# nextflow-io/nextflow

A DSL for data-driven computational pipelines

Repository: https://github.com/nextflow-io/nextflow
Canonical: https://ross.abutalabs.com/products/nextflow
Homepage: http://nextflow.io
Language: Groovy
License: Apache-2.0
License Family: permissive
Topics: bioinformatics, workflow-engine, pipeline, pipeline-framework, nextflow, cloud, groovy, sge, slurm, aws, docker, singularity, hpc, singularity-containers, reproducible-science, reproducible-research, dataflow, hello
Last push: 2026-08-26T21:57:02+00:00

## Health v2 (maintenance only)
Score: 97/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 93, longevity 100
- inputs: {"age_days": 4907, "days_push": 7, "days_rel": 49, "gap_med": 11.0, "n_releases_24m": 35}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3475, forks 807 (observed 2026-08-28T04:08:06.119388+00:00)

## What it is
Nextflow is an open-source DSL and runtime for building scalable, portable, and reproducible data-driven computational pipelines, based on a dataflow programming model. It executes pipelines across local machines, HPC schedulers (SLURM, SGE, LSF), and cloud platforms (AWS, Azure, Google Cloud, Kubernetes) with container-based dependency management.

## Use cases
- run reproducible bioinformatics pipelines on an HPC cluster
- scale genomics workflows to AWS Batch or Google Cloud
- build parallel data processing pipelines without learning a new language
- resume a failed pipeline from the last successful step
- run the same pipeline locally and on Kubernetes with containers
- share and version scientific workflows with Git integration

## When to choose
- you need reproducible, containerized scientific or data-intensive pipelines
- you want portability across HPC schedulers and multiple cloud providers
- your workflows are parallel and dataflow-oriented with many tasks
- you want automatic checkpointing and resume of pipeline runs

## When to avoid
- you need simple one-off scripts with no parallelism or portability needs
- you require a GUI-based workflow builder rather than code-first DSL
- your team is unwilling to adopt a Groovy-based DSL
- you need lightweight orchestration for microservices rather than batch data pipelines

## Facets
- artifact type: framework
- maturity: stable
- function: workflow-automation, etl, container-runtime, cloud, scheduling, developer-tools
- domain: bioinformatics, cloud-computing, microservices
- platform: cloud, self-hosted, jvm, cli
- tags: workflow-engine, hpc, dsl, reproducibility, dataflow, nf-core, singularity, slurm, aws-batch, scientific-pipelines, data-engineering, containers, automation, linux, macos, docker, kubernetes

## Member repositories
- nextflow-io/nextflow (main) score 97

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:06.119388+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 2026-08-29T18:36:32.597750+00:00, confidence not recorded.
  - readme: https://github.com/nextflow-io/nextflow (fetched 2026-08-28T04:08:06.119388+00:00, sha 5f7614e43763)
  - homepage: http://nextflow.io (fetched 2026-08-29T09:30:31.836350+00:00, sha 47b1b09e9309)
  - site_page: https://nextflow.io/about-us.html (fetched 2026-08-29T09:30:31.839022+00:00, sha bd3305d3d43c)
- Data as of 2026-08-30T08:39:29.467469+00:00.