# TheAlgorithms/Python

All Algorithms implemented in Python

Repository: https://github.com/TheAlgorithms/Python
Canonical: https://ross.abutalabs.com/products/python
Homepage: https://thealgorithms.github.io/Python/
Language: Python
License: MIT
License Family: permissive
Topics: python, algorithm, algorithms-implemented, algorithm-competitions, algos, sorts, searches, sorting-algorithms, education, learn, practice, community-driven, interview, hacktoberfest
Last push: 2026-08-25T14:09:01+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 35, longevity 100
- inputs: {"age_days": 3700, "days_push": 8, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 224047, forks 50991 (observed 2026-08-28T04:12:28.455913+00:00)

## What it is
A large community-driven collection of algorithms and data structures implemented in Python for educational purposes. It covers topics like sorting, searching, graphs, machine learning, ciphers, and dynamic programming, with reference documentation and tests.

## Use cases
- learn how classic algorithms are implemented in Python
- prepare for coding interviews with example implementations
- study sorting and searching algorithms with working code
- reference implementations of dynamic programming and graph algorithms
- practice contributing to an open-source Python project
- explore machine learning and neural network basics in pure Python

## When to choose
- you want readable, educational Python implementations of common algorithms
- you are preparing for technical interviews or algorithm competitions
- you want a well-organized reference with tests and documentation
- you are learning Python by reading and contributing code

## When to avoid
- you need production-grade, highly optimized algorithms - use the Python standard library or NumPy/SciPy instead
- you need a pip-installable algorithm library with stable APIs
- you need guaranteed correctness or performance for critical systems

## Facets
- artifact type: learning-resource
- maturity: active
- function: developer-tools
- domain: education, programming-languages, tutorials
- platform: python
- tags: algorithms, data-structures, interview-preparation, sorting, searching, educational, community-driven, education

## Member repositories
- TheAlgorithms/Python (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:12:28.455913+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 2026-08-29T16:10:29.651278+00:00, confidence not recorded.
  - readme: https://github.com/TheAlgorithms/Python (fetched 2026-08-28T04:12:28.455913+00:00, sha 530f7ba5868c)
  - homepage: https://thealgorithms.github.io/Python/ (fetched 2026-08-28T17:21:46.676017+00:00, sha 9e46dd2de526)
- Data as of 2026-08-30T08:39:29.467469+00:00.