Run lightweight local workflows
An experimental, lightweight, easily configurable workflow engine for automating development, operations, data processing, and content management tasks.
Technical Foundations
- Configuration, task definition, and flow control in YAML - Define your workflows in declarative YAML files
- Operations as system commands - Use familiar shell-like syntax for executing commands
- Expressions and logic in pure Python - Leverage Python for dynamic values and logic
Key Features
- Simple Operation Definition - Define workflows as arrays of system commands (learn more)
- Data Flow Operators - Pipe data between steps with
=>and->(learn more) - Template Substitution - Use
{{variable}}syntax to inject data into commands (learn more) - Python Expressions - Evaluate Python code for dynamic values (learn more)
- Sub-operations - Compose operations from other operations (learn more)
- MCP Server Support - Expose operations as tools for AI assistants (learn more)
Use Cases
Dyngle is designed for:
- Development workflow automation (build, test, deploy)
- Operations tasks (server management, monitoring)
- Data processing pipelines
- Content management workflows
- AI assistant tool integration