# IHaskell/IHaskell

A Haskell kernel for the Jupyter project.

Repository: https://github.com/IHaskell/IHaskell
Canonical: https://ross.abutalabs.com/products/ihaskell
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: haskell, jupyter
Last push: 2026-08-15T04:48:31+00:00

## Health v2 (maintenance only)
Score: 76/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 97, release rhythm 35, longevity 100
- inputs: {"age_days": 4755, "days_push": 18, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2646, forks 266 (observed 2026-08-28T04:07:06.735499+00:00)

## What it is
IHaskell is a Jupyter kernel that lets you run Haskell code interactively in Jupyter frontends like the console and notebook. It supports GHC 8.4 through 9.14 and provides rich output including charts and formatted results.

## Use cases
- run haskell in jupyter notebooks
- interactive haskell repl with rich output
- learn haskell in a notebook environment
- prototype haskell code with inline charts
- use haskell kernel in vscode notebooks
- try haskell in the browser via binder

## When to choose
- you want interactive, literate Haskell programming with inline visualizations
- you already use Jupyter and want Haskell as a kernel
- you are teaching or learning Haskell with executable examples

## When to avoid
- you need compiled production Haskell applications rather than interactive exploration
- you cannot install GHC and system dependencies like zeromq and cairo
- you want a kernel for a different language

## Facets
- artifact type: plugin
- maturity: active
- function: interpreter, developer-tools, data-visualization
- domain: programming-languages, developer-tools, data-science, education
- platform: windows, cross-platform
- tags: haskell, jupyter-kernel, notebook, repl, ghc, linux, macos

## Member repositories
- IHaskell/IHaskell (main) score 76

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:06.735499+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 2026-08-30T02:18:58.001702+00:00, confidence not recorded.
  - readme: https://github.com/IHaskell/IHaskell (fetched 2026-08-28T04:07:06.735499+00:00, sha 2bd20715a2de)
- Data as of 2026-08-30T08:39:29.467469+00:00.