# intake/intake

Intake is a lightweight package for finding, investigating, loading and disseminating data.

Repository: https://github.com/intake/intake
Canonical: https://ross.abutalabs.com/products/intake
Homepage: https://intake.readthedocs.io/
Language: Python
License: BSD-2-Clause
License Family: permissive
Topics: python, data-access, data-catalog
Last push: 2026-06-18T20:13:02+00:00

## Health v2 (maintenance only)
Score: 72/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 88, release rhythm 35, longevity 100
- inputs: {"age_days": 3306, "days_push": 76, "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 1085, forks 149 (observed 2026-08-28T04:03:31.988608+00:00)

## What it is
Intake is a lightweight Python package for describing data declaratively, gathering datasets into searchable catalogs, and loading data from many formats and remote storage backends. It uses a plugin/driver system so third-party packages can add support for additional data sources.

## Use cases
- build a searchable catalog of datasets
- load data from remote storage in python
- describe data sources declaratively
- find the right dataset across multiple catalogs
- standardize data access across a data science team
- load csv parquet and other formats through one interface

## When to choose
- you need a unified, declarative interface to many heterogeneous data sources
- you want to share curated dataset catalogs across a team or organization
- you work in the PyData ecosystem (pandas, dask, xarray) and want lazy data loading

## When to avoid
- you only read a single local file format and don't need cataloging
- you need a full data versioning or lineage system rather than access layer
- your stack is not Python-based

## Facets
- artifact type: library
- maturity: active
- function: data-science, etl, plugin-system, search-engine
- domain: data-science, databases, analytics
- platform: python, cross-platform
- tags: data-catalog, data-access, data-loading, catalogs, data-engineering

## Member repositories
- intake/intake (main) score 72

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:31.988608+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 2026-08-30T06:49:48.891091+00:00, confidence not recorded.
  - readme: https://github.com/intake/intake (fetched 2026-08-28T04:03:31.988608+00:00, sha dd51d2b884f2)
- Data as of 2026-08-30T08:39:29.467469+00:00.