Tutorials
This section contains learning-oriented lessons to help you get started with Torc. Each tutorial walks through a complete example from start to finish.
Tutorials:
- Configuration Files - Set up configuration files for Torc components
- Dashboard Deployment - Deploy torc-dash for local, shared, or HPC environments
- Workflow Wizard - Create workflows using the dashboard’s interactive wizard
- Many Independent Jobs - Create a workflow with 100 parallel jobs
- Diamond Workflow - Fan-out and fan-in with file dependencies
- User Data Dependencies - Pass JSON data between jobs
- Simple Parameterization - Single parameter dimension sweep
- Advanced Parameterization - Multi-dimensional hyperparameter grid search
- Multi-Stage Workflows with Barriers - Scale to thousands of jobs efficiently
- Map Python Functions - Distribute Python functions across workers
- Filtering CLI Output with Nushell - Filter jobs, results, and user data with readable queries
- Custom HPC Profile - Create an HPC profile for unsupported clusters
Start with the Configuration Files tutorial to set up your environment, then try the Dashboard Deployment tutorial if you want to use the web interface.
Example Files
The repository includes ready-to-run example workflow specifications in YAML, JSON5, and KDL formats. These complement the tutorials and demonstrate additional patterns:
| Example | Description | Tutorial |
|---|---|---|
| diamond_workflow.yaml | Fan-out/fan-in pattern | Diamond Workflow |
| hundred_jobs_parameterized.yaml | 100 parallel jobs via parameterization | Many Jobs |
| hyperparameter_sweep.yaml | ML grid search (3×3×2 = 18 jobs) | Advanced Params |
| multi_stage_barrier_pattern.yaml | Efficient multi-stage workflow | Barriers |
| resource_monitoring_demo.yaml | CPU/memory tracking | — |
| workflow_actions_simple_slurm.yaml | Automated Slurm scheduling | — |
Browse all examples:
See the examples README for the complete list and usage instructions.