# Avaiga/taipy

Turns Data and AI algorithms into production-ready web applications in no time.

Repository: https://github.com/Avaiga/taipy
Canonical: https://ross.abutalabs.com/products/taipy
Homepage: https://www.taipy.io
Language: Python
License: Apache-2.0
License Family: permissive
Topics: automation, data-engineering, data-ops, data-visualization, datascience, developer-tools, mlops, orchestration, pipeline, pipelines, python, taipy-gui, workflow, taipy-core, hacktoberfest, hacktoberfest2023, data-integration, job-scheduler, scenario, scenario-analysis
Last push: 2026-08-10T02:47:18+00:00

## Health v2 (maintenance only)
Score: 92/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 97, release rhythm 81, longevity 100
- inputs: {"age_days": 1657, "days_push": 23, "days_rel": 126, "gap_med": 0.0, "n_releases_24m": 37}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 19433, forks 1997 (observed 2026-08-28T04:11:28.630444+00:00)

## What it is
Taipy is an open-source Python framework that turns data and AI algorithms into production-ready web applications, combining a Markdown/Python-based GUI layer with pipeline orchestration and scenario management. It targets data scientists and ML engineers who want full-stack data apps without JavaScript or separate backend tooling.

## Use cases
- build a dashboard for a machine learning model in pure Python
- turn a data science prototype into a production web app
- orchestrate and schedule data pipelines with scenarios
- create interactive charts and KPI dashboards from large datasets
- compare what-if scenarios for decision support
- run long background jobs without blocking the UI
- build a chatbot or ML demo app quickly

## When to choose
- you are a Python data scientist or ML engineer who wants a web UI without learning JavaScript
- you need both GUI building and pipeline/scenario orchestration in one framework
- you want to deploy data apps with Docker or on Linux servers
- you need multi-user state management and background job execution built in

## When to avoid
- you need a highly customized, pixel-perfect frontend beyond what predefined components offer
- you are building a general-purpose web application unrelated to data or AI
- you require enterprise features like SSO, ACL, or distributed computing without a paid edition
- your team prefers mainstream stacks like React with a separate API backend

## Facets
- artifact type: framework
- maturity: active
- function: web-framework, data-visualization, scheduling, workflow-automation, gui, charts, machine-learning
- domain: data-visualization, data-science, machine-learning, web-development, developer-tools
- platform: python, cross-platform, self-hosted
- tags: low-code, mlops, scenario-management, dashboards, data-apps, pipeline-orchestration, full-stack-python, automation, web-server, docker

## Member repositories
- Avaiga/taipy (main) score 92

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:28.630444+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 2026-08-29T17:00:07.005007+00:00, confidence not recorded.
  - readme: https://github.com/Avaiga/taipy (fetched 2026-08-28T04:11:28.630444+00:00, sha 94b39b2448eb)
  - homepage: https://www.taipy.io (fetched 2026-08-29T07:58:37.274420+00:00, sha 14129e3148f0)
  - site_page: https://taipy.io/about-us (fetched 2026-08-29T07:58:37.277639+00:00, sha b10b3a7499d1)
  - site_page: https://taipy.io/blog/new-taipy-book-getting-started-with-taipy (fetched 2026-08-29T07:58:37.282715+00:00, sha 63e17ac6cc5c)
  - registry_pypi: https://pypi.org/pypi/taipy/json (fetched 2026-08-29T07:58:37.285959+00:00, sha 2d0b540adc34)
  - site_page: https://taipy.io/pricing (fetched 2026-08-29T07:58:37.281062+00:00, sha 6f6a1a5cbedb)
  - site_page: https://taipy.io/book-a-call (fetched 2026-08-29T07:58:37.284207+00:00, sha 096b582add10)
- Data as of 2026-08-30T08:39:29.467469+00:00.