# amphi-ai/amphi-etl

visual data prep powered by python

Repository: https://github.com/amphi-ai/amphi-etl
Canonical: https://ross.abutalabs.com/products/amphi-etl
Homepage: https://amphi.ai
Language: TypeScript
License: NOASSERTION
License Family: other
Topics: data, data-pipelines, etl, structured-data, unstructured-data, data-analysis, data-science, datatransformation, analytics-automation, data-preparation
Last push: 2026-08-24T01:43:02+00:00

## Health v2 (maintenance only)
Score: 70/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 35, longevity 64
- inputs: {"age_days": 896, "days_push": 10, "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 1401, forks 107 (observed 2026-08-28T04:04:37.282207+00:00)

## What it is
Amphi is a visual data preparation and ETL tool that lets users build data pipelines through a drag-and-drop interface while generating standard Python code. It runs locally as a standalone app or as a JupyterLab extension and supports AI-assisted pipeline generation.

## Use cases
- build etl pipelines visually without writing code
- clean and transform csv and excel data
- extract data from databases and rest apis into pipelines
- export pipelines as python code for airflow or prefect
- prepare structured and unstructured data for analysis
- generate data transformation code with llm assistance

## When to avoid
- you need a fully managed cloud ETL service
- you require a permissive open-source license (Amphi uses ELv2)
- you need streaming or real-time pipeline processing

## Facets
- artifact type: application
- maturity: active
- function: etl, data-science, workflow-automation, gui
- domain: data-science, analytics, developer-tools
- platform: python, cross-platform, self-hosted
- tags: visual-pipeline-builder, jupyterlab-extension, low-code, data-preparation, code-generation, data-engineering, web-server

## Member repositories
- amphi-ai/amphi-etl (main) score 70

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:37.282207+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 2026-08-30T04:39:01.681813+00:00, confidence not recorded.
  - readme: https://github.com/amphi-ai/amphi-etl (fetched 2026-08-28T04:04:37.282207+00:00, sha 6cf7a49f6053)
  - homepage: https://amphi.ai (fetched 2026-08-29T11:53:18.412806+00:00, sha 74bd1c2b554d)
  - site_page: https://community.amphi.ai/c/documentation/7 (fetched 2026-08-29T11:53:18.421788+00:00, sha 1cb247ff30ba)
  - site_page: https://community.amphi.ai/t/install-setup/19/1 (fetched 2026-08-29T11:53:18.423352+00:00, sha 7e81c9b63478)
- Data as of 2026-08-30T08:39:29.467469+00:00.