# AllenDowney/ThinkPython

Jupyter notebooks and other resources for Think Python by Allen Downey, published by O'Reilly Media.

Repository: https://github.com/AllenDowney/ThinkPython
Canonical: https://ross.abutalabs.com/products/thinkpython
Homepage: http://allendowney.github.io/ThinkPython/
Language: Jupyter Notebook
License Family: other
Last push: 2026-03-08T14:48:52+00:00

## Health v2 (maintenance only)
Score: 64/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 71, release rhythm 35, longevity 100
- inputs: {"age_days": 5143, "days_push": 178, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2713, forks 1070 (observed 2026-08-28T04:07:11.931927+00:00)

## What it is
Jupyter notebooks and supporting materials for 'Think Python: How to Think Like a Computer Scientist' (3rd edition) by Allen B. Downey, published by O'Reilly. It is an introductory Python programming textbook that lets readers read, run, and exercise code directly in notebooks, including on Colab.

## Use cases
- learn python from scratch
- teach an intro programming course
- practice python exercises in jupyter notebooks
- learn programming without installing anything using colab
- understand classes, functions, and data structures in python

## When to choose
- you are a complete beginner learning Python
- you want an interactive, notebook-based textbook
- you are an instructor looking for free course material

## When to avoid
- you need an advanced or reference-level Python resource
- you want a runnable software tool rather than learning material

## Facets
- artifact type: learning-resource
- maturity: active
- function: developer-tools
- domain: education, programming-languages, tutorials
- platform: python, cross-platform
- tags: python, textbook, jupyter-notebooks, beginner, computer-science, book

## Member repositories
- AllenDowney/ThinkPython (main) score 64

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:11.931927+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 2026-08-30T02:15:32.074769+00:00, confidence not recorded.
  - readme: https://github.com/AllenDowney/ThinkPython (fetched 2026-08-28T04:07:11.931927+00:00, sha 9fb4da0c6a3e)
  - homepage: http://allendowney.github.io/ThinkPython/ (fetched 2026-08-29T09:58:26.080916+00:00, sha 0df1b283591d)
- Data as of 2026-08-30T08:39:29.467469+00:00.