved, either provide the PyArrow schema to
|
||||
convert to or else provide a [PyArrow Table](pyarrow.Table) directly.
|
||||
|
||||
>>> import pyarrow as pa
|
||||
>>> custom_schema = pa.schema([
|
||||
... pa.field("vector", pa.list_(pa.float32(), 2)),
|
||||
... pa.field("lat", pa.float32()),
|
||||
@@ -327,7 +325,11 @@ class LanceDBConnection(DBConnection):
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self, uri: URI, *, read_consistency_interval: Optional[timedelta] = None
|
||||
self,
|
||||
uri: URI,
|
||||
*,
|
||||
read_consistency_interval: Optional[timedelta] = None,
|
||||
storage_options: Optional[Dict[str, str]] = None,
|
||||
):
|
||||
if not isinstance(uri, Path):
|
||||
scheme = get_uri_scheme(uri)
|
||||
@@ -338,9 +340,27 @@ class LanceDBConnection(DBConnection):
|
||||
uri = uri.expanduser().absolute()
|
||||
Path(uri).mkdir(parents=True, exist_ok=True)
|
||||
self._uri = str(uri)
|
||||
|
||||
self._entered = False
|
||||
self.read_consistency_interval = read_consistency_interval
|
||||
self.storage_options = storage_options
|
||||
|
||||
if read_consistency_interval is not None:
|
||||
read_consistency_interval_secs = read_consistency_interval.total_seconds()
|
||||
else:
|
||||
read_consistency_interval_secs = None
|
||||
|
||||
async def do_connect():
|
||||
return await lancedb_connect(
|
||||
sanitize_uri(uri),
|
||||
None,
|
||||
None,
|
||||
None,
|
||||
read_consistency_interval_secs,
|
||||
None,
|
||||
storage_options,
|
||||
)
|
||||
|
||||
self._conn = AsyncConnection(LOOP.run(do_connect()))
|
||||
|
||||
def __repr__(self) -> str:
|
||||
val = f"{self.__class__.__name__}({self._uri}"
|
||||
@@ -364,32 +384,7 @@ class LanceDBConnection(DBConnection):
|
||||
Iterator of str.
|
||||
A list of table names.
|
||||
"""
|
||||
try:
|
||||
asyncio.get_running_loop()
|
||||
# User application is async. Soon we will just tell them to use the
|
||||
# async version. Until then fallback to the old sync implementation.
|
||||
try:
|
||||
filesystem = fs_from_uri(self.uri)[0]
|
||||
except pa.ArrowInvalid:
|
||||
raise NotImplementedError("Unsupported scheme: " + self.uri)
|
||||
|
||||
try:
|
||||
loc = get_uri_location(self.uri)
|
||||
paths = filesystem.get_file_info(fs.FileSelector(loc))
|
||||
except FileNotFoundError:
|
||||
# It is ok if the file does not exist since it will be created
|
||||
paths = []
|
||||
tables = [
|
||||
os.path.splitext(file_info.base_name)[0]
|
||||
for file_info in paths
|
||||
if file_info.extension == "lance"
|
||||
]
|
||||
tables.sort()
|
||||
return tables
|
||||
except RuntimeError:
|
||||
# User application is sync. It is safe to use the async implementation
|
||||
# under the hood.
|
||||
return asyncio.run(self._async_get_table_names(page_token, limit))
|
||||
return LOOP.run(self._conn.table_names(start_after=page_token, limit=limit))
|
||||
|
||||
def __len__(self) -> int:
|
||||
return len(self.table_names())
|
||||
@@ -461,19 +456,16 @@ class LanceDBConnection(DBConnection):
|
||||
If True, ignore if the table does not exist.
|
||||
"""
|
||||
try:
|
||||
table_uri = _table_path(self.uri, name)
|
||||
filesystem, path = fs_from_uri(table_uri)
|
||||
filesystem.delete_dir(path)
|
||||
except FileNotFoundError:
|
||||
LOOP.run(self._conn.drop_table(name))
|
||||
except ValueError as e:
|
||||
if not ignore_missing:
|
||||
raise
|
||||
raise e
|
||||
if f"Table '{name}' was not found" not in str(e):
|
||||
raise e
|
||||
|
||||
@override
|
||||
def drop_database(self):
|
||||
dummy_table_uri = _table_path(self.uri, "dummy")
|
||||
uri = dummy_table_uri.removesuffix("dummy.lance")
|
||||
filesystem, path = fs_from_uri(uri)
|
||||
filesystem.delete_dir(path)
|
||||
LOOP.run(self._conn.drop_database())
|
||||
|
||||
|
||||
class AsyncConnection(object):
|
||||
@@ -689,6 +681,7 @@ class AsyncConnection(object):
|
||||
control over how data is saved, either provide the PyArrow schema to
|
||||
convert to or else provide a [PyArrow Table](pyarrow.Table) directly.
|
||||
|
||||
>>> import pyarrow as pa
|
||||
>>> custom_schema = pa.schema([
|
||||
... pa.field("vector", pa.list_(pa.float32(), 2)),
|
||||
... pa.field("lat", pa.float32()),
|
||||
|
||||
@@ -48,6 +48,9 @@ class OpenAIEmbeddings(TextEmbeddingFunction):
|
||||
organization: Optional[str] = None
|
||||
api_key: Optional[str] = None
|
||||
|
||||
# Set true to use Azure OpenAI API
|
||||
use_azure: bool = False
|
||||
|
||||
def ndims(self):
|
||||
return self._ndims
|
||||
|
||||
@@ -83,25 +86,33 @@ class OpenAIEmbeddings(TextEmbeddingFunction):
|
||||
"""
|
||||
openai = attempt_import_or_raise("openai")
|
||||
|
||||
valid_texts = []
|
||||
valid_indices = []
|
||||
for idx, text in enumerate(texts):
|
||||
if text:
|
||||
valid_texts.append(text)
|
||||
valid_indices.append(idx)
|
||||
|
||||
# TODO retry, rate limit, token limit
|
||||
try:
|
||||
if self.name == "text-embedding-ada-002":
|
||||
rs = self._openai_client.embeddings.create(input=texts, model=self.name)
|
||||
else:
|
||||
kwargs = {
|
||||
"input": texts,
|
||||
"model": self.name,
|
||||
}
|
||||
if self.dim:
|
||||
kwargs["dimensions"] = self.dim
|
||||
rs = self._openai_client.embeddings.create(**kwargs)
|
||||
kwargs = {
|
||||
"input": valid_texts,
|
||||
"model": self.name,
|
||||
}
|
||||
if self.name != "text-embedding-ada-002":
|
||||
kwargs["dimensions"] = self.dim
|
||||
|
||||
rs = self._openai_client.embeddings.create(**kwargs)
|
||||
valid_embeddings = {
|
||||
idx: v.embedding for v, idx in zip(rs.data, valid_indices)
|
||||
}
|
||||
except openai.BadRequestError:
|
||||
logging.exception("Bad request: %s", texts)
|
||||
return [None] * len(texts)
|
||||
except Exception:
|
||||
logging.exception("OpenAI embeddings error")
|
||||
raise
|
||||
return [v.embedding for v in rs.data]
|
||||
return [valid_embeddings.get(idx, None) for idx in range(len(texts))]
|
||||
|
||||
@cached_property
|
||||
def _openai_client(self):
|
||||
@@ -115,4 +126,8 @@ class OpenAIEmbeddings(TextEmbeddingFunction):
|
||||
kwargs["organization"] = self.organization
|
||||
if self.api_key:
|
||||
kwargs["api_key"] = self.api_key
|
||||
return openai.OpenAI(**kwargs)
|
||||
|
||||
if self.use_azure:
|
||||
return openai.AzureOpenAI(**kwargs)
|
||||
else:
|
||||
return openai.OpenAI(**kwargs)
|
||||
|
||||
@@ -12,18 +12,22 @@
|
||||
# limitations under the License.
|
||||
|
||||
import os
|
||||
from typing import ClassVar, List, Union
|
||||
from typing import ClassVar, TYPE_CHECKING, List, Union
|
||||
|
||||
import numpy as np
|
||||
import pyarrow as pa
|
||||
|
||||
from ..util import attempt_import_or_raise
|
||||
from .base import TextEmbeddingFunction
|
||||
from .base import EmbeddingFunction
|
||||
from .registry import register
|
||||
from .utils import api_key_not_found_help, TEXT
|
||||
from .utils import api_key_not_found_help, IMAGES
|
||||
|
||||
if TYPE_CHECKING:
|
||||
import PIL
|
||||
|
||||
|
||||
@register("voyageai")
|
||||
class VoyageAIEmbeddingFunction(TextEmbeddingFunction):
|
||||
class VoyageAIEmbeddingFunction(EmbeddingFunction):
|
||||
"""
|
||||
An embedding function that uses the VoyageAI API
|
||||
|
||||
@@ -36,6 +40,7 @@ class VoyageAIEmbeddingFunction(TextEmbeddingFunction):
|
||||
|
||||
* voyage-3
|
||||
* voyage-3-lite
|
||||
* voyage-multimodal-3
|
||||
* voyage-finance-2
|
||||
* voyage-multilingual-2
|
||||
* voyage-law-2
|
||||
@@ -54,7 +59,7 @@ class VoyageAIEmbeddingFunction(TextEmbeddingFunction):
|
||||
.create(name="voyage-3")
|
||||
|
||||
class TextModel(LanceModel):
|
||||
text: str = voyageai.SourceField()
|
||||
data: str = voyageai.SourceField()
|
||||
vector: Vector(voyageai.ndims()) = voyageai.VectorField()
|
||||
|
||||
data = [ { "text": "hello world" },
|
||||
@@ -77,6 +82,7 @@ class VoyageAIEmbeddingFunction(TextEmbeddingFunction):
|
||||
return 1536
|
||||
elif self.name in [
|
||||
"voyage-3",
|
||||
"voyage-multimodal-3",
|
||||
"voyage-finance-2",
|
||||
"voyage-multilingual-2",
|
||||
"voyage-law-2",
|
||||
@@ -85,19 +91,19 @@ class VoyageAIEmbeddingFunction(TextEmbeddingFunction):
|
||||
else:
|
||||
raise ValueError(f"Model {self.name} not supported")
|
||||
|
||||
def compute_query_embeddings(self, query: str, *args, **kwargs) -> List[np.array]:
|
||||
return self.compute_source_embeddings(query, input_type="query")
|
||||
def sanitize_input(self, images: IMAGES) -> Union[List[bytes], np.ndarray]:
|
||||
"""
|
||||
Sanitize the input to the embedding function.
|
||||
"""
|
||||
if isinstance(images, (str, bytes)):
|
||||
images = [images]
|
||||
elif isinstance(images, pa.Array):
|
||||
images = images.to_pylist()
|
||||
elif isinstance(images, pa.ChunkedArray):
|
||||
images = images.combine_chunks().to_pylist()
|
||||
return images
|
||||
|
||||
def compute_source_embeddings(self, texts: TEXT, *args, **kwargs) -> List[np.array]:
|
||||
texts = self.sanitize_input(texts)
|
||||
input_type = (
|
||||
kwargs.get("input_type") or "document"
|
||||
) # assume source input type if not passed by `compute_query_embeddings`
|
||||
return self.generate_embeddings(texts, input_type=input_type)
|
||||
|
||||
def generate_embeddings(
|
||||
self, texts: Union[List[str], np.ndarray], *args, **kwargs
|
||||
) -> List[np.array]:
|
||||
def generate_text_embeddings(self, text: str, **kwargs) -> np.ndarray:
|
||||
"""
|
||||
Get the embeddings for the given texts
|
||||
|
||||
@@ -109,15 +115,55 @@ class VoyageAIEmbeddingFunction(TextEmbeddingFunction):
|
||||
|
||||
truncation: Optional[bool]
|
||||
"""
|
||||
VoyageAIEmbeddingFunction._init_client()
|
||||
rs = VoyageAIEmbeddingFunction.client.embed(
|
||||
texts=texts, model=self.name, **kwargs
|
||||
)
|
||||
if self.name in ["voyage-multimodal-3"]:
|
||||
rs = VoyageAIEmbeddingFunction._get_client().multimodal_embed(
|
||||
inputs=[[text]], model=self.name, **kwargs
|
||||
)
|
||||
else:
|
||||
rs = VoyageAIEmbeddingFunction._get_client().embed(
|
||||
texts=[text], model=self.name, **kwargs
|
||||
)
|
||||
|
||||
return [emb for emb in rs.embeddings]
|
||||
return rs.embeddings[0]
|
||||
|
||||
def generate_image_embedding(
|
||||
self, image: "PIL.Image.Image", **kwargs
|
||||
) -> np.ndarray:
|
||||
rs = VoyageAIEmbeddingFunction._get_client().multimodal_embed(
|
||||
inputs=[[image]], model=self.name, **kwargs
|
||||
)
|
||||
return rs.embeddings[0]
|
||||
|
||||
def compute_query_embeddings(
|
||||
self, query: Union[str, "PIL.Image.Image"], *args, **kwargs
|
||||
) -> List[np.ndarray]:
|
||||
"""
|
||||
Compute the embeddings for a given user query
|
||||
|
||||
Parameters
|
||||
----------
|
||||
query : Union[str, PIL.Image.Image]
|
||||
The query to embed. A query can be either text or an image.
|
||||
"""
|
||||
if isinstance(query, str):
|
||||
return [self.generate_text_embeddings(query, input_type="query")]
|
||||
else:
|
||||
PIL = attempt_import_or_raise("PIL", "pillow")
|
||||
if isinstance(query, PIL.Image.Image):
|
||||
return [self.generate_image_embedding(query, input_type="query")]
|
||||
else:
|
||||
raise TypeError("Only text PIL images supported as query")
|
||||
|
||||
def compute_source_embeddings(
|
||||
self, images: IMAGES, *args, **kwargs
|
||||
) -> List[np.array]:
|
||||
images = self.sanitize_input(images)
|
||||
return [
|
||||
self.generate_image_embedding(img, input_type="document") for img in images
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
def _init_client():
|
||||
def _get_client():
|
||||
if VoyageAIEmbeddingFunction.client is None:
|
||||
voyageai = attempt_import_or_raise("voyageai")
|
||||
if os.environ.get("VOYAGE_API_KEY") is None:
|
||||
@@ -125,3 +171,4 @@ class VoyageAIEmbeddingFunction(TextEmbeddingFunction):
|
||||
VoyageAIEmbeddingFunction.client = voyageai.Client(
|
||||
os.environ["VOYAGE_API_KEY"]
|
||||
)
|
||||
return VoyageAIEmbeddingFunction.client
|
||||
|
||||
@@ -110,7 +110,16 @@ class FTS:
|
||||
remove_stop_words: bool = False,
|
||||
ascii_folding: bool = False,
|
||||
):
|
||||
self._inner = LanceDbIndex.fts(with_position=with_position)
|
||||
self._inner = LanceDbIndex.fts(
|
||||
with_position=with_position,
|
||||
base_tokenizer=base_tokenizer,
|
||||
language=language,
|
||||
max_token_length=max_token_length,
|
||||
lower_case=lower_case,
|
||||
stem=stem,
|
||||
remove_stop_words=remove_stop_words,
|
||||
ascii_folding=ascii_folding,
|
||||
)
|
||||
|
||||
|
||||
class HnswPq:
|
||||
|
||||
0
python/python/lancedb/integrations/__init__.py
Normal file
0
python/python/lancedb/integrations/__init__.py
Normal file
248
python/python/lancedb/integrations/pyarrow.py
Normal file
248
python/python/lancedb/integrations/pyarrow.py
Normal file
@@ -0,0 +1,248 @@
|
||||
import logging
|
||||
from typing import Any, List, Optional, Tuple, Union, Literal
|
||||
|
||||
import pyarrow as pa
|
||||
|
||||
from ..table import Table
|
||||
|
||||
Filter = Union[str, pa.compute.Expression]
|
||||
Keys = Union[str, List[str]]
|
||||
JoinType = Literal[
|
||||
"left semi",
|
||||
"right semi",
|
||||
"left anti",
|
||||
"right anti",
|
||||
"inner",
|
||||
"left outer",
|
||||
"right outer",
|
||||
"full outer",
|
||||
]
|
||||
|
||||
|
||||
class PyarrowScannerAdapter(pa.dataset.Scanner):
|
||||
def __init__(
|
||||
self,
|
||||
table: Table,
|
||||
columns: Optional[List[str]] = None,
|
||||
filter: Optional[Filter] = None,
|
||||
batch_size: Optional[int] = None,
|
||||
batch_readahead: Optional[int] = None,
|
||||
fragment_readahead: Optional[int] = None,
|
||||
fragment_scan_options: Optional[Any] = None,
|
||||
use_threads: bool = True,
|
||||
memory_pool: Optional[Any] = None,
|
||||
):
|
||||
self.table = table
|
||||
self.columns = columns
|
||||
self.filter = filter
|
||||
self.batch_size = batch_size
|
||||
if batch_readahead is not None:
|
||||
logging.debug("ignoring batch_readahead which has no lance equivalent")
|
||||
if fragment_readahead is not None:
|
||||
logging.debug("ignoring fragment_readahead which has no lance equivalent")
|
||||
if fragment_scan_options is not None:
|
||||
raise NotImplementedError("fragment_scan_options not supported")
|
||||
if use_threads is False:
|
||||
raise NotImplementedError("use_threads=False not supported")
|
||||
if memory_pool is not None:
|
||||
raise NotImplementedError("memory_pool not supported")
|
||||
|
||||
def count_rows(self):
|
||||
return self.table.count_rows(self.filter)
|
||||
|
||||
def from_batches(self, **kwargs):
|
||||
raise NotImplementedError
|
||||
|
||||
def from_dataset(self, **kwargs):
|
||||
raise NotImplementedError
|
||||
|
||||
def from_fragment(self, **kwargs):
|
||||
raise NotImplementedError
|
||||
|
||||
def head(self, num_rows: int):
|
||||
return self.to_reader(limit=num_rows).read_all()
|
||||
|
||||
@property
|
||||
def projected_schema(self):
|
||||
return self.head(1).schema
|
||||
|
||||
def scan_batches(self):
|
||||
return self.to_reader()
|
||||
|
||||
def take(self, indices: List[int]):
|
||||
raise NotImplementedError
|
||||
|
||||
def to_batches(self):
|
||||
return self.to_reader()
|
||||
|
||||
def to_table(self):
|
||||
return self.to_reader().read_all()
|
||||
|
||||
def to_reader(self, *, limit: Optional[int] = None):
|
||||
query = self.table.search()
|
||||
# Disable the builtin limit
|
||||
if limit is None:
|
||||
num_rows = self.count_rows()
|
||||
query.limit(num_rows)
|
||||
elif limit <= 0:
|
||||
raise ValueError("limit must be positive")
|
||||
else:
|
||||
query.limit(limit)
|
||||
if self.columns is not None:
|
||||
query = query.select(self.columns)
|
||||
if self.filter is not None:
|
||||
query = query.where(self.filter, prefilter=True)
|
||||
return query.to_batches(batch_size=self.batch_size)
|
||||
|
||||
|
||||
class PyarrowDatasetAdapter(pa.dataset.Dataset):
|
||||
def __init__(self, table: Table):
|
||||
self.table = table
|
||||
|
||||
def count_rows(self, filter: Optional[Filter] = None):
|
||||
return self.table.count_rows(filter)
|
||||
|
||||
def get_fragments(self, filter: Optional[Filter] = None):
|
||||
raise NotImplementedError
|
||||
|
||||
def head(
|
||||
self,
|
||||
num_rows: int,
|
||||
columns: Optional[List[str]] = None,
|
||||
filter: Optional[Filter] = None,
|
||||
batch_size: Optional[int] = None,
|
||||
batch_readahead: Optional[int] = None,
|
||||
fragment_readahead: Optional[int] = None,
|
||||
fragment_scan_options: Optional[Any] = None,
|
||||
use_threads: bool = True,
|
||||
memory_pool: Optional[Any] = None,
|
||||
):
|
||||
return self.scanner(
|
||||
columns,
|
||||
filter,
|
||||
batch_size,
|
||||
batch_readahead,
|
||||
fragment_readahead,
|
||||
fragment_scan_options,
|
||||
use_threads,
|
||||
memory_pool,
|
||||
).head(num_rows)
|
||||
|
||||
def join(
|
||||
self,
|
||||
right_dataset: Any,
|
||||
keys: Keys,
|
||||
right_keys: Optional[Keys] = None,
|
||||
join_type: Optional[JoinType] = None,
|
||||
left_suffix: Optional[str] = None,
|
||||
right_suffix: Optional[str] = None,
|
||||
coalesce_keys: bool = True,
|
||||
use_threads: bool = True,
|
||||
):
|
||||
raise NotImplementedError
|
||||
|
||||
def join_asof(
|
||||
self,
|
||||
right_dataset: Any,
|
||||
on: str,
|
||||
by: Keys,
|
||||
tolerance: int,
|
||||
right_on: Optional[str] = None,
|
||||
right_by: Optional[Keys] = None,
|
||||
):
|
||||
raise NotImplementedError
|
||||
|
||||
@property
|
||||
def partition_expression(self):
|
||||
raise NotImplementedError
|
||||
|
||||
def replace_schema(self, schema: pa.Schema):
|
||||
raise NotImplementedError
|
||||
|
||||
def scanner(
|
||||
self,
|
||||
columns: Optional[List[str]] = None,
|
||||
filter: Optional[Filter] = None,
|
||||
batch_size: Optional[int] = None,
|
||||
batch_readahead: Optional[int] = None,
|
||||
fragment_readahead: Optional[int] = None,
|
||||
fragment_scan_options: Optional[Any] = None,
|
||||
use_threads: bool = True,
|
||||
memory_pool: Optional[Any] = None,
|
||||
):
|
||||
return PyarrowScannerAdapter(
|
||||
self.table,
|
||||
columns,
|
||||
filter,
|
||||
batch_size,
|
||||
batch_readahead,
|
||||
fragment_readahead,
|
||||
fragment_scan_options,
|
||||
use_threads,
|
||||
memory_pool,
|
||||
)
|
||||
|
||||
@property
|
||||
def schema(self):
|
||||
return self.table.schema
|
||||
|
||||
def sort_by(self, sorting: Union[str, List[Tuple[str, bool]]]):
|
||||
raise NotImplementedError
|
||||
|
||||
def take(
|
||||
self,
|
||||
indices: List[int],
|
||||
columns: Optional[List[str]] = None,
|
||||
filter: Optional[Filter] = None,
|
||||
batch_size: Optional[int] = None,
|
||||
batch_readahead: Optional[int] = None,
|
||||
fragment_readahead: Optional[int] = None,
|
||||
fragment_scan_options: Optional[Any] = None,
|
||||
use_threads: bool = True,
|
||||
memory_pool: Optional[Any] = None,
|
||||
):
|
||||
raise NotImplementedError
|
||||
|
||||
def to_batches(
|
||||
self,
|
||||
columns: Optional[List[str]] = None,
|
||||
filter: Optional[Filter] = None,
|
||||
batch_size: Optional[int] = None,
|
||||
batch_readahead: Optional[int] = None,
|
||||
fragment_readahead: Optional[int] = None,
|
||||
fragment_scan_options: Optional[Any] = None,
|
||||
use_threads: bool = True,
|
||||
memory_pool: Optional[Any] = None,
|
||||
):
|
||||
return self.scanner(
|
||||
columns,
|
||||
filter,
|
||||
batch_size,
|
||||
batch_readahead,
|
||||
fragment_readahead,
|
||||
fragment_scan_options,
|
||||
use_threads,
|
||||
memory_pool,
|
||||
).to_batches()
|
||||
|
||||
def to_table(
|
||||
self,
|
||||
columns: Optional[List[str]] = None,
|
||||
filter: Optional[Filter] = None,
|
||||
batch_size: Optional[int] = None,
|
||||
batch_readahead: Optional[int] = None,
|
||||
fragment_readahead: Optional[int] = None,
|
||||
fragment_scan_options: Optional[Any] = None,
|
||||
use_threads: bool = True,
|
||||
memory_pool: Optional[Any] = None,
|
||||
):
|
||||
return self.scanner(
|
||||
columns,
|
||||
filter,
|
||||
batch_size,
|
||||
batch_readahead,
|
||||
fragment_readahead,
|
||||
fragment_scan_options,
|
||||
use_threads,
|
||||
memory_pool,
|
||||
).to_table()
|
||||
@@ -1,15 +1,5 @@
|
||||
# Copyright 2023 LanceDB Developers
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
# SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
"""Pydantic (v1 / v2) adapter for LanceDB"""
|
||||
|
||||
@@ -30,6 +20,7 @@ from typing import (
|
||||
Type,
|
||||
Union,
|
||||
_GenericAlias,
|
||||
GenericAlias,
|
||||
)
|
||||
|
||||
import numpy as np
|
||||
@@ -75,7 +66,7 @@ def vector(dim: int, value_type: pa.DataType = pa.float32()):
|
||||
|
||||
|
||||
def Vector(
|
||||
dim: int, value_type: pa.DataType = pa.float32()
|
||||
dim: int, value_type: pa.DataType = pa.float32(), nullable: bool = True
|
||||
) -> Type[FixedSizeListMixin]:
|
||||
"""Pydantic Vector Type.
|
||||
|
||||
@@ -88,6 +79,8 @@ def Vector(
|
||||
The dimension of the vector.
|
||||
value_type : pyarrow.DataType, optional
|
||||
The value type of the vector, by default pa.float32()
|
||||
nullable : bool, optional
|
||||
Whether the vector is nullable, by default it is True.
|
||||
|
||||
Examples
|
||||
--------
|
||||
@@ -103,7 +96,7 @@ def Vector(
|
||||
>>> assert schema == pa.schema([
|
||||
... pa.field("id", pa.int64(), False),
|
||||
... pa.field("url", pa.utf8(), False),
|
||||
... pa.field("embeddings", pa.list_(pa.float32(), 768), False)
|
||||
... pa.field("embeddings", pa.list_(pa.float32(), 768))
|
||||
... ])
|
||||
"""
|
||||
|
||||
@@ -112,6 +105,10 @@ def Vector(
|
||||
def __repr__(self):
|
||||
return f"FixedSizeList(dim={dim})"
|
||||
|
||||
@staticmethod
|
||||
def nullable() -> bool:
|
||||
return nullable
|
||||
|
||||
@staticmethod
|
||||
def dim() -> int:
|
||||
return dim
|
||||
@@ -205,9 +202,7 @@ else:
|
||||
def _pydantic_to_arrow_type(field: FieldInfo) -> pa.DataType:
|
||||
"""Convert a Pydantic FieldInfo to Arrow DataType"""
|
||||
|
||||
if isinstance(field.annotation, _GenericAlias) or (
|
||||
sys.version_info > (3, 9) and isinstance(field.annotation, types.GenericAlias)
|
||||
):
|
||||
if isinstance(field.annotation, (_GenericAlias, GenericAlias)):
|
||||
origin = field.annotation.__origin__
|
||||
args = field.annotation.__args__
|
||||
if origin is list:
|
||||
@@ -235,7 +230,7 @@ def _pydantic_to_arrow_type(field: FieldInfo) -> pa.DataType:
|
||||
|
||||
def is_nullable(field: FieldInfo) -> bool:
|
||||
"""Check if a Pydantic FieldInfo is nullable."""
|
||||
if isinstance(field.annotation, _GenericAlias):
|
||||
if isinstance(field.annotation, (_GenericAlias, GenericAlias)):
|
||||
origin = field.annotation.__origin__
|
||||
args = field.annotation.__args__
|
||||
if origin == Union:
|
||||
@@ -246,6 +241,10 @@ def is_nullable(field: FieldInfo) -> bool:
|
||||
for typ in args:
|
||||
if typ is type(None):
|
||||
return True
|
||||
elif inspect.isclass(field.annotation) and issubclass(
|
||||
field.annotation, FixedSizeListMixin
|
||||
):
|
||||
return field.annotation.nullable()
|
||||
return False
|
||||
|
||||
|
||||
|
||||
@@ -325,6 +325,14 @@ class LanceQueryBuilder(ABC):
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
@abstractmethod
|
||||
def to_batches(self, /, batch_size: Optional[int] = None) -> pa.Table:
|
||||
"""
|
||||
Execute the query and return the results as a pyarrow
|
||||
[RecordBatchReader](https://arrow.apache.org/docs/python/generated/pyarrow.RecordBatchReader.html)
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
def to_list(self) -> List[dict]:
|
||||
"""
|
||||
Execute the query and return the results as a list of dictionaries.
|
||||
@@ -869,6 +877,9 @@ class LanceFtsQueryBuilder(LanceQueryBuilder):
|
||||
check_reranker_result(results)
|
||||
return results
|
||||
|
||||
def to_batches(self, /, batch_size: Optional[int] = None):
|
||||
raise NotImplementedError("to_batches on an FTS query")
|
||||
|
||||
def tantivy_to_arrow(self) -> pa.Table:
|
||||
try:
|
||||
import tantivy
|
||||
@@ -971,6 +982,9 @@ class LanceFtsQueryBuilder(LanceQueryBuilder):
|
||||
|
||||
class LanceEmptyQueryBuilder(LanceQueryBuilder):
|
||||
def to_arrow(self) -> pa.Table:
|
||||
return self.to_batches().read_all()
|
||||
|
||||
def to_batches(self, /, batch_size: Optional[int] = None) -> pa.RecordBatchReader:
|
||||
query = Query(
|
||||
columns=self._columns,
|
||||
filter=self._where,
|
||||
@@ -980,7 +994,7 @@ class LanceEmptyQueryBuilder(LanceQueryBuilder):
|
||||
# not actually respected in remote query
|
||||
offset=self._offset or 0,
|
||||
)
|
||||
return self._table._execute_query(query).read_all()
|
||||
return self._table._execute_query(query)
|
||||
|
||||
def rerank(self, reranker: Reranker) -> LanceEmptyQueryBuilder:
|
||||
"""Rerank the results using the specified reranker.
|
||||
@@ -1135,6 +1149,9 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
|
||||
results = results.drop(["_rowid"])
|
||||
return results
|
||||
|
||||
def to_batches(self):
|
||||
raise NotImplementedError("to_batches not yet supported on a hybrid query")
|
||||
|
||||
def _rank(self, results: pa.Table, column: str, ascending: bool = True):
|
||||
if len(results) == 0:
|
||||
return results
|
||||
@@ -1502,10 +1519,11 @@ class AsyncQueryBase(object):
|
||||
... print(plan)
|
||||
>>> asyncio.run(doctest_example()) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
|
||||
ProjectionExec: expr=[vector@0 as vector, _distance@2 as _distance]
|
||||
FilterExec: _distance@2 IS NOT NULL
|
||||
SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST], preserve_partitioning=[false]
|
||||
KNNVectorDistance: metric=l2
|
||||
LanceScan: uri=..., projection=[vector], row_id=true, row_addr=false, ordered=false
|
||||
GlobalLimitExec: skip=0, fetch=10
|
||||
FilterExec: _distance@2 IS NOT NULL
|
||||
SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST], preserve_partitioning=[false]
|
||||
KNNVectorDistance: metric=l2
|
||||
LanceScan: uri=..., projection=[vector], row_id=true, row_addr=false, ordered=false
|
||||
|
||||
Parameters
|
||||
----------
|
||||
|
||||
@@ -11,7 +11,6 @@
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
import asyncio
|
||||
from datetime import timedelta
|
||||
import logging
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
@@ -25,7 +24,7 @@ import pyarrow as pa
|
||||
from overrides import override
|
||||
|
||||
from ..common import DATA
|
||||
from ..db import DBConnection
|
||||
from ..db import DBConnection, LOOP
|
||||
from ..embeddings import EmbeddingFunctionConfig
|
||||
from ..pydantic import LanceModel
|
||||
from ..table import Table
|
||||
@@ -86,18 +85,9 @@ class RemoteDBConnection(DBConnection):
|
||||
raise ValueError(f"Invalid scheme: {parsed.scheme}, only accepts db://")
|
||||
self.db_name = parsed.netloc
|
||||
|
||||
import nest_asyncio
|
||||
|
||||
nest_asyncio.apply()
|
||||
try:
|
||||
self._loop = asyncio.get_running_loop()
|
||||
except RuntimeError:
|
||||
self._loop = asyncio.new_event_loop()
|
||||
asyncio.set_event_loop(self._loop)
|
||||
|
||||
self.client_config = client_config
|
||||
|
||||
self._conn = self._loop.run_until_complete(
|
||||
self._conn = LOOP.run(
|
||||
connect_async(
|
||||
db_url,
|
||||
api_key=api_key,
|
||||
@@ -127,9 +117,7 @@ class RemoteDBConnection(DBConnection):
|
||||
-------
|
||||
An iterator of table names.
|
||||
"""
|
||||
return self._loop.run_until_complete(
|
||||
self._conn.table_names(start_after=page_token, limit=limit)
|
||||
)
|
||||
return LOOP.run(self._conn.table_names(start_after=page_token, limit=limit))
|
||||
|
||||
@override
|
||||
def open_table(self, name: str, *, index_cache_size: Optional[int] = None) -> Table:
|
||||
@@ -152,8 +140,8 @@ class RemoteDBConnection(DBConnection):
|
||||
" (there is no local cache to configure)"
|
||||
)
|
||||
|
||||
table = self._loop.run_until_complete(self._conn.open_table(name))
|
||||
return RemoteTable(table, self.db_name, self._loop)
|
||||
table = LOOP.run(self._conn.open_table(name))
|
||||
return RemoteTable(table, self.db_name)
|
||||
|
||||
@override
|
||||
def create_table(
|
||||
@@ -268,7 +256,7 @@ class RemoteDBConnection(DBConnection):
|
||||
|
||||
from .table import RemoteTable
|
||||
|
||||
table = self._loop.run_until_complete(
|
||||
table = LOOP.run(
|
||||
self._conn.create_table(
|
||||
name,
|
||||
data,
|
||||
@@ -278,7 +266,7 @@ class RemoteDBConnection(DBConnection):
|
||||
fill_value=fill_value,
|
||||
)
|
||||
)
|
||||
return RemoteTable(table, self.db_name, self._loop)
|
||||
return RemoteTable(table, self.db_name)
|
||||
|
||||
@override
|
||||
def drop_table(self, name: str):
|
||||
@@ -289,7 +277,7 @@ class RemoteDBConnection(DBConnection):
|
||||
name: str
|
||||
The name of the table.
|
||||
"""
|
||||
self._loop.run_until_complete(self._conn.drop_table(name))
|
||||
LOOP.run(self._conn.drop_table(name))
|
||||
|
||||
@override
|
||||
def rename_table(self, cur_name: str, new_name: str):
|
||||
@@ -302,7 +290,7 @@ class RemoteDBConnection(DBConnection):
|
||||
new_name: str
|
||||
The new name of the table.
|
||||
"""
|
||||
self._loop.run_until_complete(self._conn.rename_table(cur_name, new_name))
|
||||
LOOP.run(self._conn.rename_table(cur_name, new_name))
|
||||
|
||||
async def close(self):
|
||||
"""Close the connection to the database."""
|
||||
|
||||
@@ -12,12 +12,12 @@
|
||||
# limitations under the License.
|
||||
|
||||
from datetime import timedelta
|
||||
import asyncio
|
||||
import logging
|
||||
from functools import cached_property
|
||||
from typing import Dict, Iterable, List, Optional, Union, Literal
|
||||
|
||||
from lancedb.index import FTS, BTree, Bitmap, HnswPq, HnswSq, IvfPq, LabelList
|
||||
from lancedb.remote.db import LOOP
|
||||
import pyarrow as pa
|
||||
|
||||
from lancedb.common import DATA, VEC, VECTOR_COLUMN_NAME
|
||||
@@ -33,9 +33,7 @@ class RemoteTable(Table):
|
||||
self,
|
||||
table: AsyncTable,
|
||||
db_name: str,
|
||||
loop: Optional[asyncio.AbstractEventLoop] = None,
|
||||
):
|
||||
self._loop = loop
|
||||
self._table = table
|
||||
self.db_name = db_name
|
||||
|
||||
@@ -56,12 +54,12 @@ class RemoteTable(Table):
|
||||
of this Table
|
||||
|
||||
"""
|
||||
return self._loop.run_until_complete(self._table.schema())
|
||||
return LOOP.run(self._table.schema())
|
||||
|
||||
@property
|
||||
def version(self) -> int:
|
||||
"""Get the current version of the table"""
|
||||
return self._loop.run_until_complete(self._table.version())
|
||||
return LOOP.run(self._table.version())
|
||||
|
||||
@cached_property
|
||||
def embedding_functions(self) -> dict:
|
||||
@@ -98,11 +96,11 @@ class RemoteTable(Table):
|
||||
|
||||
def list_indices(self):
|
||||
"""List all the indices on the table"""
|
||||
return self._loop.run_until_complete(self._table.list_indices())
|
||||
return LOOP.run(self._table.list_indices())
|
||||
|
||||
def index_stats(self, index_uuid: str):
|
||||
"""List all the stats of a specified index"""
|
||||
return self._loop.run_until_complete(self._table.index_stats(index_uuid))
|
||||
return LOOP.run(self._table.index_stats(index_uuid))
|
||||
|
||||
def create_scalar_index(
|
||||
self,
|
||||
@@ -132,9 +130,7 @@ class RemoteTable(Table):
|
||||
else:
|
||||
raise ValueError(f"Unknown index type: {index_type}")
|
||||
|
||||
self._loop.run_until_complete(
|
||||
self._table.create_index(column, config=config, replace=replace)
|
||||
)
|
||||
LOOP.run(self._table.create_index(column, config=config, replace=replace))
|
||||
|
||||
def create_fts_index(
|
||||
self,
|
||||
@@ -142,8 +138,25 @@ class RemoteTable(Table):
|
||||
*,
|
||||
replace: bool = False,
|
||||
with_position: bool = True,
|
||||
# tokenizer configs:
|
||||
base_tokenizer: str = "simple",
|
||||
language: str = "English",
|
||||
max_token_length: Optional[int] = 40,
|
||||
lower_case: bool = True,
|
||||
stem: bool = False,
|
||||
remove_stop_words: bool = False,
|
||||
ascii_folding: bool = False,
|
||||
):
|
||||
config = FTS(with_position=with_position)
|
||||
config = FTS(
|
||||
with_position=with_position,
|
||||
base_tokenizer=base_tokenizer,
|
||||
language=language,
|
||||
max_token_length=max_token_length,
|
||||
lower_case=lower_case,
|
||||
stem=stem,
|
||||
remove_stop_words=remove_stop_words,
|
||||
ascii_folding=ascii_folding,
|
||||
)
|
||||
self._loop.run_until_complete(
|
||||
self._table.create_index(column, config=config, replace=replace)
|
||||
)
|
||||
@@ -227,9 +240,7 @@ class RemoteTable(Table):
|
||||
" 'IVF_PQ', 'IVF_HNSW_PQ', 'IVF_HNSW_SQ'"
|
||||
)
|
||||
|
||||
self._loop.run_until_complete(
|
||||
self._table.create_index(vector_column_name, config=config)
|
||||
)
|
||||
LOOP.run(self._table.create_index(vector_column_name, config=config))
|
||||
|
||||
def add(
|
||||
self,
|
||||
@@ -261,7 +272,7 @@ class RemoteTable(Table):
|
||||
The value to use when filling vectors. Only used if on_bad_vectors="fill".
|
||||
|
||||
"""
|
||||
self._loop.run_until_complete(
|
||||
LOOP.run(
|
||||
self._table.add(
|
||||
data, mode=mode, on_bad_vectors=on_bad_vectors, fill_value=fill_value
|
||||
)
|
||||
@@ -349,9 +360,7 @@ class RemoteTable(Table):
|
||||
def _execute_query(
|
||||
self, query: Query, batch_size: Optional[int] = None
|
||||
) -> pa.RecordBatchReader:
|
||||
return self._loop.run_until_complete(
|
||||
self._table._execute_query(query, batch_size=batch_size)
|
||||
)
|
||||
return LOOP.run(self._table._execute_query(query, batch_size=batch_size))
|
||||
|
||||
def merge_insert(self, on: Union[str, Iterable[str]]) -> LanceMergeInsertBuilder:
|
||||
"""Returns a [`LanceMergeInsertBuilder`][lancedb.merge.LanceMergeInsertBuilder]
|
||||
@@ -368,9 +377,7 @@ class RemoteTable(Table):
|
||||
on_bad_vectors: str,
|
||||
fill_value: float,
|
||||
):
|
||||
self._loop.run_until_complete(
|
||||
self._table._do_merge(merge, new_data, on_bad_vectors, fill_value)
|
||||
)
|
||||
LOOP.run(self._table._do_merge(merge, new_data, on_bad_vectors, fill_value))
|
||||
|
||||
def delete(self, predicate: str):
|
||||
"""Delete rows from the table.
|
||||
@@ -419,7 +426,7 @@ class RemoteTable(Table):
|
||||
x vector _distance # doctest: +SKIP
|
||||
0 2 [3.0, 4.0] 85.0 # doctest: +SKIP
|
||||
"""
|
||||
self._loop.run_until_complete(self._table.delete(predicate))
|
||||
LOOP.run(self._table.delete(predicate))
|
||||
|
||||
def update(
|
||||
self,
|
||||
@@ -469,7 +476,7 @@ class RemoteTable(Table):
|
||||
2 2 [10.0, 10.0] # doctest: +SKIP
|
||||
|
||||
"""
|
||||
self._loop.run_until_complete(
|
||||
LOOP.run(
|
||||
self._table.update(where=where, updates=values, updates_sql=values_sql)
|
||||
)
|
||||
|
||||
@@ -499,22 +506,16 @@ class RemoteTable(Table):
|
||||
)
|
||||
|
||||
def count_rows(self, filter: Optional[str] = None) -> int:
|
||||
return self._loop.run_until_complete(self._table.count_rows(filter))
|
||||
return LOOP.run(self._table.count_rows(filter))
|
||||
|
||||
def add_columns(self, transforms: Dict[str, str]):
|
||||
raise NotImplementedError(
|
||||
"add_columns() is not yet supported on the LanceDB cloud"
|
||||
)
|
||||
return LOOP.run(self._table.add_columns(transforms))
|
||||
|
||||
def alter_columns(self, alterations: Iterable[Dict[str, str]]):
|
||||
raise NotImplementedError(
|
||||
"alter_columns() is not yet supported on the LanceDB cloud"
|
||||
)
|
||||
def alter_columns(self, *alterations: Iterable[Dict[str, str]]):
|
||||
return LOOP.run(self._table.alter_columns(*alterations))
|
||||
|
||||
def drop_columns(self, columns: Iterable[str]):
|
||||
raise NotImplementedError(
|
||||
"drop_columns() is not yet supported on the LanceDB cloud"
|
||||
)
|
||||
return LOOP.run(self._table.drop_columns(columns))
|
||||
|
||||
|
||||
def add_index(tbl: pa.Table, i: int) -> pa.Table:
|
||||
|
||||
@@ -967,8 +967,6 @@ class Table(ABC):
|
||||
"""
|
||||
Add new columns with defined values.
|
||||
|
||||
This is not yet available in LanceDB Cloud.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
transforms: Dict[str, str]
|
||||
@@ -978,20 +976,21 @@ class Table(ABC):
|
||||
"""
|
||||
|
||||
@abstractmethod
|
||||
def alter_columns(self, alterations: Iterable[Dict[str, str]]):
|
||||
def alter_columns(self, *alterations: Iterable[Dict[str, str]]):
|
||||
"""
|
||||
Alter column names and nullability.
|
||||
|
||||
This is not yet available in LanceDB Cloud.
|
||||
|
||||
alterations : Iterable[Dict[str, Any]]
|
||||
A sequence of dictionaries, each with the following keys:
|
||||
- "path": str
|
||||
The column path to alter. For a top-level column, this is the name.
|
||||
For a nested column, this is the dot-separated path, e.g. "a.b.c".
|
||||
- "name": str, optional
|
||||
- "rename": str, optional
|
||||
The new name of the column. If not specified, the column name is
|
||||
not changed.
|
||||
- "data_type": pyarrow.DataType, optional
|
||||
The new data type of the column. Existing values will be casted
|
||||
to this type. If not specified, the column data type is not changed.
|
||||
- "nullable": bool, optional
|
||||
Whether the column should be nullable. If not specified, the column
|
||||
nullability is not changed. Only non-nullable columns can be changed
|
||||
@@ -1004,8 +1003,6 @@ class Table(ABC):
|
||||
"""
|
||||
Drop columns from the table.
|
||||
|
||||
This is not yet available in LanceDB Cloud.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
columns : Iterable[str]
|
||||
@@ -1080,13 +1077,16 @@ class _LanceLatestDatasetRef(_LanceDatasetRef):
|
||||
index_cache_size: Optional[int] = None
|
||||
read_consistency_interval: Optional[timedelta] = None
|
||||
last_consistency_check: Optional[float] = None
|
||||
storage_options: Optional[Dict[str, str]] = None
|
||||
_dataset: Optional[LanceDataset] = None
|
||||
|
||||
@property
|
||||
def dataset(self) -> LanceDataset:
|
||||
if not self._dataset:
|
||||
self._dataset = lance.dataset(
|
||||
self.uri, index_cache_size=self.index_cache_size
|
||||
self.uri,
|
||||
index_cache_size=self.index_cache_size,
|
||||
storage_options=self.storage_options,
|
||||
)
|
||||
self.last_consistency_check = time.monotonic()
|
||||
elif self.read_consistency_interval is not None:
|
||||
@@ -1117,13 +1117,17 @@ class _LanceTimeTravelRef(_LanceDatasetRef):
|
||||
uri: str
|
||||
version: int
|
||||
index_cache_size: Optional[int] = None
|
||||
storage_options: Optional[Dict[str, str]] = None
|
||||
_dataset: Optional[LanceDataset] = None
|
||||
|
||||
@property
|
||||
def dataset(self) -> LanceDataset:
|
||||
if not self._dataset:
|
||||
self._dataset = lance.dataset(
|
||||
self.uri, version=self.version, index_cache_size=self.index_cache_size
|
||||
self.uri,
|
||||
version=self.version,
|
||||
index_cache_size=self.index_cache_size,
|
||||
storage_options=self.storage_options,
|
||||
)
|
||||
return self._dataset
|
||||
|
||||
@@ -1172,24 +1176,27 @@ class LanceTable(Table):
|
||||
uri=self._dataset_uri,
|
||||
version=version,
|
||||
index_cache_size=index_cache_size,
|
||||
storage_options=connection.storage_options,
|
||||
)
|
||||
else:
|
||||
self._ref = _LanceLatestDatasetRef(
|
||||
uri=self._dataset_uri,
|
||||
read_consistency_interval=connection.read_consistency_interval,
|
||||
index_cache_size=index_cache_size,
|
||||
storage_options=connection.storage_options,
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def open(cls, db, name, **kwargs):
|
||||
tbl = cls(db, name, **kwargs)
|
||||
fs, path = fs_from_uri(tbl._dataset_path)
|
||||
file_info = fs.get_file_info(path)
|
||||
if file_info.type != pa.fs.FileType.Directory:
|
||||
raise FileNotFoundError(
|
||||
f"Table {name} does not exist."
|
||||
f"Please first call db.create_table({name}, data)"
|
||||
)
|
||||
|
||||
# check the dataset exists
|
||||
try:
|
||||
tbl.version
|
||||
except ValueError as e:
|
||||
if "Not found:" in str(e):
|
||||
raise FileNotFoundError(f"Table {name} does not exist")
|
||||
raise e
|
||||
|
||||
return tbl
|
||||
|
||||
@@ -1617,11 +1624,7 @@ class LanceTable(Table):
|
||||
on_bad_vectors=on_bad_vectors,
|
||||
fill_value=fill_value,
|
||||
)
|
||||
# Access the dataset_mut property to ensure that the dataset is mutable.
|
||||
self._ref.dataset_mut
|
||||
self._ref.dataset = lance.write_dataset(
|
||||
data, self._dataset_uri, schema=self.schema, mode=mode
|
||||
)
|
||||
self._ref.dataset_mut.insert(data, mode=mode, schema=self.schema)
|
||||
|
||||
def merge(
|
||||
self,
|
||||
@@ -1905,7 +1908,13 @@ class LanceTable(Table):
|
||||
|
||||
empty = pa.Table.from_batches([], schema=schema)
|
||||
try:
|
||||
lance.write_dataset(empty, tbl._dataset_uri, schema=schema, mode=mode)
|
||||
lance.write_dataset(
|
||||
empty,
|
||||
tbl._dataset_uri,
|
||||
schema=schema,
|
||||
mode=mode,
|
||||
storage_options=db.storage_options,
|
||||
)
|
||||
except OSError as err:
|
||||
if "Dataset already exists" in str(err) and exist_ok:
|
||||
if tbl.schema != schema:
|
||||
@@ -2923,6 +2932,53 @@ class AsyncTable:
|
||||
|
||||
return await self._inner.update(updates_sql, where)
|
||||
|
||||
async def add_columns(self, transforms: Dict[str, str]):
|
||||
"""
|
||||
Add new columns with defined values.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
transforms: Dict[str, str]
|
||||
A map of column name to a SQL expression to use to calculate the
|
||||
value of the new column. These expressions will be evaluated for
|
||||
each row in the table, and can reference existing columns.
|
||||
"""
|
||||
await self._inner.add_columns(list(transforms.items()))
|
||||
|
||||
async def alter_columns(self, *alterations: Iterable[Dict[str, str]]):
|
||||
"""
|
||||
Alter column names and nullability.
|
||||
|
||||
alterations : Iterable[Dict[str, Any]]
|
||||
A sequence of dictionaries, each with the following keys:
|
||||
- "path": str
|
||||
The column path to alter. For a top-level column, this is the name.
|
||||
For a nested column, this is the dot-separated path, e.g. "a.b.c".
|
||||
- "rename": str, optional
|
||||
The new name of the column. If not specified, the column name is
|
||||
not changed.
|
||||
- "data_type": pyarrow.DataType, optional
|
||||
The new data type of the column. Existing values will be casted
|
||||
to this type. If not specified, the column data type is not changed.
|
||||
- "nullable": bool, optional
|
||||
Whether the column should be nullable. If not specified, the column
|
||||
nullability is not changed. Only non-nullable columns can be changed
|
||||
to nullable. Currently, you cannot change a nullable column to
|
||||
non-nullable.
|
||||
"""
|
||||
await self._inner.alter_columns(alterations)
|
||||
|
||||
async def drop_columns(self, columns: Iterable[str]):
|
||||
"""
|
||||
Drop columns from the table.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
columns : Iterable[str]
|
||||
The names of the columns to drop.
|
||||
"""
|
||||
await self._inner.drop_columns(columns)
|
||||
|
||||
async def version(self) -> int:
|
||||
"""
|
||||
Retrieve the version of the table
|
||||
|
||||
@@ -599,7 +599,9 @@ async def test_create_in_v2_mode(tmp_path):
|
||||
)
|
||||
|
||||
async def is_in_v2_mode(tbl):
|
||||
batches = await tbl.query().to_batches(max_batch_length=1024 * 10)
|
||||
batches = (
|
||||
await tbl.query().limit(10 * 1024).to_batches(max_batch_length=1024 * 10)
|
||||
)
|
||||
num_batches = 0
|
||||
async for batch in batches:
|
||||
num_batches += 1
|
||||
|
||||
21
python/python/tests/test_duckdb.py
Normal file
21
python/python/tests/test_duckdb.py
Normal file
@@ -0,0 +1,21 @@
|
||||
import duckdb
|
||||
import pyarrow as pa
|
||||
|
||||
import lancedb
|
||||
from lancedb.integrations.pyarrow import PyarrowDatasetAdapter
|
||||
|
||||
|
||||
def test_basic_query(tmp_path):
|
||||
data = pa.table({"x": [1, 2, 3, 4], "y": [5, 6, 7, 8]})
|
||||
conn = lancedb.connect(tmp_path)
|
||||
tbl = conn.create_table("test", data)
|
||||
|
||||
adapter = PyarrowDatasetAdapter(tbl) # noqa: F841
|
||||
|
||||
duck_conn = duckdb.connect()
|
||||
|
||||
results = duck_conn.sql("SELECT SUM(x) FROM adapter").fetchall()
|
||||
assert results[0][0] == 10
|
||||
|
||||
results = duck_conn.sql("SELECT SUM(y) FROM adapter").fetchall()
|
||||
assert results[0][0] == 26
|
||||
@@ -90,10 +90,13 @@ def test_embedding_with_bad_results(tmp_path):
|
||||
self, texts: Union[List[str], np.ndarray]
|
||||
) -> list[Union[np.array, None]]:
|
||||
# Return None, which is bad if field is non-nullable
|
||||
return [
|
||||
None if i % 2 == 0 else np.random.randn(self.ndims())
|
||||
a = [
|
||||
np.full(self.ndims(), np.nan)
|
||||
if i % 2 == 0
|
||||
else np.random.randn(self.ndims())
|
||||
for i in range(len(texts))
|
||||
]
|
||||
return a
|
||||
|
||||
db = lancedb.connect(tmp_path)
|
||||
registry = EmbeddingFunctionRegistry.get_instance()
|
||||
|
||||
@@ -1,15 +1,6 @@
|
||||
# Copyright (c) 2023. LanceDB Developers
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
# SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
import importlib
|
||||
import io
|
||||
import os
|
||||
@@ -17,6 +8,7 @@ import os
|
||||
import lancedb
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
import pyarrow as pa
|
||||
import pytest
|
||||
from lancedb.embeddings import get_registry
|
||||
from lancedb.pydantic import LanceModel, Vector
|
||||
@@ -444,6 +436,30 @@ def test_watsonx_embedding(tmp_path):
|
||||
assert tbl.search("hello").limit(1).to_pandas()["text"][0] == "hello world"
|
||||
|
||||
|
||||
@pytest.mark.slow
|
||||
@pytest.mark.skipif(
|
||||
os.environ.get("OPENAI_API_KEY") is None, reason="OPENAI_API_KEY not set"
|
||||
)
|
||||
def test_openai_with_empty_strs(tmp_path):
|
||||
model = get_registry().get("openai").create(max_retries=0)
|
||||
|
||||
class TextModel(LanceModel):
|
||||
text: str = model.SourceField()
|
||||
vector: Vector(model.ndims()) = model.VectorField()
|
||||
|
||||
df = pd.DataFrame({"text": ["hello world", ""]})
|
||||
db = lancedb.connect(tmp_path)
|
||||
tbl = db.create_table("test", schema=TextModel, mode="overwrite")
|
||||
|
||||
tbl.add(df, on_bad_vectors="skip")
|
||||
tb = tbl.to_arrow()
|
||||
assert tb.schema.field_by_name("vector").type == pa.list_(
|
||||
pa.float32(), model.ndims()
|
||||
)
|
||||
assert len(tb) == 2
|
||||
assert tb["vector"].is_null().to_pylist() == [False, True]
|
||||
|
||||
|
||||
@pytest.mark.slow
|
||||
@pytest.mark.skipif(
|
||||
importlib.util.find_spec("ollama") is None, reason="Ollama not installed"
|
||||
|
||||
47
python/python/tests/test_pyarrow.py
Normal file
47
python/python/tests/test_pyarrow.py
Normal file
@@ -0,0 +1,47 @@
|
||||
import pyarrow as pa
|
||||
|
||||
import lancedb
|
||||
from lancedb.integrations.pyarrow import PyarrowDatasetAdapter
|
||||
|
||||
|
||||
def test_dataset_adapter(tmp_path):
|
||||
data = pa.table({"x": [1, 2, 3, 4], "y": [5, 6, 7, 8]})
|
||||
conn = lancedb.connect(tmp_path)
|
||||
tbl = conn.create_table("test", data)
|
||||
|
||||
adapter = PyarrowDatasetAdapter(tbl)
|
||||
|
||||
assert adapter.count_rows() == 4
|
||||
assert adapter.count_rows("x > 2") == 2
|
||||
assert adapter.schema == data.schema
|
||||
assert adapter.head(2) == data.slice(0, 2)
|
||||
assert adapter.to_table() == data
|
||||
assert adapter.to_batches().read_all() == data
|
||||
assert adapter.scanner().to_table() == data
|
||||
assert adapter.scanner().to_batches().read_all() == data
|
||||
|
||||
assert adapter.scanner().projected_schema == data.schema
|
||||
assert adapter.scanner(columns=["x"]).projected_schema == pa.schema(
|
||||
[data.schema.field("x")]
|
||||
)
|
||||
assert adapter.scanner(columns=["x"]).to_table() == pa.table({"x": [1, 2, 3, 4]})
|
||||
|
||||
# Make sure we bypass the limit
|
||||
data = pa.table({"x": range(100)})
|
||||
tbl = conn.create_table("test2", data)
|
||||
|
||||
adapter = PyarrowDatasetAdapter(tbl)
|
||||
|
||||
assert adapter.count_rows() == 100
|
||||
assert adapter.to_table().num_rows == 100
|
||||
assert adapter.head(10).num_rows == 10
|
||||
|
||||
# Empty table
|
||||
tbl = conn.create_table("test3", None, schema=pa.schema({"x": pa.int64()}))
|
||||
adapter = PyarrowDatasetAdapter(tbl)
|
||||
|
||||
assert adapter.count_rows() == 0
|
||||
assert adapter.to_table().num_rows == 0
|
||||
assert adapter.head(10).num_rows == 0
|
||||
|
||||
assert adapter.scanner().projected_schema == pa.schema({"x": pa.int64()})
|
||||
@@ -1,16 +1,5 @@
|
||||
# Copyright 2023 LanceDB Developers
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
# SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
import json
|
||||
import sys
|
||||
@@ -172,6 +161,26 @@ def test_pydantic_to_arrow_py38():
|
||||
assert schema == expect_schema
|
||||
|
||||
|
||||
def test_nullable_vector():
|
||||
class NullableModel(pydantic.BaseModel):
|
||||
vec: Vector(16, nullable=False)
|
||||
|
||||
schema = pydantic_to_schema(NullableModel)
|
||||
assert schema == pa.schema([pa.field("vec", pa.list_(pa.float32(), 16), False)])
|
||||
|
||||
class DefaultModel(pydantic.BaseModel):
|
||||
vec: Vector(16)
|
||||
|
||||
schema = pydantic_to_schema(DefaultModel)
|
||||
assert schema == pa.schema([pa.field("vec", pa.list_(pa.float32(), 16), True)])
|
||||
|
||||
class NotNullableModel(pydantic.BaseModel):
|
||||
vec: Vector(16)
|
||||
|
||||
schema = pydantic_to_schema(NotNullableModel)
|
||||
assert schema == pa.schema([pa.field("vec", pa.list_(pa.float32(), 16), True)])
|
||||
|
||||
|
||||
def test_fixed_size_list_field():
|
||||
class TestModel(pydantic.BaseModel):
|
||||
vec: Vector(16)
|
||||
@@ -192,7 +201,7 @@ def test_fixed_size_list_field():
|
||||
schema = pydantic_to_schema(TestModel)
|
||||
assert schema == pa.schema(
|
||||
[
|
||||
pa.field("vec", pa.list_(pa.float32(), 16), False),
|
||||
pa.field("vec", pa.list_(pa.float32(), 16)),
|
||||
pa.field("li", pa.list_(pa.int64()), False),
|
||||
]
|
||||
)
|
||||
|
||||
@@ -1,6 +1,7 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
# SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
import contextlib
|
||||
from datetime import timedelta
|
||||
import http.server
|
||||
@@ -187,6 +188,47 @@ async def test_retry_error():
|
||||
assert cause.status_code == 429
|
||||
|
||||
|
||||
def test_table_add_in_threadpool():
|
||||
def handler(request):
|
||||
if request.path == "/v1/table/test/insert/":
|
||||
request.send_response(200)
|
||||
request.end_headers()
|
||||
elif request.path == "/v1/table/test/create/?mode=create":
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/json")
|
||||
request.end_headers()
|
||||
request.wfile.write(b"{}")
|
||||
elif request.path == "/v1/table/test/describe/":
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/json")
|
||||
request.end_headers()
|
||||
payload = json.dumps(
|
||||
dict(
|
||||
version=1,
|
||||
schema=dict(
|
||||
fields=[
|
||||
dict(name="id", type={"type": "int64"}, nullable=False),
|
||||
]
|
||||
),
|
||||
)
|
||||
)
|
||||
request.wfile.write(payload.encode())
|
||||
else:
|
||||
request.send_response(404)
|
||||
request.end_headers()
|
||||
|
||||
with mock_lancedb_connection(handler) as db:
|
||||
table = db.create_table("test", [{"id": 1}])
|
||||
with ThreadPoolExecutor(3) as executor:
|
||||
futures = []
|
||||
for _ in range(10):
|
||||
future = executor.submit(table.add, [{"id": 1}])
|
||||
futures.append(future)
|
||||
|
||||
for future in futures:
|
||||
future.result()
|
||||
|
||||
|
||||
@contextlib.contextmanager
|
||||
def query_test_table(query_handler):
|
||||
def handler(request):
|
||||
|
||||
@@ -30,6 +30,7 @@ class MockDB:
|
||||
def __init__(self, uri: Path):
|
||||
self.uri = str(uri)
|
||||
self.read_consistency_interval = None
|
||||
self.storage_options = None
|
||||
|
||||
@functools.cached_property
|
||||
def is_managed_remote(self) -> bool:
|
||||
@@ -1292,6 +1293,19 @@ def test_add_columns(tmp_path):
|
||||
assert table.to_arrow().column_names == ["id", "new_col"]
|
||||
assert table.to_arrow()["new_col"].to_pylist() == [2, 3]
|
||||
|
||||
table.add_columns({"null_int": "cast(null as bigint)"})
|
||||
assert table.schema.field("null_int").type == pa.int64()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_add_columns_async(db_async: AsyncConnection):
|
||||
data = pa.table({"id": [0, 1]})
|
||||
table = await db_async.create_table("my_table", data=data)
|
||||
await table.add_columns({"new_col": "id + 2"})
|
||||
data = await table.to_arrow()
|
||||
assert data.column_names == ["id", "new_col"]
|
||||
assert data["new_col"].to_pylist() == [2, 3]
|
||||
|
||||
|
||||
def test_alter_columns(tmp_path):
|
||||
db = lancedb.connect(tmp_path)
|
||||
@@ -1301,6 +1315,18 @@ def test_alter_columns(tmp_path):
|
||||
assert table.to_arrow().column_names == ["new_id"]
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_alter_columns_async(db_async: AsyncConnection):
|
||||
data = pa.table({"id": [0, 1]})
|
||||
table = await db_async.create_table("my_table", data=data)
|
||||
await table.alter_columns({"path": "id", "rename": "new_id"})
|
||||
assert (await table.to_arrow()).column_names == ["new_id"]
|
||||
await table.alter_columns(dict(path="new_id", data_type=pa.int16(), nullable=True))
|
||||
data = await table.to_arrow()
|
||||
assert data.column(0).type == pa.int16()
|
||||
assert data.schema.field(0).nullable
|
||||
|
||||
|
||||
def test_drop_columns(tmp_path):
|
||||
db = lancedb.connect(tmp_path)
|
||||
data = pa.table({"id": [0, 1], "category": ["a", "b"]})
|
||||
@@ -1309,6 +1335,14 @@ def test_drop_columns(tmp_path):
|
||||
assert table.to_arrow().column_names == ["id"]
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_drop_columns_async(db_async: AsyncConnection):
|
||||
data = pa.table({"id": [0, 1], "category": ["a", "b"]})
|
||||
table = await db_async.create_table("my_table", data=data)
|
||||
await table.drop_columns(["category"])
|
||||
assert (await table.to_arrow()).column_names == ["id"]
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_time_travel(db_async: AsyncConnection):
|
||||
# Setup
|
||||
|
||||
@@ -10,7 +10,7 @@ use arrow::{
|
||||
use futures::stream::StreamExt;
|
||||
use lancedb::arrow::SendableRecordBatchStream;
|
||||
use pyo3::{pyclass, pymethods, Bound, PyAny, PyObject, PyRef, PyResult, Python};
|
||||
use pyo3_asyncio_0_21::tokio::future_into_py;
|
||||
use pyo3_async_runtimes::tokio::future_into_py;
|
||||
|
||||
use crate::error::PythonErrorExt;
|
||||
|
||||
|
||||
@@ -9,7 +9,7 @@ use pyo3::{
|
||||
exceptions::{PyRuntimeError, PyValueError},
|
||||
pyclass, pyfunction, pymethods, Bound, FromPyObject, PyAny, PyRef, PyResult, Python,
|
||||
};
|
||||
use pyo3_asyncio_0_21::tokio::future_into_py;
|
||||
use pyo3_async_runtimes::tokio::future_into_py;
|
||||
|
||||
use crate::{error::PythonErrorExt, table::Table};
|
||||
|
||||
@@ -58,6 +58,7 @@ impl Connection {
|
||||
self.inner.take();
|
||||
}
|
||||
|
||||
#[pyo3(signature = (start_after=None, limit=None))]
|
||||
pub fn table_names(
|
||||
self_: PyRef<'_, Self>,
|
||||
start_after: Option<String>,
|
||||
@@ -74,6 +75,7 @@ impl Connection {
|
||||
future_into_py(self_.py(), async move { op.execute().await.infer_error() })
|
||||
}
|
||||
|
||||
#[pyo3(signature = (name, mode, data, storage_options=None, data_storage_version=None, enable_v2_manifest_paths=None))]
|
||||
pub fn create_table<'a>(
|
||||
self_: PyRef<'a, Self>,
|
||||
name: String,
|
||||
@@ -111,6 +113,7 @@ impl Connection {
|
||||
})
|
||||
}
|
||||
|
||||
#[pyo3(signature = (name, mode, schema, storage_options=None, data_storage_version=None, enable_v2_manifest_paths=None))]
|
||||
pub fn create_empty_table<'a>(
|
||||
self_: PyRef<'a, Self>,
|
||||
name: String,
|
||||
@@ -198,6 +201,7 @@ impl Connection {
|
||||
}
|
||||
|
||||
#[pyfunction]
|
||||
#[pyo3(signature = (uri, api_key=None, region=None, host_override=None, read_consistency_interval=None, client_config=None, storage_options=None))]
|
||||
#[allow(clippy::too_many_arguments)]
|
||||
pub fn connect(
|
||||
py: Python,
|
||||
|
||||
@@ -138,7 +138,9 @@ fn http_from_rust_error(
|
||||
status_code: Option<u16>,
|
||||
) -> PyResult<PyErr> {
|
||||
let message = err.to_string();
|
||||
let http_err_cls = py.import("lancedb.remote.errors")?.getattr("HttpError")?;
|
||||
let http_err_cls = py
|
||||
.import_bound("lancedb.remote.errors")?
|
||||
.getattr("HttpError")?;
|
||||
let py_err = http_err_cls.call1((message, request_id, status_code))?;
|
||||
|
||||
// Reset the traceback since it doesn't provide additional information.
|
||||
@@ -149,5 +151,5 @@ fn http_from_rust_error(
|
||||
py_err.setattr(intern!(py, "__cause__"), cause_err)?;
|
||||
}
|
||||
|
||||
Ok(PyErr::from_value(py_err))
|
||||
Ok(PyErr::from_value_bound(py_err))
|
||||
}
|
||||
|
||||
@@ -47,6 +47,7 @@ impl Index {
|
||||
|
||||
#[pymethods]
|
||||
impl Index {
|
||||
#[pyo3(signature = (distance_type=None, num_partitions=None, num_sub_vectors=None, max_iterations=None, sample_rate=None))]
|
||||
#[staticmethod]
|
||||
pub fn ivf_pq(
|
||||
distance_type: Option<String>,
|
||||
@@ -106,6 +107,7 @@ impl Index {
|
||||
})
|
||||
}
|
||||
|
||||
#[pyo3(signature = (with_position=None, base_tokenizer=None, language=None, max_token_length=None, lower_case=None, stem=None, remove_stop_words=None, ascii_folding=None))]
|
||||
#[allow(clippy::too_many_arguments)]
|
||||
#[staticmethod]
|
||||
pub fn fts(
|
||||
@@ -146,6 +148,7 @@ impl Index {
|
||||
}
|
||||
}
|
||||
|
||||
#[pyo3(signature = (distance_type=None, num_partitions=None, num_sub_vectors=None, max_iterations=None, sample_rate=None, m=None, ef_construction=None))]
|
||||
#[staticmethod]
|
||||
pub fn hnsw_pq(
|
||||
distance_type: Option<String>,
|
||||
@@ -184,6 +187,7 @@ impl Index {
|
||||
})
|
||||
}
|
||||
|
||||
#[pyo3(signature = (distance_type=None, num_partitions=None, max_iterations=None, sample_rate=None, m=None, ef_construction=None))]
|
||||
#[staticmethod]
|
||||
pub fn hnsw_sq(
|
||||
distance_type: Option<String>,
|
||||
|
||||
@@ -16,7 +16,11 @@ use arrow::RecordBatchStream;
|
||||
use connection::{connect, Connection};
|
||||
use env_logger::Env;
|
||||
use index::{Index, IndexConfig};
|
||||
use pyo3::{pymodule, types::PyModule, wrap_pyfunction, PyResult, Python};
|
||||
use pyo3::{
|
||||
pymodule,
|
||||
types::{PyModule, PyModuleMethods},
|
||||
wrap_pyfunction, Bound, PyResult, Python,
|
||||
};
|
||||
use query::{Query, VectorQuery};
|
||||
use table::Table;
|
||||
|
||||
@@ -29,7 +33,7 @@ pub mod table;
|
||||
pub mod util;
|
||||
|
||||
#[pymodule]
|
||||
pub fn _lancedb(_py: Python, m: &PyModule) -> PyResult<()> {
|
||||
pub fn _lancedb(_py: Python, m: &Bound<'_, PyModule>) -> PyResult<()> {
|
||||
let env = Env::new()
|
||||
.filter_or("LANCEDB_LOG", "warn")
|
||||
.write_style("LANCEDB_LOG_STYLE");
|
||||
|
||||
@@ -29,7 +29,7 @@ use pyo3::PyAny;
|
||||
use pyo3::PyRef;
|
||||
use pyo3::PyResult;
|
||||
use pyo3::{pyclass, PyErr};
|
||||
use pyo3_asyncio_0_21::tokio::future_into_py;
|
||||
use pyo3_async_runtimes::tokio::future_into_py;
|
||||
|
||||
use crate::arrow::RecordBatchStream;
|
||||
use crate::error::PythonErrorExt;
|
||||
@@ -105,6 +105,7 @@ impl Query {
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[pyo3(signature = (max_batch_length=None))]
|
||||
pub fn execute(
|
||||
self_: PyRef<'_, Self>,
|
||||
max_batch_length: Option<u32>,
|
||||
@@ -203,6 +204,7 @@ impl VectorQuery {
|
||||
self.inner = self.inner.clone().bypass_vector_index()
|
||||
}
|
||||
|
||||
#[pyo3(signature = (max_batch_length=None))]
|
||||
pub fn execute(
|
||||
self_: PyRef<'_, Self>,
|
||||
max_batch_length: Option<u32>,
|
||||
|
||||
@@ -1,17 +1,21 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
use arrow::{
|
||||
datatypes::DataType,
|
||||
ffi_stream::ArrowArrayStreamReader,
|
||||
pyarrow::{FromPyArrow, ToPyArrow},
|
||||
};
|
||||
use lancedb::table::{
|
||||
AddDataMode, Duration, OptimizeAction, OptimizeOptions, Table as LanceDbTable,
|
||||
AddDataMode, ColumnAlteration, Duration, NewColumnTransform, OptimizeAction, OptimizeOptions,
|
||||
Table as LanceDbTable,
|
||||
};
|
||||
use pyo3::{
|
||||
exceptions::{PyRuntimeError, PyValueError},
|
||||
pyclass, pymethods,
|
||||
types::{IntoPyDict, PyDict, PyDictMethods, PyString},
|
||||
types::{IntoPyDict, PyAnyMethods, PyDict, PyDictMethods},
|
||||
Bound, FromPyObject, PyAny, PyRef, PyResult, Python, ToPyObject,
|
||||
};
|
||||
use pyo3_asyncio_0_21::tokio::future_into_py;
|
||||
use pyo3_async_runtimes::tokio::future_into_py;
|
||||
|
||||
use crate::{
|
||||
error::PythonErrorExt,
|
||||
@@ -137,9 +141,10 @@ impl Table {
|
||||
})
|
||||
}
|
||||
|
||||
#[pyo3(signature = (updates, r#where=None))]
|
||||
pub fn update<'a>(
|
||||
self_: PyRef<'a, Self>,
|
||||
updates: &PyDict,
|
||||
updates: &Bound<'_, PyDict>,
|
||||
r#where: Option<String>,
|
||||
) -> PyResult<Bound<'a, PyAny>> {
|
||||
let mut op = self_.inner_ref()?.update();
|
||||
@@ -147,10 +152,8 @@ impl Table {
|
||||
op = op.only_if(only_if);
|
||||
}
|
||||
for (column_name, value) in updates.into_iter() {
|
||||
let column_name: &PyString = column_name.downcast()?;
|
||||
let column_name = column_name.to_str()?.to_string();
|
||||
let value: &PyString = value.downcast()?;
|
||||
let value = value.to_str()?.to_string();
|
||||
let column_name: String = column_name.extract()?;
|
||||
let value: String = value.extract()?;
|
||||
op = op.column(column_name, value);
|
||||
}
|
||||
future_into_py(self_.py(), async move {
|
||||
@@ -159,6 +162,7 @@ impl Table {
|
||||
})
|
||||
}
|
||||
|
||||
#[pyo3(signature = (filter=None))]
|
||||
pub fn count_rows(
|
||||
self_: PyRef<'_, Self>,
|
||||
filter: Option<String>,
|
||||
@@ -169,6 +173,7 @@ impl Table {
|
||||
})
|
||||
}
|
||||
|
||||
#[pyo3(signature = (column, index=None, replace=None))]
|
||||
pub fn create_index<'a>(
|
||||
self_: PyRef<'a, Self>,
|
||||
column: String,
|
||||
@@ -263,7 +268,8 @@ impl Table {
|
||||
.unwrap();
|
||||
|
||||
let tup: Vec<(&String, &String)> = v.metadata.iter().collect();
|
||||
dict.set_item("metadata", tup.into_py_dict(py)).unwrap();
|
||||
dict.set_item("metadata", tup.into_py_dict_bound(py))
|
||||
.unwrap();
|
||||
dict.to_object(py)
|
||||
})
|
||||
.collect::<Vec<_>>()
|
||||
@@ -299,6 +305,7 @@ impl Table {
|
||||
Query::new(self.inner_ref().unwrap().query())
|
||||
}
|
||||
|
||||
#[pyo3(signature = (cleanup_since_ms=None, delete_unverified=None))]
|
||||
pub fn optimize(
|
||||
self_: PyRef<'_, Self>,
|
||||
cleanup_since_ms: Option<u64>,
|
||||
@@ -406,6 +413,72 @@ impl Table {
|
||||
.infer_error()
|
||||
})
|
||||
}
|
||||
|
||||
pub fn add_columns(
|
||||
self_: PyRef<'_, Self>,
|
||||
definitions: Vec<(String, String)>,
|
||||
) -> PyResult<Bound<'_, PyAny>> {
|
||||
let definitions = NewColumnTransform::SqlExpressions(definitions);
|
||||
|
||||
let inner = self_.inner_ref()?.clone();
|
||||
future_into_py(self_.py(), async move {
|
||||
inner.add_columns(definitions, None).await.infer_error()?;
|
||||
Ok(())
|
||||
})
|
||||
}
|
||||
|
||||
pub fn alter_columns<'a>(
|
||||
self_: PyRef<'a, Self>,
|
||||
alterations: Vec<Bound<PyDict>>,
|
||||
) -> PyResult<Bound<'a, PyAny>> {
|
||||
let alterations = alterations
|
||||
.iter()
|
||||
.map(|alteration| {
|
||||
let path = alteration
|
||||
.get_item("path")?
|
||||
.ok_or_else(|| PyValueError::new_err("Missing path"))?
|
||||
.extract()?;
|
||||
let rename = {
|
||||
// We prefer rename, but support name for backwards compatibility
|
||||
let rename = if let Ok(Some(rename)) = alteration.get_item("rename") {
|
||||
Some(rename)
|
||||
} else {
|
||||
alteration.get_item("name")?
|
||||
};
|
||||
rename.map(|name| name.extract()).transpose()?
|
||||
};
|
||||
let nullable = alteration
|
||||
.get_item("nullable")?
|
||||
.map(|val| val.extract())
|
||||
.transpose()?;
|
||||
let data_type = alteration
|
||||
.get_item("data_type")?
|
||||
.map(|val| DataType::from_pyarrow_bound(&val))
|
||||
.transpose()?;
|
||||
Ok(ColumnAlteration {
|
||||
path,
|
||||
rename,
|
||||
nullable,
|
||||
data_type,
|
||||
})
|
||||
})
|
||||
.collect::<PyResult<Vec<_>>>()?;
|
||||
|
||||
let inner = self_.inner_ref()?.clone();
|
||||
future_into_py(self_.py(), async move {
|
||||
inner.alter_columns(&alterations).await.infer_error()?;
|
||||
Ok(())
|
||||
})
|
||||
}
|
||||
|
||||
pub fn drop_columns(self_: PyRef<Self>, columns: Vec<String>) -> PyResult<Bound<PyAny>> {
|
||||
let inner = self_.inner_ref()?.clone();
|
||||
future_into_py(self_.py(), async move {
|
||||
let column_refs = columns.iter().map(String::as_str).collect::<Vec<&str>>();
|
||||
inner.drop_columns(&column_refs).await.infer_error()?;
|
||||
Ok(())
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(FromPyObject)]
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "lancedb-node"
|
||||
version = "0.13.0"
|
||||
version = "0.14.0-beta.2"
|
||||
description = "Serverless, low-latency vector database for AI applications"
|
||||
license.workspace = true
|
||||
edition.workspace = true
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "lancedb"
|
||||
version = "0.13.0"
|
||||
version = "0.14.0-beta.2"
|
||||
edition.workspace = true
|
||||
description = "LanceDB: A serverless, low-latency vector database for AI applications"
|
||||
license.workspace = true
|
||||
@@ -27,6 +27,7 @@ half = { workspace = true }
|
||||
lazy_static.workspace = true
|
||||
lance = { workspace = true }
|
||||
lance-datafusion.workspace = true
|
||||
lance-io = { workspace = true }
|
||||
lance-index = { workspace = true }
|
||||
lance-table = { workspace = true }
|
||||
lance-linalg = { workspace = true }
|
||||
|
||||
@@ -38,6 +38,9 @@ use crate::table::{NativeTable, TableDefinition, WriteOptions};
|
||||
use crate::utils::validate_table_name;
|
||||
use crate::Table;
|
||||
pub use lance_encoding::version::LanceFileVersion;
|
||||
#[cfg(feature = "remote")]
|
||||
use lance_io::object_store::StorageOptions;
|
||||
use lance_table::io::commit::commit_handler_from_url;
|
||||
|
||||
pub const LANCE_FILE_EXTENSION: &str = "lance";
|
||||
|
||||
@@ -133,7 +136,7 @@ impl IntoArrow for NoData {
|
||||
|
||||
/// A builder for configuring a [`Connection::create_table`] operation
|
||||
pub struct CreateTableBuilder<const HAS_DATA: bool, T: IntoArrow> {
|
||||
parent: Arc<dyn ConnectionInternal>,
|
||||
pub(crate) parent: Arc<dyn ConnectionInternal>,
|
||||
pub(crate) name: String,
|
||||
pub(crate) data: Option<T>,
|
||||
pub(crate) mode: CreateTableMode,
|
||||
@@ -341,7 +344,7 @@ pub struct OpenTableBuilder {
|
||||
}
|
||||
|
||||
impl OpenTableBuilder {
|
||||
fn new(parent: Arc<dyn ConnectionInternal>, name: String) -> Self {
|
||||
pub(crate) fn new(parent: Arc<dyn ConnectionInternal>, name: String) -> Self {
|
||||
Self {
|
||||
parent,
|
||||
name,
|
||||
@@ -622,7 +625,7 @@ impl ConnectBuilder {
|
||||
|
||||
/// Set the LanceDB Cloud client configuration.
|
||||
///
|
||||
/// ```
|
||||
/// ```no_run
|
||||
/// # use lancedb::connect;
|
||||
/// # use lancedb::remote::*;
|
||||
/// connect("db://my_database")
|
||||
@@ -717,12 +720,14 @@ impl ConnectBuilder {
|
||||
message: "An api_key is required when connecting to LanceDb Cloud".to_string(),
|
||||
})?;
|
||||
|
||||
let storage_options = StorageOptions(self.storage_options.clone());
|
||||
let internal = Arc::new(crate::remote::db::RemoteDatabase::try_new(
|
||||
&self.uri,
|
||||
&api_key,
|
||||
®ion,
|
||||
self.host_override,
|
||||
self.client_config,
|
||||
storage_options.into(),
|
||||
)?);
|
||||
Ok(Connection {
|
||||
internal,
|
||||
@@ -855,7 +860,7 @@ impl Database {
|
||||
let table_base_uri = if let Some(store) = engine {
|
||||
static WARN_ONCE: std::sync::Once = std::sync::Once::new();
|
||||
WARN_ONCE.call_once(|| {
|
||||
log::warn!("Specifing engine is not a publicly supported feature in lancedb yet. THE API WILL CHANGE");
|
||||
log::warn!("Specifying engine is not a publicly supported feature in lancedb yet. THE API WILL CHANGE");
|
||||
});
|
||||
let old_scheme = url.scheme().to_string();
|
||||
let new_scheme = format!("{}+{}", old_scheme, store);
|
||||
@@ -1036,6 +1041,7 @@ impl ConnectionInternal for Database {
|
||||
};
|
||||
|
||||
let mut write_params = options.write_options.lance_write_params.unwrap_or_default();
|
||||
|
||||
if matches!(&options.mode, CreateTableMode::Overwrite) {
|
||||
write_params.mode = WriteMode::Overwrite;
|
||||
}
|
||||
@@ -1122,7 +1128,7 @@ impl ConnectionInternal for Database {
|
||||
let dir_name = format!("{}.{}", name, LANCE_EXTENSION);
|
||||
let full_path = self.base_path.child(dir_name.clone());
|
||||
self.object_store
|
||||
.remove_dir_all(full_path)
|
||||
.remove_dir_all(full_path.clone())
|
||||
.await
|
||||
.map_err(|err| match err {
|
||||
// this error is not lance::Error::DatasetNotFound,
|
||||
@@ -1132,6 +1138,19 @@ impl ConnectionInternal for Database {
|
||||
},
|
||||
_ => Error::from(err),
|
||||
})?;
|
||||
|
||||
let object_store_params = ObjectStoreParams {
|
||||
storage_options: Some(self.storage_options.clone()),
|
||||
..Default::default()
|
||||
};
|
||||
let mut uri = self.uri.clone();
|
||||
if let Some(query_string) = &self.query_string {
|
||||
uri.push_str(&format!("?{}", query_string));
|
||||
}
|
||||
let commit_handler = commit_handler_from_url(&uri, &Some(object_store_params))
|
||||
.await
|
||||
.unwrap();
|
||||
commit_handler.delete(&full_path).await.unwrap();
|
||||
Ok(())
|
||||
}
|
||||
|
||||
@@ -1169,6 +1188,7 @@ mod tests {
|
||||
use lance_testing::datagen::{BatchGenerator, IncrementingInt32};
|
||||
use tempfile::tempdir;
|
||||
|
||||
use crate::query::QueryBase;
|
||||
use crate::query::{ExecutableQuery, QueryExecutionOptions};
|
||||
|
||||
use super::*;
|
||||
@@ -1296,6 +1316,7 @@ mod tests {
|
||||
// In v1 the row group size will trump max_batch_length
|
||||
let batches = tbl
|
||||
.query()
|
||||
.limit(20000)
|
||||
.execute_with_options(QueryExecutionOptions {
|
||||
max_batch_length: 50000,
|
||||
..Default::default()
|
||||
|
||||
@@ -30,7 +30,7 @@
|
||||
//!
|
||||
//! LanceDB runs in process, to use it in your Rust project, put the following in your `Cargo.toml`:
|
||||
//!
|
||||
//! ```ignore
|
||||
//! ```shell
|
||||
//! cargo install lancedb
|
||||
//! ```
|
||||
//!
|
||||
|
||||
@@ -348,7 +348,7 @@ pub trait QueryBase {
|
||||
///
|
||||
/// The filter should be supplied as an SQL query string. For example:
|
||||
///
|
||||
/// ```ignore
|
||||
/// ```sql
|
||||
/// x > 10
|
||||
/// y > 0 AND y < 100
|
||||
/// x > 5 OR y = 'test'
|
||||
@@ -364,8 +364,18 @@ pub trait QueryBase {
|
||||
///
|
||||
/// This method is only valid on tables that have a full text search index.
|
||||
///
|
||||
/// ```ignore
|
||||
/// query.full_text_search(FullTextSearchQuery::new("hello world"))
|
||||
/// ```
|
||||
/// use lance_index::scalar::FullTextSearchQuery;
|
||||
/// use lancedb::query::{QueryBase, ExecutableQuery};
|
||||
///
|
||||
/// # use lancedb::Table;
|
||||
/// # async fn query(table: &Table) -> Result<(), Box<dyn std::error::Error>> {
|
||||
/// let results = table.query()
|
||||
/// .full_text_search(FullTextSearchQuery::new("hello world".into()))
|
||||
/// .execute()
|
||||
/// .await?;
|
||||
/// # Ok(())
|
||||
/// # }
|
||||
/// ```
|
||||
fn full_text_search(self, query: FullTextSearchQuery) -> Self;
|
||||
|
||||
@@ -596,7 +606,7 @@ impl Query {
|
||||
pub(crate) fn new(parent: Arc<dyn TableInternal>) -> Self {
|
||||
Self {
|
||||
parent,
|
||||
limit: None,
|
||||
limit: Some(DEFAULT_TOP_K),
|
||||
offset: None,
|
||||
filter: None,
|
||||
full_text_search: None,
|
||||
|
||||
@@ -21,6 +21,7 @@ use reqwest::{
|
||||
};
|
||||
|
||||
use crate::error::{Error, Result};
|
||||
use crate::remote::db::RemoteOptions;
|
||||
|
||||
const REQUEST_ID_HEADER: &str = "x-request-id";
|
||||
|
||||
@@ -215,6 +216,7 @@ impl RestfulLanceDbClient<Sender> {
|
||||
region: &str,
|
||||
host_override: Option<String>,
|
||||
client_config: ClientConfig,
|
||||
options: &RemoteOptions,
|
||||
) -> Result<Self> {
|
||||
let parsed_url = url::Url::parse(db_url).map_err(|err| Error::InvalidInput {
|
||||
message: format!("db_url is not a valid URL. '{db_url}'. Error: {err}"),
|
||||
@@ -226,6 +228,14 @@ impl RestfulLanceDbClient<Sender> {
|
||||
});
|
||||
}
|
||||
let db_name = parsed_url.host_str().unwrap();
|
||||
let db_prefix = {
|
||||
let prefix = parsed_url.path().trim_start_matches('/');
|
||||
if prefix.is_empty() {
|
||||
None
|
||||
} else {
|
||||
Some(prefix)
|
||||
}
|
||||
};
|
||||
|
||||
// Get the timeouts
|
||||
let connect_timeout = Self::get_timeout(
|
||||
@@ -255,6 +265,8 @@ impl RestfulLanceDbClient<Sender> {
|
||||
region,
|
||||
db_name,
|
||||
host_override.is_some(),
|
||||
options,
|
||||
db_prefix,
|
||||
)?)
|
||||
.user_agent(client_config.user_agent)
|
||||
.build()
|
||||
@@ -262,6 +274,7 @@ impl RestfulLanceDbClient<Sender> {
|
||||
message: "Failed to build HTTP client".into(),
|
||||
source: Some(Box::new(err)),
|
||||
})?;
|
||||
|
||||
let host = match host_override {
|
||||
Some(host_override) => host_override,
|
||||
None => format!("https://{}.{}.api.lancedb.com", db_name, region),
|
||||
@@ -287,6 +300,8 @@ impl<S: HttpSend> RestfulLanceDbClient<S> {
|
||||
region: &str,
|
||||
db_name: &str,
|
||||
has_host_override: bool,
|
||||
options: &RemoteOptions,
|
||||
db_prefix: Option<&str>,
|
||||
) -> Result<HeaderMap> {
|
||||
let mut headers = HeaderMap::new();
|
||||
headers.insert(
|
||||
@@ -312,6 +327,34 @@ impl<S: HttpSend> RestfulLanceDbClient<S> {
|
||||
})?,
|
||||
);
|
||||
}
|
||||
if db_prefix.is_some() {
|
||||
headers.insert(
|
||||
"x-lancedb-database-prefix",
|
||||
HeaderValue::from_str(db_prefix.unwrap()).map_err(|_| Error::InvalidInput {
|
||||
message: format!(
|
||||
"non-ascii database prefix '{}' provided",
|
||||
db_prefix.unwrap()
|
||||
),
|
||||
})?,
|
||||
);
|
||||
}
|
||||
|
||||
if let Some(v) = options.0.get("account_name") {
|
||||
headers.insert(
|
||||
"x-azure-storage-account-name",
|
||||
HeaderValue::from_str(v).map_err(|_| Error::InvalidInput {
|
||||
message: format!("non-ascii storage account name '{}' provided", db_name),
|
||||
})?,
|
||||
);
|
||||
}
|
||||
if let Some(v) = options.0.get("azure_storage_account_name") {
|
||||
headers.insert(
|
||||
"x-azure-storage-account-name",
|
||||
HeaderValue::from_str(v).map_err(|_| Error::InvalidInput {
|
||||
message: format!("non-ascii storage account name '{}' provided", db_name),
|
||||
})?,
|
||||
);
|
||||
}
|
||||
|
||||
Ok(headers)
|
||||
}
|
||||
|
||||
@@ -12,18 +12,21 @@
|
||||
// See the License for the specific language governing permissions and
|
||||
// limitations under the License.
|
||||
|
||||
use std::collections::HashMap;
|
||||
use std::sync::Arc;
|
||||
|
||||
use arrow_array::RecordBatchReader;
|
||||
use async_trait::async_trait;
|
||||
use http::StatusCode;
|
||||
use lance_io::object_store::StorageOptions;
|
||||
use moka::future::Cache;
|
||||
use reqwest::header::CONTENT_TYPE;
|
||||
use serde::Deserialize;
|
||||
use tokio::task::spawn_blocking;
|
||||
|
||||
use crate::connection::{
|
||||
ConnectionInternal, CreateTableBuilder, NoData, OpenTableBuilder, TableNamesBuilder,
|
||||
ConnectionInternal, CreateTableBuilder, CreateTableMode, NoData, OpenTableBuilder,
|
||||
TableNamesBuilder,
|
||||
};
|
||||
use crate::embeddings::EmbeddingRegistry;
|
||||
use crate::error::Result;
|
||||
@@ -52,9 +55,16 @@ impl RemoteDatabase {
|
||||
region: &str,
|
||||
host_override: Option<String>,
|
||||
client_config: ClientConfig,
|
||||
options: RemoteOptions,
|
||||
) -> Result<Self> {
|
||||
let client =
|
||||
RestfulLanceDbClient::try_new(uri, api_key, region, host_override, client_config)?;
|
||||
let client = RestfulLanceDbClient::try_new(
|
||||
uri,
|
||||
api_key,
|
||||
region,
|
||||
host_override,
|
||||
client_config,
|
||||
&options,
|
||||
)?;
|
||||
|
||||
let table_cache = Cache::builder()
|
||||
.time_to_live(std::time::Duration::from_secs(300))
|
||||
@@ -95,6 +105,16 @@ impl<S: HttpSend> std::fmt::Display for RemoteDatabase<S> {
|
||||
}
|
||||
}
|
||||
|
||||
impl From<&CreateTableMode> for &'static str {
|
||||
fn from(val: &CreateTableMode) -> Self {
|
||||
match val {
|
||||
CreateTableMode::Create => "create",
|
||||
CreateTableMode::Overwrite => "overwrite",
|
||||
CreateTableMode::ExistOk(_) => "exist_ok",
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[async_trait]
|
||||
impl<S: HttpSend> ConnectionInternal for RemoteDatabase<S> {
|
||||
async fn table_names(&self, options: TableNamesBuilder) -> Result<Vec<String>> {
|
||||
@@ -133,14 +153,40 @@ impl<S: HttpSend> ConnectionInternal for RemoteDatabase<S> {
|
||||
let req = self
|
||||
.client
|
||||
.post(&format!("/v1/table/{}/create/", options.name))
|
||||
.query(&[("mode", Into::<&str>::into(&options.mode))])
|
||||
.body(data_buffer)
|
||||
.header(CONTENT_TYPE, ARROW_STREAM_CONTENT_TYPE);
|
||||
|
||||
let (request_id, rsp) = self.client.send(req, false).await?;
|
||||
|
||||
if rsp.status() == StatusCode::BAD_REQUEST {
|
||||
let body = rsp.text().await.err_to_http(request_id.clone())?;
|
||||
if body.contains("already exists") {
|
||||
return Err(crate::Error::TableAlreadyExists { name: options.name });
|
||||
return match options.mode {
|
||||
CreateTableMode::Create => {
|
||||
Err(crate::Error::TableAlreadyExists { name: options.name })
|
||||
}
|
||||
CreateTableMode::ExistOk(callback) => {
|
||||
let builder = OpenTableBuilder::new(options.parent, options.name);
|
||||
let builder = (callback)(builder);
|
||||
builder.execute().await
|
||||
}
|
||||
|
||||
// This should not happen, as we explicitly set the mode to overwrite and the server
|
||||
// shouldn't return an error if the table already exists.
|
||||
//
|
||||
// However if the server is an older version that doesn't support the mode parameter,
|
||||
// then we'll get the 400 response.
|
||||
CreateTableMode::Overwrite => Err(crate::Error::Http {
|
||||
source: format!(
|
||||
"unexpected response from server for create mode overwrite: {}",
|
||||
body
|
||||
)
|
||||
.into(),
|
||||
request_id,
|
||||
status_code: Some(StatusCode::BAD_REQUEST),
|
||||
}),
|
||||
};
|
||||
} else {
|
||||
return Err(crate::Error::InvalidInput { message: body });
|
||||
}
|
||||
@@ -206,6 +252,29 @@ impl<S: HttpSend> ConnectionInternal for RemoteDatabase<S> {
|
||||
}
|
||||
}
|
||||
|
||||
/// RemoteOptions contains a subset of StorageOptions that are compatible with Remote LanceDB connections
|
||||
#[derive(Clone, Debug, Default)]
|
||||
pub struct RemoteOptions(pub HashMap<String, String>);
|
||||
|
||||
impl RemoteOptions {
|
||||
pub fn new(options: HashMap<String, String>) -> Self {
|
||||
Self(options)
|
||||
}
|
||||
}
|
||||
|
||||
impl From<StorageOptions> for RemoteOptions {
|
||||
fn from(options: StorageOptions) -> Self {
|
||||
let supported_opts = vec!["account_name", "azure_storage_account_name"];
|
||||
let mut filtered = HashMap::new();
|
||||
for opt in supported_opts {
|
||||
if let Some(v) = options.0.get(opt) {
|
||||
filtered.insert(opt.to_string(), v.to_string());
|
||||
}
|
||||
}
|
||||
RemoteOptions::new(filtered)
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use std::sync::{Arc, OnceLock};
|
||||
@@ -213,7 +282,9 @@ mod tests {
|
||||
use arrow_array::{Int32Array, RecordBatch, RecordBatchIterator};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
|
||||
use crate::connection::ConnectBuilder;
|
||||
use crate::{
|
||||
connection::CreateTableMode,
|
||||
remote::{ARROW_STREAM_CONTENT_TYPE, JSON_CONTENT_TYPE},
|
||||
Connection, Error,
|
||||
};
|
||||
@@ -382,6 +453,73 @@ mod tests {
|
||||
);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_create_table_modes() {
|
||||
let test_cases = [
|
||||
(None, "mode=create"),
|
||||
(Some(CreateTableMode::Create), "mode=create"),
|
||||
(Some(CreateTableMode::Overwrite), "mode=overwrite"),
|
||||
(
|
||||
Some(CreateTableMode::ExistOk(Box::new(|b| b))),
|
||||
"mode=exist_ok",
|
||||
),
|
||||
];
|
||||
|
||||
for (mode, expected_query_string) in test_cases {
|
||||
let conn = Connection::new_with_handler(move |request| {
|
||||
assert_eq!(request.method(), &reqwest::Method::POST);
|
||||
assert_eq!(request.url().path(), "/v1/table/table1/create/");
|
||||
assert_eq!(request.url().query(), Some(expected_query_string));
|
||||
|
||||
http::Response::builder().status(200).body("").unwrap()
|
||||
});
|
||||
|
||||
let data = RecordBatch::try_new(
|
||||
Arc::new(Schema::new(vec![Field::new("a", DataType::Int32, false)])),
|
||||
vec![Arc::new(Int32Array::from(vec![1, 2, 3]))],
|
||||
)
|
||||
.unwrap();
|
||||
let reader = RecordBatchIterator::new([Ok(data.clone())], data.schema());
|
||||
let mut builder = conn.create_table("table1", reader);
|
||||
if let Some(mode) = mode {
|
||||
builder = builder.mode(mode);
|
||||
}
|
||||
builder.execute().await.unwrap();
|
||||
}
|
||||
|
||||
// check that the open table callback is called with exist_ok
|
||||
let conn = Connection::new_with_handler(|request| match request.url().path() {
|
||||
"/v1/table/table1/create/" => http::Response::builder()
|
||||
.status(400)
|
||||
.body("Table table1 already exists")
|
||||
.unwrap(),
|
||||
"/v1/table/table1/describe/" => http::Response::builder().status(200).body("").unwrap(),
|
||||
_ => {
|
||||
panic!("unexpected path: {:?}", request.url().path());
|
||||
}
|
||||
});
|
||||
let data = RecordBatch::try_new(
|
||||
Arc::new(Schema::new(vec![Field::new("a", DataType::Int32, false)])),
|
||||
vec![Arc::new(Int32Array::from(vec![1, 2, 3]))],
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let called: Arc<OnceLock<bool>> = Arc::new(OnceLock::new());
|
||||
let reader = RecordBatchIterator::new([Ok(data.clone())], data.schema());
|
||||
let called_in_cb = called.clone();
|
||||
conn.create_table("table1", reader)
|
||||
.mode(CreateTableMode::ExistOk(Box::new(move |b| {
|
||||
called_in_cb.clone().set(true).unwrap();
|
||||
b
|
||||
})))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let called = *called.get().unwrap_or(&false);
|
||||
assert!(called);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_create_table_empty() {
|
||||
let conn = Connection::new_with_handler(|request| {
|
||||
@@ -436,4 +574,16 @@ mod tests {
|
||||
});
|
||||
conn.rename_table("table1", "table2").await.unwrap();
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_connect_remote_options() {
|
||||
let db_uri = "db://my-container/my-prefix";
|
||||
let _ = ConnectBuilder::new(db_uri)
|
||||
.region("us-east-1")
|
||||
.api_key("my-api-key")
|
||||
.storage_options(vec![("azure_storage_account_name", "my-storage-account")])
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
}
|
||||
}
|
||||
|
||||
@@ -17,7 +17,7 @@ use datafusion_physical_plan::{ExecutionPlan, SendableRecordBatchStream};
|
||||
use futures::TryStreamExt;
|
||||
use http::header::CONTENT_TYPE;
|
||||
use http::StatusCode;
|
||||
use lance::arrow::json::JsonSchema;
|
||||
use lance::arrow::json::{JsonDataType, JsonSchema};
|
||||
use lance::dataset::scanner::DatasetRecordBatchStream;
|
||||
use lance::dataset::{ColumnAlteration, NewColumnTransform, Version};
|
||||
use lance_datafusion::exec::OneShotExec;
|
||||
@@ -643,25 +643,80 @@ impl<S: HttpSend> TableInternal for RemoteTable<S> {
|
||||
}
|
||||
async fn add_columns(
|
||||
&self,
|
||||
_transforms: NewColumnTransform,
|
||||
transforms: NewColumnTransform,
|
||||
_read_columns: Option<Vec<String>>,
|
||||
) -> Result<()> {
|
||||
self.check_mutable().await?;
|
||||
Err(Error::NotSupported {
|
||||
message: "add_columns is not yet supported.".into(),
|
||||
})
|
||||
match transforms {
|
||||
NewColumnTransform::SqlExpressions(expressions) => {
|
||||
let body = expressions
|
||||
.into_iter()
|
||||
.map(|(name, expression)| {
|
||||
serde_json::json!({
|
||||
"name": name,
|
||||
"expression": expression,
|
||||
})
|
||||
})
|
||||
.collect::<Vec<_>>();
|
||||
let body = serde_json::json!({ "new_columns": body });
|
||||
let request = self
|
||||
.client
|
||||
.post(&format!("/v1/table/{}/add_columns/", self.name))
|
||||
.json(&body);
|
||||
let (request_id, response) = self.client.send(request, false).await?;
|
||||
self.check_table_response(&request_id, response).await?;
|
||||
Ok(())
|
||||
}
|
||||
_ => {
|
||||
return Err(Error::NotSupported {
|
||||
message: "Only SQL expressions are supported for adding columns".into(),
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
async fn alter_columns(&self, _alterations: &[ColumnAlteration]) -> Result<()> {
|
||||
|
||||
async fn alter_columns(&self, alterations: &[ColumnAlteration]) -> Result<()> {
|
||||
self.check_mutable().await?;
|
||||
Err(Error::NotSupported {
|
||||
message: "alter_columns is not yet supported.".into(),
|
||||
})
|
||||
let body = alterations
|
||||
.iter()
|
||||
.map(|alteration| {
|
||||
let mut value = serde_json::json!({
|
||||
"path": alteration.path,
|
||||
});
|
||||
if let Some(rename) = &alteration.rename {
|
||||
value["rename"] = serde_json::Value::String(rename.clone());
|
||||
}
|
||||
if let Some(data_type) = &alteration.data_type {
|
||||
let json_data_type = JsonDataType::try_from(data_type).unwrap();
|
||||
let json_data_type = serde_json::to_value(&json_data_type).unwrap();
|
||||
value["data_type"] = json_data_type;
|
||||
}
|
||||
if let Some(nullable) = &alteration.nullable {
|
||||
value["nullable"] = serde_json::Value::Bool(*nullable);
|
||||
}
|
||||
value
|
||||
})
|
||||
.collect::<Vec<_>>();
|
||||
let body = serde_json::json!({ "alterations": body });
|
||||
let request = self
|
||||
.client
|
||||
.post(&format!("/v1/table/{}/alter_columns/", self.name))
|
||||
.json(&body);
|
||||
let (request_id, response) = self.client.send(request, false).await?;
|
||||
self.check_table_response(&request_id, response).await?;
|
||||
Ok(())
|
||||
}
|
||||
async fn drop_columns(&self, _columns: &[&str]) -> Result<()> {
|
||||
|
||||
async fn drop_columns(&self, columns: &[&str]) -> Result<()> {
|
||||
self.check_mutable().await?;
|
||||
Err(Error::NotSupported {
|
||||
message: "drop_columns is not yet supported.".into(),
|
||||
})
|
||||
let body = serde_json::json!({ "columns": columns });
|
||||
let request = self
|
||||
.client
|
||||
.post(&format!("/v1/table/{}/drop_columns/", self.name))
|
||||
.json(&body);
|
||||
let (request_id, response) = self.client.send(request, false).await?;
|
||||
self.check_table_response(&request_id, response).await?;
|
||||
Ok(())
|
||||
}
|
||||
|
||||
async fn list_indices(&self) -> Result<Vec<IndexConfig>> {
|
||||
@@ -844,7 +899,17 @@ mod tests {
|
||||
Box::pin(table.update().column("a", "a + 1").execute().map_ok(|_| ())),
|
||||
Box::pin(table.add(example_data()).execute().map_ok(|_| ())),
|
||||
Box::pin(table.merge_insert(&["test"]).execute(example_data())),
|
||||
Box::pin(table.delete("false")), // TODO: other endpoints.
|
||||
Box::pin(table.delete("false")),
|
||||
Box::pin(table.add_columns(
|
||||
NewColumnTransform::SqlExpressions(vec![("x".into(), "y".into())]),
|
||||
None,
|
||||
)),
|
||||
Box::pin(async {
|
||||
let alterations = vec![ColumnAlteration::new("x".into()).rename("y".into())];
|
||||
table.alter_columns(&alterations).await
|
||||
}),
|
||||
Box::pin(table.drop_columns(&["a"])),
|
||||
// TODO: other endpoints.
|
||||
];
|
||||
|
||||
for result in results {
|
||||
@@ -1227,6 +1292,7 @@ mod tests {
|
||||
"prefilter": true,
|
||||
"distance_type": "l2",
|
||||
"nprobes": 20,
|
||||
"k": 10,
|
||||
"ef": Option::<usize>::None,
|
||||
"refine_factor": null,
|
||||
"version": null,
|
||||
@@ -1798,4 +1864,114 @@ mod tests {
|
||||
.await;
|
||||
assert!(matches!(res, Err(Error::NotSupported { .. })));
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_add_columns() {
|
||||
let table = Table::new_with_handler("my_table", |request| {
|
||||
assert_eq!(request.method(), "POST");
|
||||
assert_eq!(request.url().path(), "/v1/table/my_table/add_columns/");
|
||||
assert_eq!(
|
||||
request.headers().get("Content-Type").unwrap(),
|
||||
JSON_CONTENT_TYPE
|
||||
);
|
||||
|
||||
let body = request.body().unwrap().as_bytes().unwrap();
|
||||
let body = std::str::from_utf8(body).unwrap();
|
||||
let value: serde_json::Value = serde_json::from_str(body).unwrap();
|
||||
let new_columns = value.get("new_columns").unwrap().as_array().unwrap();
|
||||
assert!(new_columns.len() == 2);
|
||||
|
||||
let col_name = new_columns[0]["name"].as_str().unwrap();
|
||||
let expression = new_columns[0]["expression"].as_str().unwrap();
|
||||
assert_eq!(col_name, "b");
|
||||
assert_eq!(expression, "a + 1");
|
||||
|
||||
let col_name = new_columns[1]["name"].as_str().unwrap();
|
||||
let expression = new_columns[1]["expression"].as_str().unwrap();
|
||||
assert_eq!(col_name, "x");
|
||||
assert_eq!(expression, "cast(NULL as int32)");
|
||||
|
||||
http::Response::builder().status(200).body("{}").unwrap()
|
||||
});
|
||||
|
||||
table
|
||||
.add_columns(
|
||||
NewColumnTransform::SqlExpressions(vec![
|
||||
("b".into(), "a + 1".into()),
|
||||
("x".into(), "cast(NULL as int32)".into()),
|
||||
]),
|
||||
None,
|
||||
)
|
||||
.await
|
||||
.unwrap();
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_alter_columns() {
|
||||
let table = Table::new_with_handler("my_table", |request| {
|
||||
assert_eq!(request.method(), "POST");
|
||||
assert_eq!(request.url().path(), "/v1/table/my_table/alter_columns/");
|
||||
assert_eq!(
|
||||
request.headers().get("Content-Type").unwrap(),
|
||||
JSON_CONTENT_TYPE
|
||||
);
|
||||
|
||||
let body = request.body().unwrap().as_bytes().unwrap();
|
||||
let body = std::str::from_utf8(body).unwrap();
|
||||
let value: serde_json::Value = serde_json::from_str(body).unwrap();
|
||||
let alterations = value.get("alterations").unwrap().as_array().unwrap();
|
||||
assert!(alterations.len() == 2);
|
||||
|
||||
let path = alterations[0]["path"].as_str().unwrap();
|
||||
let data_type = alterations[0]["data_type"]["type"].as_str().unwrap();
|
||||
assert_eq!(path, "b.c");
|
||||
assert_eq!(data_type, "int32");
|
||||
|
||||
let path = alterations[1]["path"].as_str().unwrap();
|
||||
let nullable = alterations[1]["nullable"].as_bool().unwrap();
|
||||
let rename = alterations[1]["rename"].as_str().unwrap();
|
||||
assert_eq!(path, "x");
|
||||
assert!(nullable);
|
||||
assert_eq!(rename, "y");
|
||||
|
||||
http::Response::builder().status(200).body("{}").unwrap()
|
||||
});
|
||||
|
||||
table
|
||||
.alter_columns(&[
|
||||
ColumnAlteration::new("b.c".into()).cast_to(DataType::Int32),
|
||||
ColumnAlteration::new("x".into())
|
||||
.rename("y".into())
|
||||
.set_nullable(true),
|
||||
])
|
||||
.await
|
||||
.unwrap();
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_drop_columns() {
|
||||
let table = Table::new_with_handler("my_table", |request| {
|
||||
assert_eq!(request.method(), "POST");
|
||||
assert_eq!(request.url().path(), "/v1/table/my_table/drop_columns/");
|
||||
assert_eq!(
|
||||
request.headers().get("Content-Type").unwrap(),
|
||||
JSON_CONTENT_TYPE
|
||||
);
|
||||
|
||||
let body = request.body().unwrap().as_bytes().unwrap();
|
||||
let body = std::str::from_utf8(body).unwrap();
|
||||
let value: serde_json::Value = serde_json::from_str(body).unwrap();
|
||||
let columns = value.get("columns").unwrap().as_array().unwrap();
|
||||
assert!(columns.len() == 2);
|
||||
|
||||
let col1 = columns[0].as_str().unwrap();
|
||||
let col2 = columns[1].as_str().unwrap();
|
||||
assert_eq!(col1, "a");
|
||||
assert_eq!(col2, "b");
|
||||
|
||||
http::Response::builder().status(200).body("{}").unwrap()
|
||||
});
|
||||
|
||||
table.drop_columns(&["a", "b"]).await.unwrap();
|
||||
}
|
||||
}
|
||||
|
||||
@@ -14,7 +14,6 @@
|
||||
|
||||
//! LanceDB Table APIs
|
||||
|
||||
use std::collections::HashMap;
|
||||
use std::path::Path;
|
||||
use std::sync::Arc;
|
||||
|
||||
@@ -37,7 +36,8 @@ pub use lance::dataset::ColumnAlteration;
|
||||
pub use lance::dataset::NewColumnTransform;
|
||||
pub use lance::dataset::ReadParams;
|
||||
use lance::dataset::{
|
||||
Dataset, UpdateBuilder as LanceUpdateBuilder, Version, WhenMatched, WriteMode, WriteParams,
|
||||
Dataset, InsertBuilder, UpdateBuilder as LanceUpdateBuilder, Version, WhenMatched, WriteMode,
|
||||
WriteParams,
|
||||
};
|
||||
use lance::dataset::{MergeInsertBuilder as LanceMergeInsertBuilder, WhenNotMatchedBySource};
|
||||
use lance::io::WrappingObjectStore;
|
||||
@@ -1046,12 +1046,6 @@ pub struct NativeTable {
|
||||
name: String,
|
||||
uri: String,
|
||||
pub(crate) dataset: dataset::DatasetConsistencyWrapper,
|
||||
|
||||
// the object store wrapper to use on write path
|
||||
store_wrapper: Option<Arc<dyn WrappingObjectStore>>,
|
||||
|
||||
storage_options: HashMap<String, String>,
|
||||
|
||||
// This comes from the connection options. We store here so we can pass down
|
||||
// to the dataset when we recreate it (for example, in checkout_latest).
|
||||
read_consistency_interval: Option<std::time::Duration>,
|
||||
@@ -1117,13 +1111,6 @@ impl NativeTable {
|
||||
None => params,
|
||||
};
|
||||
|
||||
let storage_options = params
|
||||
.store_options
|
||||
.clone()
|
||||
.unwrap_or_default()
|
||||
.storage_options
|
||||
.unwrap_or_default();
|
||||
|
||||
let dataset = DatasetBuilder::from_uri(uri)
|
||||
.with_read_params(params)
|
||||
.load()
|
||||
@@ -1141,8 +1128,6 @@ impl NativeTable {
|
||||
name: name.to_string(),
|
||||
uri: uri.to_string(),
|
||||
dataset,
|
||||
store_wrapper: write_store_wrapper,
|
||||
storage_options,
|
||||
read_consistency_interval,
|
||||
})
|
||||
}
|
||||
@@ -1191,12 +1176,6 @@ impl NativeTable {
|
||||
Some(wrapper) => params.patch_with_store_wrapper(wrapper)?,
|
||||
None => params,
|
||||
};
|
||||
let storage_options = params
|
||||
.store_params
|
||||
.clone()
|
||||
.unwrap_or_default()
|
||||
.storage_options
|
||||
.unwrap_or_default();
|
||||
|
||||
let dataset = Dataset::write(batches, uri, Some(params))
|
||||
.await
|
||||
@@ -1210,8 +1189,6 @@ impl NativeTable {
|
||||
name: name.to_string(),
|
||||
uri: uri.to_string(),
|
||||
dataset: DatasetConsistencyWrapper::new_latest(dataset, read_consistency_interval),
|
||||
store_wrapper: write_store_wrapper,
|
||||
storage_options,
|
||||
read_consistency_interval,
|
||||
})
|
||||
}
|
||||
@@ -1758,10 +1735,13 @@ impl TableInternal for NativeTable {
|
||||
add: AddDataBuilder<NoData>,
|
||||
data: Box<dyn RecordBatchReader + Send>,
|
||||
) -> Result<()> {
|
||||
let data =
|
||||
MaybeEmbedded::try_new(data, self.table_definition().await?, add.embedding_registry)?;
|
||||
let data = Box::new(MaybeEmbedded::try_new(
|
||||
data,
|
||||
self.table_definition().await?,
|
||||
add.embedding_registry,
|
||||
)?) as Box<dyn RecordBatchReader + Send>;
|
||||
|
||||
let mut lance_params = add.write_options.lance_write_params.unwrap_or(WriteParams {
|
||||
let lance_params = add.write_options.lance_write_params.unwrap_or(WriteParams {
|
||||
mode: match add.mode {
|
||||
AddDataMode::Append => WriteMode::Append,
|
||||
AddDataMode::Overwrite => WriteMode::Overwrite,
|
||||
@@ -1769,27 +1749,15 @@ impl TableInternal for NativeTable {
|
||||
..Default::default()
|
||||
});
|
||||
|
||||
// Bring storage options from table
|
||||
let storage_options = lance_params
|
||||
.store_params
|
||||
.get_or_insert(Default::default())
|
||||
.storage_options
|
||||
.get_or_insert(Default::default());
|
||||
for (key, value) in self.storage_options.iter() {
|
||||
if !storage_options.contains_key(key) {
|
||||
storage_options.insert(key.clone(), value.clone());
|
||||
}
|
||||
}
|
||||
|
||||
// patch the params if we have a write store wrapper
|
||||
let lance_params = match self.store_wrapper.clone() {
|
||||
Some(wrapper) => lance_params.patch_with_store_wrapper(wrapper)?,
|
||||
None => lance_params,
|
||||
let dataset = {
|
||||
// Limited scope for the mutable borrow of self.dataset avoids deadlock.
|
||||
let ds = self.dataset.get_mut().await?;
|
||||
InsertBuilder::new(Arc::new(ds.clone()))
|
||||
.with_params(&lance_params)
|
||||
.execute_stream(data)
|
||||
.await?
|
||||
};
|
||||
|
||||
self.dataset.ensure_mutable().await?;
|
||||
let dataset = Dataset::write(data, &self.uri, Some(lance_params)).await?;
|
||||
|
||||
self.dataset.set_latest(dataset).await;
|
||||
Ok(())
|
||||
}
|
||||
|
||||
@@ -15,6 +15,7 @@
|
||||
use std::sync::Arc;
|
||||
|
||||
use arrow_schema::{DataType, Schema};
|
||||
use lance::arrow::json::JsonDataType;
|
||||
use lance::dataset::{ReadParams, WriteParams};
|
||||
use lance::io::{ObjectStoreParams, WrappingObjectStore};
|
||||
use lazy_static::lazy_static;
|
||||
@@ -175,6 +176,15 @@ pub fn supported_vector_data_type(dtype: &DataType) -> bool {
|
||||
}
|
||||
}
|
||||
|
||||
/// Note: this is temporary until we get a proper datatype conversion in Lance.
|
||||
pub fn string_to_datatype(s: &str) -> Option<DataType> {
|
||||
let data_type = serde_json::Value::String(s.to_string());
|
||||
let json_type =
|
||||
serde_json::Value::Object([("type".to_string(), data_type)].iter().cloned().collect());
|
||||
let json_type: JsonDataType = serde_json::from_value(json_type).ok()?;
|
||||
(&json_type).try_into().ok()
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
@@ -239,4 +249,11 @@ mod tests {
|
||||
assert!(validate_table_name("my@table").is_err());
|
||||
assert!(validate_table_name("name with space").is_err());
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_string_to_datatype() {
|
||||
let string = "int32";
|
||||
let expected = DataType::Int32;
|
||||
assert_eq!(string_to_datatype(string), Some(expected));
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user