SciSharp/NumSharp
High Performance Computation for N-D Tensors in .NET, similar API to NumPy. observed · 2026-08-28
Health v2 · maintenance only
92/100
- Activity 99
- Release rhythm 78
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 37
- age_days: 2885
- days_rel: 66
- days_push: 9
- n_releases_24m: 4
Adoption not part of the score
1477 stars · 205 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
NumSharp is a .NET library providing NumPy-shaped N-dimensional arrays with broadcasting, slicing views, dtype-aware math, and runtime-generated SIMD kernels. It lets C# and F# code use a NumPy-like programming model without embedding CPython.
Use cases
- do numpy-style array math in C#
- n-dimensional tensor operations in .NET
- numerical computing without Python
- broadcasting and slicing arrays in F#
- build machine learning infrastructure in .NET
- replace Python numpy dependency in a C# pipeline
When to choose
- you want NumPy API parity in pure .NET code
- you need high-performance unmanaged array storage with SIMD fast paths
- your project targets NumPy 2.x behavior as source of truth
When to avoid
- you need the full scientific Python ecosystem (SciPy, pandas) rather than arrays
- you need GPU acceleration out of the box
- you require complete NumPy coverage - some areas are still being tightened
Facets
library · maturity active
math machine-learning data-science data-science machine-learning developer-tools dotnet cross-platform numpy ndarray numerical-computing scientific-computing simd csharp fsharp
2 sources
- readme: https://github.com/SciSharp/NumSharp · fetched 2026-08-28 · e2266accca30
- homepage: https://scisharp.github.io/NumSharp/ · fetched 2026-08-29 · ca27508e1006
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| SciSharp/NumSharp | main | 92 |
For agents
markdown · JSON · MCP: product_card(name="SciSharp/NumSharp")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem