Popper

• Getting Started
  • Installation
  • Create Your First Workflow
  • Run your workflow
  • Debug your workflow
  • Next Steps

• CLI features
  • New workflow initialization
  • Executing a workflow
  • Executing a step interactively
  • Parametrizing workflows with substitutions
  • Customizing container engine behavior
  • Continuously validating a workflow
  • Translating workflows for other task runners
  • Visualizing workflows

• Concepts
  • Resources
  • Glossary

• Workflow Syntax and Execution Runtime
  • Syntax
  • Execution Runtime
  • Container Engines
  • Resource Managers
  • Life of a Workflow

• Guides
  • Choosing a location for your step
  • Using shell scripts to define step logic
  • Hello world step example
  • Creating a Docker container
  • Implementing a workflow for an existing set of scripts
  • Building images using BuildKit
  • Computational research with Python and JupyterLab
  • Computational research with R and RStudio Server

• Other Resources

• FAQ
  • How can I create a virtual environment to install Popper
  • How can we deal with large datasets? For example I have to work on large data of hundreds GB, how would this be integrated into Popper?
  • How can Popper capture more complex workflows? For example, automatically restarting failed tasks?
  • Can I follow Popper in computational science research, as opposed to computer science?
  • How to apply the Popper protocol for applications that take large quantities of computer time?

• Contributing

Indices and tables

• Index
• Module Index
• Search Page