Files
lancedb/nodejs
Tom LaMarre 917aabd077 fix(node): support specifying arrow field types by name (#2704)
The [`FieldLike` type in
arrow.ts](5ec12c9971/nodejs/lancedb/arrow.ts (L71-L78))
can have a `type: string` property, but before this change, actually
trying to create a table that has a schema that specifies field types by
name results in an error:

```
Error: Expected a Type but object was null/undefined
```

This change adds support for mapping some type name strings to arrow
`DataType`s, so that passing `FieldLike`s with a `type: string` property
to `sanitizeField` does not throw an error.

The type names that can be passed are upper/lowercase variations of the
keys of the `constructorsByTypeName` object. This does not support
mapping types that need parameters, such as timestamps which need
timezones.

With this, it is possible to create empty tables from `SchemaLike`
objects without instantiating arrow types, e.g.:

```
    import { SchemaLike } from "../lancedb/arrow"
    // ...
    const schemaLike = {
      fields: [
        {
          name: "id",
          type: "int64",
          nullable: true,
        },
        {
          name: "vector",
          type: "float64",
          nullable: true,
        },
      ],
    // ...
    } satisfies SchemaLike;
    const table = await con.createEmptyTable("test", schemaLike);
 ```

This change also makes `FieldLike.nullable` required since the `sanitizeField` function throws if it is undefined.
2025-10-08 04:40:06 -07:00
..
2025-08-13 10:05:57 -07:00
2025-03-21 10:56:29 -07:00
2025-01-29 08:27:07 -08:00
2025-07-23 12:20:36 -07:00
2025-03-21 10:56:29 -07:00

LanceDB JavaScript SDK

A JavaScript library for LanceDB.

Installation

npm install @lancedb/lancedb

This will download the appropriate native library for your platform. We currently support:

  • Linux (x86_64 and aarch64 on glibc and musl)
  • MacOS (Intel and ARM/M1/M2)
  • Windows (x86_64 and aarch64)

Usage

Basic Example

import * as lancedb from "@lancedb/lancedb";
const db = await lancedb.connect("data/sample-lancedb");
const table = await db.createTable("my_table", [
  { id: 1, vector: [0.1, 1.0], item: "foo", price: 10.0 },
  { id: 2, vector: [3.9, 0.5], item: "bar", price: 20.0 },
]);
const results = await table.vectorSearch([0.1, 0.3]).limit(20).toArray();
console.log(results);

The quickstart contains a more complete example.

Development

See CONTRIBUTING.md for information on how to contribute to LanceDB.