Installation

Install the package

npm install numpy-ts

yarn add numpy-ts

pnpm add numpy-ts

bun add numpy-ts

Requirements

Environment	Minimum Version
Node.js	>= 20.1.0
Bun	>= 1.0
Deno	>= 1.37
Browsers	ES2020+ (Chrome 80+, Firefox 78+, Safari 14+, Edge 80+)
TypeScript	>= 5.0 (recommended)

numpy-ts has zero runtime dependencies. The installed size is the library itself.

CDN usage (browsers)

You can load numpy-ts directly in the browser without a build step:

<script type="module">
  import * as np from 'https://esm.sh/numpy-ts';

  const a = np.array([[1, 2], [3, 4]]);
  console.log(a);
</script>

<script type="module">
  import * as np from "https://cdn.jsdelivr.net/npm/numpy-ts/+esm";

  const a = np.array([[1, 2], [3, 4]]);
  console.log(a);
</script>

<script type="module">
  import * as np from 'https://unpkg.com/numpy-ts/dist/numpy-ts.browser.js';

  const a = np.array([[1, 2], [3, 4]]);
  console.log(a);
</script>

Choose your entry point

numpy-ts ships two entry points. Pick the one that fits your use case:

Entry Point	Import Path	Returns	Bundle Size	Use When
Full	`numpy-ts`	`NDArray`	~200-300 KB	You want method chaining, the complete API, and file I/O on server runtimes
Core	`numpy-ts/core`	`NDArrayCore`	~10-40 KB	Bundle size matters; you only need specific functions

See the Tree-Shaking guide for a detailed comparison.

Full library (`numpy-ts`)

The default entry point. Functions return NDArray, which supports method chaining (.add(), .reshape(), .T, etc.). On server runtimes (Node.js, Bun, Deno), file I/O operations (loadNpy, saveNpy, loadNpzFile, savez, loadtxt, savetxt) are available directly. In browsers, calling file I/O functions throws a clear error.

import * as np from 'numpy-ts';

const a = np.array([1, 2, 3, 4]);
const b = a.add(10).reshape([2, 2]).T;  // Method chaining

// File I/O — works on Node.js, Bun, and Deno
const arr = await np.loadNpy('data.npy');
await np.saveNpy('output.npy', arr);

Best for applications, scripts, and projects where developer experience matters more than bundle size.

Tree-shakeable core (`numpy-ts/core`)

Functions return NDArrayCore (no method chaining). Your bundler (webpack, Vite, esbuild, Rollup) will only include the functions you actually import.

import { array, add, reshape, transpose } from 'numpy-ts/core';

const a = array([1, 2, 3, 4]);
const b = transpose(reshape(add(a, 10), [2, 2]));

Best for libraries, frontend apps where every kilobyte counts, and when you only need a handful of functions.

Importing just array and add from numpy-ts/core results in a bundle around 10 KB minified. The full entry point is always ~200-300 KB regardless of what you use.

Next steps

Quickstart

Create arrays, run operations, and explore the API in 5 minutes.

NumPy Migration Guide

Coming from Python NumPy? See what is different in TypeScript.

Tree-Shaking

Understand how the two entry points affect your bundle size.

numpy-ts

Getting Started

Guides

Resources

Install the package

Requirements

CDN usage (browsers)

Choose your entry point

Full library (`numpy-ts`)

Tree-shakeable core (`numpy-ts/core`)

Next steps

Quickstart

NumPy Migration Guide

Tree-Shaking

​Install the package

​Requirements

​CDN usage (browsers)

​Choose your entry point

​Full library (numpy-ts)

​Tree-shakeable core (numpy-ts/core)

​Next steps

Quickstart

NumPy Migration Guide

Tree-Shaking

Install the package

Requirements

CDN usage (browsers)

Choose your entry point

Full library (`numpy-ts`)

Tree-shakeable core (`numpy-ts/core`)

Next steps