# giotto-ai/giotto-tda

A high-performance topological machine learning toolbox in Python

Repository: https://github.com/giotto-ai/giotto-tda
Canonical: https://ross.abutalabs.com/products/giotto-tda
Homepage: https://giotto-ai.github.io/gtda-docs
Language: Python
License: NOASSERTION
License Family: other
Topics: topological-machine-learning, topological-data-analysis, machine-learning, scikit-learn, tda, mapper, topology, computational-topology
Last push: 2024-06-18T01:03:15+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 2514, "days_push": 807, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1002, forks 201 (observed 2026-09-03T02:15:12.336059+00:00)

## What it is
giotto-tda is a high-performance Python toolbox for topological machine learning, built on top of scikit-learn. It provides tools for topological data analysis such as persistent homology and the Mapper algorithm, exposed as scikit-learn-compatible transformers.

## Use cases
- compute persistent homology of point clouds and time series
- run the Mapper algorithm on high-dimensional data
- build scikit-learn pipelines with topological features
- extract topological features for machine learning models
- visualize persistence diagrams and Mapper graphs
- apply topological data analysis in Python

## When to choose
- you need TDA tools that integrate with scikit-learn pipelines
- you want persistent homology or Mapper with a high-performance Python implementation
- you need topological feature extraction for ML workflows

## When to avoid
- you need a permissively licensed library (it is AGPLv3)
- you need general-purpose machine learning without topological methods
- you require frequent updates or support for the latest Python versions

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, data-science, data-visualization
- domain: machine-learning, data-science
- platform: python, cross-platform
- tags: topological-data-analysis, persistent-homology, mapper, scikit-learn, tda, computational-topology, algorithms

## Member repositories
- giotto-ai/giotto-tda (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-09-03T02:15:12.336059+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 2026-08-30T07:14:00.390435+00:00, confidence not recorded.
  - readme: https://github.com/giotto-ai/giotto-tda (fetched 2026-09-03T02:15:12.336059+00:00, sha 83f035a1d0fa)
  - homepage: https://giotto-ai.github.io/gtda-docs (fetched 2026-08-29T13:13:56.741863+00:00, sha 767cc2e33b3f)
  - registry_pypi: https://pypi.org/pypi/giotto-tda/json (fetched 2026-08-29T13:13:56.751021+00:00, sha db34ee749ed2)
- Data as of 2026-08-30T08:39:29.467469+00:00.