# onlybooks/python-algorithm-interview

<파이썬 알고리즘 인터뷰> 95가지 알고리즘 문제 풀이로 완성하는 코딩 테스트

Repository: https://github.com/onlybooks/python-algorithm-interview
Canonical: https://ross.abutalabs.com/products/python-algorithm-interview
Language: Python
License Family: other
Last push: 2023-09-22T10:15:28+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2287, "days_push": 1076, "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 1264, forks 327 (observed 2026-08-28T04:04:10.807085+00:00)

## What it is
Companion repository for the Korean book 'Python Algorithm Interview', containing solutions to 95 algorithm problems (mostly LeetCode) in Python with some C and Go examples. It is a study resource for coding test and technical interview preparation.

## Use cases
- prepare for coding interview questions
- practice leetcode problems in python
- study data structures and algorithms
- learn common algorithm interview solutions
- review string, array, and linked list problem patterns
- find reference solutions for algorithm problems

## When to choose
- you are preparing for a coding test or technical interview in Python
- you want worked solutions to classic LeetCode-style problems
- you are reading the book and want its code examples

## When to avoid
- you need a runnable algorithm library or package
- you want an actively developed problem set with new content
- you need solutions in languages other than Python

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: developer-tools
- domain: education, tutorials, programming-languages
- platform: python
- tags: coding-interview, leetcode, algorithm-problems, book-companion, data-structures, korean, algorithms

## Member repositories
- onlybooks/python-algorithm-interview (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:10.807085+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 2026-08-30T05:04:04.027539+00:00, confidence not recorded.
  - readme: https://github.com/onlybooks/python-algorithm-interview (fetched 2026-08-28T04:04:10.807085+00:00, sha 01b53073137b)
- Data as of 2026-08-30T08:39:29.467469+00:00.