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numpy-ts
Complete NumPy implementation for TypeScript and JavaScript
For agents: numpy-ts: a NumPy-compatible array library for TypeScript and JavaScript, with versioned guides on installation, quickstart, broadcasting, dtypes and indexing (
numpytypescriptjavascriptarray computingnumerical library
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Their llms.txt
The beginning of the file, from our validated copy saved 2026-10-24T12:26:37.248Z. Cached copy · Source on numpyts.dev
# numpy-ts
> Complete NumPy implementation for TypeScript and JavaScript
- [v1.7.x (85 pages)](https://numpyts.dev/_llms/v1-7-x.txt): Documentation for v1.7.x.
## v1.6.x
### Guides
#### numpy-ts
- [numpy-ts](https://numpyts.dev/index.md)
- [Installation](https://numpyts.dev/v1.6.x/guides/installation.md): Install numpy-ts and choose the right entry point for your project.
#### Getting Started
- [Quickstart](https://numpyts.dev/v1.6.x/guides/quickstart.md): Create arrays, perform operations, and explore numpy-ts in 5 minutes.
- [NumPy Migration Guide](https://numpyts.dev/v1.6.x/guides/numpy-migration.md): A side-by-side guide for Python NumPy users moving to numpy-ts in TypeScript/JavaScript.
#### Guides
- [Array Basics](https://numpyts.dev/v1.6.x/guides/array-basics.md): Create, inspect, and convert NDArrays -- the core data structure of numpy-ts.
- [Data Types (dtypes)](https://numpyts.dev/v1.6.x/guides/dtypes.md): All 14 supported dtypes, type promotion rules, BigInt handling, and complex numbers.
- [Broadcasting](https://numpyts.dev/v1.6.x/guides/broadcasting.md): How numpy-ts combines arrays with different shapes in element-wise operations.
- [Slicing & Indexing](https://numpyts.dev/v1.6.x/guides/slicing-indexing.md): Select sub-arrays, individual elements, rows, and columns using string-based slicing and advanced indexing.
- [Views & Copies](https://numpyts.dev/v1.6.x/guides/views-copies.md): Understand when numpy-ts shares memory between arrays and when it allocates new data.
- [Tree-Shaking & Bundle Size](https://numpyts.dev/v1.6.x/guides/tree-shaking.md): Understand the two ways to use numpy-ts and how they affect your bundle.
- [File I/O](https://numpyts.dev/v1.6.x/guides/file-io.md): Save and load arrays in .npy, .npz, and text formats. File-based I/O works on Node.js, Bun, and Deno; buffer-based I/O works everywhere including browsers.
- [TypeScript Patterns](https://numpyts.dev/v1.6.x/guides/typescript-patterns.md): Type-safe patterns for using numpy-ts in TypeScript projects and libraries.
- [WASM Acceleration](https://numpyts.dev/v1.6.x/guides/wasm-acceleration.md)
- [Memory Management](https://numpyts.dev/v1.6.x/guides/memory-management.md)
#### Resources
- [Changelog & Release Notes](https://numpyts.dev/changelog.md)
- [NumPy API Coverage](https://numpyts.dev/v1.6.x/guides/api-coverage.md): Current numpy-ts coverage versus NumPy (auto-generated).
- [Roadmap](https://numpyts.dev/v1.6.x/guides/roadmap.md): What's coming next for numpy-ts.
- [AI Disclosure](https://numpyts.dev/v1.6.x/guides/ai-disclosure.md)
### API Reference
#### Overview
- [API Reference Overview](https://numpyts.dev/v1.6.x/api/overview.md): Complete API reference for numpy-ts -- 476 of 507 NumPy functions implemented in pure TypeScript.
#### NDArray
- [NDArray Class](https://numpyts.dev/v1.6.x/api/ndarray/class.md): The NDArray and NDArrayCore classes -- properties, element access, slicing, conversion, and static methods.
- [NDArray Methods](https
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