# dabeaz/python-cookbook

Code samples from the "Python Cookbook, 3rd Edition", published by O'Reilly & Associates, May, 2013.

Repository: https://github.com/dabeaz/python-cookbook
Canonical: https://ross.abutalabs.com/products/python-cookbook
Language: Python
License Family: other
Last push: 2023-09-20T23:36:43+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4895, "days_push": 1078, "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 4025, forks 1760 (observed 2026-08-28T04:08:32.594989+00:00)

## What it is
The official code samples repository for 'Python Cookbook, 3rd Edition' by David Beazley, published by O'Reilly in 2013. It provides runnable Python recipes demonstrating practical solutions to common programming problems.

## Use cases
- learn practical python programming techniques
- find code recipes for common python tasks
- study idiomatic python examples
- supplement reading the python cookbook book
- find solutions for data structures and algorithms in python

## When to choose
- you want proven, well-explained solutions to common Python problems
- you are learning intermediate-to-advanced Python idioms
- you are reading the Python Cookbook 3rd edition and want the source code

## When to avoid
- you need a maintained library with a license for production use
- you need solutions for modern Python 3.12+ features introduced after 2013
- you want a tutorial for absolute beginners

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: developer-tools
- domain: programming-languages, tutorials, education
- platform: python, cross-platform
- tags: python-cookbook, code-samples, oreilly, recipes, book-companion

## Member repositories
- dabeaz/python-cookbook (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:32.594989+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 2026-08-29T18:23:54.045523+00:00, confidence not recorded.
  - readme: https://github.com/dabeaz/python-cookbook (fetched 2026-08-28T04:08:32.594989+00:00, sha 9735b862ed42)
- Data as of 2026-08-30T08:39:29.467469+00:00.