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Introduction

Coflux is an open-source workflow engine for orchestrating and observing computational workflows defined in plain Python. You define workflows using simple decorators — no DSLs, no YAML, no DAG definitions — and Coflux handles scheduling, retries, caching, and observability.

You can use it to build data pipelines, coordinate background tasks, or orchestrate real-time workflows.

Why Coflux?

  • Plain Python: Workflows are regular Python functions with decorators. They remain callable outside of Coflux, making them easy to test and debug.
  • Self-hosted: You run the server. Your data stays in your infrastructure.
  • Workspace inheritance: Branch your production environment into development workspaces, re-run specific steps with real data, and experiment without affecting production.
  • Live observation: Studio provides a web UI for exploring run graphs, timelines, logs, and results in real time.

Getting started

The following guide walks you through defining and running your first workflow:

  1. Installing the CLI
  2. Starting the server
  3. Defining a workflow
  4. Running a worker
  5. Submitting a run
  6. Connecting from Studio (optional)