# AnswerDotAI/fastcore

Python supercharged for the fastai library

Repository: https://github.com/AnswerDotAI/fastcore
Canonical: https://ross.abutalabs.com/products/fastcore
Homepage: http://fastcore.fast.ai
Language: Jupyter Notebook
License: Apache-2.0
License Family: permissive
Topics: python, fastai, languages, developer-tools, data-structures, functional-programming, parallel-processing, dispatch, documentation-generator
Last push: 2026-09-03T01:20:43+00:00

## Health v2 (maintenance only)
Score: 96/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 100, release rhythm 88, longevity 100
- inputs: {"age_days": 2466, "days_push": 0, "days_rel": 0, "gap_med": 1, "n_releases_24m": 176}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1105, forks 294 (observed 2026-09-03T02:15:00.586375+00:00)

## What it is
fastcore is a Python utility library that extends the language with features inspired by Ruby, Haskell, and NumPy, including an enhanced list type, function adapters, dispatch, parallel processing helpers, and scripting utilities. It serves as the foundation library for the fastai ecosystem and is designed for safe wildcard imports.

## Use cases
- add functional programming helpers like currying and binding to Python
- simplify parallel processing in Python scripts
- get a NumPy-like enhanced list type for Python
- build command-line scripts with type-annotated argparse helpers
- generate documentation from docments annotations
- write cleaner Python with fewer standard library rough edges

## When to choose
- you work in the fastai ecosystem and need its foundation utilities
- you want Ruby/Haskell-inspired conveniences in Python
- you need lightweight parallelism and async helpers without heavy dependencies
- you build Python CLIs and want docments-based argument parsing

## When to avoid
- you prefer sticking strictly to the Python standard library
- your project requires Python versions older than 3.11 with fastcore v2
- you need a single-purpose library rather than a broad utility grab-bag
- you depend on removed fastcore v1 APIs without pinning fastcore<2

## Facets
- artifact type: library
- maturity: active
- function: developer-tools, concurrency, documentation, cli, serialization
- domain: developer-tools, programming-languages, machine-learning
- platform: python, cross-platform
- tags: functional-programming, python-extensions, fastai, dispatch, data-structures, monkey-patching, scripting

## Member repositories
- AnswerDotAI/fastcore (main) score 96

## Provenance
- Observed fields: from GitHub, fetched 2026-09-03T02:15:00.586375+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 2026-08-30T06:44:20.474732+00:00, confidence not recorded.
  - readme: https://github.com/AnswerDotAI/fastcore (fetched 2026-09-03T02:15:00.586375+00:00, sha 78b6980e5cc3)
  - homepage: http://fastcore.fast.ai (fetched 2026-08-29T12:48:00.781583+00:00, sha 7d21e1cea62e)
- Data as of 2026-08-30T08:39:29.467469+00:00.