Bump version: 0.30.2-beta.2 → 0.30.2

This code previously referenced `self._client`, which does not exist.
This change makes it correctly call `self._conn.close()`

.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.27.0-beta.2"
+current_version = "0.27.2-beta.1"
 parse = """(?x)
     (?P<major>0|[1-9]\\d*)\\.
     (?P<minor>0|[1-9]\\d*)\\.

.github/workflows/build_linux_wheel/action.yml

@@ -23,12 +23,15 @@ runs:
   steps:
     - name: CONFIRM ARM BUILD
       shell: bash
+      env:
+        ARM_BUILD: ${{ inputs.arm-build }}
       run: |
-        echo "ARM BUILD: ${{ inputs.arm-build }}"
+        echo "ARM BUILD: $ARM_BUILD"
     - name: Build x86_64 Manylinux wheel
       if: ${{ inputs.arm-build == 'false' }}
       uses: PyO3/maturin-action@v1
       with:
+        maturin-version: "1.12.4"
         command: build
         working-directory: python
         docker-options: "-e PIP_EXTRA_INDEX_URL='https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/'"
@@ -44,6 +47,7 @@ runs:
       if: ${{ inputs.arm-build == 'true' }}
       uses: PyO3/maturin-action@v1
       with:
+        maturin-version: "1.12.4"
         command: build
         working-directory: python
         docker-options: "-e PIP_EXTRA_INDEX_URL='https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/'"

.github/workflows/build_mac_wheel/action.yml

@@ -20,6 +20,7 @@ runs:
       uses: PyO3/maturin-action@v1
       with:
         command: build
+        maturin-version: "1.12.4"
         # TODO: pass through interpreter
         args: ${{ inputs.args }}
         docker-options: "-e PIP_EXTRA_INDEX_URL='https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/'"

.github/workflows/build_windows_wheel/action.yml

@@ -25,6 +25,7 @@ runs:
       uses: PyO3/maturin-action@v1
       with:
         command: build
+        maturin-version: "1.12.4"
         args: ${{ inputs.args }}
         docker-options: "-e PIP_EXTRA_INDEX_URL='https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/'"
         working-directory: python

.github/workflows/dev.yml

@@ -15,7 +15,7 @@ jobs:
     name: Label PR
     runs-on: ubuntu-latest
     steps:
-      - uses: srvaroa/labeler@master
+      - uses: srvaroa/labeler@v1
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
   commitlint:
@@ -24,7 +24,7 @@ jobs:
     name: Verify PR title / description conforms to semantic-release
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/setup-node@v3
+      - uses: actions/setup-node@v4
         with:
           node-version: "18"
       # These rules are disabled because Github will always ensure there
@@ -47,7 +47,7 @@ jobs:
 
             ${{ github.event.pull_request.body }}
       - if: failure()
-        uses: actions/github-script@v6
+        uses: actions/github-script@v7
         with:
           script: |
             const message = `**ACTION NEEDED**

.github/workflows/docs.yml

@@ -53,7 +53,7 @@ jobs:
           python -m pip install --extra-index-url https://pypi.fury.io/lance-format/ --extra-index-url https://pypi.fury.io/lancedb/ -e .
           python -m pip install --extra-index-url https://pypi.fury.io/lance-format/ --extra-index-url https://pypi.fury.io/lancedb/ -r ../docs/requirements.txt
       - name: Set up node
-        uses: actions/setup-node@v3
+        uses: actions/setup-node@v4
         with:
           node-version: 20
           cache: 'npm'
@@ -68,7 +68,7 @@ jobs:
         run: |
           PYTHONPATH=. mkdocs build
       - name: Setup Pages
-        uses: actions/configure-pages@v2
+        uses: actions/configure-pages@v5
       - name: Upload artifact
         uses: actions/upload-pages-artifact@v3
         with:

.github/workflows/nodejs.yml

@@ -7,6 +7,7 @@ on:
   pull_request:
     paths:
       - Cargo.toml
+      - Cargo.lock
       - nodejs/**
       - rust/**
       - docs/src/js/**
@@ -37,7 +38,7 @@ jobs:
       with:
         fetch-depth: 0
         lfs: true
-    - uses: actions/setup-node@v3
+    - uses: actions/setup-node@v4
       with:
         node-version: 20
         cache: 'npm'
@@ -77,7 +78,7 @@ jobs:
       with:
         fetch-depth: 0
         lfs: true
-    - uses: actions/setup-node@v3
+    - uses: actions/setup-node@v4
       name: Setup Node.js 20 for build
       with:
         # @napi-rs/cli v3 requires Node >= 20.12 (via @inquirer/prompts@8).
@@ -94,7 +95,7 @@ jobs:
       run: |
         npm ci --include=optional
         npm run build:debug -- --profile ci
-    - uses: actions/setup-node@v3
+    - uses: actions/setup-node@v4
       name: Setup Node.js ${{ matrix.node-version }} for test
       with:
         node-version: ${{ matrix.node-version }}
@@ -143,7 +144,7 @@ jobs:
       with:
         fetch-depth: 0
         lfs: true
-    - uses: actions/setup-node@v3
+    - uses: actions/setup-node@v4
       with:
         node-version: 20
         cache: 'npm'

.github/workflows/npm-publish.yml

@@ -19,6 +19,7 @@ on:
     paths:
       - .github/workflows/npm-publish.yml
       - Cargo.toml # Change in dependency frequently breaks builds
+      - Cargo.lock
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.ref }}
@@ -124,7 +125,12 @@ jobs:
             pre_build: |-
               set -e &&
               apt-get update &&
-              apt-get install -y protobuf-compiler pkg-config
+              apt-get install -y protobuf-compiler pkg-config &&
+              # The base image (manylinux2014-cross) sets TARGET_CC to the old
+              # GCC 4.8 cross-compiler. aws-lc-sys checks TARGET_CC before CC,
+              # so it picks up GCC even though the napi-rs image sets CC=clang.
+              # Override to use the image's clang-18 which supports -fuse-ld=lld.
+              export TARGET_CC=clang TARGET_CXX=clang++
           - target: x86_64-unknown-linux-musl
             # This one seems to need some extra memory
             host: ubuntu-2404-8x-x64
@@ -144,9 +150,10 @@ jobs:
               set -e &&
               apt-get update &&
               apt-get install -y protobuf-compiler pkg-config &&
-              # https://github.com/aws/aws-lc-rs/issues/737#issuecomment-2725918627
+              export TARGET_CC=clang TARGET_CXX=clang++ &&
-              ln -s /usr/aarch64-unknown-linux-gnu/lib/gcc/aarch64-unknown-linux-gnu/4.8.5/crtbeginS.o /usr/aarch64-unknown-linux-gnu/aarch64-unknown-linux-gnu/sysroot/usr/lib/crtbeginS.o &&
+              # The manylinux2014 sysroot has glibc 2.17 headers which lack
-              ln -s /usr/aarch64-unknown-linux-gnu/lib/gcc /usr/aarch64-unknown-linux-gnu/aarch64-unknown-linux-gnu/sysroot/usr/lib/gcc &&
+              # AT_HWCAP2 (added in Linux 3.17). Define it for aws-lc-sys.
+              export CFLAGS="$CFLAGS -DAT_HWCAP2=26" &&
               rustup target add aarch64-unknown-linux-gnu
           - target: aarch64-unknown-linux-musl
             host: ubuntu-2404-8x-x64
@@ -266,7 +273,7 @@ jobs:
           - target: x86_64-unknown-linux-gnu
             host: ubuntu-latest
           - target: aarch64-unknown-linux-gnu
-            host: buildjet-16vcpu-ubuntu-2204-arm
+            host: ubuntu-2404-8x-arm64
         node:
           - '20'
     runs-on: ${{ matrix.settings.host }}
@@ -356,7 +363,8 @@ jobs:
           if [[ $DRY_RUN == "true" ]]; then
             ARGS="$ARGS --dry-run"
           fi
-          if [[ $GITHUB_REF =~ refs/tags/v(.*)-beta.* ]]; then
+          VERSION=$(node -p "require('./package.json').version")
+          if [[ $VERSION == *-* ]]; then
             ARGS="$ARGS --tag preview"
           fi
           npm publish $ARGS

.github/workflows/pypi-publish.yml

@@ -9,6 +9,7 @@ on:
     paths:
       - .github/workflows/pypi-publish.yml
       - Cargo.toml # Change in dependency frequently breaks builds
+      - Cargo.lock
 
 env:
   PIP_EXTRA_INDEX_URL: "https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/"

.github/workflows/python.yml

@@ -7,9 +7,14 @@ on:
   pull_request:
     paths:
       - Cargo.toml
+      - Cargo.lock
       - python/**
       - rust/**
       - .github/workflows/python.yml
+      - .github/workflows/build_linux_wheel/**
+      - .github/workflows/build_mac_wheel/**
+      - .github/workflows/build_windows_wheel/**
+      - .github/workflows/run_tests/**
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}

.github/workflows/rust.yml

@@ -7,6 +7,7 @@ on:
   pull_request:
     paths:
       - Cargo.toml
+      - Cargo.lock
       - rust/**
       - .github/workflows/rust.yml
 
@@ -206,14 +207,14 @@ jobs:
       - name: Downgrade  dependencies
         # These packages have newer requirements for MSRV
         run: |
-          cargo update -p aws-sdk-bedrockruntime --precise 1.64.0
+          cargo update -p aws-sdk-bedrockruntime --precise 1.77.0
-          cargo update -p aws-sdk-dynamodb --precise 1.55.0
+          cargo update -p aws-sdk-dynamodb --precise 1.68.0
-          cargo update -p aws-config --precise 1.5.10
+          cargo update -p aws-config --precise 1.6.0
-          cargo update -p aws-sdk-kms --precise 1.51.0
+          cargo update -p aws-sdk-kms --precise 1.63.0
-          cargo update -p aws-sdk-s3 --precise 1.65.0
+          cargo update -p aws-sdk-s3 --precise 1.79.0
-          cargo update -p aws-sdk-sso --precise 1.50.0
+          cargo update -p aws-sdk-sso --precise 1.62.0
-          cargo update -p aws-sdk-ssooidc --precise 1.51.0
+          cargo update -p aws-sdk-ssooidc --precise 1.63.0
-          cargo update -p aws-sdk-sts --precise 1.51.0
+          cargo update -p aws-sdk-sts --precise 1.63.0
           cargo update -p home --precise 0.5.9
       - name: cargo +${{ matrix.msrv }} check
         env:

Cargo.toml

@@ -5,7 +5,7 @@ exclude = ["python"]
 resolver = "2"
 
 [workspace.package]
-edition = "2021"
+edition = "2024"
 authors = ["LanceDB Devs <dev@lancedb.com>"]
 license = "Apache-2.0"
 repository = "https://github.com/lancedb/lancedb"
@@ -15,20 +15,20 @@ categories = ["database-implementations"]
 rust-version = "1.91.0"
 
 [workspace.dependencies]
-lance = { "version" = "=3.0.0-rc.2", default-features = false, "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
+lance = { version = "=4.0.0", default-features = false }
-lance-core = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-core = { version = "=4.0.0" }
-lance-datagen = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-datagen = { version = "=4.0.0" }
-lance-file = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-file = { version = "=4.0.0" }
-lance-io = { "version" = "=3.0.0-rc.2", default-features = false, "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-io = { version = "=4.0.0", default-features = false }
-lance-index = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-index = { version = "=4.0.0" }
-lance-linalg = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-linalg = { version = "=4.0.0" }
-lance-namespace = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace = { version = "=4.0.0" }
-lance-namespace-impls = { "version" = "=3.0.0-rc.2", default-features = false, "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace-impls = { version = "=4.0.0", default-features = false }
-lance-table = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-table = { version = "=4.0.0" }
-lance-testing = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-testing = { version = "=4.0.0" }
-lance-datafusion = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-datafusion = { version = "=4.0.0" }
-lance-encoding = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-encoding = { version = "=4.0.0" }
-lance-arrow = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-arrow = { version = "=4.0.0" }
 ahash = "0.8"
 # Note that this one does not include pyarrow
 arrow = { version = "57.2", optional = false }

ci/check_lance_release.py

@@ -3,6 +3,7 @@
 from __future__ import annotations
 
 import argparse
+import functools
 import json
 import os
 import re
@@ -26,6 +27,7 @@ SEMVER_RE = re.compile(
 )
 
 
+@functools.total_ordering
 @dataclass(frozen=True)
 class SemVer:
     major: int
@@ -156,7 +158,9 @@ def read_current_version(repo_root: Path) -> str:
 
 
 def determine_latest_tag(tags: Iterable[TagInfo]) -> TagInfo:
-    return max(tags, key=lambda tag: tag.semver)
+    # Stable releases (no prerelease) are always preferred over pre-releases.
+    # Within each group, standard semver ordering applies.
+    return max(tags, key=lambda tag: (not tag.semver.prerelease, tag.semver))
 
 
 def write_outputs(args: argparse.Namespace, payload: dict) -> None:

docker-compose.yml

@@ -1,7 +1,7 @@
 version: "3.9"
 services:
   localstack:
-    image: localstack/localstack:3.3
+    image: localstack/localstack:4.0
     ports:
       - 4566:4566
     environment:

dockerfiles/Dockerfile

@@ -1,27 +1,27 @@
-#Simple base dockerfile that supports basic dependencies required to run lance with FTS and Hybrid Search
+# Simple base dockerfile that supports basic dependencies required to run lance with FTS and Hybrid Search
-#Usage docker build -t lancedb:latest -f Dockerfile .
+# Usage: docker build -t lancedb:latest -f Dockerfile .
-FROM python:3.10-slim-buster
+FROM python:3.12-slim-bookworm
 
-# Install Rust
+# Install build dependencies in a single layer
-RUN apt-get update && apt-get install -y curl build-essential && \
+RUN apt-get update && \
-  curl https://sh.rustup.rs -sSf | sh -s -- -y
+  apt-get install -y --no-install-recommends \
-
+    curl \
-# Set the environment variable for Rust
+    build-essential \
-ENV PATH="/root/.cargo/bin:${PATH}"
+    protobuf-compiler \
-
+    git \
-# Install protobuf compiler
+    ca-certificates && \
-RUN apt-get install -y protobuf-compiler && \
   apt-get clean && \
   rm -rf /var/lib/apt/lists/*
 
-RUN apt-get -y update &&\
+# Install Rust (pinned installer, non-interactive)
-  apt-get -y upgrade && \
+RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y --default-toolchain stable --profile minimal
-  apt-get -y install git
 
+# Set the environment variable for Rust
+ENV PATH="/root/.cargo/bin:${PATH}"
 
 # Verify installations
 RUN python --version && \
   rustc --version && \
   protoc --version
 
-RUN pip install tantivy lancedb
+RUN pip install --no-cache-dir tantivy lancedb

docs/mkdocs.yml

@@ -52,14 +52,21 @@ plugins:
           options:
             docstring_style: numpy
             heading_level: 3
-            show_source: true
-            show_symbol_type_in_heading: true
             show_signature_annotations: true
             show_root_heading: true
+            show_docstring_examples: true
+            show_docstring_attributes: false
+            show_docstring_other_parameters: true
+            show_symbol_type_heading: true
+            show_labels: false
+            show_if_no_docstring: true
+            show_source: false
             members_order: source
             docstring_section_style: list
             signature_crossrefs: true
             separate_signature: true
+            filters:
+              - "!^_"
           import:
             # for cross references
             - https://arrow.apache.org/docs/objects.inv
@@ -113,7 +120,7 @@ markdown_extensions:
       emoji_index: !!python/name:material.extensions.emoji.twemoji
       emoji_generator: !!python/name:material.extensions.emoji.to_svg
   - markdown.extensions.toc:
-      toc_depth: 3
+      toc_depth: 4
       permalink: true
       permalink_title: Anchor link to this section
 

docs/requirements.txt

@@ -1,9 +1,9 @@
-mkdocs==1.5.3
+mkdocs==1.6.1
 mkdocs-jupyter==0.24.1
-mkdocs-material==9.5.3
+mkdocs-material==9.6.23
-mkdocs-autorefs<=1.0
+mkdocs-autorefs>=0.5,<=1.0
-mkdocstrings[python]==0.25.2
+mkdocstrings[python]>=0.24,<1.0
-griffe
+griffe>=0.40,<1.0
-mkdocs-render-swagger-plugin
+mkdocs-render-swagger-plugin>=0.1.0
-pydantic
+pydantic>=2.0,<3.0
-mkdocs-redirects
+mkdocs-redirects>=1.2.0

docs/src/java/java.md

@@ -14,7 +14,7 @@ Add the following dependency to your `pom.xml`:
 <dependency>
     <groupId>com.lancedb</groupId>
     <artifactId>lancedb-core</artifactId>
-    <version>0.27.0-beta.2</version>
+    <version>0.27.2-beta.1</version>
 </dependency>
 ```
 

docs/src/js/classes/Table.md

@@ -71,11 +71,12 @@ Add new columns with defined values.
 
 #### Parameters
 
-* **newColumnTransforms**: [`AddColumnsSql`](../interfaces/AddColumnsSql.md)[]
+* **newColumnTransforms**: `Field`<`any`> \| `Field`<`any`>[] \| `Schema`<`any`> \| [`AddColumnsSql`](../interfaces/AddColumnsSql.md)[]
-    pairs of column names and
+    Either:
-    the SQL expression to use to calculate the value of the new column. These
+    - An array of objects with column names and SQL expressions to calculate values
-    expressions will be evaluated for each row in the table, and can
+    - A single Arrow Field defining one column with its data type (column will be initialized with null values)
-    reference existing columns in the table.
+    - An array of Arrow Fields defining columns with their data types (columns will be initialized with null values)
+    - An Arrow Schema defining columns with their data types (columns will be initialized with null values)
 
 #### Returns
 
@@ -484,19 +485,7 @@ Modeled after ``VACUUM`` in PostgreSQL.
  - Prune: Removes old versions of the dataset
  - Index: Optimizes the indices, adding new data to existing indices
 
- Experimental API
+ The frequency an application should call optimize is based on the frequency of
- ----------------
-
- The optimization process is undergoing active development and may change.
- Our goal with these changes is to improve the performance of optimization and
- reduce the complexity.
-
- That being said, it is essential today to run optimize if you want the best
- performance.  It should be stable and safe to use in production, but it our
- hope that the API may be simplified (or not even need to be called) in the
- future.
-
- The frequency an application shoudl call optimize is based on the frequency of
  data modifications.  If data is frequently added, deleted, or updated then
  optimize should be run frequently.  A good rule of thumb is to run optimize if
  you have added or modified 100,000 or more records or run more than 20 data

docs/src/js/interfaces/DeleteResult.md

@@ -8,6 +8,14 @@
 
 ## Properties
 
+### numDeletedRows
+
+```ts
+numDeletedRows: number;
+```
+
+***
+
 ### version
 
 ```ts

docs/src/js/interfaces/OptimizeOptions.md

@@ -37,3 +37,12 @@ tbl.optimize({cleanupOlderThan: new Date()});
 ```ts
 deleteUnverified: boolean;
 ```
+
+Because they may be part of an in-progress transaction, files newer than
+7 days old are not deleted by default. If you are sure that there are no
+in-progress transactions, then you can set this to true to delete all
+files older than `cleanupOlderThan`.
+
+**WARNING**: This should only be set to true if you can guarantee that
+no other process is currently working on this dataset. Otherwise the
+dataset could be put into a corrupted state.

docs/src/js/namespaces/embedding/classes/EmbeddingFunction.md

@@ -52,7 +52,7 @@ new EmbeddingFunction<T, M>(): EmbeddingFunction<T, M>
 ### computeQueryEmbeddings()
 
 ```ts
-computeQueryEmbeddings(data): Promise<number[] | Float32Array | Float64Array>
+computeQueryEmbeddings(data): Promise<number[] | Uint8Array | Float32Array | Float64Array>
 ```
 
 Compute the embeddings for a single query
@@ -63,7 +63,7 @@ Compute the embeddings for a single query
 
 #### Returns
 
-`Promise`&lt;`number`[] \| `Float32Array` \| `Float64Array`&gt;
+`Promise`&lt;`number`[] \| `Uint8Array` \| `Float32Array` \| `Float64Array`&gt;
 
 ***
 

docs/src/js/namespaces/embedding/classes/TextEmbeddingFunction.md

@@ -37,7 +37,7 @@ new TextEmbeddingFunction<M>(): TextEmbeddingFunction<M>
 ### computeQueryEmbeddings()
 
 ```ts
-computeQueryEmbeddings(data): Promise<number[] | Float32Array | Float64Array>
+computeQueryEmbeddings(data): Promise<number[] | Uint8Array | Float32Array | Float64Array>
 ```
 
 Compute the embeddings for a single query
@@ -48,7 +48,7 @@ Compute the embeddings for a single query
 
 #### Returns
 
-`Promise`&lt;`number`[] \| `Float32Array` \| `Float64Array`&gt;
+`Promise`&lt;`number`[] \| `Uint8Array` \| `Float32Array` \| `Float64Array`&gt;
 
 #### Overrides
 

docs/src/js/type-aliases/IntoVector.md

@@ -7,5 +7,10 @@
 # Type Alias: IntoVector
 
 ```ts
-type IntoVector: Float32Array | Float64Array | number[] | Promise<Float32Array | Float64Array | number[]>;
+type IntoVector:
+  | Float32Array
+  | Float64Array
+  | Uint8Array
+  | number[]
+  | Promise<Float32Array | Float64Array | Uint8Array | number[]>;
 ```

docs/src/python/python.md

@@ -36,6 +36,20 @@ is also an [asynchronous API client](#connections-asynchronous).
 
 ::: lancedb.table.Tags
 
+## Expressions
+
+Type-safe expression builder for filters and projections. Use these instead
+of raw SQL strings with [where][lancedb.query.LanceQueryBuilder.where] and
+[select][lancedb.query.LanceQueryBuilder.select].
+
+::: lancedb.expr.Expr
+
+::: lancedb.expr.col
+
+::: lancedb.expr.lit
+
+::: lancedb.expr.func
+
 ## Querying (Synchronous)
 
 ::: lancedb.query.Query

java/README.md

@@ -1,4 +1,4 @@
-# LanceDB Java SDK
+# LanceDB Java Enterprise Client
 
 ## Configuration and Initialization
 

java/lancedb-core/pom.xml

@@ -8,7 +8,7 @@
     <parent>
       <groupId>com.lancedb</groupId>
       <artifactId>lancedb-parent</artifactId>
-      <version>0.27.0-beta.2</version>
+      <version>0.27.2-beta.1</version>
       <relativePath>../pom.xml</relativePath>
     </parent>
 
@@ -56,21 +56,21 @@
         <dependency>
             <groupId>org.apache.logging.log4j</groupId>
             <artifactId>log4j-slf4j2-impl</artifactId>
-            <version>2.24.3</version>
+            <version>2.25.3</version>
             <scope>test</scope>
         </dependency>
 
         <dependency>
             <groupId>org.apache.logging.log4j</groupId>
             <artifactId>log4j-core</artifactId>
-            <version>2.24.3</version>
+            <version>2.25.3</version>
             <scope>test</scope>
         </dependency>
 
         <dependency>
             <groupId>org.apache.logging.log4j</groupId>
             <artifactId>log4j-api</artifactId>
-            <version>2.24.3</version>
+            <version>2.25.3</version>
             <scope>test</scope>
         </dependency>
     </dependencies>

java/pom.xml

@@ -6,7 +6,7 @@
 
     <groupId>com.lancedb</groupId>
     <artifactId>lancedb-parent</artifactId>
-    <version>0.27.0-beta.2</version>
+    <version>0.27.2-beta.1</version>
     <packaging>pom</packaging>
     <name>${project.artifactId}</name>
     <description>LanceDB Java SDK Parent POM</description>
@@ -28,7 +28,7 @@
     <properties>
         <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
         <arrow.version>15.0.0</arrow.version>
-        <lance-core.version>3.1.0-beta.2</lance-core.version>
+        <lance-core.version>3.0.1</lance-core.version>
         <spotless.skip>false</spotless.skip>
         <spotless.version>2.30.0</spotless.version>
         <spotless.java.googlejavaformat.version>1.7</spotless.java.googlejavaformat.version>
@@ -111,7 +111,7 @@
             <plugin>
                 <groupId>org.apache.maven.plugins</groupId>
                 <artifactId>maven-source-plugin</artifactId>
-                <version>2.2.1</version>
+                <version>3.3.1</version>
                 <executions>
                     <execution>
                         <id>attach-sources</id>
@@ -124,7 +124,7 @@
             <plugin>
                 <groupId>org.apache.maven.plugins</groupId>
                 <artifactId>maven-javadoc-plugin</artifactId>
-                <version>2.9.1</version>
+                <version>3.11.2</version>
                 <executions>
                     <execution>
                         <id>attach-javadocs</id>
@@ -178,15 +178,15 @@
             <plugins>
                 <plugin>
                     <artifactId>maven-clean-plugin</artifactId>
-                    <version>3.1.0</version>
+                    <version>3.4.1</version>
                 </plugin>
                 <plugin>
                     <artifactId>maven-resources-plugin</artifactId>
-                    <version>3.0.2</version>
+                    <version>3.3.1</version>
                 </plugin>
                 <plugin>
                     <artifactId>maven-compiler-plugin</artifactId>
-                    <version>3.8.1</version>
+                    <version>3.14.0</version>
                     <configuration>
                         <compilerArgs>
                             <arg>-h</arg>
@@ -205,11 +205,11 @@
                 </plugin>
                 <plugin>
                     <artifactId>maven-jar-plugin</artifactId>
-                    <version>3.0.2</version>
+                    <version>3.4.2</version>
                 </plugin>
                 <plugin>
                     <artifactId>maven-install-plugin</artifactId>
-                    <version>2.5.2</version>
+                    <version>3.1.3</version>
                 </plugin>
                 <plugin>
                     <groupId>com.diffplug.spotless</groupId>
@@ -327,7 +327,7 @@
                     <plugin>
                         <groupId>org.apache.maven.plugins</groupId>
                         <artifactId>maven-gpg-plugin</artifactId>
-                        <version>1.5</version>
+                        <version>3.2.7</version>
                         <executions>
                             <execution>
                                 <id>sign-artifacts</id>

nodejs/Cargo.toml

@@ -1,7 +1,7 @@
 [package]
 name = "lancedb-nodejs"
 edition.workspace = true
-version = "0.27.0-beta.2"
+version = "0.27.2-beta.1"
 license.workspace = true
 description.workspace = true
 repository.workspace = true
@@ -15,6 +15,8 @@ crate-type = ["cdylib"]
 async-trait.workspace = true
 arrow-ipc.workspace = true
 arrow-array.workspace = true
+arrow-buffer = "57.2"
+half.workspace = true
 arrow-schema.workspace = true
 env_logger.workspace = true
 futures.workspace = true
@@ -25,12 +27,12 @@ napi = { version = "3.8.3", default-features = false, features = [
 ] }
 napi-derive = "3.5.2"
 # Prevent dynamic linking of lzma, which comes from datafusion
-lzma-sys = { version = "*", features = ["static"] }
+lzma-sys = { version = "0.1", features = ["static"] }
 log.workspace = true
 
-# Workaround for build failure until we can fix it.
+# Pin to resolve build failures; update periodically for security patches.
-aws-lc-sys = "=0.28.0"
+aws-lc-sys = "=0.38.0"
-aws-lc-rs = "=1.13.0"
+aws-lc-rs = "=1.16.1"
 
 [build-dependencies]
 napi-build = "2.3.1"

nodejs/__test__/arrow.test.ts

@@ -63,6 +63,7 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
       tableFromIPC,
       DataType,
       Dictionary,
+      Uint8: ArrowUint8,
       // biome-ignore lint/suspicious/noExplicitAny: <explanation>
     } = <any>arrow;
     type Schema = ApacheArrow["Schema"];
@@ -362,6 +363,38 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
         ).toEqual(new Float64().toString());
       });
 
+      it("will infer FixedSizeList<Float32> from Float32Array values", async function () {
+        const table = makeArrowTable([
+          { id: "a", vector: new Float32Array([0.1, 0.2, 0.3]) },
+          { id: "b", vector: new Float32Array([0.4, 0.5, 0.6]) },
+        ]);
+
+        expect(DataType.isFixedSizeList(table.getChild("vector")?.type)).toBe(
+          true,
+        );
+        const vectorType = table.getChild("vector")?.type;
+        expect(vectorType.listSize).toBe(3);
+        expect(vectorType.children[0].type.toString()).toEqual(
+          new Float32().toString(),
+        );
+      });
+
+      it("will infer FixedSizeList<Uint8> from Uint8Array values", async function () {
+        const table = makeArrowTable([
+          { id: "a", vector: new Uint8Array([1, 2, 3]) },
+          { id: "b", vector: new Uint8Array([4, 5, 6]) },
+        ]);
+
+        expect(DataType.isFixedSizeList(table.getChild("vector")?.type)).toBe(
+          true,
+        );
+        const vectorType = table.getChild("vector")?.type;
+        expect(vectorType.listSize).toBe(3);
+        expect(vectorType.children[0].type.toString()).toEqual(
+          new ArrowUint8().toString(),
+        );
+      });
+
       it("will use dictionary encoded strings if asked", async function () {
         const table = makeArrowTable([{ str: "hello" }]);
         expect(DataType.isUtf8(table.getChild("str")?.type)).toBe(true);

nodejs/__test__/table.test.ts

@@ -1259,6 +1259,98 @@ describe("schema evolution", function () {
     expect(await table.schema()).toEqual(expectedSchema);
   });
 
+  it("can add columns with schema for explicit data types", async function () {
+    const con = await connect(tmpDir.name);
+    const table = await con.createTable("vectors", [
+      { id: 1n, vector: [0.1, 0.2] },
+    ]);
+
+    // Define schema for new columns with explicit data types
+    // Note: All columns must be nullable when using addColumns with Schema
+    // because they are initially populated with null values
+    const newColumnsSchema = new Schema([
+      new Field("price", new Float64(), true),
+      new Field("category", new Utf8(), true),
+      new Field("rating", new Int32(), true),
+    ]);
+
+    const result = await table.addColumns(newColumnsSchema);
+    expect(result).toHaveProperty("version");
+    expect(result.version).toBe(2);
+
+    const expectedSchema = new Schema([
+      new Field("id", new Int64(), true),
+      new Field(
+        "vector",
+        new FixedSizeList(2, new Field("item", new Float32(), true)),
+        true,
+      ),
+      new Field("price", new Float64(), true),
+      new Field("category", new Utf8(), true),
+      new Field("rating", new Int32(), true),
+    ]);
+    expect(await table.schema()).toEqual(expectedSchema);
+
+    // Verify that new columns are populated with null values
+    const results = await table.query().toArray();
+    expect(results).toHaveLength(1);
+    expect(results[0].price).toBeNull();
+    expect(results[0].category).toBeNull();
+    expect(results[0].rating).toBeNull();
+  });
+
+  it("can add a single column using Field", async function () {
+    const con = await connect(tmpDir.name);
+    const table = await con.createTable("vectors", [
+      { id: 1n, vector: [0.1, 0.2] },
+    ]);
+
+    // Add a single field
+    const priceField = new Field("price", new Float64(), true);
+    const result = await table.addColumns(priceField);
+    expect(result).toHaveProperty("version");
+    expect(result.version).toBe(2);
+
+    const expectedSchema = new Schema([
+      new Field("id", new Int64(), 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(expectedSchema);
+  });
+
+  it("can add multiple columns using array of Fields", async function () {
+    const con = await connect(tmpDir.name);
+    const table = await con.createTable("vectors", [
+      { id: 1n, vector: [0.1, 0.2] },
+    ]);
+
+    // Add multiple fields as array
+    const fields = [
+      new Field("price", new Float64(), true),
+      new Field("category", new Utf8(), true),
+    ];
+    const result = await table.addColumns(fields);
+    expect(result).toHaveProperty("version");
+    expect(result.version).toBe(2);
+
+    const expectedSchema = new Schema([
+      new Field("id", new Int64(), true),
+      new Field(
+        "vector",
+        new FixedSizeList(2, new Field("item", new Float32(), true)),
+        true,
+      ),
+      new Field("price", new Float64(), true),
+      new Field("category", new Utf8(), true),
+    ]);
+    expect(await table.schema()).toEqual(expectedSchema);
+  });
+
   it("can alter the columns in the schema", async function () {
     const con = await connect(tmpDir.name);
     const schema = new Schema([
@@ -1697,6 +1789,65 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
       expect(results2[0].text).toBe(data[1].text);
     });
 
+    test("full text search fast search", async () => {
+      const db = await connect(tmpDir.name);
+      const data = [{ text: "hello world", vector: [0.1, 0.2, 0.3], id: 1 }];
+      const table = await db.createTable("test", data);
+      await table.createIndex("text", {
+        config: Index.fts(),
+      });
+
+      // Insert unindexed data after creating the index.
+      await table.add([{ text: "xyz", vector: [0.4, 0.5, 0.6], id: 2 }]);
+
+      const withFlatSearch = await table
+        .search("xyz", "fts")
+        .limit(10)
+        .toArray();
+      expect(withFlatSearch.length).toBeGreaterThan(0);
+
+      const fastSearchResults = await table
+        .search("xyz", "fts")
+        .fastSearch()
+        .limit(10)
+        .toArray();
+      expect(fastSearchResults.length).toBe(0);
+
+      const nearestToTextFastSearch = await table
+        .query()
+        .nearestToText("xyz")
+        .fastSearch()
+        .limit(10)
+        .toArray();
+      expect(nearestToTextFastSearch.length).toBe(0);
+
+      // fastSearch should be chainable with other methods.
+      const chainedFastSearch = await table
+        .search("xyz", "fts")
+        .fastSearch()
+        .select(["text"])
+        .limit(5)
+        .toArray();
+      expect(chainedFastSearch.length).toBe(0);
+
+      await table.optimize();
+
+      const indexedFastSearch = await table
+        .search("xyz", "fts")
+        .fastSearch()
+        .limit(10)
+        .toArray();
+      expect(indexedFastSearch.length).toBeGreaterThan(0);
+
+      const indexedNearestToTextFastSearch = await table
+        .query()
+        .nearestToText("xyz")
+        .fastSearch()
+        .limit(10)
+        .toArray();
+      expect(indexedNearestToTextFastSearch.length).toBeGreaterThan(0);
+    });
+
     test("prewarm full text search index", async () => {
       const db = await connect(tmpDir.name);
       const data = [
@@ -2145,3 +2296,36 @@ describe("when creating an empty table", () => {
     expect((actualSchema.fields[1].type as Float64).precision).toBe(2);
   });
 });
+
+// Ensure we can create float32 arrays without using Arrow
+// by utilizing native JS TypedArray support
+//
+// https://github.com/lancedb/lancedb/issues/3115
+describe("when creating a table with Float32Array vectors", () => {
+  let tmpDir: tmp.DirResult;
+  beforeEach(() => {
+    tmpDir = tmp.dirSync({ unsafeCleanup: true });
+  });
+  afterEach(() => {
+    tmpDir.removeCallback();
+  });
+
+  it("should persist Float32Array as FixedSizeList<Float32> in the LanceDB schema", async () => {
+    const db = await connect(tmpDir.name);
+    const table = await db.createTable("test", [
+      { id: "a", vector: new Float32Array([0.1, 0.2, 0.3]) },
+      { id: "b", vector: new Float32Array([0.4, 0.5, 0.6]) },
+    ]);
+
+    const schema = await table.schema();
+    const vectorField = schema.fields.find((f) => f.name === "vector");
+    expect(vectorField).toBeDefined();
+    expect(vectorField!.type).toBeInstanceOf(FixedSizeList);
+
+    const fsl = vectorField!.type as FixedSizeList;
+    expect(fsl.listSize).toBe(3);
+    expect(fsl.children[0].type.typeId).toBe(Type.Float);
+    // precision: HALF=0, SINGLE=1, DOUBLE=2
+    expect((fsl.children[0].type as Float32).precision).toBe(1);
+  });
+});

nodejs/__test__/vector_types.test.ts

@@ -0,0 +1,110 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+import * as tmp from "tmp";
+
+import { type Table, connect } from "../lancedb";
+import {
+  Field,
+  FixedSizeList,
+  Float32,
+  Int64,
+  Schema,
+  makeArrowTable,
+} from "../lancedb/arrow";
+
+describe("Vector query with different typed arrays", () => {
+  let tmpDir: tmp.DirResult;
+
+  afterEach(() => {
+    tmpDir?.removeCallback();
+  });
+
+  async function createFloat32Table(): Promise<Table> {
+    tmpDir = tmp.dirSync({ unsafeCleanup: true });
+    const db = await connect(tmpDir.name);
+    const schema = new Schema([
+      new Field("id", new Int64(), true),
+      new Field(
+        "vec",
+        new FixedSizeList(2, new Field("item", new Float32())),
+        true,
+      ),
+    ]);
+    const data = makeArrowTable(
+      [
+        { id: 1n, vec: [1.0, 0.0] },
+        { id: 2n, vec: [0.0, 1.0] },
+        { id: 3n, vec: [1.0, 1.0] },
+      ],
+      { schema },
+    );
+    return db.createTable("test_f32", data);
+  }
+
+  it("should search with Float32Array (baseline)", async () => {
+    const table = await createFloat32Table();
+    const results = await table
+      .query()
+      .nearestTo(new Float32Array([1.0, 0.0]))
+      .limit(1)
+      .toArray();
+
+    expect(results.length).toBe(1);
+    expect(Number(results[0].id)).toBe(1);
+  });
+
+  it("should search with number[] (backward compat)", async () => {
+    const table = await createFloat32Table();
+    const results = await table
+      .query()
+      .nearestTo([1.0, 0.0])
+      .limit(1)
+      .toArray();
+
+    expect(results.length).toBe(1);
+    expect(Number(results[0].id)).toBe(1);
+  });
+
+  it("should search with Float64Array via raw path", async () => {
+    const table = await createFloat32Table();
+    const results = await table
+      .query()
+      .nearestTo(new Float64Array([1.0, 0.0]))
+      .limit(1)
+      .toArray();
+
+    expect(results.length).toBe(1);
+    expect(Number(results[0].id)).toBe(1);
+  });
+
+  it("should add multiple query vectors with Float64Array", async () => {
+    const table = await createFloat32Table();
+    const results = await table
+      .query()
+      .nearestTo(new Float64Array([1.0, 0.0]))
+      .addQueryVector(new Float64Array([0.0, 1.0]))
+      .limit(2)
+      .toArray();
+
+    expect(results.length).toBeGreaterThanOrEqual(2);
+  });
+
+  // Float16Array is only available in Node 22+; not in TypeScript's standard lib yet
+  const float16ArrayCtor = (globalThis as unknown as Record<string, unknown>)
+    .Float16Array as (new (values: number[]) => unknown) | undefined;
+  const hasFloat16 = float16ArrayCtor !== undefined;
+  const f16it = hasFloat16 ? it : it.skip;
+
+  f16it("should search with Float16Array via raw path", async () => {
+    const table = await createFloat32Table();
+    const results = await table
+      .query()
+      .nearestTo(new float16ArrayCtor!([1.0, 0.0]) as Float32Array)
+      .limit(1)
+      .toArray();
+
+    expect(results.length).toBe(1);
+    expect(Number(results[0].id)).toBe(1);
+  });
+});

nodejs/examples/package-lock.json

@@ -30,12 +30,15 @@
         "x64",
         "arm64"
       ],
+      "dev": true,
       "license": "Apache-2.0",
+      "optional": true,
       "os": [
         "darwin",
         "linux",
         "win32"
       ],
+      "peer": true,
       "dependencies": {
         "reflect-metadata": "^0.2.2"
       },
@@ -91,14 +94,15 @@
       }
     },
     "node_modules/@babel/code-frame": {
-      "version": "7.26.2",
+      "version": "7.29.0",
-      "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.26.2.tgz",
+      "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.29.0.tgz",
-      "integrity": "sha512-RJlIHRueQgwWitWgF8OdFYGZX328Ax5BCemNGlqHfplnRT9ESi8JkFlvaVYbS+UubVY6dpv87Fs2u5M29iNFVQ==",
+      "integrity": "sha512-9NhCeYjq9+3uxgdtp20LSiJXJvN0FeCtNGpJxuMFZ1Kv3cWUNb6DOhJwUvcVCzKGR66cw4njwM6hrJLqgOwbcw==",
       "dev": true,
+      "license": "MIT",
       "dependencies": {
-        "@babel/helper-validator-identifier": "^7.25.9",
+        "@babel/helper-validator-identifier": "^7.28.5",
         "js-tokens": "^4.0.0",
-        "picocolors": "^1.0.0"
+        "picocolors": "^1.1.1"
       },
       "engines": {
         "node": ">=6.9.0"
@@ -233,19 +237,21 @@
       }
     },
     "node_modules/@babel/helper-string-parser": {
-      "version": "7.25.9",
+      "version": "7.27.1",
-      "resolved": "https://registry.npmjs.org/@babel/helper-string-parser/-/helper-string-parser-7.25.9.tgz",
+      "resolved": "https://registry.npmjs.org/@babel/helper-string-parser/-/helper-string-parser-7.27.1.tgz",
-      "integrity": "sha512-4A/SCr/2KLd5jrtOMFzaKjVtAei3+2r/NChoBNoZ3EyP/+GlhoaEGoWOZUmFmoITP7zOJyHIMm+DYRd8o3PvHA==",
+      "integrity": "sha512-qMlSxKbpRlAridDExk92nSobyDdpPijUq2DW6oDnUqd0iOGxmQjyqhMIihI9+zv4LPyZdRje2cavWPbCbWm3eA==",
       "dev": true,
+      "license": "MIT",
       "engines": {
         "node": ">=6.9.0"
       }
     },
     "node_modules/@babel/helper-validator-identifier": {
-      "version": "7.25.9",
+      "version": "7.28.5",
-      "resolved": "https://registry.npmjs.org/@babel/helper-validator-identifier/-/helper-validator-identifier-7.25.9.tgz",
+      "resolved": "https://registry.npmjs.org/@babel/helper-validator-identifier/-/helper-validator-identifier-7.28.5.tgz",
-      "integrity": "sha512-Ed61U6XJc3CVRfkERJWDz4dJwKe7iLmmJsbOGu9wSloNSFttHV0I8g6UAgb7qnK5ly5bGLPd4oXZlxCdANBOWQ==",
+      "integrity": "sha512-qSs4ifwzKJSV39ucNjsvc6WVHs6b7S03sOh2OcHF9UHfVPqWWALUsNUVzhSBiItjRZoLHx7nIarVjqKVusUZ1Q==",
       "dev": true,
+      "license": "MIT",
       "engines": {
         "node": ">=6.9.0"
       }
@@ -260,25 +266,27 @@
       }
     },
     "node_modules/@babel/helpers": {
-      "version": "7.26.0",
+      "version": "7.28.6",
-      "resolved": "https://registry.npmjs.org/@babel/helpers/-/helpers-7.26.0.tgz",
+      "resolved": "https://registry.npmjs.org/@babel/helpers/-/helpers-7.28.6.tgz",
-      "integrity": "sha512-tbhNuIxNcVb21pInl3ZSjksLCvgdZy9KwJ8brv993QtIVKJBBkYXz4q4ZbAv31GdnC+R90np23L5FbEBlthAEw==",
+      "integrity": "sha512-xOBvwq86HHdB7WUDTfKfT/Vuxh7gElQ+Sfti2Cy6yIWNW05P8iUslOVcZ4/sKbE+/jQaukQAdz/gf3724kYdqw==",
       "dev": true,
+      "license": "MIT",
       "dependencies": {
-        "@babel/template": "^7.25.9",
+        "@babel/template": "^7.28.6",
-        "@babel/types": "^7.26.0"
+        "@babel/types": "^7.28.6"
       },
       "engines": {
         "node": ">=6.9.0"
       }
     },
     "node_modules/@babel/parser": {
-      "version": "7.26.2",
+      "version": "7.29.0",
-      "resolved": "https://registry.npmjs.org/@babel/parser/-/parser-7.26.2.tgz",
+      "resolved": "https://registry.npmjs.org/@babel/parser/-/parser-7.29.0.tgz",
-      "integrity": "sha512-DWMCZH9WA4Maitz2q21SRKHo9QXZxkDsbNZoVD62gusNtNBBqDg9i7uOhASfTfIGNzW+O+r7+jAlM8dwphcJKQ==",
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       "version": "2.0.2",
       "resolved": "https://registry.npmjs.org/which/-/which-2.0.2.tgz",
       "integrity": "sha512-BLI3Tl1TW3Pvl70l3yq3Y64i+awpwXqsGBYWkkqMtnbXgrMD+yj7rhW0kuEDxzJaYXGjEW5ogapKNMEKNMjibA==",
+      "dev": true,
       "dependencies": {
         "isexe": "^2.0.0"
       },
@@ -4809,23 +4733,6 @@
         "url": "https://github.com/chalk/wrap-ansi?sponsor=1"
       }
     },
-    "node_modules/wrap-ansi-cjs": {
-      "name": "wrap-ansi",
-      "version": "7.0.0",
-      "resolved": "https://registry.npmjs.org/wrap-ansi/-/wrap-ansi-7.0.0.tgz",
-      "integrity": "sha512-YVGIj2kamLSTxw6NsZjoBxfSwsn0ycdesmc4p+Q21c5zPuZ1pl+NfxVdxPtdHvmNVOQ6XSYG4AUtyt/Fi7D16Q==",
-      "dependencies": {
-        "ansi-styles": "^4.0.0",
-        "string-width": "^4.1.0",
-        "strip-ansi": "^6.0.0"
-      },
-      "engines": {
-        "node": ">=10"
-      },
-      "funding": {
-        "url": "https://github.com/chalk/wrap-ansi?sponsor=1"
-      }
-    },
     "node_modules/wrappy": {
       "version": "1.0.2",
       "resolved": "https://registry.npmjs.org/wrappy/-/wrappy-1.0.2.tgz",

nodejs/lancedb/arrow.ts

@@ -20,6 +20,8 @@ import {
   Float32,
   Float64,
   Int,
+  Int8,
+  Int16,
   Int32,
   Int64,
   LargeBinary,
@@ -35,6 +37,8 @@ import {
   Timestamp,
   Type,
   Uint8,
+  Uint16,
+  Uint32,
   Utf8,
   Vector,
   makeVector as arrowMakeVector,
@@ -113,8 +117,9 @@ export type TableLike =
 export type IntoVector =
   | Float32Array
   | Float64Array
+  | Uint8Array
   | number[]
-  | Promise<Float32Array | Float64Array | number[]>;
+  | Promise<Float32Array | Float64Array | Uint8Array | number[]>;
 
 export type MultiVector = IntoVector[];
 
@@ -122,14 +127,48 @@ export function isMultiVector(value: unknown): value is MultiVector {
   return Array.isArray(value) && isIntoVector(value[0]);
 }
 
+// Float16Array is not in TypeScript's standard lib yet; access dynamically
+type Float16ArrayCtor = new (
+  ...args: unknown[]
+) => { buffer: ArrayBuffer; byteOffset: number; byteLength: number };
+const float16ArrayCtor = (globalThis as unknown as Record<string, unknown>)
+  .Float16Array as Float16ArrayCtor | undefined;
+
 export function isIntoVector(value: unknown): value is IntoVector {
   return (
     value instanceof Float32Array ||
     value instanceof Float64Array ||
+    value instanceof Uint8Array ||
+    (float16ArrayCtor !== undefined && value instanceof float16ArrayCtor) ||
     (Array.isArray(value) && !Array.isArray(value[0]))
   );
 }
 
+/**
+ * Extract the underlying byte buffer and data type from a typed array
+ * for passing to the Rust NAPI layer without precision loss.
+ */
+export function extractVectorBuffer(
+  vector: Float32Array | Float64Array | Uint8Array,
+): { data: Uint8Array; dtype: string } | null {
+  if (float16ArrayCtor !== undefined && vector instanceof float16ArrayCtor) {
+    return {
+      data: new Uint8Array(vector.buffer, vector.byteOffset, vector.byteLength),
+      dtype: "float16",
+    };
+  }
+  if (vector instanceof Float64Array) {
+    return {
+      data: new Uint8Array(vector.buffer, vector.byteOffset, vector.byteLength),
+      dtype: "float64",
+    };
+  }
+  if (vector instanceof Uint8Array && !(vector instanceof Float32Array)) {
+    return { data: vector, dtype: "uint8" };
+  }
+  return null;
+}
+
 export function isArrowTable(value: object): value is TableLike {
   if (value instanceof ArrowTable) return true;
   return "schema" in value && "batches" in value;
@@ -529,7 +568,8 @@ function isObject(value: unknown): value is Record<string, unknown> {
     !(value instanceof Date) &&
     !(value instanceof Set) &&
     !(value instanceof Map) &&
-    !(value instanceof Buffer)
+    !(value instanceof Buffer) &&
+    !ArrayBuffer.isView(value)
   );
 }
 
@@ -588,6 +628,13 @@ function inferType(
     return new Bool();
   } else if (value instanceof Buffer) {
     return new Binary();
+  } else if (ArrayBuffer.isView(value) && !(value instanceof DataView)) {
+    const info = typedArrayToArrowType(value);
+    if (info !== undefined) {
+      const child = new Field("item", info.elementType, true);
+      return new FixedSizeList(info.length, child);
+    }
+    return undefined;
   } else if (Array.isArray(value)) {
     if (value.length === 0) {
       return undefined; // Without any values we can't infer the type
@@ -746,6 +793,32 @@ function makeListVector(lists: unknown[][]): Vector<unknown> {
   return listBuilder.finish().toVector();
 }
 
+/**
+ * Map a JS TypedArray instance to the corresponding Arrow element DataType
+ * and its length. Returns undefined if the value is not a recognized TypedArray.
+ */
+function typedArrayToArrowType(
+  value: ArrayBufferView,
+): { elementType: DataType; length: number } | undefined {
+  if (value instanceof Float32Array)
+    return { elementType: new Float32(), length: value.length };
+  if (value instanceof Float64Array)
+    return { elementType: new Float64(), length: value.length };
+  if (value instanceof Uint8Array)
+    return { elementType: new Uint8(), length: value.length };
+  if (value instanceof Uint16Array)
+    return { elementType: new Uint16(), length: value.length };
+  if (value instanceof Uint32Array)
+    return { elementType: new Uint32(), length: value.length };
+  if (value instanceof Int8Array)
+    return { elementType: new Int8(), length: value.length };
+  if (value instanceof Int16Array)
+    return { elementType: new Int16(), length: value.length };
+  if (value instanceof Int32Array)
+    return { elementType: new Int32(), length: value.length };
+  return undefined;
+}
+
 /** Helper function to convert an Array of JS values to an Arrow Vector */
 function makeVector(
   values: unknown[],
@@ -814,6 +887,16 @@ function makeVector(
       "makeVector cannot infer the type if all values are null or undefined",
     );
   }
+  if (ArrayBuffer.isView(sampleValue) && !(sampleValue instanceof DataView)) {
+    const info = typedArrayToArrowType(sampleValue);
+    if (info !== undefined) {
+      const fslType = new FixedSizeList(
+        info.length,
+        new Field("item", info.elementType, true),
+      );
+      return vectorFromArray(values, fslType);
+    }
+  }
   if (Array.isArray(sampleValue)) {
     // Default Arrow inference doesn't handle list types
     return makeListVector(values as unknown[][]);

nodejs/lancedb/query.ts

@@ -5,6 +5,7 @@ import {
   Table as ArrowTable,
   type IntoVector,
   RecordBatch,
+  extractVectorBuffer,
   fromBufferToRecordBatch,
   fromRecordBatchToBuffer,
   tableFromIPC,
@@ -661,10 +662,8 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
       const res = (async () => {
         try {
           const v = await vector;
-          const arr = Float32Array.from(v);
-          //
           // biome-ignore lint/suspicious/noExplicitAny: we need to get the `inner`, but js has no package scoping
-          const value: any = this.addQueryVector(arr);
+          const value: any = this.addQueryVector(v);
           const inner = value.inner as
             | NativeVectorQuery
             | Promise<NativeVectorQuery>;
@@ -676,7 +675,12 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
       return new VectorQuery(res);
     } else {
       super.doCall((inner) => {
-        inner.addQueryVector(Float32Array.from(vector));
+        const raw = Array.isArray(vector) ? null : extractVectorBuffer(vector);
+        if (raw) {
+          inner.addQueryVectorRaw(raw.data, raw.dtype);
+        } else {
+          inner.addQueryVector(Float32Array.from(vector as number[]));
+        }
       });
       return this;
     }
@@ -765,14 +769,23 @@ export class Query extends StandardQueryBase<NativeQuery> {
    * a default `limit` of 10 will be used.  @see {@link Query#limit}
    */
   nearestTo(vector: IntoVector): VectorQuery {
+    const callNearestTo = (
+      inner: NativeQuery,
+      resolved: Float32Array | Float64Array | Uint8Array | number[],
+    ): NativeVectorQuery => {
+      const raw = Array.isArray(resolved)
+        ? null
+        : extractVectorBuffer(resolved);
+      if (raw) {
+        return inner.nearestToRaw(raw.data, raw.dtype);
+      }
+      return inner.nearestTo(Float32Array.from(resolved as number[]));
+    };
+
     if (this.inner instanceof Promise) {
       const nativeQuery = this.inner.then(async (inner) => {
-        if (vector instanceof Promise) {
+        const resolved = vector instanceof Promise ? await vector : vector;
-          const arr = await vector.then((v) => Float32Array.from(v));
+        return callNearestTo(inner, resolved);
-          return inner.nearestTo(arr);
-        } else {
-          return inner.nearestTo(Float32Array.from(vector));
-        }
       });
       return new VectorQuery(nativeQuery);
     }
@@ -780,10 +793,8 @@ export class Query extends StandardQueryBase<NativeQuery> {
       const res = (async () => {
         try {
           const v = await vector;
-          const arr = Float32Array.from(v);
-          //
           // biome-ignore lint/suspicious/noExplicitAny: we need to get the `inner`, but js has no package scoping
-          const value: any = this.nearestTo(arr);
+          const value: any = this.nearestTo(v);
           const inner = value.inner as
             | NativeVectorQuery
             | Promise<NativeVectorQuery>;
@@ -794,7 +805,7 @@ export class Query extends StandardQueryBase<NativeQuery> {
       })();
       return new VectorQuery(res);
     } else {
-      const vectorQuery = this.inner.nearestTo(Float32Array.from(vector));
+      const vectorQuery = callNearestTo(this.inner, vector);
       return new VectorQuery(vectorQuery);
     }
   }

nodejs/lancedb/table.ts

@@ -5,12 +5,15 @@ import {
   Table as ArrowTable,
   Data,
   DataType,
+  Field,
   IntoVector,
   MultiVector,
   Schema,
   dataTypeToJson,
   fromDataToBuffer,
+  fromTableToBuffer,
   isMultiVector,
+  makeEmptyTable,
   tableFromIPC,
 } from "./arrow";
 
@@ -84,6 +87,16 @@ export interface OptimizeOptions {
    * tbl.optimize({cleanupOlderThan: new Date()});
    */
   cleanupOlderThan: Date;
+  /**
+   * Because they may be part of an in-progress transaction, files newer than
+   * 7 days old are not deleted by default. If you are sure that there are no
+   * in-progress transactions, then you can set this to true to delete all
+   * files older than `cleanupOlderThan`.
+   *
+   * **WARNING**: This should only be set to true if you can guarantee that
+   * no other process is currently working on this dataset. Otherwise the
+   * dataset could be put into a corrupted state.
+   */
   deleteUnverified: boolean;
 }
 
@@ -381,15 +394,16 @@ export abstract class Table {
   abstract vectorSearch(vector: IntoVector | MultiVector): VectorQuery;
   /**
    * Add new columns with defined values.
-   * @param {AddColumnsSql[]} newColumnTransforms pairs of column names and
+   * @param {AddColumnsSql[] | Field | Field[] | Schema} newColumnTransforms Either:
-   * the SQL expression to use to calculate the value of the new column. These
+   *   - An array of objects with column names and SQL expressions to calculate values
-   * expressions will be evaluated for each row in the table, and can
+   *   - A single Arrow Field defining one column with its data type (column will be initialized with null values)
-   * reference existing columns in the table.
+   *   - An array of Arrow Fields defining columns with their data types (columns will be initialized with null values)
+   *   - An Arrow Schema defining columns with their data types (columns will be initialized with null values)
    * @returns {Promise<AddColumnsResult>} A promise that resolves to an object
    * containing the new version number of the table after adding the columns.
    */
   abstract addColumns(
-    newColumnTransforms: AddColumnsSql[],
+    newColumnTransforms: AddColumnsSql[] | Field | Field[] | Schema,
   ): Promise<AddColumnsResult>;
 
   /**
@@ -501,19 +515,7 @@ export abstract class Table {
    *  - Index: Optimizes the indices, adding new data to existing indices
    *
    *
-   *  Experimental API
+   *  The frequency an application should call optimize is based on the frequency of
-   *  ----------------
-   *
-   *  The optimization process is undergoing active development and may change.
-   *  Our goal with these changes is to improve the performance of optimization and
-   *  reduce the complexity.
-   *
-   *  That being said, it is essential today to run optimize if you want the best
-   *  performance.  It should be stable and safe to use in production, but it our
-   *  hope that the API may be simplified (or not even need to be called) in the
-   *  future.
-   *
-   *  The frequency an application shoudl call optimize is based on the frequency of
    *  data modifications.  If data is frequently added, deleted, or updated then
    *  optimize should be run frequently.  A good rule of thumb is to run optimize if
    *  you have added or modified 100,000 or more records or run more than 20 data
@@ -806,9 +808,40 @@ export class LocalTable extends Table {
   // TODO: Support BatchUDF
 
   async addColumns(
-    newColumnTransforms: AddColumnsSql[],
+    newColumnTransforms: AddColumnsSql[] | Field | Field[] | Schema,
   ): Promise<AddColumnsResult> {
-    return await this.inner.addColumns(newColumnTransforms);
+    // Handle single Field -> convert to array of Fields
+    if (newColumnTransforms instanceof Field) {
+      newColumnTransforms = [newColumnTransforms];
+    }
+
+    // Handle array of Fields -> convert to Schema
+    if (
+      Array.isArray(newColumnTransforms) &&
+      newColumnTransforms.length > 0 &&
+      newColumnTransforms[0] instanceof Field
+    ) {
+      const fields = newColumnTransforms as Field[];
+      newColumnTransforms = new Schema(fields);
+    }
+
+    // Handle Schema -> use schema-based approach
+    if (newColumnTransforms instanceof Schema) {
+      const schema = newColumnTransforms;
+      // Convert schema to buffer using Arrow IPC format
+      const emptyTable = makeEmptyTable(schema);
+      const schemaBuf = await fromTableToBuffer(emptyTable);
+      return await this.inner.addColumnsWithSchema(schemaBuf);
+    }
+
+    // Handle SQL expressions (existing functionality)
+    if (Array.isArray(newColumnTransforms)) {
+      return await this.inner.addColumns(
+        newColumnTransforms as AddColumnsSql[],
+      );
+    }
+
+    throw new Error("Invalid input type for addColumns");
   }
 
   async alterColumns(

nodejs/npm/darwin-arm64/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-arm64",
-	"version": "0.27.0-beta.2",
+	"version": "0.27.2-beta.1",
 	"os": ["darwin"],
 	"cpu": ["arm64"],
 	"main": "lancedb.darwin-arm64.node",

nodejs/npm/linux-arm64-gnu/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-gnu",
-	"version": "0.27.0-beta.2",
+	"version": "0.27.2-beta.1",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-gnu.node",

nodejs/npm/linux-arm64-musl/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-musl",
-	"version": "0.27.0-beta.2",
+	"version": "0.27.2-beta.1",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-musl.node",

nodejs/npm/linux-x64-gnu/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-gnu",
-	"version": "0.27.0-beta.2",
+	"version": "0.27.2-beta.1",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-gnu.node",

nodejs/npm/linux-x64-musl/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-musl",
-	"version": "0.27.0-beta.2",
+	"version": "0.27.2-beta.1",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-musl.node",

nodejs/npm/win32-arm64-msvc/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@lancedb/lancedb-win32-arm64-msvc",
-  "version": "0.27.0-beta.2",
+  "version": "0.27.2-beta.1",
   "os": [
     "win32"
   ],

nodejs/npm/win32-x64-msvc/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-win32-x64-msvc",
-	"version": "0.27.0-beta.2",
+	"version": "0.27.2-beta.1",
 	"os": ["win32"],
 	"cpu": ["x64"],
 	"main": "lancedb.win32-x64-msvc.node",

nodejs/package.json

@@ -11,7 +11,7 @@
     "ann"
   ],
   "private": false,
-  "version": "0.27.0-beta.2",
+  "version": "0.27.2-beta.1",
   "main": "dist/index.js",
   "exports": {
     ".": "./dist/index.js",

nodejs/src/connection.rs

@@ -8,10 +8,10 @@ use lancedb::database::{CreateTableMode, Database};
 use napi::bindgen_prelude::*;
 use napi_derive::*;
 
+use crate::ConnectionOptions;
 use crate::error::NapiErrorExt;
 use crate::header::JsHeaderProvider;
 use crate::table::Table;
-use crate::ConnectionOptions;
 use lancedb::connection::{ConnectBuilder, Connection as LanceDBConnection};
 
 use lancedb::ipc::{ipc_file_to_batches, ipc_file_to_schema};

nodejs/src/index.rs

@@ -3,12 +3,12 @@
 
 use std::sync::Mutex;
 
+use lancedb::index::Index as LanceDbIndex;
 use lancedb::index::scalar::{BTreeIndexBuilder, FtsIndexBuilder};
 use lancedb::index::vector::{
     IvfFlatIndexBuilder, IvfHnswPqIndexBuilder, IvfHnswSqIndexBuilder, IvfPqIndexBuilder,
     IvfRqIndexBuilder,
 };
-use lancedb::index::Index as LanceDbIndex;
 use napi_derive::napi;
 
 use crate::util::parse_distance_type;

nodejs/src/query.rs

@@ -3,6 +3,12 @@
 
 use std::sync::Arc;
 
+use arrow_array::{
+    Array, Float16Array as ArrowFloat16Array, Float32Array as ArrowFloat32Array,
+    Float64Array as ArrowFloat64Array, UInt8Array as ArrowUInt8Array,
+};
+use arrow_buffer::ScalarBuffer;
+use half::f16;
 use lancedb::index::scalar::{
     BooleanQuery, BoostQuery, FtsQuery, FullTextSearchQuery, MatchQuery, MultiMatchQuery, Occur,
     Operator, PhraseQuery,
@@ -17,13 +23,40 @@ use lancedb::query::VectorQuery as LanceDbVectorQuery;
 use napi::bindgen_prelude::*;
 use napi_derive::napi;
 
-use crate::error::convert_error;
 use crate::error::NapiErrorExt;
+use crate::error::convert_error;
 use crate::iterator::RecordBatchIterator;
 use crate::rerankers::RerankHybridCallbackArgs;
 use crate::rerankers::Reranker;
 use crate::util::{parse_distance_type, schema_to_buffer};
 
+fn bytes_to_arrow_array(data: Uint8Array, dtype: String) -> napi::Result<Arc<dyn Array>> {
+    let buf = arrow_buffer::Buffer::from(data.to_vec());
+    let num_bytes = buf.len();
+    match dtype.as_str() {
+        "float16" => {
+            let scalar_buf = ScalarBuffer::<f16>::new(buf, 0, num_bytes / 2);
+            Ok(Arc::new(ArrowFloat16Array::new(scalar_buf, None)))
+        }
+        "float32" => {
+            let scalar_buf = ScalarBuffer::<f32>::new(buf, 0, num_bytes / 4);
+            Ok(Arc::new(ArrowFloat32Array::new(scalar_buf, None)))
+        }
+        "float64" => {
+            let scalar_buf = ScalarBuffer::<f64>::new(buf, 0, num_bytes / 8);
+            Ok(Arc::new(ArrowFloat64Array::new(scalar_buf, None)))
+        }
+        "uint8" => {
+            let scalar_buf = ScalarBuffer::<u8>::new(buf, 0, num_bytes);
+            Ok(Arc::new(ArrowUInt8Array::new(scalar_buf, None)))
+        }
+        _ => Err(napi::Error::from_reason(format!(
+            "Unsupported vector dtype: {}. Expected one of: float16, float32, float64, uint8",
+            dtype
+        ))),
+    }
+}
+
 #[napi]
 pub struct Query {
     inner: LanceDbQuery,
@@ -78,6 +111,13 @@ impl Query {
         Ok(VectorQuery { inner })
     }
 
+    #[napi]
+    pub fn nearest_to_raw(&mut self, data: Uint8Array, dtype: String) -> Result<VectorQuery> {
+        let array = bytes_to_arrow_array(data, dtype)?;
+        let inner = self.inner.clone().nearest_to(array).default_error()?;
+        Ok(VectorQuery { inner })
+    }
+
     #[napi]
     pub fn fast_search(&mut self) {
         self.inner = self.inner.clone().fast_search();
@@ -163,6 +203,13 @@ impl VectorQuery {
         Ok(())
     }
 
+    #[napi]
+    pub fn add_query_vector_raw(&mut self, data: Uint8Array, dtype: String) -> Result<()> {
+        let array = bytes_to_arrow_array(data, dtype)?;
+        self.inner = self.inner.clone().add_query_vector(array).default_error()?;
+        Ok(())
+    }
+
     #[napi]
     pub fn distance_type(&mut self, distance_type: String) -> napi::Result<()> {
         let distance_type = parse_distance_type(distance_type)?;
@@ -551,15 +598,12 @@ fn parse_fts_query(query: Object) -> napi::Result<FullTextSearchQuery> {
             }
         };
         let mut query = FullTextSearchQuery::new_query(query);
-        if let Some(cols) = columns {
+        if let Some(cols) = columns
-            if !cols.is_empty() {
+            && !cols.is_empty()
-                query = query.with_columns(&cols).map_err(|e| {
+        {
-                    napi::Error::from_reason(format!(
+            query = query.with_columns(&cols).map_err(|e| {
-                        "Failed to set full text search columns: {}",
+                napi::Error::from_reason(format!("Failed to set full text search columns: {}", e))
-                        e
+            })?;
-                    ))
-                })?;
-            }
         }
         Ok(query)
     } else {

nodejs/src/session.rs

@@ -95,7 +95,7 @@ impl napi::bindgen_prelude::FromNapiValue for Session {
         napi_val: napi::sys::napi_value,
     ) -> napi::Result<Self> {
         let object: napi::bindgen_prelude::ClassInstance<Self> =
-            napi::bindgen_prelude::ClassInstance::from_napi_value(env, napi_val)?;
+            unsafe { napi::bindgen_prelude::ClassInstance::from_napi_value(env, napi_val)? };
         Ok((*object).clone())
     }
 }

nodejs/src/table.rs

@@ -3,7 +3,7 @@
 
 use std::collections::HashMap;
 
-use lancedb::ipc::ipc_file_to_batches;
+use lancedb::ipc::{ipc_file_to_batches, ipc_file_to_schema};
 use lancedb::table::{
     AddDataMode, ColumnAlteration as LanceColumnAlteration, Duration, NewColumnTransform,
     OptimizeAction, OptimizeOptions, Table as LanceDbTable,
@@ -279,6 +279,23 @@ impl Table {
         Ok(res.into())
     }
 
+    #[napi(catch_unwind)]
+    pub async fn add_columns_with_schema(
+        &self,
+        schema_buf: Buffer,
+    ) -> napi::Result<AddColumnsResult> {
+        let schema = ipc_file_to_schema(schema_buf.to_vec())
+            .map_err(|e| napi::Error::from_reason(format!("Failed to read IPC schema: {}", e)))?;
+
+        let transforms = NewColumnTransform::AllNulls(schema);
+        let res = self
+            .inner_ref()?
+            .add_columns(transforms, None)
+            .await
+            .default_error()?;
+        Ok(res.into())
+    }
+
     #[napi(catch_unwind)]
     pub async fn alter_columns(
         &self,
@@ -753,12 +770,14 @@ impl From<lancedb::table::AddResult> for AddResult {
 
 #[napi(object)]
 pub struct DeleteResult {
+    pub num_deleted_rows: i64,
     pub version: i64,
 }
 
 impl From<lancedb::table::DeleteResult> for DeleteResult {
     fn from(value: lancedb::table::DeleteResult) -> Self {
         Self {
+            num_deleted_rows: value.num_deleted_rows as i64,
             version: value.version as i64,
         }
     }

python/.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.30.0-beta.3"
+current_version = "0.30.2"
 parse = """(?x)
     (?P<major>0|[1-9]\\d*)\\.
     (?P<minor>0|[1-9]\\d*)\\.

python/.gitignore

@@ -1,3 +1,5 @@
 # Test data created by some example tests
 data/
 _lancedb.pyd
+# macOS debug symbols bundle generated during build
+*.dSYM/

python/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "lancedb-python"
-version = "0.30.0-beta.3"
+version = "0.30.2"
 edition.workspace = true
 description = "Python bindings for LanceDB"
 license.workspace = true
@@ -16,11 +16,14 @@ crate-type = ["cdylib"]
 [dependencies]
 arrow = { version = "57.2", features = ["pyarrow"] }
 async-trait = "0.1"
+bytes = "1"
 lancedb = { path = "../rust/lancedb", default-features = false }
 lance-core.workspace = true
 lance-namespace.workspace = true
+lance-namespace-impls.workspace = true
 lance-io.workspace = true
 env_logger.workspace = true
+log.workspace = true
 pyo3 = { version = "0.26", features = ["extension-module", "abi3-py39"] }
 pyo3-async-runtimes = { version = "0.26", features = [
     "attributes",
@@ -28,6 +31,8 @@ pyo3-async-runtimes = { version = "0.26", features = [
 ] }
 pin-project = "1.1.5"
 futures.workspace = true
+serde = "1"
+serde_json = "1"
 snafu.workspace = true
 tokio = { version = "1.40", features = ["sync"] }
 

python/README.md

@@ -1,4 +1,4 @@
-# LanceDB
+# LanceDB Python SDK
 
 A Python library for [LanceDB](https://github.com/lancedb/lancedb).
 

python/pyproject.toml

@@ -3,10 +3,10 @@ name = "lancedb"
 # version in Cargo.toml
 dynamic = ["version"]
 dependencies = [
-    "deprecation",
+    "deprecation>=2.1.0",
-    "numpy",
+    "numpy>=1.24.0",
     "overrides>=0.7; python_version<'3.12'",
-    "packaging",
+    "packaging>=23.0",
     "pyarrow>=16",
     "pydantic>=1.10",
     "tqdm>=4.27.0",
@@ -45,51 +45,51 @@ repository = "https://github.com/lancedb/lancedb"
 
 [project.optional-dependencies]
 pylance = [
-    "pylance>=1.0.0b14",
+    "pylance>=4.0.0b7",
 ]
 tests = [
-    "aiohttp",
+    "aiohttp>=3.9.0",
-    "boto3",
+    "boto3>=1.28.57",
     "pandas>=1.4",
-    "pytest",
+    "pytest>=7.0",
-    "pytest-mock",
+    "pytest-mock>=3.10",
-    "pytest-asyncio",
+    "pytest-asyncio>=0.21",
-    "duckdb",
+    "duckdb>=0.9.0",
-    "pytz",
+    "pytz>=2023.3",
     "polars>=0.19, <=1.3.0",
-    "tantivy",
+    "tantivy>=0.20.0",
-    "pyarrow-stubs",
+    "pyarrow-stubs>=16.0",
-    "pylance>=1.0.0b14,<3.0.0",
+    "pylance>=4.0.0b7",
-    "requests",
+    "requests>=2.31.0",
-    "datafusion<52",
+    "datafusion>=52,<53",
 ]
 dev = [
-    "ruff",
+    "ruff>=0.3.0",
-    "pre-commit",
+    "pre-commit>=3.5.0",
-    "pyright",
+    "pyright>=1.1.350",
     'typing-extensions>=4.0.0; python_version < "3.11"',
 ]
 docs = ["mkdocs", "mkdocs-jupyter", "mkdocs-material", "mkdocstrings-python"]
-clip = ["torch", "pillow", "open-clip-torch"]
+clip = ["torch", "pillow>=12.1.1", "open-clip-torch"]
-siglip = ["torch", "pillow", "transformers>=4.41.0","sentencepiece"]
+siglip = ["torch", "pillow>=12.1.1", "transformers>=4.41.0","sentencepiece"]
 embeddings = [
     "requests>=2.31.0",
     "openai>=1.6.1",
-    "sentence-transformers",
+    "sentence-transformers>=2.2.0",
-    "torch",
+    "torch>=2.0.0",
-    "pillow",
+    "pillow>=12.1.1",
-    "open-clip-torch",
+    "open-clip-torch>=2.20.0",
-    "cohere",
+    "cohere>=4.0",
     "colpali-engine>=0.3.10",
-    "huggingface_hub",
+    "huggingface_hub>=0.19.0",
-    "InstructorEmbedding",
+    "InstructorEmbedding>=1.0.1",
-    "google.generativeai",
+    "google.generativeai>=0.3.0",
     "boto3>=1.28.57",
-    "awscli>=1.29.57",
+    "awscli>=1.44.38",
     "botocore>=1.31.57",
     'ibm-watsonx-ai>=1.1.2; python_version >= "3.10"',
     "ollama>=0.3.0",
-    "sentencepiece"
+    "sentencepiece>=0.1.99"
 ]
 azure = ["adlfs>=2024.2.0"]
 

python/python/lancedb/__init__.py

@@ -18,6 +18,7 @@ from .db import AsyncConnection, DBConnection, LanceDBConnection
 from .io import StorageOptionsProvider
 from .remote import ClientConfig
 from .remote.db import RemoteDBConnection
+from .expr import Expr, col, lit, func
 from .schema import vector
 from .table import AsyncTable, Table
 from ._lancedb import Session
@@ -271,6 +272,10 @@ __all__ = [
     "AsyncConnection",
     "AsyncLanceNamespaceDBConnection",
     "AsyncTable",
+    "col",
+    "Expr",
+    "func",
+    "lit",
     "URI",
     "sanitize_uri",
     "vector",

python/python/lancedb/_lancedb.pyi

@@ -27,6 +27,32 @@ from .remote import ClientConfig
 IvfHnswPq: type[HnswPq] = HnswPq
 IvfHnswSq: type[HnswSq] = HnswSq
 
+class PyExpr:
+    """A type-safe DataFusion expression node (Rust-side handle)."""
+
+    def eq(self, other: "PyExpr") -> "PyExpr": ...
+    def ne(self, other: "PyExpr") -> "PyExpr": ...
+    def lt(self, other: "PyExpr") -> "PyExpr": ...
+    def lte(self, other: "PyExpr") -> "PyExpr": ...
+    def gt(self, other: "PyExpr") -> "PyExpr": ...
+    def gte(self, other: "PyExpr") -> "PyExpr": ...
+    def and_(self, other: "PyExpr") -> "PyExpr": ...
+    def or_(self, other: "PyExpr") -> "PyExpr": ...
+    def not_(self) -> "PyExpr": ...
+    def add(self, other: "PyExpr") -> "PyExpr": ...
+    def sub(self, other: "PyExpr") -> "PyExpr": ...
+    def mul(self, other: "PyExpr") -> "PyExpr": ...
+    def div(self, other: "PyExpr") -> "PyExpr": ...
+    def lower(self) -> "PyExpr": ...
+    def upper(self) -> "PyExpr": ...
+    def contains(self, substr: "PyExpr") -> "PyExpr": ...
+    def cast(self, data_type: pa.DataType) -> "PyExpr": ...
+    def to_sql(self) -> str: ...
+
+def expr_col(name: str) -> PyExpr: ...
+def expr_lit(value: Union[bool, int, float, str]) -> PyExpr: ...
+def expr_func(name: str, args: List[PyExpr]) -> PyExpr: ...
+
 class Session:
     def __init__(
         self,
@@ -135,7 +161,10 @@ class Table:
     def close(self) -> None: ...
     async def schema(self) -> pa.Schema: ...
     async def add(
-        self, data: pa.RecordBatchReader, mode: Literal["append", "overwrite"]
+        self,
+        data: pa.RecordBatchReader,
+        mode: Literal["append", "overwrite"],
+        progress: Optional[Any] = None,
     ) -> AddResult: ...
     async def update(
         self, updates: Dict[str, str], where: Optional[str]
@@ -166,6 +195,8 @@ class Table:
     async def checkout(self, version: Union[int, str]): ...
     async def checkout_latest(self): ...
     async def restore(self, version: Optional[Union[int, str]] = None): ...
+    async def prewarm_index(self, index_name: str) -> None: ...
+    async def prewarm_data(self, columns: Optional[List[str]] = None) -> None: ...
     async def list_indices(self) -> list[IndexConfig]: ...
     async def delete(self, filter: str) -> DeleteResult: ...
     async def add_columns(self, columns: list[tuple[str, str]]) -> AddColumnsResult: ...
@@ -220,7 +251,9 @@ class RecordBatchStream:
 
 class Query:
     def where(self, filter: str): ...
-    def select(self, columns: Tuple[str, str]): ...
+    def where_expr(self, expr: PyExpr): ...
+    def select(self, columns: List[Tuple[str, str]]): ...
+    def select_expr(self, columns: List[Tuple[str, PyExpr]]): ...
     def select_columns(self, columns: List[str]): ...
     def limit(self, limit: int): ...
     def offset(self, offset: int): ...
@@ -246,7 +279,9 @@ class TakeQuery:
 
 class FTSQuery:
     def where(self, filter: str): ...
-    def select(self, columns: List[str]): ...
+    def where_expr(self, expr: PyExpr): ...
+    def select(self, columns: List[Tuple[str, str]]): ...
+    def select_expr(self, columns: List[Tuple[str, PyExpr]]): ...
     def limit(self, limit: int): ...
     def offset(self, offset: int): ...
     def fast_search(self): ...
@@ -265,7 +300,9 @@ class VectorQuery:
     async def output_schema(self) -> pa.Schema: ...
     async def execute(self) -> RecordBatchStream: ...
     def where(self, filter: str): ...
-    def select(self, columns: List[str]): ...
+    def where_expr(self, expr: PyExpr): ...
+    def select(self, columns: List[Tuple[str, str]]): ...
+    def select_expr(self, columns: List[Tuple[str, PyExpr]]): ...
     def select_with_projection(self, columns: Tuple[str, str]): ...
     def limit(self, limit: int): ...
     def offset(self, offset: int): ...
@@ -282,7 +319,9 @@ class VectorQuery:
 
 class HybridQuery:
     def where(self, filter: str): ...
-    def select(self, columns: List[str]): ...
+    def where_expr(self, expr: PyExpr): ...
+    def select(self, columns: List[Tuple[str, str]]): ...
+    def select_expr(self, columns: List[Tuple[str, PyExpr]]): ...
     def limit(self, limit: int): ...
     def offset(self, offset: int): ...
     def fast_search(self): ...

python/python/lancedb/db.py

@@ -8,7 +8,7 @@ from abc import abstractmethod
 from datetime import timedelta
 from pathlib import Path
 import sys
-from typing import TYPE_CHECKING, Dict, Iterable, List, Literal, Optional, Union
+from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Literal, Optional, Union
 
 if sys.version_info >= (3, 12):
     from typing import override
@@ -1541,6 +1541,8 @@ class AsyncConnection(object):
         storage_options_provider: Optional["StorageOptionsProvider"] = None,
         index_cache_size: Optional[int] = None,
         location: Optional[str] = None,
+        namespace_client: Optional[Any] = None,
+        managed_versioning: Optional[bool] = None,
     ) -> AsyncTable:
         """Open a Lance Table in the database.
 
@@ -1573,6 +1575,9 @@ class AsyncConnection(object):
             The explicit location (URI) of the table. If provided, the table will be
             opened from this location instead of deriving it from the database URI
             and table name.
+        managed_versioning: bool, optional
+            Whether managed versioning is enabled for this table. If provided,
+            avoids a redundant describe_table call when namespace_client is set.
 
         Returns
         -------
@@ -1587,6 +1592,8 @@ class AsyncConnection(object):
             storage_options_provider=storage_options_provider,
             index_cache_size=index_cache_size,
             location=location,
+            namespace_client=namespace_client,
+            managed_versioning=managed_versioning,
         )
         return AsyncTable(table)
 

python/python/lancedb/embeddings/utils.py

@@ -10,6 +10,7 @@ import sys
 import threading
 import time
 import urllib.error
+import urllib.request
 import weakref
 import logging
 from functools import wraps

python/python/lancedb/expr.py

@@ -0,0 +1,298 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+"""Type-safe expression builder for filters and projections.
+
+Instead of writing raw SQL strings you can build expressions with Python
+operators::
+
+    from lancedb.expr import col, lit
+
+    # filter: age > 18 AND status = 'active'
+    filt = (col("age") > lit(18)) & (col("status") == lit("active"))
+
+    # projection: compute a derived column
+    proj = {"score": col("raw_score") * lit(1.5)}
+
+    table.search().where(filt).select(proj).to_list()
+"""
+
+from __future__ import annotations
+
+from typing import Union
+
+import pyarrow as pa
+
+from lancedb._lancedb import PyExpr, expr_col, expr_lit, expr_func
+
+__all__ = ["Expr", "col", "lit", "func"]
+
+_STR_TO_PA_TYPE: dict = {
+    "bool": pa.bool_(),
+    "boolean": pa.bool_(),
+    "int8": pa.int8(),
+    "int16": pa.int16(),
+    "int32": pa.int32(),
+    "int64": pa.int64(),
+    "uint8": pa.uint8(),
+    "uint16": pa.uint16(),
+    "uint32": pa.uint32(),
+    "uint64": pa.uint64(),
+    "float16": pa.float16(),
+    "float32": pa.float32(),
+    "float": pa.float32(),
+    "float64": pa.float64(),
+    "double": pa.float64(),
+    "string": pa.string(),
+    "utf8": pa.string(),
+    "str": pa.string(),
+    "large_string": pa.large_utf8(),
+    "large_utf8": pa.large_utf8(),
+    "date32": pa.date32(),
+    "date": pa.date32(),
+    "date64": pa.date64(),
+}
+
+
+def _coerce(value: "ExprLike") -> "Expr":
+    """Return *value* as an :class:`Expr`, wrapping plain Python values via
+    :func:`lit` if needed."""
+    if isinstance(value, Expr):
+        return value
+    return lit(value)
+
+
+# Type alias used in annotations.
+ExprLike = Union["Expr", bool, int, float, str]
+
+
+class Expr:
+    """A type-safe expression node.
+
+    Construct instances with :func:`col` and :func:`lit`, then combine them
+    using Python operators or the named methods below.
+
+    Examples
+    --------
+    >>> from lancedb.expr import col, lit
+    >>> filt = (col("age") > lit(18)) & (col("name").lower() == lit("alice"))
+    >>> proj = {"double": col("x") * lit(2)}
+    """
+
+    # Make Expr unhashable so that == returns an Expr rather than being used
+    # for dict keys / set membership.
+    __hash__ = None  # type: ignore[assignment]
+
+    def __init__(self, inner: PyExpr) -> None:
+        self._inner = inner
+
+    # ── comparisons ──────────────────────────────────────────────────────────
+
+    def __eq__(self, other: ExprLike) -> "Expr":  # type: ignore[override]
+        """Equal to (``col("x") == 1``)."""
+        return Expr(self._inner.eq(_coerce(other)._inner))
+
+    def __ne__(self, other: ExprLike) -> "Expr":  # type: ignore[override]
+        """Not equal to (``col("x") != 1``)."""
+        return Expr(self._inner.ne(_coerce(other)._inner))
+
+    def __lt__(self, other: ExprLike) -> "Expr":
+        """Less than (``col("x") < 1``)."""
+        return Expr(self._inner.lt(_coerce(other)._inner))
+
+    def __le__(self, other: ExprLike) -> "Expr":
+        """Less than or equal to (``col("x") <= 1``)."""
+        return Expr(self._inner.lte(_coerce(other)._inner))
+
+    def __gt__(self, other: ExprLike) -> "Expr":
+        """Greater than (``col("x") > 1``)."""
+        return Expr(self._inner.gt(_coerce(other)._inner))
+
+    def __ge__(self, other: ExprLike) -> "Expr":
+        """Greater than or equal to (``col("x") >= 1``)."""
+        return Expr(self._inner.gte(_coerce(other)._inner))
+
+    # ── logical ──────────────────────────────────────────────────────────────
+
+    def __and__(self, other: "Expr") -> "Expr":
+        """Logical AND (``expr_a & expr_b``)."""
+        return Expr(self._inner.and_(_coerce(other)._inner))
+
+    def __or__(self, other: "Expr") -> "Expr":
+        """Logical OR (``expr_a | expr_b``)."""
+        return Expr(self._inner.or_(_coerce(other)._inner))
+
+    def __invert__(self) -> "Expr":
+        """Logical NOT (``~expr``)."""
+        return Expr(self._inner.not_())
+
+    # ── arithmetic ───────────────────────────────────────────────────────────
+
+    def __add__(self, other: ExprLike) -> "Expr":
+        """Add (``col("x") + 1``)."""
+        return Expr(self._inner.add(_coerce(other)._inner))
+
+    def __radd__(self, other: ExprLike) -> "Expr":
+        """Right-hand add (``1 + col("x")``)."""
+        return Expr(_coerce(other)._inner.add(self._inner))
+
+    def __sub__(self, other: ExprLike) -> "Expr":
+        """Subtract (``col("x") - 1``)."""
+        return Expr(self._inner.sub(_coerce(other)._inner))
+
+    def __rsub__(self, other: ExprLike) -> "Expr":
+        """Right-hand subtract (``1 - col("x")``)."""
+        return Expr(_coerce(other)._inner.sub(self._inner))
+
+    def __mul__(self, other: ExprLike) -> "Expr":
+        """Multiply (``col("x") * 2``)."""
+        return Expr(self._inner.mul(_coerce(other)._inner))
+
+    def __rmul__(self, other: ExprLike) -> "Expr":
+        """Right-hand multiply (``2 * col("x")``)."""
+        return Expr(_coerce(other)._inner.mul(self._inner))
+
+    def __truediv__(self, other: ExprLike) -> "Expr":
+        """Divide (``col("x") / 2``)."""
+        return Expr(self._inner.div(_coerce(other)._inner))
+
+    def __rtruediv__(self, other: ExprLike) -> "Expr":
+        """Right-hand divide (``1 / col("x")``)."""
+        return Expr(_coerce(other)._inner.div(self._inner))
+
+    # ── string methods ───────────────────────────────────────────────────────
+
+    def lower(self) -> "Expr":
+        """Convert string column values to lowercase."""
+        return Expr(self._inner.lower())
+
+    def upper(self) -> "Expr":
+        """Convert string column values to uppercase."""
+        return Expr(self._inner.upper())
+
+    def contains(self, substr: "ExprLike") -> "Expr":
+        """Return True where the string contains *substr*."""
+        return Expr(self._inner.contains(_coerce(substr)._inner))
+
+    # ── type cast ────────────────────────────────────────────────────────────
+
+    def cast(self, data_type: Union[str, "pa.DataType"]) -> "Expr":
+        """Cast values to *data_type*.
+
+        Parameters
+        ----------
+        data_type:
+            A PyArrow ``DataType`` (e.g. ``pa.int32()``) or one of the type
+            name strings: ``"bool"``, ``"int8"``, ``"int16"``, ``"int32"``,
+            ``"int64"``, ``"uint8"``–``"uint64"``, ``"float32"``,
+            ``"float64"``, ``"string"``, ``"date32"``, ``"date64"``.
+        """
+        if isinstance(data_type, str):
+            try:
+                data_type = _STR_TO_PA_TYPE[data_type]
+            except KeyError:
+                raise ValueError(
+                    f"unsupported data type: '{data_type}'. Supported: "
+                    f"{', '.join(_STR_TO_PA_TYPE)}"
+                )
+        return Expr(self._inner.cast(data_type))
+
+    # ── named comparison helpers (alternative to operators) ──────────────────
+
+    def eq(self, other: ExprLike) -> "Expr":
+        """Equal to."""
+        return self.__eq__(other)
+
+    def ne(self, other: ExprLike) -> "Expr":
+        """Not equal to."""
+        return self.__ne__(other)
+
+    def lt(self, other: ExprLike) -> "Expr":
+        """Less than."""
+        return self.__lt__(other)
+
+    def lte(self, other: ExprLike) -> "Expr":
+        """Less than or equal to."""
+        return self.__le__(other)
+
+    def gt(self, other: ExprLike) -> "Expr":
+        """Greater than."""
+        return self.__gt__(other)
+
+    def gte(self, other: ExprLike) -> "Expr":
+        """Greater than or equal to."""
+        return self.__ge__(other)
+
+    def and_(self, other: "Expr") -> "Expr":
+        """Logical AND."""
+        return self.__and__(other)
+
+    def or_(self, other: "Expr") -> "Expr":
+        """Logical OR."""
+        return self.__or__(other)
+
+    # ── utilities ────────────────────────────────────────────────────────────
+
+    def to_sql(self) -> str:
+        """Render the expression as a SQL string (useful for debugging)."""
+        return self._inner.to_sql()
+
+    def __repr__(self) -> str:
+        return f"Expr({self._inner.to_sql()})"
+
+
+# ── free functions ────────────────────────────────────────────────────────────
+
+
+def col(name: str) -> Expr:
+    """Reference a table column by name.
+
+    Parameters
+    ----------
+    name:
+        The column name.
+
+    Examples
+    --------
+    >>> from lancedb.expr import col, lit
+    >>> col("age") > lit(18)
+    Expr((age > 18))
+    """
+    return Expr(expr_col(name))
+
+
+def lit(value: Union[bool, int, float, str]) -> Expr:
+    """Create a literal (constant) value expression.
+
+    Parameters
+    ----------
+    value:
+        A Python ``bool``, ``int``, ``float``, or ``str``.
+
+    Examples
+    --------
+    >>> from lancedb.expr import col, lit
+    >>> col("price") * lit(1.1)
+    Expr((price * 1.1))
+    """
+    return Expr(expr_lit(value))
+
+
+def func(name: str, *args: ExprLike) -> Expr:
+    """Call an arbitrary SQL function by name.
+
+    Parameters
+    ----------
+    name:
+        The SQL function name (e.g. ``"lower"``, ``"upper"``).
+    *args:
+        The function arguments as :class:`Expr` or plain Python literals.
+
+    Examples
+    --------
+    >>> from lancedb.expr import col, func
+    >>> func("lower", col("name"))
+    Expr(lower(name))
+    """
+    inner_args = [_coerce(a)._inner for a in args]
+    return Expr(expr_func(name, inner_args))

python/python/lancedb/namespace.py

@@ -12,7 +12,7 @@ from __future__ import annotations
 
 import asyncio
 import sys
-from typing import Dict, Iterable, List, Optional, Union
+from typing import Any, Dict, Iterable, List, Optional, Union
 
 if sys.version_info >= (3, 12):
     from typing import override
@@ -240,7 +240,7 @@ class LanceNamespaceDBConnection(DBConnection):
         session : Optional[Session]
             A session to use for this connection
         """
-        self._ns = namespace
+        self._namespace_client = namespace
         self.read_consistency_interval = read_consistency_interval
         self.storage_options = storage_options or {}
         self.session = session
@@ -269,7 +269,7 @@ class LanceNamespaceDBConnection(DBConnection):
         if namespace is None:
             namespace = []
         request = ListTablesRequest(id=namespace, page_token=page_token, limit=limit)
-        response = self._ns.list_tables(request)
+        response = self._namespace_client.list_tables(request)
         return response.tables if response.tables else []
 
     @override
@@ -309,7 +309,9 @@ class LanceNamespaceDBConnection(DBConnection):
             # Try to describe the table first to see if it exists
             try:
                 describe_request = DescribeTableRequest(id=table_id)
-                describe_response = self._ns.describe_table(describe_request)
+                describe_response = self._namespace_client.describe_table(
+                    describe_request
+                )
                 location = describe_response.location
                 namespace_storage_options = describe_response.storage_options
             except Exception:
@@ -323,7 +325,7 @@ class LanceNamespaceDBConnection(DBConnection):
                 location=None,
                 properties=self.storage_options if self.storage_options else None,
             )
-            declare_response = self._ns.declare_table(declare_request)
+            declare_response = self._namespace_client.declare_table(declare_request)
 
             if not declare_response.location:
                 raise ValueError(
@@ -353,7 +355,7 @@ class LanceNamespaceDBConnection(DBConnection):
         # Only create if namespace returned storage_options (not None)
         if storage_options_provider is None and namespace_storage_options is not None:
             storage_options_provider = LanceNamespaceStorageOptionsProvider(
-                namespace=self._ns,
+                namespace=self._namespace_client,
                 table_id=table_id,
             )
 
@@ -371,6 +373,7 @@ class LanceNamespaceDBConnection(DBConnection):
             storage_options=merged_storage_options,
             storage_options_provider=storage_options_provider,
             location=location,
+            namespace_client=self._namespace_client,
         )
 
         return tbl
@@ -389,7 +392,7 @@ class LanceNamespaceDBConnection(DBConnection):
             namespace = []
         table_id = namespace + [name]
         request = DescribeTableRequest(id=table_id)
-        response = self._ns.describe_table(request)
+        response = self._namespace_client.describe_table(request)
 
         # Merge storage options: self.storage_options < user options < namespace options
         merged_storage_options = dict(self.storage_options)
@@ -402,10 +405,14 @@ class LanceNamespaceDBConnection(DBConnection):
         # Only create if namespace returned storage_options (not None)
         if storage_options_provider is None and response.storage_options is not None:
             storage_options_provider = LanceNamespaceStorageOptionsProvider(
-                namespace=self._ns,
+                namespace=self._namespace_client,
                 table_id=table_id,
             )
 
+        # Pass managed_versioning to avoid redundant describe_table call in Rust.
+        # Convert None to False since we already have the answer from describe_table.
+        managed_versioning = response.managed_versioning is True
+
         return self._lance_table_from_uri(
             name,
             response.location,
@@ -413,6 +420,8 @@ class LanceNamespaceDBConnection(DBConnection):
             storage_options=merged_storage_options,
             storage_options_provider=storage_options_provider,
             index_cache_size=index_cache_size,
+            namespace_client=self._namespace_client,
+            managed_versioning=managed_versioning,
         )
 
     @override
@@ -422,7 +431,7 @@ class LanceNamespaceDBConnection(DBConnection):
             namespace = []
         table_id = namespace + [name]
         request = DropTableRequest(id=table_id)
-        self._ns.drop_table(request)
+        self._namespace_client.drop_table(request)
 
     @override
     def rename_table(
@@ -484,7 +493,7 @@ class LanceNamespaceDBConnection(DBConnection):
         request = ListNamespacesRequest(
             id=namespace, page_token=page_token, limit=limit
         )
-        response = self._ns.list_namespaces(request)
+        response = self._namespace_client.list_namespaces(request)
         return ListNamespacesResponse(
             namespaces=response.namespaces if response.namespaces else [],
             page_token=response.page_token,
@@ -520,7 +529,7 @@ class LanceNamespaceDBConnection(DBConnection):
             mode=_normalize_create_namespace_mode(mode),
             properties=properties,
         )
-        response = self._ns.create_namespace(request)
+        response = self._namespace_client.create_namespace(request)
         return CreateNamespaceResponse(
             properties=response.properties if hasattr(response, "properties") else None
         )
@@ -555,7 +564,7 @@ class LanceNamespaceDBConnection(DBConnection):
             mode=_normalize_drop_namespace_mode(mode),
             behavior=_normalize_drop_namespace_behavior(behavior),
         )
-        response = self._ns.drop_namespace(request)
+        response = self._namespace_client.drop_namespace(request)
         return DropNamespaceResponse(
             properties=(
                 response.properties if hasattr(response, "properties") else None
@@ -581,7 +590,7 @@ class LanceNamespaceDBConnection(DBConnection):
             Response containing the namespace properties.
         """
         request = DescribeNamespaceRequest(id=namespace)
-        response = self._ns.describe_namespace(request)
+        response = self._namespace_client.describe_namespace(request)
         return DescribeNamespaceResponse(
             properties=response.properties if hasattr(response, "properties") else None
         )
@@ -615,7 +624,7 @@ class LanceNamespaceDBConnection(DBConnection):
         if namespace is None:
             namespace = []
         request = ListTablesRequest(id=namespace, page_token=page_token, limit=limit)
-        response = self._ns.list_tables(request)
+        response = self._namespace_client.list_tables(request)
         return ListTablesResponse(
             tables=response.tables if response.tables else [],
             page_token=response.page_token,
@@ -630,6 +639,8 @@ class LanceNamespaceDBConnection(DBConnection):
         storage_options: Optional[Dict[str, str]] = None,
         storage_options_provider: Optional[StorageOptionsProvider] = None,
         index_cache_size: Optional[int] = None,
+        namespace_client: Optional[Any] = None,
+        managed_versioning: Optional[bool] = None,
     ) -> LanceTable:
         # Open a table directly from a URI using the location parameter
         # Note: storage_options should already be merged by the caller
@@ -643,6 +654,8 @@ class LanceNamespaceDBConnection(DBConnection):
         )
 
         # Open the table using the temporary connection with the location parameter
+        # Pass namespace_client to enable managed versioning support
+        # Pass managed_versioning to avoid redundant describe_table call
         return LanceTable.open(
             temp_conn,
             name,
@@ -651,6 +664,8 @@ class LanceNamespaceDBConnection(DBConnection):
             storage_options_provider=storage_options_provider,
             index_cache_size=index_cache_size,
             location=table_uri,
+            namespace_client=namespace_client,
+            managed_versioning=managed_versioning,
         )
 
 
@@ -685,7 +700,7 @@ class AsyncLanceNamespaceDBConnection:
         session : Optional[Session]
             A session to use for this connection
         """
-        self._ns = namespace
+        self._namespace_client = namespace
         self.read_consistency_interval = read_consistency_interval
         self.storage_options = storage_options or {}
         self.session = session
@@ -713,7 +728,7 @@ class AsyncLanceNamespaceDBConnection:
         if namespace is None:
             namespace = []
         request = ListTablesRequest(id=namespace, page_token=page_token, limit=limit)
-        response = self._ns.list_tables(request)
+        response = self._namespace_client.list_tables(request)
         return response.tables if response.tables else []
 
     async def create_table(
@@ -750,7 +765,9 @@ class AsyncLanceNamespaceDBConnection:
             # Try to describe the table first to see if it exists
             try:
                 describe_request = DescribeTableRequest(id=table_id)
-                describe_response = self._ns.describe_table(describe_request)
+                describe_response = self._namespace_client.describe_table(
+                    describe_request
+                )
                 location = describe_response.location
                 namespace_storage_options = describe_response.storage_options
             except Exception:
@@ -764,7 +781,7 @@ class AsyncLanceNamespaceDBConnection:
                 location=None,
                 properties=self.storage_options if self.storage_options else None,
             )
-            declare_response = self._ns.declare_table(declare_request)
+            declare_response = self._namespace_client.declare_table(declare_request)
 
             if not declare_response.location:
                 raise ValueError(
@@ -797,7 +814,7 @@ class AsyncLanceNamespaceDBConnection:
                 and namespace_storage_options is not None
             ):
                 provider = LanceNamespaceStorageOptionsProvider(
-                    namespace=self._ns,
+                    namespace=self._namespace_client,
                     table_id=table_id,
                 )
             else:
@@ -817,6 +834,7 @@ class AsyncLanceNamespaceDBConnection:
                 storage_options=merged_storage_options,
                 storage_options_provider=provider,
                 location=location,
+                namespace_client=self._namespace_client,
             )
 
         lance_table = await asyncio.to_thread(_create_table)
@@ -837,7 +855,7 @@ class AsyncLanceNamespaceDBConnection:
             namespace = []
         table_id = namespace + [name]
         request = DescribeTableRequest(id=table_id)
-        response = self._ns.describe_table(request)
+        response = self._namespace_client.describe_table(request)
 
         # Merge storage options: self.storage_options < user options < namespace options
         merged_storage_options = dict(self.storage_options)
@@ -849,10 +867,14 @@ class AsyncLanceNamespaceDBConnection:
         # Create a storage options provider if not provided by user
         if storage_options_provider is None and response.storage_options is not None:
             storage_options_provider = LanceNamespaceStorageOptionsProvider(
-                namespace=self._ns,
+                namespace=self._namespace_client,
                 table_id=table_id,
             )
 
+        # Capture managed_versioning from describe response.
+        # Convert None to False since we already have the answer from describe_table.
+        managed_versioning = response.managed_versioning is True
+
         # Open table in a thread
         def _open_table():
             temp_conn = LanceDBConnection(
@@ -870,6 +892,8 @@ class AsyncLanceNamespaceDBConnection:
                 storage_options_provider=storage_options_provider,
                 index_cache_size=index_cache_size,
                 location=response.location,
+                namespace_client=self._namespace_client,
+                managed_versioning=managed_versioning,
             )
 
         lance_table = await asyncio.to_thread(_open_table)
@@ -881,7 +905,7 @@ class AsyncLanceNamespaceDBConnection:
             namespace = []
         table_id = namespace + [name]
         request = DropTableRequest(id=table_id)
-        self._ns.drop_table(request)
+        self._namespace_client.drop_table(request)
 
     async def rename_table(
         self,
@@ -943,7 +967,7 @@ class AsyncLanceNamespaceDBConnection:
         request = ListNamespacesRequest(
             id=namespace, page_token=page_token, limit=limit
         )
-        response = self._ns.list_namespaces(request)
+        response = self._namespace_client.list_namespaces(request)
         return ListNamespacesResponse(
             namespaces=response.namespaces if response.namespaces else [],
             page_token=response.page_token,
@@ -978,7 +1002,7 @@ class AsyncLanceNamespaceDBConnection:
             mode=_normalize_create_namespace_mode(mode),
             properties=properties,
         )
-        response = self._ns.create_namespace(request)
+        response = self._namespace_client.create_namespace(request)
         return CreateNamespaceResponse(
             properties=response.properties if hasattr(response, "properties") else None
         )
@@ -1012,7 +1036,7 @@ class AsyncLanceNamespaceDBConnection:
             mode=_normalize_drop_namespace_mode(mode),
             behavior=_normalize_drop_namespace_behavior(behavior),
         )
-        response = self._ns.drop_namespace(request)
+        response = self._namespace_client.drop_namespace(request)
         return DropNamespaceResponse(
             properties=(
                 response.properties if hasattr(response, "properties") else None
@@ -1039,7 +1063,7 @@ class AsyncLanceNamespaceDBConnection:
             Response containing the namespace properties.
         """
         request = DescribeNamespaceRequest(id=namespace)
-        response = self._ns.describe_namespace(request)
+        response = self._namespace_client.describe_namespace(request)
         return DescribeNamespaceResponse(
             properties=response.properties if hasattr(response, "properties") else None
         )
@@ -1072,7 +1096,7 @@ class AsyncLanceNamespaceDBConnection:
         if namespace is None:
             namespace = []
         request = ListTablesRequest(id=namespace, page_token=page_token, limit=limit)
-        response = self._ns.list_tables(request)
+        response = self._namespace_client.list_tables(request)
         return ListTablesResponse(
             tables=response.tables if response.tables else [],
             page_token=response.page_token,

python/python/lancedb/query.py

@@ -38,6 +38,7 @@ from .rerankers.base import Reranker
 from .rerankers.rrf import RRFReranker
 from .rerankers.util import check_reranker_result
 from .util import flatten_columns
+from .expr import Expr
 from lancedb._lancedb import fts_query_to_json
 from typing_extensions import Annotated
 
@@ -70,7 +71,7 @@ def ensure_vector_query(
 ) -> Union[List[float], List[List[float]], pa.Array, List[pa.Array]]:
     if isinstance(val, list):
         if len(val) == 0:
-            return ValueError("Vector query must be a non-empty list")
+            raise ValueError("Vector query must be a non-empty list")
         sample = val[0]
     else:
         if isinstance(val, float):
@@ -83,7 +84,7 @@ def ensure_vector_query(
         return val
     if isinstance(sample, list):
         if len(sample) == 0:
-            return ValueError("Vector query must be a non-empty list")
+            raise ValueError("Vector query must be a non-empty list")
         if isinstance(sample[0], float):
             # val is list of list of floats
             return val
@@ -449,8 +450,8 @@ class Query(pydantic.BaseModel):
         ensure_vector_query,
     ] = None
 
-    # sql filter to refine the query with
+    # sql filter or type-safe Expr to refine the query with
-    filter: Optional[str] = None
+    filter: Optional[Union[str, Expr]] = None
 
     # if True then apply the filter after vector search
     postfilter: Optional[bool] = None
@@ -464,8 +465,8 @@ class Query(pydantic.BaseModel):
     # distance type to use for vector search
     distance_type: Optional[str] = None
 
-    # which columns to return in the results
+    # which columns to return in the results (dict values may be str or Expr)
-    columns: Optional[Union[List[str], Dict[str, str]]] = None
+    columns: Optional[Union[List[str], Dict[str, Union[str, Expr]]]] = None
 
     # minimum number of IVF partitions to search
     #
@@ -606,6 +607,7 @@ class LanceQueryBuilder(ABC):
                 query,
                 ordering_field_name=ordering_field_name,
                 fts_columns=fts_columns,
+                fast_search=fast_search,
             )
 
         if isinstance(query, list):
@@ -855,14 +857,15 @@ class LanceQueryBuilder(ABC):
             self._offset = offset
         return self
 
-    def select(self, columns: Union[list[str], dict[str, str]]) -> Self:
+    def select(self, columns: Union[list[str], dict[str, Union[str, Expr]]]) -> Self:
         """Set the columns to return.
 
         Parameters
         ----------
-        columns: list of str, or dict of str to str default None
+        columns: list of str, or dict of str to str or Expr
             List of column names to be fetched.
-            Or a dictionary of column names to SQL expressions.
+            Or a dictionary of column names to SQL expressions or
+            :class:`~lancedb.expr.Expr` objects.
             All columns are fetched if None or unspecified.
 
         Returns
@@ -876,15 +879,15 @@ class LanceQueryBuilder(ABC):
             raise ValueError("columns must be a list or a dictionary")
         return self
 
-    def where(self, where: str, prefilter: bool = True) -> Self:
+    def where(self, where: Union[str, Expr], prefilter: bool = True) -> Self:
         """Set the where clause.
 
         Parameters
         ----------
-        where: str
+        where: str or :class:`~lancedb.expr.Expr`
-            The where clause which is a valid SQL where clause. See
+            The filter condition.  Can be a SQL string or a type-safe
-            `Lance filter pushdown <https://lance.org/guide/read_and_write#filter-push-down>`_
+            :class:`~lancedb.expr.Expr` built with :func:`~lancedb.expr.col`
-            for valid SQL expressions.
+            and :func:`~lancedb.expr.lit`.
         prefilter: bool, default True
             If True, apply the filter before vector search, otherwise the
             filter is applied on the result of vector search.
@@ -1354,15 +1357,17 @@ class LanceVectorQueryBuilder(LanceQueryBuilder):
 
         return result_set
 
-    def where(self, where: str, prefilter: bool = None) -> LanceVectorQueryBuilder:
+    def where(
+        self, where: Union[str, Expr], prefilter: bool = None
+    ) -> LanceVectorQueryBuilder:
         """Set the where clause.
 
         Parameters
         ----------
-        where: str
+        where: str or :class:`~lancedb.expr.Expr`
-            The where clause which is a valid SQL where clause. See
+            The filter condition.  Can be a SQL string or a type-safe
-            `Lance filter pushdown <https://lance.org/guide/read_and_write#filter-push-down>`_
+            :class:`~lancedb.expr.Expr` built with :func:`~lancedb.expr.col`
-            for valid SQL expressions.
+            and :func:`~lancedb.expr.lit`.
         prefilter: bool, default True
             If True, apply the filter before vector search, otherwise the
             filter is applied on the result of vector search.
@@ -1456,13 +1461,14 @@ class LanceFtsQueryBuilder(LanceQueryBuilder):
         query: str | FullTextQuery,
         ordering_field_name: Optional[str] = None,
         fts_columns: Optional[Union[str, List[str]]] = None,
+        fast_search: bool = None,
     ):
         super().__init__(table)
         self._query = query
         self._phrase_query = False
         self.ordering_field_name = ordering_field_name
         self._reranker = None
-        self._fast_search = None
+        self._fast_search = fast_search
         if isinstance(fts_columns, str):
             fts_columns = [fts_columns]
         self._fts_columns = fts_columns
@@ -2203,8 +2209,8 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
             self._vector_query.select(self._columns)
             self._fts_query.select(self._columns)
         if self._where:
-            self._vector_query.where(self._where, self._postfilter)
+            self._vector_query.where(self._where, not self._postfilter)
-            self._fts_query.where(self._where, self._postfilter)
+            self._fts_query.where(self._where, not self._postfilter)
         if self._with_row_id:
             self._vector_query.with_row_id(True)
             self._fts_query.with_row_id(True)
@@ -2284,10 +2290,20 @@ class AsyncQueryBase(object):
         """
         if isinstance(columns, list) and all(isinstance(c, str) for c in columns):
             self._inner.select_columns(columns)
-        elif isinstance(columns, dict) and all(
+        elif isinstance(columns, dict) and all(isinstance(k, str) for k in columns):
-            isinstance(k, str) and isinstance(v, str) for k, v in columns.items()
+            if any(isinstance(v, Expr) for v in columns.values()):
-        ):
+                # At least one value is an Expr — use the type-safe path.
-            self._inner.select(list(columns.items()))
+                from .expr import _coerce
+
+                pairs = [(k, _coerce(v)._inner) for k, v in columns.items()]
+                self._inner.select_expr(pairs)
+            elif all(isinstance(v, str) for v in columns.values()):
+                self._inner.select(list(columns.items()))
+            else:
+                raise TypeError(
+                    "dict values must be str or Expr, got "
+                    + str({k: type(v) for k, v in columns.items()})
+                )
         else:
             raise TypeError("columns must be a list of column names or a dict")
         return self
@@ -2527,11 +2543,13 @@ class AsyncStandardQuery(AsyncQueryBase):
         """
         super().__init__(inner)
 
-    def where(self, predicate: str) -> Self:
+    def where(self, predicate: Union[str, Expr]) -> Self:
         """
         Only return rows matching the given predicate
 
-        The predicate should be supplied as an SQL query string.
+        The predicate can be a SQL string or a type-safe
+        :class:`~lancedb.expr.Expr` built with :func:`~lancedb.expr.col`
+        and :func:`~lancedb.expr.lit`.
 
         Examples
         --------
@@ -2543,7 +2561,10 @@ class AsyncStandardQuery(AsyncQueryBase):
         Filtering performance can often be improved by creating a scalar index
         on the filter column(s).
         """
-        self._inner.where(predicate)
+        if isinstance(predicate, Expr):
+            self._inner.where_expr(predicate._inner)
+        else:
+            self._inner.where(predicate)
         return self
 
     def limit(self, limit: int) -> Self:

python/python/lancedb/remote/db.py

@@ -568,4 +568,4 @@ class RemoteDBConnection(DBConnection):
 
     async def close(self):
         """Close the connection to the database."""
-        self._client.close()
+        self._conn.close()

python/python/lancedb/remote/table.py

@@ -4,7 +4,7 @@
 from datetime import timedelta
 import logging
 from functools import cached_property
-from typing import Dict, Iterable, List, Optional, Union, Literal
+from typing import Any, Callable, Dict, Iterable, List, Optional, Union, Literal
 import warnings
 
 from lancedb._lancedb import (
@@ -35,6 +35,7 @@ import pyarrow as pa
 from lancedb.common import DATA, VEC, VECTOR_COLUMN_NAME
 from lancedb.merge import LanceMergeInsertBuilder
 from lancedb.embeddings import EmbeddingFunctionRegistry
+from lancedb.table import _normalize_progress
 
 from ..query import LanceVectorQueryBuilder, LanceQueryBuilder, LanceTakeQueryBuilder
 from ..table import AsyncTable, IndexStatistics, Query, Table, Tags
@@ -218,8 +219,6 @@ class RemoteTable(Table):
         train: bool = True,
     ):
         """Create an index on the table.
-        Currently, the only parameters that matter are
-        the metric and the vector column name.
 
         Parameters
         ----------
@@ -250,11 +249,6 @@ class RemoteTable(Table):
         >>> table.create_index("l2", "vector") # doctest: +SKIP
         """
 
-        if num_sub_vectors is not None:
-            logging.warning(
-                "num_sub_vectors is not supported on LanceDB cloud."
-                "This parameter will be tuned automatically."
-            )
         if accelerator is not None:
             logging.warning(
                 "GPU accelerator is not yet supported on LanceDB cloud."
@@ -315,6 +309,7 @@ class RemoteTable(Table):
         mode: str = "append",
         on_bad_vectors: str = "error",
         fill_value: float = 0.0,
+        progress: Optional[Union[bool, Callable, Any]] = None,
     ) -> AddResult:
         """Add more data to the [Table](Table). It has the same API signature as
         the OSS version.
@@ -337,17 +332,29 @@ class RemoteTable(Table):
             One of "error", "drop", "fill".
         fill_value: float, default 0.
             The value to use when filling vectors. Only used if on_bad_vectors="fill".
+        progress: bool, callable, or tqdm-like, optional
+            A callback or tqdm-compatible progress bar. See
+            :meth:`Table.add` for details.
 
         Returns
         -------
         AddResult
             An object containing the new version number of the table after adding data.
         """
-        return LOOP.run(
+        progress, owns = _normalize_progress(progress)
-            self._table.add(
+        try:
-                data, mode=mode, on_bad_vectors=on_bad_vectors, fill_value=fill_value
+            return LOOP.run(
+                self._table.add(
+                    data,
+                    mode=mode,
+                    on_bad_vectors=on_bad_vectors,
+                    fill_value=fill_value,
+                    progress=progress,
+                )
             )
-        )
+        finally:
+            if owns:
+                progress.close()
 
     def search(
         self,
@@ -647,6 +654,45 @@ class RemoteTable(Table):
     def drop_index(self, index_name: str):
         return LOOP.run(self._table.drop_index(index_name))
 
+    def prewarm_index(self, name: str) -> None:
+        """Prewarm an index in the table.
+
+        This is a hint to the database that the index will be accessed in the
+        future and should be loaded into memory if possible.  This can reduce
+        cold-start latency for subsequent queries.
+
+        This call initiates prewarming and returns once the request is accepted.
+        It is idempotent and safe to call from multiple clients concurrently.
+
+        Parameters
+        ----------
+        name: str
+            The name of the index to prewarm
+        """
+        return LOOP.run(self._table.prewarm_index(name))
+
+    def prewarm_data(self, columns: Optional[List[str]] = None) -> None:
+        """Prewarm data for the table.
+
+        This is a hint to the database that the given columns will be accessed
+        in the future and the database should prefetch the data if possible.
+        Currently only supported on remote tables.
+
+        This call initiates prewarming and returns once the request is accepted.
+        It is idempotent and safe to call from multiple clients concurrently.
+
+        This operation has a large upfront cost but can speed up future queries
+        that need to fetch the given columns.  Large columns such as embeddings
+        or binary data may not be practical to prewarm.  This feature is intended
+        for workloads that issue many queries against the same columns.
+
+        Parameters
+        ----------
+        columns: list of str, optional
+            The columns to prewarm. If None, all columns are prewarmed.
+        """
+        return LOOP.run(self._table.prewarm_data(columns))
+
     def wait_for_index(
         self, index_names: Iterable[str], timeout: timedelta = timedelta(seconds=300)
     ):

python/python/lancedb/table.py

@@ -14,6 +14,7 @@ from functools import cached_property
 from typing import (
     TYPE_CHECKING,
     Any,
+    Callable,
     Dict,
     Iterable,
     List,
@@ -277,7 +278,7 @@ def _sanitize_data(
 
     if metadata:
         new_metadata = target_schema.metadata or {}
-        new_metadata = new_metadata.update(metadata)
+        new_metadata.update(metadata)
         target_schema = target_schema.with_metadata(new_metadata)
 
     _validate_schema(target_schema)
@@ -556,6 +557,21 @@ def _table_uri(base: str, table_name: str) -> str:
     return join_uri(base, f"{table_name}.lance")
 
 
+def _normalize_progress(progress):
+    """Normalize a ``progress`` parameter for :meth:`Table.add`.
+
+    Returns ``(progress_obj, owns)`` where *owns* is True when we created a
+    tqdm bar that the caller must close.
+    """
+    if progress is True:
+        from tqdm.auto import tqdm
+
+        return tqdm(unit=" rows"), True
+    if progress is False or progress is None:
+        return None, False
+    return progress, False
+
+
 class Table(ABC):
     """
     A Table is a collection of Records in a LanceDB Database.
@@ -974,6 +990,7 @@ class Table(ABC):
         mode: AddMode = "append",
         on_bad_vectors: OnBadVectorsType = "error",
         fill_value: float = 0.0,
+        progress: Optional[Union[bool, Callable, Any]] = None,
     ) -> AddResult:
         """Add more data to the [Table](Table).
 
@@ -995,6 +1012,29 @@ class Table(ABC):
             One of "error", "drop", "fill".
         fill_value: float, default 0.
             The value to use when filling vectors. Only used if on_bad_vectors="fill".
+        progress: bool, callable, or tqdm-like, optional
+            Progress reporting during the add operation. Can be:
+
+            - ``True`` to automatically create and display a tqdm progress
+              bar (requires ``tqdm`` to be installed)::
+
+                table.add(data, progress=True)
+
+            - A **callable** that receives a dict with keys ``output_rows``,
+              ``output_bytes``, ``total_rows``, ``elapsed_seconds``,
+              ``active_tasks``, ``total_tasks``, and ``done``::
+
+                def on_progress(p):
+                    print(f"{p['output_rows']}/{p['total_rows']} rows, "
+                          f"{p['active_tasks']}/{p['total_tasks']} workers")
+                table.add(data, progress=on_progress)
+
+            - A **tqdm-compatible** progress bar whose ``total`` and
+              ``update()`` will be called automatically. The postfix shows
+              write throughput (MB/s) and active worker count::
+
+                with tqdm() as pbar:
+                    table.add(data, progress=pbar)
 
         Returns
         -------
@@ -1331,7 +1371,7 @@ class Table(ABC):
         1  2  [3.0, 4.0]
         2  3  [5.0, 6.0]
         >>> table.delete("x = 2")
-        DeleteResult(version=2)
+        DeleteResult(num_deleted_rows=1, version=2)
         >>> table.to_pandas()
            x      vector
         0  1  [1.0, 2.0]
@@ -1345,7 +1385,7 @@ class Table(ABC):
         >>> to_remove
         '1, 5'
         >>> table.delete(f"x IN ({to_remove})")
-        DeleteResult(version=3)
+        DeleteResult(num_deleted_rows=1, version=3)
         >>> table.to_pandas()
            x      vector
         0  3  [5.0, 6.0]
@@ -1506,22 +1546,17 @@ class Table(ABC):
             in-progress operation (e.g. appending new data) and these files will not
             be deleted unless they are at least 7 days old. If delete_unverified is True
             then these files will be deleted regardless of their age.
+
+            .. warning::
+
+                This should only be set to True if you can guarantee that no other
+                process is currently working on this dataset. Otherwise the dataset
+                could be put into a corrupted state.
+
         retrain: bool, default False
             This parameter is no longer used and is deprecated.
 
-        Experimental API
+        The frequency an application should call optimize is based on the frequency of
-        ----------------
-
-        The optimization process is undergoing active development and may change.
-        Our goal with these changes is to improve the performance of optimization and
-        reduce the complexity.
-
-        That being said, it is essential today to run optimize if you want the best
-        performance.  It should be stable and safe to use in production, but it our
-        hope that the API may be simplified (or not even need to be called) in the
-        future.
-
-        The frequency an application shoudl call optimize is based on the frequency of
         data modifications.  If data is frequently added, deleted, or updated then
         optimize should be run frequently.  A good rule of thumb is to run optimize if
         you have added or modified 100,000 or more records or run more than 20 data
@@ -1746,6 +1781,8 @@ class LanceTable(Table):
         storage_options_provider: Optional["StorageOptionsProvider"] = None,
         index_cache_size: Optional[int] = None,
         location: Optional[str] = None,
+        namespace_client: Optional[Any] = None,
+        managed_versioning: Optional[bool] = None,
         _async: AsyncTable = None,
     ):
         if namespace is None:
@@ -1753,6 +1790,7 @@ class LanceTable(Table):
         self._conn = connection
         self._namespace = namespace
         self._location = location  # Store location for use in _dataset_path
+        self._namespace_client = namespace_client
         if _async is not None:
             self._table = _async
         else:
@@ -1764,6 +1802,8 @@ class LanceTable(Table):
                     storage_options_provider=storage_options_provider,
                     index_cache_size=index_cache_size,
                     location=location,
+                    namespace_client=namespace_client,
+                    managed_versioning=managed_versioning,
                 )
             )
 
@@ -1806,6 +1846,8 @@ class LanceTable(Table):
         storage_options_provider: Optional["StorageOptionsProvider"] = None,
         index_cache_size: Optional[int] = None,
         location: Optional[str] = None,
+        namespace_client: Optional[Any] = None,
+        managed_versioning: Optional[bool] = None,
     ):
         if namespace is None:
             namespace = []
@@ -1817,6 +1859,8 @@ class LanceTable(Table):
             storage_options_provider=storage_options_provider,
             index_cache_size=index_cache_size,
             location=location,
+            namespace_client=namespace_client,
+            managed_versioning=managed_versioning,
         )
 
         # check the dataset exists
@@ -1848,6 +1892,16 @@ class LanceTable(Table):
                 "Please install with `pip install pylance`."
             )
 
+        if self._namespace_client is not None:
+            table_id = self._namespace + [self.name]
+            return lance.dataset(
+                version=self.version,
+                storage_options=self._conn.storage_options,
+                namespace=self._namespace_client,
+                table_id=table_id,
+                **kwargs,
+            )
+
         return lance.dataset(
             self._dataset_path,
             version=self.version,
@@ -2200,12 +2254,18 @@ class LanceTable(Table):
 
     def prewarm_index(self, name: str) -> None:
         """
-        Prewarms an index in the table
+        Prewarm an index in the table.
 
-        This loads the entire index into memory
+        This is a hint to the database that the index will be accessed in the
+        future and should be loaded into memory if possible.  This can reduce
+        cold-start latency for subsequent queries.
 
-        If the index does not fit into the available cache this call
+        This call initiates prewarming and returns once the request is accepted.
-        may be wasteful
+        It is idempotent and safe to call from multiple clients concurrently.
+
+        It is generally wasteful to call this if the index does not fit into the
+        available cache.  Not all index types support prewarming; unsupported
+        indices will silently ignore the request.
 
         Parameters
         ----------
@@ -2214,6 +2274,29 @@ class LanceTable(Table):
         """
         return LOOP.run(self._table.prewarm_index(name))
 
+    def prewarm_data(self, columns: Optional[List[str]] = None) -> None:
+        """
+        Prewarm data for the table.
+
+        This is a hint to the database that the given columns will be accessed
+        in the future and the database should prefetch the data if possible.
+        Currently only supported on remote tables.
+
+        This call initiates prewarming and returns once the request is accepted.
+        It is idempotent and safe to call from multiple clients concurrently.
+
+        This operation has a large upfront cost but can speed up future queries
+        that need to fetch the given columns.  Large columns such as embeddings
+        or binary data may not be practical to prewarm.  This feature is intended
+        for workloads that issue many queries against the same columns.
+
+        Parameters
+        ----------
+        columns: list of str, optional
+            The columns to prewarm. If None, all columns are prewarmed.
+        """
+        return LOOP.run(self._table.prewarm_data(columns))
+
     def wait_for_index(
         self, index_names: Iterable[str], timeout: timedelta = timedelta(seconds=300)
     ) -> None:
@@ -2449,6 +2532,7 @@ class LanceTable(Table):
         mode: AddMode = "append",
         on_bad_vectors: OnBadVectorsType = "error",
         fill_value: float = 0.0,
+        progress: Optional[Union[bool, Callable, Any]] = None,
     ) -> AddResult:
         """Add data to the table.
         If vector columns are missing and the table
@@ -2467,17 +2551,29 @@ class LanceTable(Table):
             One of "error", "drop", "fill", "null".
         fill_value: float, default 0.
             The value to use when filling vectors. Only used if on_bad_vectors="fill".
+        progress: bool, callable, or tqdm-like, optional
+            A callback or tqdm-compatible progress bar. See
+            :meth:`Table.add` for details.
 
         Returns
         -------
         int
             The number of vectors in the table.
         """
-        return LOOP.run(
+        progress, owns = _normalize_progress(progress)
-            self._table.add(
+        try:
-                data, mode=mode, on_bad_vectors=on_bad_vectors, fill_value=fill_value
+            return LOOP.run(
+                self._table.add(
+                    data,
+                    mode=mode,
+                    on_bad_vectors=on_bad_vectors,
+                    fill_value=fill_value,
+                    progress=progress,
+                )
             )
-        )
+        finally:
+            if owns:
+                progress.close()
 
     def merge(
         self,
@@ -2713,6 +2809,7 @@ class LanceTable(Table):
         data_storage_version: Optional[str] = None,
         enable_v2_manifest_paths: Optional[bool] = None,
         location: Optional[str] = None,
+        namespace_client: Optional[Any] = None,
     ):
         """
         Create a new table.
@@ -2773,6 +2870,7 @@ class LanceTable(Table):
         self._conn = db
         self._namespace = namespace
         self._location = location
+        self._namespace_client = namespace_client
 
         if data_storage_version is not None:
             warnings.warn(
@@ -2997,22 +3095,17 @@ class LanceTable(Table):
             in-progress operation (e.g. appending new data) and these files will not
             be deleted unless they are at least 7 days old. If delete_unverified is True
             then these files will be deleted regardless of their age.
+
+            .. warning::
+
+                This should only be set to True if you can guarantee that no other
+                process is currently working on this dataset. Otherwise the dataset
+                could be put into a corrupted state.
+
         retrain: bool, default False
             This parameter is no longer used and is deprecated.
 
-        Experimental API
+        The frequency an application should call optimize is based on the frequency of
-        ----------------
-
-        The optimization process is undergoing active development and may change.
-        Our goal with these changes is to improve the performance of optimization and
-        reduce the complexity.
-
-        That being said, it is essential today to run optimize if you want the best
-        performance.  It should be stable and safe to use in production, but it our
-        hope that the API may be simplified (or not even need to be called) in the
-        future.
-
-        The frequency an application shoudl call optimize is based on the frequency of
         data modifications.  If data is frequently added, deleted, or updated then
         optimize should be run frequently.  A good rule of thumb is to run optimize if
         you have added or modified 100,000 or more records or run more than 20 data
@@ -3613,19 +3706,47 @@ class AsyncTable:
         """
         Prewarm an index in the table.
 
+        This is a hint to the database that the index will be accessed in the
+        future and should be loaded into memory if possible.  This can reduce
+        cold-start latency for subsequent queries.
+
+        This call initiates prewarming and returns once the request is accepted.
+        It is idempotent and safe to call from multiple clients concurrently.
+
+        It is generally wasteful to call this if the index does not fit into the
+        available cache.  Not all index types support prewarming; unsupported
+        indices will silently ignore the request.
+
         Parameters
         ----------
         name: str
             The name of the index to prewarm
-
-        Notes
-        -----
-        This will load the index into memory.  This may reduce the cold-start time for
-        future queries.  If the index does not fit in the cache then this call may be
-        wasteful.
         """
         await self._inner.prewarm_index(name)
 
+    async def prewarm_data(self, columns: Optional[List[str]] = None) -> None:
+        """
+        Prewarm data for the table.
+
+        This is a hint to the database that the given columns will be accessed
+        in the future and the database should prefetch the data if possible.
+        Currently only supported on remote tables.
+
+        This call initiates prewarming and returns once the request is accepted.
+        It is idempotent and safe to call from multiple clients concurrently.
+
+        This operation has a large upfront cost but can speed up future queries
+        that need to fetch the given columns.  Large columns such as embeddings
+        or binary data may not be practical to prewarm.  This feature is intended
+        for workloads that issue many queries against the same columns.
+
+        Parameters
+        ----------
+        columns: list of str, optional
+            The columns to prewarm. If None, all columns are prewarmed.
+        """
+        await self._inner.prewarm_data(columns)
+
     async def wait_for_index(
         self, index_names: Iterable[str], timeout: timedelta = timedelta(seconds=300)
     ) -> None:
@@ -3701,6 +3822,7 @@ class AsyncTable:
         mode: Optional[Literal["append", "overwrite"]] = "append",
         on_bad_vectors: Optional[OnBadVectorsType] = None,
         fill_value: Optional[float] = None,
+        progress: Optional[Union[bool, Callable, Any]] = None,
     ) -> AddResult:
         """Add more data to the [Table](Table).
 
@@ -3722,6 +3844,9 @@ class AsyncTable:
             One of "error", "drop", "fill", "null".
         fill_value: float, default 0.
             The value to use when filling vectors. Only used if on_bad_vectors="fill".
+        progress: callable or tqdm-like, optional
+            A callback or tqdm-compatible progress bar. See
+            :meth:`Table.add` for details.
 
         """
         schema = await self.schema()
@@ -3732,7 +3857,13 @@ class AsyncTable:
 
         # _santitize_data is an old code path, but we will use it until the
         # new code path is ready.
-        if on_bad_vectors != "error" or (
+        if mode == "overwrite":
+            # For overwrite, apply the same preprocessing as create_table
+            # so vector columns are inferred as FixedSizeList.
+            data, _ = sanitize_create_table(
+                data, None, on_bad_vectors=on_bad_vectors, fill_value=fill_value
+            )
+        elif on_bad_vectors != "error" or (
             schema.metadata is not None and b"embedding_functions" in schema.metadata
         ):
             data = _sanitize_data(
@@ -3745,8 +3876,9 @@ class AsyncTable:
             )
         _register_optional_converters()
         data = to_scannable(data)
+        progress, owns = _normalize_progress(progress)
         try:
-            return await self._inner.add(data, mode or "append")
+            return await self._inner.add(data, mode or "append", progress=progress)
         except RuntimeError as e:
             if "Cast error" in str(e):
                 raise ValueError(e)
@@ -3754,6 +3886,9 @@ class AsyncTable:
                 raise ValueError(e)
             else:
                 raise
+        finally:
+            if owns:
+                progress.close()
 
     def merge_insert(self, on: Union[str, Iterable[str]]) -> LanceMergeInsertBuilder:
         """
@@ -4076,7 +4211,7 @@ class AsyncTable:
             async_query = async_query.offset(query.offset)
         if query.columns:
             async_query = async_query.select(query.columns)
-        if query.filter:
+        if query.filter is not None:
             async_query = async_query.where(query.filter)
         if query.fast_search:
             async_query = async_query.fast_search()
@@ -4215,7 +4350,7 @@ class AsyncTable:
         1  2  [3.0, 4.0]
         2  3  [5.0, 6.0]
         >>> table.delete("x = 2")
-        DeleteResult(version=2)
+        DeleteResult(num_deleted_rows=1, version=2)
         >>> table.to_pandas()
            x      vector
         0  1  [1.0, 2.0]
@@ -4229,7 +4364,7 @@ class AsyncTable:
         >>> to_remove
         '1, 5'
         >>> table.delete(f"x IN ({to_remove})")
-        DeleteResult(version=3)
+        DeleteResult(num_deleted_rows=1, version=3)
         >>> table.to_pandas()
            x      vector
         0  3  [5.0, 6.0]
@@ -4552,22 +4687,17 @@ class AsyncTable:
             in-progress operation (e.g. appending new data) and these files will not
             be deleted unless they are at least 7 days old. If delete_unverified is True
             then these files will be deleted regardless of their age.
+
+            .. warning::
+
+                This should only be set to True if you can guarantee that no other
+                process is currently working on this dataset. Otherwise the dataset
+                could be put into a corrupted state.
+
         retrain: bool, default False
             This parameter is no longer used and is deprecated.
 
-        Experimental API
+        The frequency an application should call optimize is based on the frequency of
-        ----------------
-
-        The optimization process is undergoing active development and may change.
-        Our goal with these changes is to improve the performance of optimization and
-        reduce the complexity.
-
-        That being said, it is essential today to run optimize if you want the best
-        performance.  It should be stable and safe to use in production, but it our
-        hope that the API may be simplified (or not even need to be called) in the
-        future.
-
-        The frequency an application shoudl call optimize is based on the frequency of
         data modifications.  If data is frequently added, deleted, or updated then
         optimize should be run frequently.  A good rule of thumb is to run optimize if
         you have added or modified 100,000 or more records or run more than 20 data
@@ -4688,7 +4818,16 @@ class IndexStatistics:
     num_indexed_rows: int
     num_unindexed_rows: int
     index_type: Literal[
-        "IVF_PQ", "IVF_HNSW_PQ", "IVF_HNSW_SQ", "FTS", "BTREE", "BITMAP", "LABEL_LIST"
+        "IVF_FLAT",
+        "IVF_SQ",
+        "IVF_PQ",
+        "IVF_RQ",
+        "IVF_HNSW_SQ",
+        "IVF_HNSW_PQ",
+        "FTS",
+        "BTREE",
+        "BITMAP",
+        "LABEL_LIST",
     ]
     distance_type: Optional[Literal["l2", "cosine", "dot"]] = None
     num_indices: Optional[int] = None

python/python/lancedb/util.py

@@ -324,6 +324,16 @@ def _(value: list):
     return "[" + ", ".join(map(value_to_sql, value)) + "]"
 
 
+@value_to_sql.register(dict)
+def _(value: dict):
+    # https://datafusion.apache.org/user-guide/sql/scalar_functions.html#named-struct
+    return (
+        "named_struct("
+        + ", ".join(f"'{k}', {value_to_sql(v)}" for k, v in value.items())
+        + ")"
+    )
+
+
 @value_to_sql.register(np.ndarray)
 def _(value: np.ndarray):
     return value_to_sql(value.tolist())

python/python/tests/test_embeddings.py

@@ -546,3 +546,24 @@ def test_openai_no_retry_on_401(mock_sleep):
     assert mock_func.call_count == 1
     # Verify that sleep was never called (no retries)
     assert mock_sleep.call_count == 0
+
+
+def test_url_retrieve_downloads_image():
+    """
+    Embedding functions like open-clip, siglip, and jinaai use url_retrieve()
+    to download images from HTTP URLs. For example, open_clip._to_pil() calls:
+
+        PIL_Image.open(io.BytesIO(url_retrieve(image)))
+
+    Verify that url_retrieve() can download an image and open it as PIL Image,
+    matching the real usage pattern in embedding functions.
+    """
+    import io
+
+    Image = pytest.importorskip("PIL.Image")
+    from lancedb.embeddings.utils import url_retrieve
+
+    image_url = "http://farm1.staticflickr.com/53/167798175_7c7845bbbd_z.jpg"
+    image_bytes = url_retrieve(image_url)
+    img = Image.open(io.BytesIO(image_bytes))
+    assert img.size[0] > 0 and img.size[1] > 0

python/python/tests/test_fts.py

@@ -27,6 +27,7 @@ from lancedb.query import (
     PhraseQuery,
     BooleanQuery,
     Occur,
+    LanceFtsQueryBuilder,
 )
 import numpy as np
 import pyarrow as pa
@@ -920,6 +921,10 @@ def test_fts_fast_search(table):
     assert query.limit == 5
     assert query.columns == ["text"]
 
+    # fast_search should be enabled by keyword argument too
+    query = LanceFtsQueryBuilder(table, "xyz", fast_search=True).to_query_object()
+    assert query.fast_search is True
+
     # Verify it executes without error and skips unindexed data
     results = table.search("xyz", query_type="fts").fast_search().limit(5).to_list()
     assert len(results) == 0

python/python/tests/test_hybrid_query.py

@@ -177,6 +177,60 @@ async def test_analyze_plan(table: AsyncTable):
     assert "metrics=" in res
 
 
+@pytest.fixture
+def table_with_id(tmpdir_factory) -> Table:
+    tmp_path = str(tmpdir_factory.mktemp("data"))
+    db = lancedb.connect(tmp_path)
+    data = pa.table(
+        {
+            "id": pa.array([1, 2, 3, 4], type=pa.int64()),
+            "text": pa.array(["a", "b", "cat", "dog"]),
+            "vector": pa.array(
+                [[0.1, 0.1], [2, 2], [-0.1, -0.1], [0.5, -0.5]],
+                type=pa.list_(pa.float32(), list_size=2),
+            ),
+        }
+    )
+    table = db.create_table("test_with_id", data)
+    table.create_fts_index("text", with_position=False, use_tantivy=False)
+    return table
+
+
+def test_hybrid_prefilter_explain_plan(table_with_id: Table):
+    """
+    Verify that the prefilter logic is not inverted in LanceHybridQueryBuilder.
+    """
+    plan_prefilter = (
+        table_with_id.search(query_type="hybrid")
+        .vector([0.0, 0.0])
+        .text("dog")
+        .where("id = 1", prefilter=True)
+        .limit(2)
+        .explain_plan(verbose=True)
+    )
+
+    plan_postfilter = (
+        table_with_id.search(query_type="hybrid")
+        .vector([0.0, 0.0])
+        .text("dog")
+        .where("id = 1", prefilter=False)
+        .limit(2)
+        .explain_plan(verbose=True)
+    )
+
+    # prefilter=True: filter is pushed into the LanceRead scan.
+    # The FTS sub-plan exposes this as "full_filter=id = Int64(1)" inside LanceRead.
+    assert "full_filter=id = Int64(1)" in plan_prefilter, (
+        f"Should push the filter into the scan.\nPlan:\n{plan_prefilter}"
+    )
+
+    # prefilter=False: filter is applied as a separate FilterExec after the search.
+    # The filter must NOT be embedded in the scan.
+    assert "full_filter=id = Int64(1)" not in plan_postfilter, (
+        f"Should NOT push the filter into the scan.\nPlan:\n{plan_postfilter}"
+    )
+
+
 def test_normalize_scores():
     cases = [
         (pa.array([0.1, 0.4]), pa.array([0.0, 1.0])),

python/python/tests/test_index.py

@@ -3,6 +3,7 @@
 
 from datetime import timedelta
 import random
+from typing import get_args, get_type_hints
 
 import pyarrow as pa
 import pytest
@@ -22,6 +23,7 @@ from lancedb.index import (
     HnswSq,
     FTS,
 )
+from lancedb.table import IndexStatistics
 
 
 @pytest_asyncio.fixture
@@ -283,3 +285,23 @@ async def test_create_index_with_binary_vectors(binary_table: AsyncTable):
     for v in range(256):
         res = await binary_table.query().nearest_to([v] * 128).to_arrow()
         assert res["id"][0].as_py() == v
+
+
+def test_index_statistics_index_type_lists_all_supported_values():
+    expected_index_types = {
+        "IVF_FLAT",
+        "IVF_SQ",
+        "IVF_PQ",
+        "IVF_RQ",
+        "IVF_HNSW_SQ",
+        "IVF_HNSW_PQ",
+        "FTS",
+        "BTREE",
+        "BITMAP",
+        "LABEL_LIST",
+    }
+
+    assert (
+        set(get_args(get_type_hints(IndexStatistics)["index_type"]))
+        == expected_index_types
+    )

python/python/tests/test_namespace.py

@@ -8,6 +8,7 @@ import shutil
 import pytest
 import pyarrow as pa
 import lancedb
+from lance_namespace.errors import NamespaceNotEmptyError, TableNotFoundError
 
 
 class TestNamespaceConnection:
@@ -130,7 +131,7 @@ class TestNamespaceConnection:
         assert len(list(db.table_names(namespace=["test_ns"]))) == 0
 
         # Should not be able to open dropped table
-        with pytest.raises(RuntimeError):
+        with pytest.raises(TableNotFoundError):
             db.open_table("table1", namespace=["test_ns"])
 
     def test_create_table_with_schema(self):
@@ -340,7 +341,7 @@ class TestNamespaceConnection:
         db.create_table("test_table", schema=schema, namespace=["test_namespace"])
 
         # Try to drop namespace with tables - should fail
-        with pytest.raises(RuntimeError, match="is not empty"):
+        with pytest.raises(NamespaceNotEmptyError):
             db.drop_namespace(["test_namespace"])
 
         # Drop table first

python/python/tests/test_namespace_integration.py

@@ -147,7 +147,12 @@ class TrackingNamespace(LanceNamespace):
         This simulates a credential rotation system where each call returns
         new credentials that expire after credential_expires_in_seconds.
         """
-        modified = copy.deepcopy(storage_options) if storage_options else {}
+        # Start from base storage options (endpoint, region, allow_http, etc.)
+        # because DirectoryNamespace returns None for storage_options from
+        # describe_table/declare_table when no credential vendor is configured.
+        modified = copy.deepcopy(self.base_storage_options)
+        if storage_options:
+            modified.update(storage_options)
 
         # Increment credentials to simulate rotation
         modified["aws_access_key_id"] = f"AKID_{count}"

python/python/tests/test_query.py

@@ -30,6 +30,7 @@ from lancedb.query import (
     PhraseQuery,
     Query,
     FullTextSearchQuery,
+    ensure_vector_query,
 )
 from lancedb.rerankers.cross_encoder import CrossEncoderReranker
 from lancedb.table import AsyncTable, LanceTable
@@ -1501,6 +1502,18 @@ def test_search_empty_table(mem_db):
     assert results == []
 
 
+def test_ensure_vector_query_empty_list():
+    """Regression: ensure_vector_query used to return instead of raise ValueError."""
+    with pytest.raises(ValueError, match="non-empty"):
+        ensure_vector_query([])
+
+
+def test_ensure_vector_query_nested_empty_list():
+    """Regression: ensure_vector_query used to return instead of raise ValueError."""
+    with pytest.raises(ValueError, match="non-empty"):
+        ensure_vector_query([[]])
+
+
 def test_fast_search(tmp_path):
     db = lancedb.connect(tmp_path)
 

python/python/tests/test_remote_db.py

@@ -1201,6 +1201,18 @@ async def test_header_provider_overrides_static_headers():
         await db.table_names()
 
 
+def test_close():
+    """Test that close() works without AttributeError."""
+    import asyncio
+
+    def handler(req):
+        req.send_response(200)
+        req.end_headers()
+
+    with mock_lancedb_connection(handler) as db:
+        asyncio.run(db.close())
+
+
 @pytest.mark.parametrize("exception", [KeyboardInterrupt, SystemExit, GeneratorExit])
 def test_background_loop_cancellation(exception):
     """Test that BackgroundEventLoop.run() cancels the future on interrupt."""

python/python/tests/test_table.py

@@ -326,6 +326,24 @@ def test_add_struct(mem_db: DBConnection):
     table = mem_db.create_table("test2", schema=schema)
     table.add(data)
 
+    struct_type = pa.struct(
+        [
+            ("b", pa.int64()),
+            ("a", pa.int64()),
+        ]
+    )
+    expected = pa.table(
+        {
+            "s_list": [
+                [
+                    pa.scalar({"b": 1, "a": 2}, type=struct_type),
+                    pa.scalar({"b": 4, "a": None}, type=struct_type),
+                ]
+            ],
+        }
+    )
+    assert table.to_arrow() == expected
+
 
 def test_add_subschema(mem_db: DBConnection):
     schema = pa.schema(
@@ -509,6 +527,132 @@ async def test_add_async(mem_db_async: AsyncConnection):
     assert await table.count_rows() == 3
 
 
+def test_add_overwrite_infers_vector_schema(mem_db: DBConnection):
+    """Overwrite should infer vector columns the same way create_table does.
+
+    Regression test for https://github.com/lancedb/lancedb/issues/3183
+    """
+    table = mem_db.create_table(
+        "test_overwrite_vec",
+        data=[
+            {"vector": [1.0, 2.0, 3.0, 4.0], "item": "foo"},
+            {"vector": [5.0, 6.0, 7.0, 8.0], "item": "bar"},
+        ],
+    )
+    # create_table infers vector as fixed_size_list<float32, 4>
+    original_type = table.schema.field("vector").type
+    assert pa.types.is_fixed_size_list(original_type)
+
+    # overwrite with plain Python lists (PyArrow infers list<double>)
+    table.add(
+        [
+            {"vector": [10.0, 20.0, 30.0, 40.0], "item": "baz"},
+        ],
+        mode="overwrite",
+    )
+    # overwrite should infer vector column the same way as create_table
+    new_type = table.schema.field("vector").type
+    assert pa.types.is_fixed_size_list(new_type), (
+        f"Expected fixed_size_list after overwrite, got {new_type}"
+    )
+
+
+def test_add_progress_callback(mem_db: DBConnection):
+    table = mem_db.create_table(
+        "test",
+        data=[{"id": 1}, {"id": 2}],
+    )
+
+    updates = []
+    table.add([{"id": 3}, {"id": 4}], progress=lambda p: updates.append(dict(p)))
+
+    assert len(table) == 4
+    # The done callback always fires, so we should always get at least one.
+    assert len(updates) >= 1, "expected at least one progress callback"
+    for p in updates:
+        assert "output_rows" in p
+        assert "output_bytes" in p
+        assert "total_rows" in p
+        assert "elapsed_seconds" in p
+        assert "active_tasks" in p
+        assert "total_tasks" in p
+        assert "done" in p
+    # The last callback should have done=True.
+    assert updates[-1]["done"] is True
+
+
+def test_add_progress_tqdm_like(mem_db: DBConnection):
+    """Test that a tqdm-like object gets total set and update() called."""
+
+    class FakeBar:
+        def __init__(self):
+            self.total = None
+            self.n = 0
+            self.postfix = None
+
+        def update(self, n):
+            self.n += n
+
+        def set_postfix_str(self, s):
+            self.postfix = s
+
+        def refresh(self):
+            pass
+
+    table = mem_db.create_table(
+        "test",
+        data=[{"id": 1}, {"id": 2}],
+    )
+
+    bar = FakeBar()
+    table.add([{"id": 3}, {"id": 4}], progress=bar)
+
+    assert len(table) == 4
+    # Postfix should contain throughput and worker count
+    if bar.postfix is not None:
+        assert "MB/s" in bar.postfix
+        assert "workers" in bar.postfix
+
+
+def test_add_progress_bool(mem_db: DBConnection):
+    """Test that progress=True creates and closes a tqdm bar automatically."""
+    table = mem_db.create_table(
+        "test",
+        data=[{"id": 1}, {"id": 2}],
+    )
+
+    table.add([{"id": 3}, {"id": 4}], progress=True)
+    assert len(table) == 4
+
+    # progress=False should be the same as None
+    table.add([{"id": 5}], progress=False)
+    assert len(table) == 5
+
+
+@pytest.mark.asyncio
+async def test_add_progress_callback_async(mem_db_async: AsyncConnection):
+    """Progress callbacks work through the async path too."""
+    table = await mem_db_async.create_table("test", data=[{"id": 1}, {"id": 2}])
+
+    updates = []
+    await table.add([{"id": 3}, {"id": 4}], progress=lambda p: updates.append(dict(p)))
+
+    assert await table.count_rows() == 4
+    assert len(updates) >= 1
+    assert updates[-1]["done"] is True
+
+
+def test_add_progress_callback_error(mem_db: DBConnection):
+    """A failing callback must not prevent the write from succeeding."""
+    table = mem_db.create_table("test", data=[{"id": 1}, {"id": 2}])
+
+    def bad_callback(p):
+        raise RuntimeError("boom")
+
+    table.add([{"id": 3}, {"id": 4}], progress=bad_callback)
+    assert len(table) == 4
+
+
 def test_polars(mem_db: DBConnection):
     data = {
         "vector": [[3.1, 4.1], [5.9, 26.5]],
@@ -2029,3 +2173,33 @@ def test_table_uri(tmp_path):
     db = lancedb.connect(tmp_path)
     table = db.create_table("my_table", data=[{"x": 0}])
     assert table.uri == str(tmp_path / "my_table.lance")
+
+
+def test_sanitize_data_metadata_not_stripped():
+    """Regression test: dict.update() returns None, so assigning its result
+    would silently replace metadata with None, causing with_metadata(None)
+    to strip all schema metadata from the target schema."""
+    from lancedb.table import _sanitize_data
+
+    schema = pa.schema(
+        [pa.field("x", pa.int64())],
+        metadata={b"existing_key": b"existing_value"},
+    )
+    batch = pa.record_batch([pa.array([1, 2, 3])], schema=schema)
+
+    # Use a different field type so the reader and target schemas differ,
+    # forcing _cast_to_target_schema to rebuild the schema with the
+    # target's metadata (instead of taking the fast-path).
+    target_schema = pa.schema(
+        [pa.field("x", pa.int32())],
+        metadata={b"existing_key": b"existing_value"},
+    )
+
+    reader = pa.RecordBatchReader.from_batches(schema, [batch])
+    metadata = {b"new_key": b"new_value"}
+    result = _sanitize_data(reader, target_schema=target_schema, metadata=metadata)
+
+    result_schema = result.schema
+    assert result_schema.metadata is not None
+    assert result_schema.metadata[b"existing_key"] == b"existing_value"
+    assert result_schema.metadata[b"new_key"] == b"new_value"

python/python/tests/test_util.py

@@ -121,6 +121,32 @@ def test_value_to_sql_string(tmp_path):
         assert table.to_pandas().query("search == @value")["replace"].item() == value
 
 
+def test_value_to_sql_dict():
+    # Simple flat struct
+    assert value_to_sql({"a": 1, "b": "hello"}) == "named_struct('a', 1, 'b', 'hello')"
+
+    # Nested struct
+    assert (
+        value_to_sql({"outer": {"inner": 1}})
+        == "named_struct('outer', named_struct('inner', 1))"
+    )
+
+    # List inside struct
+    assert value_to_sql({"a": [1, 2]}) == "named_struct('a', [1, 2])"
+
+    # Mixed types
+    assert (
+        value_to_sql({"name": "test", "count": 42, "rate": 3.14, "active": True})
+        == "named_struct('name', 'test', 'count', 42, 'rate', 3.14, 'active', TRUE)"
+    )
+
+    # Null value inside struct
+    assert value_to_sql({"a": None}) == "named_struct('a', NULL)"
+
+    # Empty dict
+    assert value_to_sql({}) == "named_struct()"
+
+
 def test_append_vector_columns():
     registry = EmbeddingFunctionRegistry.get_instance()
     registry.register("test")(MockTextEmbeddingFunction)

python/src/arrow.rs

@@ -10,7 +10,7 @@ use arrow::{
 use futures::stream::StreamExt;
 use lancedb::arrow::SendableRecordBatchStream;
 use pyo3::{
-    exceptions::PyStopAsyncIteration, pyclass, pymethods, Bound, Py, PyAny, PyRef, PyResult, Python,
+    Bound, Py, PyAny, PyRef, PyResult, Python, exceptions::PyStopAsyncIteration, pyclass, pymethods,
 };
 use pyo3_async_runtimes::tokio::future_into_py;
 

python/src/connection.rs

@@ -9,15 +9,16 @@ use lancedb::{
     database::{CreateTableMode, Database, ReadConsistency},
 };
 use pyo3::{
+    Bound, FromPyObject, Py, PyAny, PyRef, PyResult, Python,
     exceptions::{PyRuntimeError, PyValueError},
     pyclass, pyfunction, pymethods,
     types::{PyDict, PyDictMethods},
-    Bound, FromPyObject, Py, PyAny, PyRef, PyResult, Python,
 };
 use pyo3_async_runtimes::tokio::future_into_py;
 
 use crate::{
-    error::PythonErrorExt, storage_options::py_object_to_storage_options_provider, table::Table,
+    error::PythonErrorExt, namespace::extract_namespace_arc,
+    storage_options::py_object_to_storage_options_provider, table::Table,
 };
 
 #[pyclass]
@@ -182,7 +183,8 @@ impl Connection {
         })
     }
 
-    #[pyo3(signature = (name, namespace=vec![], storage_options = None, storage_options_provider=None, index_cache_size = None, location=None))]
+    #[allow(clippy::too_many_arguments)]
+    #[pyo3(signature = (name, namespace=vec![], storage_options = None, storage_options_provider=None, index_cache_size = None, location=None, namespace_client=None, managed_versioning=None))]
     pub fn open_table(
         self_: PyRef<'_, Self>,
         name: String,
@@ -191,11 +193,13 @@ impl Connection {
         storage_options_provider: Option<Py<PyAny>>,
         index_cache_size: Option<u32>,
         location: Option<String>,
+        namespace_client: Option<Py<PyAny>>,
+        managed_versioning: Option<bool>,
     ) -> PyResult<Bound<'_, PyAny>> {
         let inner = self_.get_inner()?.clone();
 
         let mut builder = inner.open_table(name);
-        builder = builder.namespace(namespace);
+        builder = builder.namespace(namespace.clone());
         if let Some(storage_options) = storage_options {
             builder = builder.storage_options(storage_options);
         }
@@ -209,6 +213,20 @@ impl Connection {
         if let Some(location) = location {
             builder = builder.location(location);
         }
+        // Extract namespace client from Python object if provided
+        let ns_client = if let Some(ns_obj) = namespace_client {
+            let py = self_.py();
+            Some(extract_namespace_arc(py, ns_obj)?)
+        } else {
+            None
+        };
+        if let Some(ns_client) = ns_client {
+            builder = builder.namespace_client(ns_client);
+        }
+        // Pass managed_versioning if provided to avoid redundant describe_table call
+        if let Some(enabled) = managed_versioning {
+            builder = builder.managed_versioning(enabled);
+        }
 
         future_into_py(self_.py(), async move {
             let table = builder.execute().await.infer_error()?;

python/src/error.rs

@@ -2,10 +2,10 @@
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 
 use pyo3::{
+    PyErr, PyResult, Python,
     exceptions::{PyIOError, PyNotImplementedError, PyOSError, PyRuntimeError, PyValueError},
     intern,
     types::{PyAnyMethods, PyNone},
-    PyErr, PyResult, Python,
 };
 
 use lancedb::error::Error as LanceError;

python/src/expr.rs

@@ -0,0 +1,175 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+//! PyO3 bindings for the LanceDB expression builder API.
+//!
+//! This module exposes [`PyExpr`] and helper free functions so Python can
+//! build type-safe filter / projection expressions that map directly to
+//! DataFusion [`Expr`] nodes, bypassing SQL string parsing.
+
+use arrow::{datatypes::DataType, pyarrow::PyArrowType};
+use lancedb::expr::{DfExpr, col as ldb_col, contains, expr_cast, lit as df_lit, lower, upper};
+use pyo3::{Bound, PyAny, PyResult, exceptions::PyValueError, prelude::*, pyfunction};
+
+/// A type-safe DataFusion expression.
+///
+/// Instances are constructed via the free functions [`expr_col`] and
+/// [`expr_lit`] and combined with the methods on this struct.  On the Python
+/// side a thin wrapper class (`lancedb.expr.Expr`) delegates to these methods
+/// and adds Python operator overloads.
+#[pyclass(name = "PyExpr")]
+#[derive(Clone)]
+pub struct PyExpr(pub DfExpr);
+
+#[pymethods]
+impl PyExpr {
+    // ── comparisons ──────────────────────────────────────────────────────────
+
+    fn eq(&self, other: &Self) -> Self {
+        Self(self.0.clone().eq(other.0.clone()))
+    }
+
+    fn ne(&self, other: &Self) -> Self {
+        Self(self.0.clone().not_eq(other.0.clone()))
+    }
+
+    fn lt(&self, other: &Self) -> Self {
+        Self(self.0.clone().lt(other.0.clone()))
+    }
+
+    fn lte(&self, other: &Self) -> Self {
+        Self(self.0.clone().lt_eq(other.0.clone()))
+    }
+
+    fn gt(&self, other: &Self) -> Self {
+        Self(self.0.clone().gt(other.0.clone()))
+    }
+
+    fn gte(&self, other: &Self) -> Self {
+        Self(self.0.clone().gt_eq(other.0.clone()))
+    }
+
+    // ── logical ──────────────────────────────────────────────────────────────
+
+    fn and_(&self, other: &Self) -> Self {
+        Self(self.0.clone().and(other.0.clone()))
+    }
+
+    fn or_(&self, other: &Self) -> Self {
+        Self(self.0.clone().or(other.0.clone()))
+    }
+
+    fn not_(&self) -> Self {
+        use std::ops::Not;
+        Self(self.0.clone().not())
+    }
+
+    // ── arithmetic ───────────────────────────────────────────────────────────
+
+    fn add(&self, other: &Self) -> Self {
+        use std::ops::Add;
+        Self(self.0.clone().add(other.0.clone()))
+    }
+
+    fn sub(&self, other: &Self) -> Self {
+        use std::ops::Sub;
+        Self(self.0.clone().sub(other.0.clone()))
+    }
+
+    fn mul(&self, other: &Self) -> Self {
+        use std::ops::Mul;
+        Self(self.0.clone().mul(other.0.clone()))
+    }
+
+    fn div(&self, other: &Self) -> Self {
+        use std::ops::Div;
+        Self(self.0.clone().div(other.0.clone()))
+    }
+
+    // ── string functions ─────────────────────────────────────────────────────
+
+    /// Convert string column to lowercase.
+    fn lower(&self) -> Self {
+        Self(lower(self.0.clone()))
+    }
+
+    /// Convert string column to uppercase.
+    fn upper(&self) -> Self {
+        Self(upper(self.0.clone()))
+    }
+
+    /// Test whether the string contains `substr`.
+    fn contains(&self, substr: &Self) -> Self {
+        Self(contains(self.0.clone(), substr.0.clone()))
+    }
+
+    // ── type cast ────────────────────────────────────────────────────────────
+
+    /// Cast the expression to `data_type`.
+    ///
+    /// `data_type` must be a PyArrow `DataType` (e.g. `pa.int32()`).
+    /// On the Python side, `lancedb.expr.Expr.cast` also accepts type name
+    /// strings via `pa.lib.ensure_type` before forwarding here.
+    fn cast(&self, data_type: PyArrowType<DataType>) -> Self {
+        Self(expr_cast(self.0.clone(), data_type.0))
+    }
+
+    // ── utilities ────────────────────────────────────────────────────────────
+
+    /// Render the expression as a SQL string (useful for debugging).
+    fn to_sql(&self) -> PyResult<String> {
+        lancedb::expr::expr_to_sql_string(&self.0).map_err(|e| PyValueError::new_err(e.to_string()))
+    }
+
+    fn __repr__(&self) -> PyResult<String> {
+        let sql =
+            lancedb::expr::expr_to_sql_string(&self.0).unwrap_or_else(|_| "<expr>".to_string());
+        Ok(format!("PyExpr({})", sql))
+    }
+}
+
+// ── free functions ────────────────────────────────────────────────────────────
+
+/// Create a column reference expression.
+///
+/// The column name is preserved exactly as given (case-sensitive), so
+/// `col("firstName")` correctly references a field named `firstName`.
+#[pyfunction]
+pub fn expr_col(name: &str) -> PyExpr {
+    PyExpr(ldb_col(name))
+}
+
+/// Create a literal value expression.
+///
+/// Supported Python types: `bool`, `int`, `float`, `str`.
+#[pyfunction]
+pub fn expr_lit(value: Bound<'_, PyAny>) -> PyResult<PyExpr> {
+    // bool must be checked before int because bool is a subclass of int in Python
+    if let Ok(b) = value.extract::<bool>() {
+        return Ok(PyExpr(df_lit(b)));
+    }
+    if let Ok(i) = value.extract::<i64>() {
+        return Ok(PyExpr(df_lit(i)));
+    }
+    if let Ok(f) = value.extract::<f64>() {
+        return Ok(PyExpr(df_lit(f)));
+    }
+    if let Ok(s) = value.extract::<String>() {
+        return Ok(PyExpr(df_lit(s)));
+    }
+    Err(PyValueError::new_err(format!(
+        "unsupported literal type: {}. Supported: bool, int, float, str",
+        value.get_type().name()?
+    )))
+}
+
+/// Call an arbitrary registered SQL function by name.
+///
+/// See `lancedb::expr::func` for the list of supported function names.
+#[pyfunction]
+pub fn expr_func(name: &str, args: Vec<PyExpr>) -> PyResult<PyExpr> {
+    let df_args: Vec<DfExpr> = args.into_iter().map(|e| e.0).collect();
+    lancedb::expr::func(name, df_args)
+        .map(PyExpr)
+        .map_err(|e| PyValueError::new_err(e.to_string()))
+}

python/src/index.rs

@@ -3,17 +3,17 @@
 
 use lancedb::index::vector::{IvfFlatIndexBuilder, IvfRqIndexBuilder, IvfSqIndexBuilder};
 use lancedb::index::{
+    Index as LanceDbIndex,
     scalar::{BTreeIndexBuilder, FtsIndexBuilder},
     vector::{IvfHnswPqIndexBuilder, IvfHnswSqIndexBuilder, IvfPqIndexBuilder},
-    Index as LanceDbIndex,
 };
-use pyo3::types::PyStringMethods;
 use pyo3::IntoPyObject;
+use pyo3::types::PyStringMethods;
 use pyo3::{
+    Bound, FromPyObject, PyAny, PyResult, Python,
     exceptions::{PyKeyError, PyValueError},
     intern, pyclass, pymethods,
     types::PyAnyMethods,
-    Bound, FromPyObject, PyAny, PyResult, Python,
 };
 
 use crate::util::parse_distance_type;
@@ -41,7 +41,12 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                 let inner_opts = FtsIndexBuilder::default()
                     .base_tokenizer(params.base_tokenizer)
                     .language(&params.language)
-                    .map_err(|_| PyValueError::new_err(format!("LanceDB does not support the requested language: '{}'", params.language)))?
+                    .map_err(|_| {
+                        PyValueError::new_err(format!(
+                            "LanceDB does not support the requested language: '{}'",
+                            params.language
+                        ))
+                    })?
                     .with_position(params.with_position)
                     .lower_case(params.lower_case)
                     .max_token_length(params.max_token_length)
@@ -52,7 +57,7 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                     .ngram_max_length(params.ngram_max_length)
                     .ngram_prefix_only(params.prefix_only);
                 Ok(LanceDbIndex::FTS(inner_opts))
-            },
+            }
             "IvfFlat" => {
                 let params = source.extract::<IvfFlatParams>()?;
                 let distance_type = parse_distance_type(params.distance_type)?;
@@ -64,10 +69,11 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                     ivf_flat_builder = ivf_flat_builder.num_partitions(num_partitions);
                 }
                 if let Some(target_partition_size) = params.target_partition_size {
-                    ivf_flat_builder = ivf_flat_builder.target_partition_size(target_partition_size);
+                    ivf_flat_builder =
+                        ivf_flat_builder.target_partition_size(target_partition_size);
                 }
                 Ok(LanceDbIndex::IvfFlat(ivf_flat_builder))
-            },
+            }
             "IvfPq" => {
                 let params = source.extract::<IvfPqParams>()?;
                 let distance_type = parse_distance_type(params.distance_type)?;
@@ -86,7 +92,7 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                     ivf_pq_builder = ivf_pq_builder.num_sub_vectors(num_sub_vectors);
                 }
                 Ok(LanceDbIndex::IvfPq(ivf_pq_builder))
-            },
+            }
             "IvfSq" => {
                 let params = source.extract::<IvfSqParams>()?;
                 let distance_type = parse_distance_type(params.distance_type)?;
@@ -101,7 +107,7 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                     ivf_sq_builder = ivf_sq_builder.target_partition_size(target_partition_size);
                 }
                 Ok(LanceDbIndex::IvfSq(ivf_sq_builder))
-            },
+            }
             "IvfRq" => {
                 let params = source.extract::<IvfRqParams>()?;
                 let distance_type = parse_distance_type(params.distance_type)?;
@@ -117,7 +123,7 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                     ivf_rq_builder = ivf_rq_builder.target_partition_size(target_partition_size);
                 }
                 Ok(LanceDbIndex::IvfRq(ivf_rq_builder))
-            },
+            }
             "HnswPq" => {
                 let params = source.extract::<IvfHnswPqParams>()?;
                 let distance_type = parse_distance_type(params.distance_type)?;
@@ -138,7 +144,7 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                     hnsw_pq_builder = hnsw_pq_builder.num_sub_vectors(num_sub_vectors);
                 }
                 Ok(LanceDbIndex::IvfHnswPq(hnsw_pq_builder))
-            },
+            }
             "HnswSq" => {
                 let params = source.extract::<IvfHnswSqParams>()?;
                 let distance_type = parse_distance_type(params.distance_type)?;
@@ -155,7 +161,7 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                     hnsw_sq_builder = hnsw_sq_builder.target_partition_size(target_partition_size);
                 }
                 Ok(LanceDbIndex::IvfHnswSq(hnsw_sq_builder))
-            },
+            }
             not_supported => Err(PyValueError::new_err(format!(
                 "Invalid index type '{}'.  Must be one of BTree, Bitmap, LabelList, FTS, IvfPq, IvfSq, IvfHnswPq, or IvfHnswSq",
                 not_supported

python/src/lib.rs

@@ -2,14 +2,15 @@
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 
 use arrow::RecordBatchStream;
-use connection::{connect, Connection};
+use connection::{Connection, connect};
 use env_logger::Env;
+use expr::{PyExpr, expr_col, expr_func, expr_lit};
 use index::IndexConfig;
 use permutation::{PyAsyncPermutationBuilder, PyPermutationReader};
 use pyo3::{
-    pymodule,
+    Bound, PyResult, Python, pymodule,
     types::{PyModule, PyModuleMethods},
-    wrap_pyfunction, Bound, PyResult, Python,
+    wrap_pyfunction,
 };
 use query::{FTSQuery, HybridQuery, Query, VectorQuery};
 use session::Session;
@@ -21,8 +22,10 @@ use table::{
 pub mod arrow;
 pub mod connection;
 pub mod error;
+pub mod expr;
 pub mod header;
 pub mod index;
+pub mod namespace;
 pub mod permutation;
 pub mod query;
 pub mod session;
@@ -54,10 +57,14 @@ pub fn _lancedb(_py: Python, m: &Bound<'_, PyModule>) -> PyResult<()> {
     m.add_class::<UpdateResult>()?;
     m.add_class::<PyAsyncPermutationBuilder>()?;
     m.add_class::<PyPermutationReader>()?;
+    m.add_class::<PyExpr>()?;
     m.add_function(wrap_pyfunction!(connect, m)?)?;
     m.add_function(wrap_pyfunction!(permutation::async_permutation_builder, m)?)?;
     m.add_function(wrap_pyfunction!(util::validate_table_name, m)?)?;
     m.add_function(wrap_pyfunction!(query::fts_query_to_json, m)?)?;
+    m.add_function(wrap_pyfunction!(expr_col, m)?)?;
+    m.add_function(wrap_pyfunction!(expr_lit, m)?)?;
+    m.add_function(wrap_pyfunction!(expr_func, m)?)?;
     m.add("__version__", env!("CARGO_PKG_VERSION"))?;
     Ok(())
 }

python/src/namespace.rs

@@ -0,0 +1,696 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+//! Namespace utilities for Python bindings
+
+use std::collections::HashMap;
+use std::sync::Arc;
+
+use async_trait::async_trait;
+use bytes::Bytes;
+use lance_namespace::LanceNamespace as LanceNamespaceTrait;
+use lance_namespace::models::*;
+use pyo3::prelude::*;
+use pyo3::types::PyDict;
+
+/// Wrapper that allows any Python object implementing LanceNamespace protocol
+/// to be used as a Rust LanceNamespace.
+///
+/// This is similar to PyLanceNamespace in lance's Python bindings - it wraps a Python
+/// object and calls back into Python when namespace methods are invoked.
+pub struct PyLanceNamespace {
+    py_namespace: Arc<Py<PyAny>>,
+    namespace_id: String,
+}
+
+impl PyLanceNamespace {
+    /// Create a new PyLanceNamespace wrapper around a Python namespace object.
+    pub fn new(_py: Python<'_>, py_namespace: &Bound<'_, PyAny>) -> PyResult<Self> {
+        let namespace_id = py_namespace
+            .call_method0("namespace_id")?
+            .extract::<String>()?;
+
+        Ok(Self {
+            py_namespace: Arc::new(py_namespace.clone().unbind()),
+            namespace_id,
+        })
+    }
+
+    /// Create an Arc<dyn LanceNamespace> from a Python namespace object.
+    pub fn create_arc(
+        py: Python<'_>,
+        py_namespace: &Bound<'_, PyAny>,
+    ) -> PyResult<Arc<dyn LanceNamespaceTrait>> {
+        let wrapper = Self::new(py, py_namespace)?;
+        Ok(Arc::new(wrapper))
+    }
+}
+
+impl std::fmt::Debug for PyLanceNamespace {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        write!(f, "PyLanceNamespace {{ id: {} }}", self.namespace_id)
+    }
+}
+
+/// Get or create the DictWithModelDump class in Python.
+/// This class acts like a dict but also has model_dump() method.
+/// This allows it to work with both:
+/// - depythonize (which expects a dict/Mapping)
+/// - Python code that calls .model_dump() (like DirectoryNamespace wrapper)
+fn get_dict_with_model_dump_class(py: Python<'_>) -> PyResult<Bound<'_, PyAny>> {
+    // Use a module-level cache via __builtins__
+    let builtins = py.import("builtins")?;
+    if builtins.hasattr("_DictWithModelDump")? {
+        return builtins.getattr("_DictWithModelDump");
+    }
+
+    // Create the class using exec
+    let locals = PyDict::new(py);
+    py.run(
+        c"class DictWithModelDump(dict):
+    def model_dump(self):
+        return dict(self)",
+        None,
+        Some(&locals),
+    )?;
+    let class = locals.get_item("DictWithModelDump")?.ok_or_else(|| {
+        pyo3::exceptions::PyRuntimeError::new_err("Failed to create DictWithModelDump class")
+    })?;
+
+    // Cache it
+    builtins.setattr("_DictWithModelDump", &class)?;
+    Ok(class)
+}
+
+/// Helper to call a Python namespace method with JSON serialization.
+/// For methods that take a request and return a response.
+/// Uses DictWithModelDump to pass a dict that also has model_dump() method,
+/// making it compatible with both depythonize and Python wrappers.
+async fn call_py_method<Req, Resp>(
+    py_namespace: Arc<Py<PyAny>>,
+    method_name: &'static str,
+    request: Req,
+) -> lance_core::Result<Resp>
+where
+    Req: serde::Serialize + Send + 'static,
+    Resp: serde::de::DeserializeOwned + Send + 'static,
+{
+    let request_json = serde_json::to_string(&request).map_err(|e| {
+        lance_core::Error::io(format!(
+            "Failed to serialize request for {}: {}",
+            method_name, e
+        ))
+    })?;
+
+    let response_json = tokio::task::spawn_blocking(move || {
+        Python::attach(|py| {
+            let json_module = py.import("json")?;
+            let request_dict = json_module.call_method1("loads", (&request_json,))?;
+
+            // Wrap dict in DictWithModelDump so it works with both depythonize and .model_dump()
+            let dict_class = get_dict_with_model_dump_class(py)?;
+            let request_arg = dict_class.call1((request_dict,))?;
+
+            // Call the Python method
+            let result = py_namespace.call_method1(py, method_name, (request_arg,))?;
+
+            // Convert response to dict, then to JSON
+            // Pydantic models have model_dump() method
+            let result_dict = if result.bind(py).hasattr("model_dump")? {
+                result.call_method0(py, "model_dump")?
+            } else {
+                result
+            };
+            let response_json: String = json_module
+                .call_method1("dumps", (result_dict,))?
+                .extract()?;
+            Ok::<_, PyErr>(response_json)
+        })
+    })
+    .await
+    .map_err(|e| lance_core::Error::io(format!("Task join error for {}: {}", method_name, e)))?
+    .map_err(|e: PyErr| lance_core::Error::io(format!("Python error in {}: {}", method_name, e)))?;
+
+    serde_json::from_str(&response_json).map_err(|e| {
+        lance_core::Error::io(format!(
+            "Failed to deserialize response from {}: {}",
+            method_name, e
+        ))
+    })
+}
+
+/// Helper for methods that return () on success
+async fn call_py_method_unit<Req>(
+    py_namespace: Arc<Py<PyAny>>,
+    method_name: &'static str,
+    request: Req,
+) -> lance_core::Result<()>
+where
+    Req: serde::Serialize + Send + 'static,
+{
+    let request_json = serde_json::to_string(&request).map_err(|e| {
+        lance_core::Error::io(format!(
+            "Failed to serialize request for {}: {}",
+            method_name, e
+        ))
+    })?;
+
+    tokio::task::spawn_blocking(move || {
+        Python::attach(|py| {
+            let json_module = py.import("json")?;
+            let request_dict = json_module.call_method1("loads", (&request_json,))?;
+
+            // Wrap dict in DictWithModelDump
+            let dict_class = get_dict_with_model_dump_class(py)?;
+            let request_arg = dict_class.call1((request_dict,))?;
+
+            // Call the Python method
+            py_namespace.call_method1(py, method_name, (request_arg,))?;
+            Ok::<_, PyErr>(())
+        })
+    })
+    .await
+    .map_err(|e| lance_core::Error::io(format!("Task join error for {}: {}", method_name, e)))?
+    .map_err(|e: PyErr| lance_core::Error::io(format!("Python error in {}: {}", method_name, e)))
+}
+
+/// Helper for methods that return a primitive type
+async fn call_py_method_primitive<Req, Resp>(
+    py_namespace: Arc<Py<PyAny>>,
+    method_name: &'static str,
+    request: Req,
+) -> lance_core::Result<Resp>
+where
+    Req: serde::Serialize + Send + 'static,
+    Resp: for<'py> pyo3::FromPyObject<'py> + Send + 'static,
+{
+    let request_json = serde_json::to_string(&request).map_err(|e| {
+        lance_core::Error::io(format!(
+            "Failed to serialize request for {}: {}",
+            method_name, e
+        ))
+    })?;
+
+    tokio::task::spawn_blocking(move || {
+        Python::attach(|py| {
+            let json_module = py.import("json")?;
+            let request_dict = json_module.call_method1("loads", (&request_json,))?;
+
+            // Wrap dict in DictWithModelDump
+            let dict_class = get_dict_with_model_dump_class(py)?;
+            let request_arg = dict_class.call1((request_dict,))?;
+
+            // Call the Python method
+            let result = py_namespace.call_method1(py, method_name, (request_arg,))?;
+            let value: Resp = result.extract(py)?;
+            Ok::<_, PyErr>(value)
+        })
+    })
+    .await
+    .map_err(|e| lance_core::Error::io(format!("Task join error for {}: {}", method_name, e)))?
+    .map_err(|e: PyErr| lance_core::Error::io(format!("Python error in {}: {}", method_name, e)))
+}
+
+/// Helper for methods that return Bytes
+async fn call_py_method_bytes<Req>(
+    py_namespace: Arc<Py<PyAny>>,
+    method_name: &'static str,
+    request: Req,
+) -> lance_core::Result<Bytes>
+where
+    Req: serde::Serialize + Send + 'static,
+{
+    let request_json = serde_json::to_string(&request).map_err(|e| {
+        lance_core::Error::io(format!(
+            "Failed to serialize request for {}: {}",
+            method_name, e
+        ))
+    })?;
+
+    tokio::task::spawn_blocking(move || {
+        Python::attach(|py| {
+            let json_module = py.import("json")?;
+            let request_dict = json_module.call_method1("loads", (&request_json,))?;
+
+            // Wrap dict in DictWithModelDump
+            let dict_class = get_dict_with_model_dump_class(py)?;
+            let request_arg = dict_class.call1((request_dict,))?;
+
+            // Call the Python method
+            let result = py_namespace.call_method1(py, method_name, (request_arg,))?;
+            let bytes_data: Vec<u8> = result.extract(py)?;
+            Ok::<_, PyErr>(Bytes::from(bytes_data))
+        })
+    })
+    .await
+    .map_err(|e| lance_core::Error::io(format!("Task join error for {}: {}", method_name, e)))?
+    .map_err(|e: PyErr| lance_core::Error::io(format!("Python error in {}: {}", method_name, e)))
+}
+
+/// Helper for methods that take request + data and return a response
+async fn call_py_method_with_data<Req, Resp>(
+    py_namespace: Arc<Py<PyAny>>,
+    method_name: &'static str,
+    request: Req,
+    data: Bytes,
+) -> lance_core::Result<Resp>
+where
+    Req: serde::Serialize + Send + 'static,
+    Resp: serde::de::DeserializeOwned + Send + 'static,
+{
+    let request_json = serde_json::to_string(&request).map_err(|e| {
+        lance_core::Error::io(format!(
+            "Failed to serialize request for {}: {}",
+            method_name, e
+        ))
+    })?;
+
+    let response_json = tokio::task::spawn_blocking(move || {
+        Python::attach(|py| {
+            let json_module = py.import("json")?;
+            let request_dict = json_module.call_method1("loads", (&request_json,))?;
+
+            // Wrap dict in DictWithModelDump
+            let dict_class = get_dict_with_model_dump_class(py)?;
+            let request_arg = dict_class.call1((request_dict,))?;
+
+            // Pass request and bytes to Python method
+            let py_bytes = pyo3::types::PyBytes::new(py, &data);
+            let result = py_namespace.call_method1(py, method_name, (request_arg, py_bytes))?;
+
+            // Convert response dict to JSON
+            let response_json: String = json_module.call_method1("dumps", (result,))?.extract()?;
+            Ok::<_, PyErr>(response_json)
+        })
+    })
+    .await
+    .map_err(|e| lance_core::Error::io(format!("Task join error for {}: {}", method_name, e)))?
+    .map_err(|e: PyErr| lance_core::Error::io(format!("Python error in {}: {}", method_name, e)))?;
+
+    serde_json::from_str(&response_json).map_err(|e| {
+        lance_core::Error::io(format!(
+            "Failed to deserialize response from {}: {}",
+            method_name, e
+        ))
+    })
+}
+
+#[async_trait]
+impl LanceNamespaceTrait for PyLanceNamespace {
+    fn namespace_id(&self) -> String {
+        self.namespace_id.clone()
+    }
+
+    async fn list_namespaces(
+        &self,
+        request: ListNamespacesRequest,
+    ) -> lance_core::Result<ListNamespacesResponse> {
+        call_py_method(self.py_namespace.clone(), "list_namespaces", request).await
+    }
+
+    async fn describe_namespace(
+        &self,
+        request: DescribeNamespaceRequest,
+    ) -> lance_core::Result<DescribeNamespaceResponse> {
+        call_py_method(self.py_namespace.clone(), "describe_namespace", request).await
+    }
+
+    async fn create_namespace(
+        &self,
+        request: CreateNamespaceRequest,
+    ) -> lance_core::Result<CreateNamespaceResponse> {
+        call_py_method(self.py_namespace.clone(), "create_namespace", request).await
+    }
+
+    async fn drop_namespace(
+        &self,
+        request: DropNamespaceRequest,
+    ) -> lance_core::Result<DropNamespaceResponse> {
+        call_py_method(self.py_namespace.clone(), "drop_namespace", request).await
+    }
+
+    async fn namespace_exists(&self, request: NamespaceExistsRequest) -> lance_core::Result<()> {
+        call_py_method_unit(self.py_namespace.clone(), "namespace_exists", request).await
+    }
+
+    async fn list_tables(
+        &self,
+        request: ListTablesRequest,
+    ) -> lance_core::Result<ListTablesResponse> {
+        call_py_method(self.py_namespace.clone(), "list_tables", request).await
+    }
+
+    async fn describe_table(
+        &self,
+        request: DescribeTableRequest,
+    ) -> lance_core::Result<DescribeTableResponse> {
+        call_py_method(self.py_namespace.clone(), "describe_table", request).await
+    }
+
+    async fn register_table(
+        &self,
+        request: RegisterTableRequest,
+    ) -> lance_core::Result<RegisterTableResponse> {
+        call_py_method(self.py_namespace.clone(), "register_table", request).await
+    }
+
+    async fn table_exists(&self, request: TableExistsRequest) -> lance_core::Result<()> {
+        call_py_method_unit(self.py_namespace.clone(), "table_exists", request).await
+    }
+
+    async fn drop_table(&self, request: DropTableRequest) -> lance_core::Result<DropTableResponse> {
+        call_py_method(self.py_namespace.clone(), "drop_table", request).await
+    }
+
+    async fn deregister_table(
+        &self,
+        request: DeregisterTableRequest,
+    ) -> lance_core::Result<DeregisterTableResponse> {
+        call_py_method(self.py_namespace.clone(), "deregister_table", request).await
+    }
+
+    async fn count_table_rows(&self, request: CountTableRowsRequest) -> lance_core::Result<i64> {
+        call_py_method_primitive(self.py_namespace.clone(), "count_table_rows", request).await
+    }
+
+    async fn create_table(
+        &self,
+        request: CreateTableRequest,
+        request_data: Bytes,
+    ) -> lance_core::Result<CreateTableResponse> {
+        call_py_method_with_data(
+            self.py_namespace.clone(),
+            "create_table",
+            request,
+            request_data,
+        )
+        .await
+    }
+
+    async fn declare_table(
+        &self,
+        request: DeclareTableRequest,
+    ) -> lance_core::Result<DeclareTableResponse> {
+        call_py_method(self.py_namespace.clone(), "declare_table", request).await
+    }
+
+    async fn insert_into_table(
+        &self,
+        request: InsertIntoTableRequest,
+        request_data: Bytes,
+    ) -> lance_core::Result<InsertIntoTableResponse> {
+        call_py_method_with_data(
+            self.py_namespace.clone(),
+            "insert_into_table",
+            request,
+            request_data,
+        )
+        .await
+    }
+
+    async fn merge_insert_into_table(
+        &self,
+        request: MergeInsertIntoTableRequest,
+        request_data: Bytes,
+    ) -> lance_core::Result<MergeInsertIntoTableResponse> {
+        call_py_method_with_data(
+            self.py_namespace.clone(),
+            "merge_insert_into_table",
+            request,
+            request_data,
+        )
+        .await
+    }
+
+    async fn update_table(
+        &self,
+        request: UpdateTableRequest,
+    ) -> lance_core::Result<UpdateTableResponse> {
+        call_py_method(self.py_namespace.clone(), "update_table", request).await
+    }
+
+    async fn delete_from_table(
+        &self,
+        request: DeleteFromTableRequest,
+    ) -> lance_core::Result<DeleteFromTableResponse> {
+        call_py_method(self.py_namespace.clone(), "delete_from_table", request).await
+    }
+
+    async fn query_table(&self, request: QueryTableRequest) -> lance_core::Result<Bytes> {
+        call_py_method_bytes(self.py_namespace.clone(), "query_table", request).await
+    }
+
+    async fn create_table_index(
+        &self,
+        request: CreateTableIndexRequest,
+    ) -> lance_core::Result<CreateTableIndexResponse> {
+        call_py_method(self.py_namespace.clone(), "create_table_index", request).await
+    }
+
+    async fn list_table_indices(
+        &self,
+        request: ListTableIndicesRequest,
+    ) -> lance_core::Result<ListTableIndicesResponse> {
+        call_py_method(self.py_namespace.clone(), "list_table_indices", request).await
+    }
+
+    async fn describe_table_index_stats(
+        &self,
+        request: DescribeTableIndexStatsRequest,
+    ) -> lance_core::Result<DescribeTableIndexStatsResponse> {
+        call_py_method(
+            self.py_namespace.clone(),
+            "describe_table_index_stats",
+            request,
+        )
+        .await
+    }
+
+    async fn describe_transaction(
+        &self,
+        request: DescribeTransactionRequest,
+    ) -> lance_core::Result<DescribeTransactionResponse> {
+        call_py_method(self.py_namespace.clone(), "describe_transaction", request).await
+    }
+
+    async fn alter_transaction(
+        &self,
+        request: AlterTransactionRequest,
+    ) -> lance_core::Result<AlterTransactionResponse> {
+        call_py_method(self.py_namespace.clone(), "alter_transaction", request).await
+    }
+
+    async fn create_table_scalar_index(
+        &self,
+        request: CreateTableIndexRequest,
+    ) -> lance_core::Result<CreateTableScalarIndexResponse> {
+        call_py_method(
+            self.py_namespace.clone(),
+            "create_table_scalar_index",
+            request,
+        )
+        .await
+    }
+
+    async fn drop_table_index(
+        &self,
+        request: DropTableIndexRequest,
+    ) -> lance_core::Result<DropTableIndexResponse> {
+        call_py_method(self.py_namespace.clone(), "drop_table_index", request).await
+    }
+
+    async fn list_all_tables(
+        &self,
+        request: ListTablesRequest,
+    ) -> lance_core::Result<ListTablesResponse> {
+        call_py_method(self.py_namespace.clone(), "list_all_tables", request).await
+    }
+
+    async fn restore_table(
+        &self,
+        request: RestoreTableRequest,
+    ) -> lance_core::Result<RestoreTableResponse> {
+        call_py_method(self.py_namespace.clone(), "restore_table", request).await
+    }
+
+    async fn rename_table(
+        &self,
+        request: RenameTableRequest,
+    ) -> lance_core::Result<RenameTableResponse> {
+        call_py_method(self.py_namespace.clone(), "rename_table", request).await
+    }
+
+    async fn list_table_versions(
+        &self,
+        request: ListTableVersionsRequest,
+    ) -> lance_core::Result<ListTableVersionsResponse> {
+        call_py_method(self.py_namespace.clone(), "list_table_versions", request).await
+    }
+
+    async fn create_table_version(
+        &self,
+        request: CreateTableVersionRequest,
+    ) -> lance_core::Result<CreateTableVersionResponse> {
+        call_py_method(self.py_namespace.clone(), "create_table_version", request).await
+    }
+
+    async fn describe_table_version(
+        &self,
+        request: DescribeTableVersionRequest,
+    ) -> lance_core::Result<DescribeTableVersionResponse> {
+        call_py_method(self.py_namespace.clone(), "describe_table_version", request).await
+    }
+
+    async fn batch_delete_table_versions(
+        &self,
+        request: BatchDeleteTableVersionsRequest,
+    ) -> lance_core::Result<BatchDeleteTableVersionsResponse> {
+        call_py_method(
+            self.py_namespace.clone(),
+            "batch_delete_table_versions",
+            request,
+        )
+        .await
+    }
+
+    async fn update_table_schema_metadata(
+        &self,
+        request: UpdateTableSchemaMetadataRequest,
+    ) -> lance_core::Result<UpdateTableSchemaMetadataResponse> {
+        call_py_method(
+            self.py_namespace.clone(),
+            "update_table_schema_metadata",
+            request,
+        )
+        .await
+    }
+
+    async fn get_table_stats(
+        &self,
+        request: GetTableStatsRequest,
+    ) -> lance_core::Result<GetTableStatsResponse> {
+        call_py_method(self.py_namespace.clone(), "get_table_stats", request).await
+    }
+
+    async fn explain_table_query_plan(
+        &self,
+        request: ExplainTableQueryPlanRequest,
+    ) -> lance_core::Result<String> {
+        call_py_method_primitive(
+            self.py_namespace.clone(),
+            "explain_table_query_plan",
+            request,
+        )
+        .await
+    }
+
+    async fn analyze_table_query_plan(
+        &self,
+        request: AnalyzeTableQueryPlanRequest,
+    ) -> lance_core::Result<String> {
+        call_py_method_primitive(
+            self.py_namespace.clone(),
+            "analyze_table_query_plan",
+            request,
+        )
+        .await
+    }
+
+    async fn alter_table_add_columns(
+        &self,
+        request: AlterTableAddColumnsRequest,
+    ) -> lance_core::Result<AlterTableAddColumnsResponse> {
+        call_py_method(
+            self.py_namespace.clone(),
+            "alter_table_add_columns",
+            request,
+        )
+        .await
+    }
+
+    async fn alter_table_alter_columns(
+        &self,
+        request: AlterTableAlterColumnsRequest,
+    ) -> lance_core::Result<AlterTableAlterColumnsResponse> {
+        call_py_method(
+            self.py_namespace.clone(),
+            "alter_table_alter_columns",
+            request,
+        )
+        .await
+    }
+
+    async fn alter_table_drop_columns(
+        &self,
+        request: AlterTableDropColumnsRequest,
+    ) -> lance_core::Result<AlterTableDropColumnsResponse> {
+        call_py_method(
+            self.py_namespace.clone(),
+            "alter_table_drop_columns",
+            request,
+        )
+        .await
+    }
+
+    async fn list_table_tags(
+        &self,
+        request: ListTableTagsRequest,
+    ) -> lance_core::Result<ListTableTagsResponse> {
+        call_py_method(self.py_namespace.clone(), "list_table_tags", request).await
+    }
+
+    async fn create_table_tag(
+        &self,
+        request: CreateTableTagRequest,
+    ) -> lance_core::Result<CreateTableTagResponse> {
+        call_py_method(self.py_namespace.clone(), "create_table_tag", request).await
+    }
+
+    async fn delete_table_tag(
+        &self,
+        request: DeleteTableTagRequest,
+    ) -> lance_core::Result<DeleteTableTagResponse> {
+        call_py_method(self.py_namespace.clone(), "delete_table_tag", request).await
+    }
+
+    async fn update_table_tag(
+        &self,
+        request: UpdateTableTagRequest,
+    ) -> lance_core::Result<UpdateTableTagResponse> {
+        call_py_method(self.py_namespace.clone(), "update_table_tag", request).await
+    }
+
+    async fn get_table_tag_version(
+        &self,
+        request: GetTableTagVersionRequest,
+    ) -> lance_core::Result<GetTableTagVersionResponse> {
+        call_py_method(self.py_namespace.clone(), "get_table_tag_version", request).await
+    }
+}
+
+/// Convert Python dict to HashMap<String, String>
+#[allow(dead_code)]
+fn dict_to_hashmap(dict: &Bound<'_, PyDict>) -> PyResult<HashMap<String, String>> {
+    let mut map = HashMap::new();
+    for (key, value) in dict.iter() {
+        let key_str: String = key.extract()?;
+        let value_str: String = value.extract()?;
+        map.insert(key_str, value_str);
+    }
+    Ok(map)
+}
+
+/// Extract an Arc<dyn LanceNamespace> from a Python namespace object.
+///
+/// This function wraps any Python namespace object with PyLanceNamespace.
+/// The PyLanceNamespace wrapper uses DictWithModelDump to pass requests,
+/// which works with both:
+/// - Native namespaces (DirectoryNamespace, RestNamespace) that use depythonize (expects dict)
+/// - Custom Python implementations that call .model_dump() on the request
+pub fn extract_namespace_arc(
+    py: Python<'_>,
+    ns: Py<PyAny>,
+) -> PyResult<Arc<dyn LanceNamespaceTrait>> {
+    let ns_ref = ns.bind(py);
+    PyLanceNamespace::create_arc(py, ns_ref)
+}

python/src/permutation.rs

@@ -16,10 +16,10 @@ use lancedb::{
     query::Select,
 };
 use pyo3::{
+    Bound, PyAny, PyRef, PyRefMut, PyResult, Python,
     exceptions::PyRuntimeError,
     pyclass, pymethods,
     types::{PyAnyMethods, PyDict, PyDictMethods, PyType},
-    Bound, PyAny, PyRef, PyRefMut, PyResult, Python,
 };
 use pyo3_async_runtimes::tokio::future_into_py;
 

python/src/query.rs

@@ -4,9 +4,9 @@
 use std::sync::Arc;
 use std::time::Duration;
 
-use arrow::array::make_array;
 use arrow::array::Array;
 use arrow::array::ArrayData;
+use arrow::array::make_array;
 use arrow::pyarrow::FromPyArrow;
 use arrow::pyarrow::IntoPyArrow;
 use arrow::pyarrow::ToPyArrow;
@@ -22,25 +22,23 @@ use lancedb::query::{
     VectorQuery as LanceDbVectorQuery,
 };
 use lancedb::table::AnyQuery;
-use pyo3::prelude::{PyAnyMethods, PyDictMethods};
-use pyo3::pyfunction;
-use pyo3::pymethods;
-use pyo3::types::PyList;
-use pyo3::types::{PyDict, PyString};
 use pyo3::Bound;
 use pyo3::IntoPyObject;
 use pyo3::PyAny;
 use pyo3::PyRef;
 use pyo3::PyResult;
 use pyo3::Python;
-use pyo3::{exceptions::PyRuntimeError, FromPyObject};
+use pyo3::prelude::{PyAnyMethods, PyDictMethods};
-use pyo3::{
+use pyo3::pyfunction;
-    exceptions::{PyNotImplementedError, PyValueError},
+use pyo3::pymethods;
-    intern,
+use pyo3::types::PyList;
-};
+use pyo3::types::{PyDict, PyString};
-use pyo3::{pyclass, PyErr};
+use pyo3::{FromPyObject, exceptions::PyRuntimeError};
+use pyo3::{PyErr, pyclass};
+use pyo3::{exceptions::PyValueError, intern};
 use pyo3_async_runtimes::tokio::future_into_py;
 
+use crate::expr::PyExpr;
 use crate::util::parse_distance_type;
 use crate::{arrow::RecordBatchStream, util::PyLanceDB};
 use crate::{error::PythonErrorExt, index::class_name};
@@ -316,6 +314,19 @@ impl<'py> IntoPyObject<'py> for PySelect {
             Select::All => Ok(py.None().into_bound(py).into_any()),
             Select::Columns(columns) => Ok(columns.into_pyobject(py)?.into_any()),
             Select::Dynamic(columns) => Ok(columns.into_pyobject(py)?.into_any()),
+            Select::Expr(pairs) => {
+                // Serialize DataFusion Expr -> SQL string so Python sees the same
+                // format as Select::Dynamic: a list of (name, sql_string) tuples.
+                let sql_pairs: PyResult<Vec<(String, String)>> = pairs
+                    .into_iter()
+                    .map(|(name, expr)| {
+                        lancedb::expr::expr_to_sql_string(&expr)
+                            .map(|sql| (name, sql))
+                            .map_err(|e| PyRuntimeError::new_err(e.to_string()))
+                    })
+                    .collect();
+                Ok(sql_pairs?.into_pyobject(py)?.into_any())
+            }
         }
     }
 }
@@ -331,9 +342,13 @@ impl<'py> IntoPyObject<'py> for PyQueryFilter {
 
     fn into_pyobject(self, py: pyo3::Python<'py>) -> PyResult<Self::Output> {
         match self.0 {
-            QueryFilter::Datafusion(_) => Err(PyNotImplementedError::new_err(
+            QueryFilter::Datafusion(expr) => {
-                "Datafusion filter has no conversion to Python",
+                // Serialize the DataFusion expression to a SQL string so that
-            )),
+                // callers (e.g. remote tables) see the same format as Sql.
+                let sql = lancedb::expr::expr_to_sql_string(&expr)
+                    .map_err(|e| PyRuntimeError::new_err(e.to_string()))?;
+                Ok(sql.into_pyobject(py)?.into_any())
+            }
             QueryFilter::Sql(sql) => Ok(sql.into_pyobject(py)?.into_any()),
             QueryFilter::Substrait(substrait) => Ok(substrait.into_pyobject(py)?.into_any()),
         }
@@ -357,10 +372,20 @@ impl Query {
         self.inner = self.inner.clone().only_if(predicate);
     }
 
+    pub fn where_expr(&mut self, expr: PyExpr) {
+        self.inner = self.inner.clone().only_if_expr(expr.0);
+    }
+
     pub fn select(&mut self, columns: Vec<(String, String)>) {
         self.inner = self.inner.clone().select(Select::dynamic(&columns));
     }
 
+    pub fn select_expr(&mut self, columns: Vec<(String, PyExpr)>) {
+        let pairs: Vec<(String, lancedb::expr::DfExpr)> =
+            columns.into_iter().map(|(name, e)| (name, e.0)).collect();
+        self.inner = self.inner.clone().select(Select::Expr(pairs));
+    }
+
     pub fn select_columns(&mut self, columns: Vec<String>) {
         self.inner = self.inner.clone().select(Select::columns(&columns));
     }
@@ -594,10 +619,20 @@ impl FTSQuery {
         self.inner = self.inner.clone().only_if(predicate);
     }
 
+    pub fn where_expr(&mut self, expr: PyExpr) {
+        self.inner = self.inner.clone().only_if_expr(expr.0);
+    }
+
     pub fn select(&mut self, columns: Vec<(String, String)>) {
         self.inner = self.inner.clone().select(Select::dynamic(&columns));
     }
 
+    pub fn select_expr(&mut self, columns: Vec<(String, PyExpr)>) {
+        let pairs: Vec<(String, lancedb::expr::DfExpr)> =
+            columns.into_iter().map(|(name, e)| (name, e.0)).collect();
+        self.inner = self.inner.clone().select(Select::Expr(pairs));
+    }
+
     pub fn select_columns(&mut self, columns: Vec<String>) {
         self.inner = self.inner.clone().select(Select::columns(&columns));
     }
@@ -712,6 +747,10 @@ impl VectorQuery {
         self.inner = self.inner.clone().only_if(predicate);
     }
 
+    pub fn where_expr(&mut self, expr: PyExpr) {
+        self.inner = self.inner.clone().only_if_expr(expr.0);
+    }
+
     pub fn add_query_vector(&mut self, vector: Bound<'_, PyAny>) -> PyResult<()> {
         let data: ArrayData = ArrayData::from_pyarrow_bound(&vector)?;
         let array = make_array(data);
@@ -723,6 +762,12 @@ impl VectorQuery {
         self.inner = self.inner.clone().select(Select::dynamic(&columns));
     }
 
+    pub fn select_expr(&mut self, columns: Vec<(String, PyExpr)>) {
+        let pairs: Vec<(String, lancedb::expr::DfExpr)> =
+            columns.into_iter().map(|(name, e)| (name, e.0)).collect();
+        self.inner = self.inner.clone().select(Select::Expr(pairs));
+    }
+
     pub fn select_columns(&mut self, columns: Vec<String>) {
         self.inner = self.inner.clone().select(Select::columns(&columns));
     }
@@ -877,11 +922,21 @@ impl HybridQuery {
         self.inner_fts.r#where(predicate);
     }
 
+    pub fn where_expr(&mut self, expr: PyExpr) {
+        self.inner_vec.where_expr(expr.clone());
+        self.inner_fts.where_expr(expr);
+    }
+
     pub fn select(&mut self, columns: Vec<(String, String)>) {
         self.inner_vec.select(columns.clone());
         self.inner_fts.select(columns);
     }
 
+    pub fn select_expr(&mut self, columns: Vec<(String, PyExpr)>) {
+        self.inner_vec.select_expr(columns.clone());
+        self.inner_fts.select_expr(columns);
+    }
+
     pub fn select_columns(&mut self, columns: Vec<String>) {
         self.inner_vec.select_columns(columns.clone());
         self.inner_fts.select_columns(columns);

python/src/session.rs

@@ -4,7 +4,7 @@
 use std::sync::Arc;
 
 use lancedb::{ObjectStoreRegistry, Session as LanceSession};
-use pyo3::{pyclass, pymethods, PyResult};
+use pyo3::{PyResult, pyclass, pymethods};
 
 /// A session for managing caches and object stores across LanceDB operations.
 ///

python/src/storage_options.rs

@@ -66,13 +66,10 @@ impl StorageOptionsProvider for PyStorageOptionsProviderWrapper {
                     .inner
                     .bind(py)
                     .call_method0("fetch_storage_options")
-                    .map_err(|e| lance_core::Error::IO {
+                    .map_err(|e| lance_core::Error::io_source(Box::new(std::io::Error::other(format!(
-                        source: Box::new(std::io::Error::other(format!(
+                        "Failed to call fetch_storage_options: {}",
-                            "Failed to call fetch_storage_options: {}",
+                        e
-                            e
+                    )))))?;
-                        ))),
-                        location: snafu::location!(),
-                    })?;
 
                 // If result is None, return None
                 if result.is_none() {
@@ -81,26 +78,19 @@ impl StorageOptionsProvider for PyStorageOptionsProviderWrapper {
 
                 // Extract the result dict - should be a flat Map<String, String>
                 let result_dict = result.downcast::<PyDict>().map_err(|_| {
-                    lance_core::Error::InvalidInput {
+                    lance_core::Error::invalid_input(
-                        source: "fetch_storage_options() must return None or a dict of string key-value pairs".into(),
+                        "fetch_storage_options() must return a dict of string key-value pairs or None",
-                        location: snafu::location!(),
+                    )
-                    }
                 })?;
 
                 // Convert all entries to HashMap<String, String>
                 let mut storage_options = HashMap::new();
                 for (key, value) in result_dict.iter() {
                     let key_str: String = key.extract().map_err(|e| {
-                        lance_core::Error::InvalidInput {
+                        lance_core::Error::invalid_input(format!("Storage option key must be a string: {}", e))
-                            source: format!("Storage option key must be a string: {}", e).into(),
-                            location: snafu::location!(),
-                        }
                     })?;
                     let value_str: String = value.extract().map_err(|e| {
-                        lance_core::Error::InvalidInput {
+                        lance_core::Error::invalid_input(format!("Storage option value must be a string: {}", e))
-                            source: format!("Storage option value must be a string: {}", e).into(),
-                            location: snafu::location!(),
-                        }
                     })?;
                     storage_options.insert(key_str, value_str);
                 }
@@ -109,13 +99,10 @@ impl StorageOptionsProvider for PyStorageOptionsProviderWrapper {
             })
         })
         .await
-        .map_err(|e| lance_core::Error::IO {
+        .map_err(|e| lance_core::Error::io_source(Box::new(std::io::Error::other(format!(
-            source: Box::new(std::io::Error::other(format!(
+            "Task join error: {}",
-                "Task join error: {}",
+            e
-                e
+        )))))?
-            ))),
-            location: snafu::location!(),
-        })?
     }
 
     fn provider_id(&self) -> String {

python/src/table.rs

@@ -5,7 +5,7 @@ use std::{collections::HashMap, sync::Arc};
 use crate::{
     connection::Connection,
     error::PythonErrorExt,
-    index::{extract_index_params, IndexConfig},
+    index::{IndexConfig, extract_index_params},
     query::{Query, TakeQuery},
     table::scannable::PyScannable,
 };
@@ -19,10 +19,10 @@ use lancedb::table::{
     Table as LanceDbTable,
 };
 use pyo3::{
+    Bound, FromPyObject, Py, PyAny, PyRef, PyResult, Python,
     exceptions::{PyKeyError, PyRuntimeError, PyValueError},
     pyclass, pymethods,
     types::{IntoPyDict, PyAnyMethods, PyDict, PyDictMethods},
-    Bound, FromPyObject, PyAny, PyRef, PyResult, Python,
 };
 use pyo3_async_runtimes::tokio::future_into_py;
 
@@ -112,19 +112,24 @@ impl From<lancedb::table::AddResult> for AddResult {
 #[pyclass(get_all)]
 #[derive(Clone, Debug)]
 pub struct DeleteResult {
+    pub num_deleted_rows: u64,
     pub version: u64,
 }
 
 #[pymethods]
 impl DeleteResult {
     pub fn __repr__(&self) -> String {
-        format!("DeleteResult(version={})", self.version)
+        format!(
+            "DeleteResult(num_deleted_rows={}, version={})",
+            self.num_deleted_rows, self.version
+        )
     }
 }
 
 impl From<lancedb::table::DeleteResult> for DeleteResult {
     fn from(result: lancedb::table::DeleteResult) -> Self {
         Self {
+            num_deleted_rows: result.num_deleted_rows,
             version: result.version,
         }
     }
@@ -294,10 +299,12 @@ impl Table {
         })
     }
 
+    #[pyo3(signature = (data, mode, progress=None))]
     pub fn add<'a>(
         self_: PyRef<'a, Self>,
         data: PyScannable,
         mode: String,
+        progress: Option<Py<PyAny>>,
     ) -> PyResult<Bound<'a, PyAny>> {
         let mut op = self_.inner_ref()?.add(data);
         if mode == "append" {
@@ -307,6 +314,81 @@ impl Table {
         } else {
             return Err(PyValueError::new_err(format!("Invalid mode: {}", mode)));
         }
+        if let Some(progress_obj) = progress {
+            let is_callable = Python::attach(|py| progress_obj.bind(py).is_callable());
+            if is_callable {
+                // Callback: call with a dict of progress info.
+                op = op.progress(move |p| {
+                    Python::attach(|py| {
+                        let dict = PyDict::new(py);
+                        if let Err(e) = dict
+                            .set_item("output_rows", p.output_rows())
+                            .and_then(|_| dict.set_item("output_bytes", p.output_bytes()))
+                            .and_then(|_| dict.set_item("total_rows", p.total_rows()))
+                            .and_then(|_| {
+                                dict.set_item("elapsed_seconds", p.elapsed().as_secs_f64())
+                            })
+                            .and_then(|_| dict.set_item("active_tasks", p.active_tasks()))
+                            .and_then(|_| dict.set_item("total_tasks", p.total_tasks()))
+                            .and_then(|_| dict.set_item("done", p.done()))
+                        {
+                            log::warn!("progress dict error: {e}");
+                            return;
+                        }
+                        if let Err(e) = progress_obj.call1(py, (dict,)) {
+                            log::warn!("progress callback error: {e}");
+                        }
+                    });
+                });
+            } else {
+                // tqdm-like: has update() method.
+                let mut last_rows: usize = 0;
+                let mut total_set = false;
+                op = op.progress(move |p| {
+                    let current = p.output_rows();
+                    let prev = last_rows;
+                    last_rows = current;
+                    Python::attach(|py| {
+                        if let Some(total) = p.total_rows()
+                            && !total_set
+                        {
+                            if let Err(e) = progress_obj.setattr(py, "total", total) {
+                                log::warn!("progress setattr error: {e}");
+                            }
+                            total_set = true;
+                        }
+                        let delta = current.saturating_sub(prev);
+                        if delta > 0 {
+                            if let Err(e) = progress_obj.call_method1(py, "update", (delta,)) {
+                                log::warn!("progress update error: {e}");
+                            }
+                            // Show throughput and active workers in tqdm postfix.
+                            let elapsed = p.elapsed().as_secs_f64();
+                            if elapsed > 0.0 {
+                                let mb_per_sec = p.output_bytes() as f64 / elapsed / 1_000_000.0;
+                                let postfix = format!(
+                                    "{:.1} MB/s | {}/{} workers",
+                                    mb_per_sec,
+                                    p.active_tasks(),
+                                    p.total_tasks()
+                                );
+                                if let Err(e) =
+                                    progress_obj.call_method1(py, "set_postfix_str", (postfix,))
+                                {
+                                    log::warn!("progress set_postfix_str error: {e}");
+                                }
+                            }
+                        }
+                        if p.done() {
+                            // Force a final refresh so the bar shows completion.
+                            if let Err(e) = progress_obj.call_method0(py, "refresh") {
+                                log::warn!("progress refresh error: {e}");
+                            }
+                        }
+                    });
+                });
+            }
+        }
 
         future_into_py(self_.py(), async move {
             let result = op.execute().await.infer_error()?;
@@ -421,6 +503,17 @@ impl Table {
         })
     }
 
+    pub fn prewarm_data(
+        self_: PyRef<'_, Self>,
+        columns: Option<Vec<String>>,
+    ) -> PyResult<Bound<'_, PyAny>> {
+        let inner = self_.inner_ref()?.clone();
+        future_into_py(self_.py(), async move {
+            inner.prewarm_data(columns).await.infer_error()?;
+            Ok(())
+        })
+    }
+
     pub fn list_indices(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
         let inner = self_.inner_ref()?.clone();
         future_into_py(self_.py(), async move {
@@ -537,7 +630,7 @@ impl Table {
         let inner = self_.inner_ref()?.clone();
         future_into_py(self_.py(), async move {
             let versions = inner.list_versions().await.infer_error()?;
-            let versions_as_dict = Python::attach(|py| {
+            Python::attach(|py| {
                 versions
                     .iter()
                     .map(|v| {
@@ -554,9 +647,7 @@ impl Table {
                         Ok(dict.unbind())
                     })
                     .collect::<PyResult<Vec<_>>>()
-            });
+            })
-
-            versions_as_dict
         })
     }
 

python/src/table/scannable.rs

@@ -10,11 +10,11 @@ use arrow::{
 };
 use futures::StreamExt;
 use lancedb::{
+    Error,
     arrow::{SendableRecordBatchStream, SimpleRecordBatchStream},
     data::scannable::Scannable,
-    Error,
 };
-use pyo3::{types::PyAnyMethods, FromPyObject, Py, PyAny, Python};
+use pyo3::{FromPyObject, Py, PyAny, Python, types::PyAnyMethods};
 
 /// Adapter that implements Scannable for a Python reader factory callable.
 ///
@@ -99,15 +99,15 @@ impl Scannable for PyScannable {
                         // Channel closed. Check if the task panicked — a panic
                         // drops the sender without sending an error, so without
                         // this check we'd silently return a truncated stream.
-                        if let Some(handle) = join_handle {
+                        if let Some(handle) = join_handle
-                            if let Err(join_err) = handle.await {
+                            && let Err(join_err) = handle.await
-                                return Some((
+                        {
-                                    Err(Error::Runtime {
+                            return Some((
-                                        message: format!("Reader task panicked: {}", join_err),
+                                Err(Error::Runtime {
-                                    }),
+                                    message: format!("Reader task panicked: {}", join_err),
-                                    (rx, None),
+                                }),
-                                ));
+                                (rx, None),
-                            }
+                            ));
                         }
                         None
                     }

python/src/util.rs

@@ -5,8 +5,9 @@ use std::sync::Mutex;
 
 use lancedb::DistanceType;
 use pyo3::{
+    PyResult,
     exceptions::{PyRuntimeError, PyValueError},
-    pyfunction, PyResult,
+    pyfunction,
 };
 
 /// A wrapper around a rust builder

python/tests/test_expr.py

@@ -0,0 +1,387 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+"""Tests for the type-safe expression builder API."""
+
+import pytest
+import pyarrow as pa
+import lancedb
+from lancedb.expr import Expr, col, lit, func
+
+
+# ── unit tests for Expr construction ─────────────────────────────────────────
+
+
+class TestExprConstruction:
+    def test_col_returns_expr(self):
+        e = col("age")
+        assert isinstance(e, Expr)
+
+    def test_lit_int(self):
+        e = lit(42)
+        assert isinstance(e, Expr)
+
+    def test_lit_float(self):
+        e = lit(3.14)
+        assert isinstance(e, Expr)
+
+    def test_lit_str(self):
+        e = lit("hello")
+        assert isinstance(e, Expr)
+
+    def test_lit_bool(self):
+        e = lit(True)
+        assert isinstance(e, Expr)
+
+    def test_lit_unsupported_type_raises(self):
+        with pytest.raises(Exception):
+            lit([1, 2, 3])
+
+    def test_func(self):
+        e = func("lower", col("name"))
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "lower(name)"
+
+    def test_func_unknown_raises(self):
+        with pytest.raises(Exception):
+            func("not_a_real_function", col("x"))
+
+
+class TestExprOperators:
+    def test_eq_operator(self):
+        e = col("x") == lit(1)
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(x = 1)"
+
+    def test_ne_operator(self):
+        e = col("x") != lit(1)
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(x <> 1)"
+
+    def test_lt_operator(self):
+        e = col("age") < lit(18)
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(age < 18)"
+
+    def test_le_operator(self):
+        e = col("age") <= lit(18)
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(age <= 18)"
+
+    def test_gt_operator(self):
+        e = col("age") > lit(18)
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(age > 18)"
+
+    def test_ge_operator(self):
+        e = col("age") >= lit(18)
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(age >= 18)"
+
+    def test_and_operator(self):
+        e = (col("age") > lit(18)) & (col("status") == lit("active"))
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "((age > 18) AND (status = 'active'))"
+
+    def test_or_operator(self):
+        e = (col("a") == lit(1)) | (col("b") == lit(2))
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "((a = 1) OR (b = 2))"
+
+    def test_invert_operator(self):
+        e = ~(col("active") == lit(True))
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "NOT (active = true)"
+
+    def test_add_operator(self):
+        e = col("x") + lit(1)
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(x + 1)"
+
+    def test_sub_operator(self):
+        e = col("x") - lit(1)
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(x - 1)"
+
+    def test_mul_operator(self):
+        e = col("price") * lit(1.1)
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(price * 1.1)"
+
+    def test_div_operator(self):
+        e = col("total") / lit(2)
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(total / 2)"
+
+    def test_radd(self):
+        e = lit(1) + col("x")
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(1 + x)"
+
+    def test_rmul(self):
+        e = lit(2) * col("x")
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(2 * x)"
+
+    def test_coerce_plain_int(self):
+        # Operators should auto-wrap plain Python values via lit()
+        e = col("age") > 18
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(age > 18)"
+
+    def test_coerce_plain_str(self):
+        e = col("name") == "alice"
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(name = 'alice')"
+
+
+class TestExprStringMethods:
+    def test_lower(self):
+        e = col("name").lower()
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "lower(name)"
+
+    def test_upper(self):
+        e = col("name").upper()
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "upper(name)"
+
+    def test_contains(self):
+        e = col("text").contains(lit("hello"))
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "contains(text, 'hello')"
+
+    def test_contains_with_str_coerce(self):
+        e = col("text").contains("hello")
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "contains(text, 'hello')"
+
+    def test_chained_lower_eq(self):
+        e = col("name").lower() == lit("alice")
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(lower(name) = 'alice')"
+
+
+class TestExprCast:
+    def test_cast_string(self):
+        e = col("id").cast("string")
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "CAST(id AS VARCHAR)"
+
+    def test_cast_int32(self):
+        e = col("score").cast("int32")
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "CAST(score AS INTEGER)"
+
+    def test_cast_float64(self):
+        e = col("val").cast("float64")
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "CAST(val AS DOUBLE)"
+
+    def test_cast_pyarrow_type(self):
+        e = col("score").cast(pa.int32())
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "CAST(score AS INTEGER)"
+
+    def test_cast_pyarrow_float64(self):
+        e = col("val").cast(pa.float64())
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "CAST(val AS DOUBLE)"
+
+    def test_cast_pyarrow_string(self):
+        e = col("id").cast(pa.string())
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "CAST(id AS VARCHAR)"
+
+    def test_cast_pyarrow_and_string_equivalent(self):
+        # pa.int32() and "int32" should produce equivalent SQL
+        sql_str = col("x").cast("int32").to_sql()
+        sql_pa = col("x").cast(pa.int32()).to_sql()
+        assert sql_str == sql_pa
+
+
+class TestExprNamedMethods:
+    def test_eq_method(self):
+        e = col("x").eq(lit(1))
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(x = 1)"
+
+    def test_gt_method(self):
+        e = col("x").gt(lit(0))
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(x > 0)"
+
+    def test_and_method(self):
+        e = col("x").gt(lit(0)).and_(col("y").lt(lit(10)))
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "((x > 0) AND (y < 10))"
+
+    def test_or_method(self):
+        e = col("x").eq(lit(1)).or_(col("x").eq(lit(2)))
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "((x = 1) OR (x = 2))"
+
+
+class TestExprRepr:
+    def test_repr(self):
+        e = col("age") > lit(18)
+        assert repr(e) == "Expr((age > 18))"
+
+    def test_to_sql(self):
+        e = col("age") > 18
+        assert e.to_sql() == "(age > 18)"
+
+    def test_unhashable(self):
+        e = col("x")
+        with pytest.raises(TypeError):
+            {e: 1}
+
+
+# ── integration tests: end-to-end query against a real table ─────────────────
+
+
+@pytest.fixture
+def simple_table(tmp_path):
+    db = lancedb.connect(str(tmp_path))
+    data = pa.table(
+        {
+            "id": [1, 2, 3, 4, 5],
+            "name": ["Alice", "Bob", "Charlie", "alice", "BOB"],
+            "age": [25, 17, 30, 22, 15],
+            "score": [1.5, 2.0, 3.5, 4.0, 0.5],
+        }
+    )
+    return db.create_table("test", data)
+
+
+class TestExprFilter:
+    def test_simple_gt_filter(self, simple_table):
+        result = simple_table.search().where(col("age") > lit(20)).to_arrow()
+        assert result.num_rows == 3  # ages 25, 30, 22
+
+    def test_compound_and_filter(self, simple_table):
+        result = (
+            simple_table.search()
+            .where((col("age") > lit(18)) & (col("score") > lit(2.0)))
+            .to_arrow()
+        )
+        assert result.num_rows == 2  # (30, 3.5) and (22, 4.0)
+
+    def test_string_equality_filter(self, simple_table):
+        result = simple_table.search().where(col("name") == lit("Bob")).to_arrow()
+        assert result.num_rows == 1
+
+    def test_or_filter(self, simple_table):
+        result = (
+            simple_table.search()
+            .where((col("age") < lit(18)) | (col("age") > lit(28)))
+            .to_arrow()
+        )
+        assert result.num_rows == 3  # ages 17, 30, 15
+
+    def test_coercion_no_lit(self, simple_table):
+        # Python values should be auto-coerced
+        result = simple_table.search().where(col("age") > 20).to_arrow()
+        assert result.num_rows == 3
+
+    def test_string_sql_still_works(self, simple_table):
+        # Backwards compatibility: plain strings still accepted
+        result = simple_table.search().where("age > 20").to_arrow()
+        assert result.num_rows == 3
+
+
+class TestExprProjection:
+    def test_select_with_expr(self, simple_table):
+        result = (
+            simple_table.search()
+            .select({"double_score": col("score") * lit(2)})
+            .to_arrow()
+        )
+        assert "double_score" in result.schema.names
+
+    def test_select_mixed_str_and_expr(self, simple_table):
+        result = (
+            simple_table.search()
+            .select({"id": "id", "double_score": col("score") * lit(2)})
+            .to_arrow()
+        )
+        assert "id" in result.schema.names
+        assert "double_score" in result.schema.names
+
+    def test_select_list_of_columns(self, simple_table):
+        # Plain list of str still works
+        result = simple_table.search().select(["id", "name"]).to_arrow()
+        assert result.schema.names == ["id", "name"]
+
+
+# ── column name edge cases ────────────────────────────────────────────────────
+
+
+class TestColNaming:
+    """Unit tests verifying that col() preserves identifiers exactly.
+
+    Identifiers that need quoting (camelCase, spaces, leading digits, unicode)
+    are wrapped in backticks to match the lance SQL parser's dialect.
+    """
+
+    def test_camel_case_preserved_in_sql(self):
+        # camelCase is quoted with backticks so the case round-trips correctly.
+        assert col("firstName").to_sql() == "`firstName`"
+
+    def test_camel_case_in_expression(self):
+        assert (col("firstName") > lit(18)).to_sql() == "(`firstName` > 18)"
+
+    def test_space_in_name_quoted(self):
+        assert col("first name").to_sql() == "`first name`"
+
+    def test_space_in_expression(self):
+        assert (col("first name") == lit("A")).to_sql() == "(`first name` = 'A')"
+
+    def test_leading_digit_quoted(self):
+        assert col("2fast").to_sql() == "`2fast`"
+
+    def test_unicode_quoted(self):
+        assert col("名前").to_sql() == "`名前`"
+
+    def test_snake_case_unquoted(self):
+        # Plain snake_case needs no quoting.
+        assert col("first_name").to_sql() == "first_name"
+
+
+@pytest.fixture
+def special_col_table(tmp_path):
+    db = lancedb.connect(str(tmp_path))
+    data = pa.table(
+        {
+            "firstName": ["Alice", "Bob", "Charlie"],
+            "first name": ["A", "B", "C"],
+            "score": [10, 20, 30],
+        }
+    )
+    return db.create_table("special", data)
+
+
+class TestColNamingIntegration:
+    def test_camel_case_filter(self, special_col_table):
+        result = (
+            special_col_table.search()
+            .where(col("firstName") == lit("Alice"))
+            .to_arrow()
+        )
+        assert result.num_rows == 1
+        assert result["firstName"][0].as_py() == "Alice"
+
+    def test_space_in_col_filter(self, special_col_table):
+        result = (
+            special_col_table.search().where(col("first name") == lit("B")).to_arrow()
+        )
+        assert result.num_rows == 1
+
+    def test_camel_case_projection(self, special_col_table):
+        result = (
+            special_col_table.search()
+            .select({"upper_name": col("firstName").upper()})
+            .to_arrow()
+        )
+        assert "upper_name" in result.schema.names
+        assert sorted(result["upper_name"].to_pylist()) == ["ALICE", "BOB", "CHARLIE"]

python/uv.lock

@@ -2006,7 +2006,7 @@ requires-dist = [
     { name = "botocore", marker = "extra == 'embeddings'", specifier = ">=1.31.57" },
     { name = "cohere", marker = "extra == 'embeddings'" },
     { name = "colpali-engine", marker = "extra == 'embeddings'", specifier = ">=0.3.10" },
-    { name = "datafusion", marker = "extra == 'tests'" },
+    { name = "datafusion", marker = "extra == 'tests'", specifier = "<52" },
     { name = "deprecation" },
     { name = "duckdb", marker = "extra == 'tests'" },
     { name = "google-generativeai", marker = "extra == 'embeddings'" },
@@ -2035,7 +2035,7 @@ requires-dist = [
     { name = "pyarrow-stubs", marker = "extra == 'tests'" },
     { name = "pydantic", specifier = ">=1.10" },
     { name = "pylance", marker = "extra == 'pylance'", specifier = ">=1.0.0b14" },
-    { name = "pylance", marker = "extra == 'tests'", specifier = ">=1.0.0b14" },
+    { name = "pylance", marker = "extra == 'tests'", specifier = ">=1.0.0b14,<3.0.0" },
     { name = "pyright", marker = "extra == 'dev'" },
     { name = "pytest", marker = "extra == 'tests'" },
     { name = "pytest-asyncio", marker = "extra == 'tests'" },

rust/lancedb/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "lancedb"
-version = "0.27.0-beta.2"
+version = "0.27.2-beta.1"
 edition.workspace = true
 description = "LanceDB: A serverless, low-latency vector database for AI applications"
 license.workspace = true

rust/lancedb/README.md

@@ -1,4 +1,4 @@
-# LanceDB Rust
+# LanceDB Rust SDK
 
 <a href="https://crates.io/crates/vectordb">![img](https://img.shields.io/crates/v/vectordb)</a>
 <a href="https://docs.rs/vectordb/latest/vectordb/">![Docs.rs](https://img.shields.io/docsrs/vectordb)</a>

rust/lancedb/examples/bedrock.rs

@@ -9,10 +9,9 @@ use aws_config::Region;
 use aws_sdk_bedrockruntime::Client;
 use futures::StreamExt;
 use lancedb::{
-    connect,
+    Result, connect,
-    embeddings::{bedrock::BedrockEmbeddingFunction, EmbeddingDefinition, EmbeddingFunction},
+    embeddings::{EmbeddingDefinition, EmbeddingFunction, bedrock::BedrockEmbeddingFunction},
     query::{ExecutableQuery, QueryBase},
-    Result,
 };
 
 #[tokio::main]

rust/lancedb/examples/full_text_search.rs

@@ -10,10 +10,10 @@ use futures::TryStreamExt;
 use lance_index::scalar::FullTextSearchQuery;
 use lancedb::connection::Connection;
 
-use lancedb::index::scalar::FtsIndexBuilder;
 use lancedb::index::Index;
+use lancedb::index::scalar::FtsIndexBuilder;
 use lancedb::query::{ExecutableQuery, QueryBase};
-use lancedb::{connect, Result, Table};
+use lancedb::{Result, Table, connect};
 use rand::random;
 
 #[tokio::main]
@@ -46,19 +46,21 @@ fn create_some_records() -> Result<Box<dyn arrow_array::RecordBatchReader + Send
         .collect::<Vec<_>>();
     let n_terms = 3;
     let batches = RecordBatchIterator::new(
-        vec![RecordBatch::try_new(
+        vec![
-            schema.clone(),
+            RecordBatch::try_new(
-            vec![
+                schema.clone(),
-                Arc::new(Int32Array::from_iter_values(0..TOTAL as i32)),
+                vec![
-                Arc::new(StringArray::from_iter_values((0..TOTAL).map(|_| {
+                    Arc::new(Int32Array::from_iter_values(0..TOTAL as i32)),
-                    (0..n_terms)
+                    Arc::new(StringArray::from_iter_values((0..TOTAL).map(|_| {
-                        .map(|_| words[random::<u32>() as usize % words.len()])
+                        (0..n_terms)
-                        .collect::<Vec<_>>()
+                            .map(|_| words[random::<u32>() as usize % words.len()])
-                        .join(" ")
+                            .collect::<Vec<_>>()
-                }))),
+                            .join(" ")
-            ],
+                    }))),
-        )
+                ],
-        .unwrap()]
+            )
+            .unwrap(),
+        ]
         .into_iter()
         .map(Ok),
         schema.clone(),

rust/lancedb/examples/hybrid_search.rs

@@ -5,16 +5,15 @@ use arrow_array::{RecordBatch, StringArray};
 use arrow_schema::{DataType, Field, Schema};
 use futures::TryStreamExt;
 use lance_index::scalar::FullTextSearchQuery;
-use lancedb::index::scalar::FtsIndexBuilder;
 use lancedb::index::Index;
+use lancedb::index::scalar::FtsIndexBuilder;
 use lancedb::{
-    connect,
+    Result, Table, connect,
     embeddings::{
-        sentence_transformers::SentenceTransformersEmbeddings, EmbeddingDefinition,
+        EmbeddingDefinition, EmbeddingFunction,
-        EmbeddingFunction,
+        sentence_transformers::SentenceTransformersEmbeddings,
     },
     query::{QueryBase, QueryExecutionOptions},
-    Result, Table,
 };
 use std::{iter::once, sync::Arc};
 

rust/lancedb/examples/ivf_pq.rs

@@ -14,10 +14,10 @@ use arrow_schema::{DataType, Field, Schema};
 use futures::TryStreamExt;
 use lancedb::connection::Connection;
 
-use lancedb::index::vector::IvfPqIndexBuilder;
 use lancedb::index::Index;
+use lancedb::index::vector::IvfPqIndexBuilder;
 use lancedb::query::{ExecutableQuery, QueryBase};
-use lancedb::{connect, DistanceType, Result, Table};
+use lancedb::{DistanceType, Result, Table, connect};
 
 #[tokio::main]
 async fn main() -> Result<()> {
@@ -51,19 +51,21 @@ fn create_some_records() -> Result<Box<dyn arrow_array::RecordBatchReader + Send
 
     // Create a RecordBatch stream.
     let batches = RecordBatchIterator::new(
-        vec![RecordBatch::try_new(
+        vec![
-            schema.clone(),
+            RecordBatch::try_new(
-            vec![
+                schema.clone(),
-                Arc::new(Int32Array::from_iter_values(0..TOTAL as i32)),
+                vec![
-                Arc::new(
+                    Arc::new(Int32Array::from_iter_values(0..TOTAL as i32)),
-                    FixedSizeListArray::from_iter_primitive::<Float32Type, _, _>(
+                    Arc::new(
-                        (0..TOTAL).map(|_| Some(vec![Some(1.0); DIM])),
+                        FixedSizeListArray::from_iter_primitive::<Float32Type, _, _>(
-                        DIM as i32,
+                            (0..TOTAL).map(|_| Some(vec![Some(1.0); DIM])),
+                            DIM as i32,
+                        ),
                     ),
-                ),
+                ],
-            ],
+            )
-        )
+            .unwrap(),
-        .unwrap()]
+        ]
         .into_iter()
         .map(Ok),
         schema.clone(),

rust/lancedb/examples/openai.rs

@@ -8,10 +8,9 @@ use std::{iter::once, sync::Arc};
 use arrow_array::{RecordBatch, StringArray};
 use futures::StreamExt;
 use lancedb::{
-    connect,
+    Result, connect,
-    embeddings::{openai::OpenAIEmbeddingFunction, EmbeddingDefinition, EmbeddingFunction},
+    embeddings::{EmbeddingDefinition, EmbeddingFunction, openai::OpenAIEmbeddingFunction},
     query::{ExecutableQuery, QueryBase},
-    Result,
 };
 
 // --8<-- [end:imports]