A lightweight, powerful, and flexible workflow engine that executes tasks defined in YAML configuration files. Create modular, reusable workflows by connecting tasks through YAML definitions, with support for parallel processing, batch operations, and state management.
Most workflow tools (Airflow, Prefect, Dagster) are designed for distributed cloud infrastructure with complex server setups. yaml-workflow takes a different approach:
| yaml-workflow | Airflow / Prefect / Dagster | |
|---|---|---|
| Setup | pip install yaml-workflow |
Server, database, scheduler, workers |
| Configuration | Plain YAML files | Python DAGs + infrastructure config |
| Dependencies | 3 (PyYAML, Jinja2, Click) | 50+ packages, Docker, PostgreSQL |
| Use case | Local automation, scripts, CI/CD, data pipelines | Enterprise orchestration at scale |
| Learning curve | Minutes | Hours to days |
| State | File-based, resumable | Database-backed |
Choose yaml-workflow when you need:
- Simple task automation without infrastructure overhead
- Reproducible pipelines defined in version-controlled YAML
- Batch processing with parallel execution
- State persistence and workflow resume after failures
- A lightweight alternative to shell scripts with better error handling
- YAML-driven workflow definition with Jinja2 templating
- Multiple task types: shell, Python, file, template, HTTP, batch
- Parallel execution with configurable worker pools
- State persistence and resume capability
- Dry-run mode to preview without executing
- Workflow visualization (ASCII and Mermaid)
- Retry mechanisms with configurable strategies
- Namespaced variables (
args,env,steps,batch) - Flow control with custom step sequences and conditions
- Extensible task system via
@register_taskdecorator
# Install
pip install yaml-workflow
# Initialize example workflows
yaml-workflow init
# Run a workflow with parameters
yaml-workflow run workflows/hello_world.yaml name=AliceExample workflow (hello_world.yaml):
name: Hello World
description: A simple greeting workflow
params:
name:
type: string
default: World
steps:
- name: create_greeting
task: template
inputs:
template: "Hello, {{ args.name }}!"
output_file: greeting.txt
- name: show_greeting
task: shell
inputs:
command: cat greeting.txtyaml-workflow visualize workflows/data_pipeline.yaml Workflow: Data Pipeline
┌─────────────────┐
│ detect_format │
│ python_code │
└─────────────────┘
│
▼
┌──────────────┐ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│ process_json │ │ process_csv │ │ process_xml │ │handle_unknown│
│ shell │ │ shell │ │ shell │ │ shell │
└──────────────┘ └──────────────┘ └──────────────┘ └──────────────┘
│
▼
┌─────────────────┐
│ generate_report │
│ python_code │
└─────────────────┘
Adjacent conditional steps are automatically grouped as branches. Use --format mermaid to export for docs or GitHub rendering.
Preview what a workflow would do without executing anything:
yaml-workflow run workflows/hello_world.yaml name=Alice --dry-run[DRY-RUN] Workflow: Hello World
[DRY-RUN] Steps: 2 to execute
[DRY-RUN] Step 'create_greeting' — task: template — WOULD EXECUTE
template: Hello, Alice!
output_file: greeting.txt
[DRY-RUN] Step 'show_greeting' — task: shell — WOULD EXECUTE
command: cat greeting.txt
[DRY-RUN] Complete. 2 step(s) would execute, 0 would be skipped.
[DRY-RUN] No files were written. No tasks were executed.
# List available workflows
yaml-workflow list
# Validate a workflow
yaml-workflow validate workflows/hello_world.yaml
# Resume a failed workflow
yaml-workflow run workflows/hello_world.yaml --resumeFull documentation is available at orieg.github.io/yaml-workflow.
- Getting Started - Installation and first workflow
- Task Types - Shell, Python, file, template, and batch tasks
- Workflow Structure - YAML configuration reference
- Templating - Jinja2 variable substitution
- State Management - Persistence and resume
- Task Development - Creating custom tasks
- API Reference - Full API documentation
Contributions are welcome! See the Contributing Guide for development setup and guidelines.
This project is licensed under the MIT License - see the LICENSE file for details.