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

# Complete NumPy for TypeScript The most comprehensive NumPy implementation for TypeScript and JavaScript. Write numerical computing code with the same API you already know from Python -- fully type-safe, tree-shakeable, and validated against NumPy itself. ```bash theme={null} npm install numpy-ts ``` ```bash theme={null} yarn add numpy-ts ``` ```bash theme={null} pnpm add numpy-ts ``` ## Why numpy-ts? 476 of 507 NumPy functions implemented. From basic arithmetic to FFT, linear algebra, random distributions, and beyond. 1.13x faster than NumPy on average across 7,200 benchmarks. Faster in 12 of 18 categories, across all array sizes and dtypes. No native modules, no third-party packages. Pure TypeScript + WASM that runs everywhere JavaScript runs. Over 20,000 tests compare outputs directly against NumPy. If NumPy produces a result, numpy-ts matches it. Full TypeScript type definitions for every function, dtype, and array operation. Catch errors at compile time, not runtime. Import only what you need. Bundlers eliminate unused code automatically, keeping your production builds small. ## Quick Example ```typescript theme={null} import * as np from 'numpy-ts'; // Create arrays -- just like NumPy const a = np.array([[1, 2], [3, 4]]); const b = np.zeros([2, 2]); // Broadcasting works as expected const c = a.add(1); // [[2, 3], [4, 5]] const d = a.multiply(2); // [[2, 4], [6, 8]] // Linear algebra const inv = np.linalg.inv(a); const det = np.linalg.det(a); // -2 // Dot products and matrix multiplication const e = np.dot(a, np.array([[5, 6], [7, 8]])); // [[19, 22], [43, 50]] // Reshape, slice, and manipulate const r = np.arange(12); const grid = np.reshape(r, [3, 4]); ``` ## Get Started Install numpy-ts and write your first array operations in under 5 minutes. Browse all 476 implemented functions with signatures, parameters, and examples. Real-world examples covering linear algebra, signal processing, statistics, and more. Detailed performance comparisons against NumPy across 18 categories, multiple dtypes, and array sizes. ## Coming from NumPy? numpy-ts mirrors the NumPy API as closely as possible. Most code translates directly: ```python theme={null} import numpy as np a = np.array([[1, 2], [3, 4]]) b = np.linalg.inv(a) c = np.dot(a, b) # identity matrix d = np.sum(a, axis=0) # [4, 6] e = a[0, :] # [1, 2] ``` ```typescript theme={null} import * as np from 'numpy-ts'; const a = np.array([[1, 2], [3, 4]]); const b = np.linalg.inv(a); const c = np.dot(a, b); // identity matrix const d = np.sum(a, { axis: 0 }); // [4, 6] const e = a.get([0, ':']); // [1, 2] ``` See the [NumPy Migration Guide](/migration) for a complete translation reference. ***

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