# google/haskell-trainings

Haskell 101 and 102: slides and codelabs

Repository: https://github.com/google/haskell-trainings
Canonical: https://ross.abutalabs.com/products/haskell-trainings
Language: Haskell
License: Apache-2.0
License Family: permissive
Archived: true
Last push: 2023-04-10T00:27:48+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 2779, "days_push": 1242, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1410, forks 108 (observed 2026-08-28T04:04:38.839659+00:00)

## What it is
Google's Haskell 101 and 102 training materials, containing LaTeX slides and hands-on codelab exercises with solutions. It was created in 2016 to teach newcomers the Haskell programming language.

## Use cases
- learn haskell from scratch
- haskell tutorial with exercises
- functional programming training course
- haskell codelabs for beginners
- self-study haskell slides and exercises
- teach a haskell workshop

## When to choose
- you want a structured, exercise-driven introduction to Haskell
- you prefer learning with slides plus hands-on codelabs and solutions
- you want free training material from an experienced engineering team

## When to avoid
- you need an actively maintained course updated for modern tooling
- you want interactive in-browser lessons rather than local ghc/Stack/Cabal setup
- you need Haskell training beyond an introductory 101/102 level

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, developer-tools
- domain: programming-languages, tutorials, education
- platform: cross-platform, cli
- tags: haskell, codelabs, slides, functional-programming, training

## Member repositories
- google/haskell-trainings (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:38.839659+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 2026-08-30T04:38:28.300470+00:00, confidence not recorded.
  - readme: https://github.com/google/haskell-trainings (fetched 2026-08-28T04:04:38.839659+00:00, sha 2fcf17551a50)
- Data as of 2026-08-30T08:39:29.467469+00:00.