> ## Documentation Index
> Fetch the complete documentation index at: https://numpyts.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Installation

> Install numpy-ts and choose the right entry point for your project.

## Install the package

<CodeGroup>
  ```bash npm theme={null}
  npm install numpy-ts
  ```

  ```bash yarn theme={null}
  yarn add numpy-ts
  ```

  ```bash pnpm theme={null}
  pnpm add numpy-ts
  ```

  ```bash bun theme={null}
  bun add numpy-ts
  ```
</CodeGroup>

## 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)                                    |

<Note>
  numpy-ts has **zero runtime dependencies**. The installed size is the library itself.
</Note>

## CDN usage (browsers)

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

<CodeGroup>
  ```html esm.sh theme={null}
  <script type="module">
    import * as np from 'https://esm.sh/numpy-ts';

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

  ```html unpkg theme={null}
  <script type="module">
    import * as np from 'https://unpkg.com/numpy-ts?module';

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

  ```html jsdelivr theme={null}
  <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>
  ```
</CodeGroup>

## 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](.//tree-shaking) 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.

```typescript theme={null}
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.

```typescript theme={null}
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.

<Tip>
  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.
</Tip>

## Next steps

<CardGroup cols={3}>
  <Card title="Quickstart" icon="bolt" href=".//quickstart">
    Create arrays, run operations, and explore the API in 5 minutes.
  </Card>

  <Card title="NumPy Migration Guide" icon="code-compare" href=".//numpy-migration">
    Coming from Python NumPy? See what is different in TypeScript.
  </Card>

  <Card title="Tree-Shaking" icon="leaf" href=".//tree-shaking">
    Understand how the two entry points affect your bundle size.
  </Card>
</CardGroup>