Skip to main content

A lightweight, powerful, and flexible workflow engine that executes tasks defined in YAML configuration files

Project description

YAML Workflow

PyPI version Python versions CI codecov License: MIT

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.

Why yaml-workflow?

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

Features

  • YAML-driven workflow definition with Jinja2 templating
  • Multiple task types: shell, Python, file, template, HTTP, batch
  • Workflow composition via imports — reuse steps across workflows
  • Plugin system via entry points — pip install yaml-workflow-myplugin
  • Watch mode — --watch to re-run on file changes
  • Dry-run mode to preview without executing
  • Workflow visualization (ASCII branching DAG and Mermaid)
  • Parallel execution with configurable worker pools
  • State persistence and resume capability
  • Retry mechanisms with configurable strategies
  • Namespaced variables (args, env, steps, batch)
  • Flow control with custom step sequences and conditions
  • Extensible task system via @register_task decorator

Quick Start

# Install
pip install yaml-workflow

# Initialize example workflows
yaml-workflow init

# Run a workflow with parameters
yaml-workflow run workflows/hello_world.yaml name=Alice

Example 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.txt

Visualize workflows

yaml-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.

Dry-run mode

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.

Workflow composition

Reuse steps across workflows with imports:

# main.yaml
imports:
  - ./shared/logging_steps.yaml
  - ./shared/common_params.yaml

steps:
  - name: my_step
    task: shell
    inputs:
      command: echo "runs after imported steps"

Imported steps are prepended. Imported params provide defaults that the main workflow can override. Supports transitive imports with circular detection.

Watch mode

Automatically re-run on file changes during development:

yaml-workflow run workflows/hello_world.yaml name=Alice --watch

Monitors the workflow file and all imported files. Press Ctrl+C to stop.

More commands

# 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 --resume

Documentation

Full documentation is available at orieg.github.io/yaml-workflow.

Contributing

Contributions are welcome! See the Contributing Guide for development setup and guidelines.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

yaml_workflow-0.6.1.dev0.tar.gz (67.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

yaml_workflow-0.6.1.dev0-py3-none-any.whl (85.1 kB view details)

Uploaded Python 3

File details

Details for the file yaml_workflow-0.6.1.dev0.tar.gz.

File metadata

  • Download URL: yaml_workflow-0.6.1.dev0.tar.gz
  • Upload date:
  • Size: 67.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for yaml_workflow-0.6.1.dev0.tar.gz
Algorithm Hash digest
SHA256 da63b70f820e5399612e680741abfca042177f9a449964d35e18157de1582eff
MD5 b368c083bc0ee4e39b2f49936a3b3f08
BLAKE2b-256 ab60345835f8a001b5f90110a37cfca50675892d61a7954dc98e43ad1cac6a09

See more details on using hashes here.

Provenance

The following attestation bundles were made for yaml_workflow-0.6.1.dev0.tar.gz:

Publisher: publish.yml on orieg/yaml-workflow

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file yaml_workflow-0.6.1.dev0-py3-none-any.whl.

File metadata

File hashes

Hashes for yaml_workflow-0.6.1.dev0-py3-none-any.whl
Algorithm Hash digest
SHA256 29e705c8b2f561233a236048909fb63468cf2dd90d6b92e1e7efaa2bdfb07d83
MD5 932140ef6a5270681bed79888a01bdf6
BLAKE2b-256 2e7eed9a50f46c747b554815dad28f4efa603b5f6f5ceba8287b5d1274339c94

See more details on using hashes here.

Provenance

The following attestation bundles were made for yaml_workflow-0.6.1.dev0-py3-none-any.whl:

Publisher: publish.yml on orieg/yaml-workflow

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page