# E-xyza/zigler

zig nifs in elixir

Repository: https://github.com/E-xyza/zigler
Canonical: https://ross.abutalabs.com/products/zigler
Language: Elixir
License: MIT
License Family: permissive
Last push: 2026-07-09T16:36:29+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 91, release rhythm 47, longevity 100
- inputs: {"age_days": 2528, "days_push": 55, "days_rel": 353, "gap_med": 1, "n_releases_24m": 2}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1058, forks 60 (observed 2026-08-28T04:03:25.059037+00:00)

## What it is
Zigler is an Elixir (and experimental Erlang) library that makes it easy to write Zig-based NIFs (Native Implemented Functions) for the BEAM VM. It provides automatic type marshalling between Elixir/Erlang and Zig code, with inline Zig code support via the ~Z sigil.

## Use cases
- write zig nifs in elixir
- call zig code from elixir
- create native functions for the beam vm
- performance-critical code in elixir
- cross-compile nifs for nerves embedded devices
- marshal elixir types to zig and back

## When to choose
- you need native performance in an Elixir/Erlang application
- you want to write NIFs in Zig instead of C
- you're targeting Nerves embedded platforms and need cross-compilation
- you want automatic memory management integration with the BEAM allocator

## When to avoid
- you only need pure Elixir performance
- you want to avoid native code compilation entirely
- you need stable Erlang support (it's experimental)
- your team has no Zig experience and the task doesn't require native speed

## Facets
- artifact type: library
- maturity: active
- function: sdk, compiler, developer-tools
- domain: developer-tools, programming-languages, cross-platform
- platform: windows, elixir, jvm
- tags: zig, nif, elixir, erlang, native-code, ffi, beam, linux, macos

## Member repositories
- E-xyza/zigler (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:25.059037+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 2026-08-30T06:57:32.024383+00:00, confidence not recorded.
  - readme: https://github.com/E-xyza/zigler (fetched 2026-08-28T04:03:25.059037+00:00, sha 9f249ba39df3)
- Data as of 2026-08-30T08:39:29.467469+00:00.