# scverse/gget

🧬 gget enables efficient querying of genomic reference databases

Repository: https://github.com/scverse/gget
Canonical: https://ross.abutalabs.com/products/gget
Homepage: https://scverse.org/gget
Language: Python
License: BSD-2-Clause
License Family: permissive
Topics: alphafold2, databases, enrichment-analysis, ensembl, gget, ncbi, reference, uniprot, alphafold, archs4, blast, enrichr, genomics, proteomics, rna-seq, transcriptomics, cellxgene
Last push: 2026-08-31T22:03:50+00:00

## Health v2 (maintenance only)
Score: 92/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 100, release rhythm 78, longevity 100
- inputs: {"age_days": 1582, "days_push": 2, "days_rel": 66, "gap_med": 44.5, "n_releases_24m": 11}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1195, forks 93 (observed 2026-09-01T02:14:06.608273+00:00)

## What it is
gget is a free, open-source Python package and command-line tool for efficiently querying genomic reference databases such as Ensembl, UniProt, NCBI, and AlphaFold. It consists of interoperable modules that each perform a type of database query (gene search, sequence retrieval, BLAST, enrichment analysis, ortholog lookup) in a single line of code.

## Use cases
- fetch Ensembl reference and annotation files for a species
- search for genes by name or description and get their Ensembl IDs
- retrieve gene and transcript metadata from an Ensembl ID
- fetch amino acid or nucleotide sequences of genes
- BLAST or align a sequence against reference databases
- run enrichment analysis on a list of genes
- find orthologs of a gene across species
- query protein structure predictions from AlphaFold

## When to choose
- you need quick programmatic or command-line access to genomic reference databases like Ensembl, UniProt, or NCBI
- you want one-line queries for gene info, sequences, or orthologs in Python or Jupyter
- you need sequence alignment (BLAST/BLAT/diamond/muscle) without setting up local databases
- you are doing transcriptomics or proteomics work and want enrichment analysis or AlphaFold structure lookups

## When to avoid
- you need a full-featured genome browser or heavy-duty local bioinformatics pipelines
- you require offline access to genomic databases with no internet queries
- you need a graphical interface rather than CLI or Python API
- your work is outside genomics/proteomics and unrelated to biological reference data

## Facets
- artifact type: library
- maturity: active
- function: search-engine, cli, sdk, data-science
- domain: bioinformatics, data-science, developer-tools
- platform: python, cli, cross-platform
- tags: genomics, ensembl, uniprot, alphafold, blast, enrichment-analysis, bioinformatics, transcriptomics, proteomics, single-cell

## Member repositories
- scverse/gget (main) score 92

## Provenance
- Observed fields: from GitHub, fetched 2026-09-01T02:14:06.608273+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 2026-08-30T06:23:20.777760+00:00, confidence not recorded.
  - readme: https://github.com/scverse/gget (fetched 2026-09-01T02:14:06.608273+00:00, sha 6bac03bc8806)
  - homepage: https://scverse.org/gget (fetched 2026-08-29T12:30:52.461798+00:00, sha 05b4b18650ab)
  - site_page: https://scverse.org/gget/en/installation.html (fetched 2026-08-29T12:30:52.471051+00:00, sha 766dda1cef1e)
  - site_page: https://scverse.org/gget/es/installation.html (fetched 2026-08-29T12:30:52.472803+00:00, sha dd0fc26a97f1)
- Data as of 2026-08-30T08:39:29.467469+00:00.