# dpilger26/NumCpp

C++ implementation of the Python Numpy library

Repository: https://github.com/dpilger26/NumCpp
Canonical: https://ross.abutalabs.com/products/numcpp
Homepage: https://dpilger26.github.io/NumCpp
Language: C++
License: MIT
License Family: permissive
Topics: python, numpy, c-plus-plus, numerical-analysis, scientific-computing, algorithms, data-structures, cpp, mathematical-functions
Last push: 2026-03-17T02:41:59+00:00

## Health v2 (maintenance only)
Score: 74/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 72, release rhythm 63, longevity 100
- inputs: {"age_days": 3129, "days_push": 169, "days_rel": 169, "gap_med": 75.0, "n_releases_24m": 7}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3962, forks 577 (observed 2026-08-28T04:08:30.596285+00:00)

## What it is
NumCpp is a templatized, header-only C++ library that reimplements the Python NumPy API, centered on an NdArray container with NumPy-style mathematical functions. It supports C++17 through C++23 and requires Boost 1.73+.

## Use cases
- port numpy code to c++
- n-dimensional array math in c++
- linear algebra and matrix operations in c++
- scientific computing without python
- numpy-style api for c++ projects
- numerical analysis in c++

## When to choose
- you want NumPy-like array math in a C++ codebase
- you need a header-only dependency with no build step
- you're porting Python numerical code to C++

## When to avoid
- you need GPU acceleration or distributed arrays
- you need tensors beyond 2D plus DataCube convenience
- you're already in Python and can just use NumPy

## Facets
- artifact type: library
- maturity: active
- function: math, data-science, machine-learning
- domain: data-science, developer-tools
- platform: cpp, cross-platform, windows
- tags: numpy, header-only, ndarray, numerical-computing, scientific-computing, linear-algebra, algorithms, linux, macos

## Member repositories
- dpilger26/NumCpp (main) score 74

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:30.596285+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:24:27.029088+00:00, confidence not recorded.
  - readme: https://github.com/dpilger26/NumCpp (fetched 2026-08-28T04:08:30.596285+00:00, sha 9d96f4f2032b)
  - homepage: https://dpilger26.github.io/NumCpp (fetched 2026-08-29T09:17:54.546937+00:00, sha f727afb1b13b)
- Data as of 2026-08-30T08:39:29.467469+00:00.