Bionic

Note

Bionic is in alpha and under active development.

Release: v0.5.0 — Quick Links: Source | Issues | Get Started

Bionic is a Python framework for building, running, and sharing data science workflows. It’s designed for writing research code: code where the point is to learn something from the code’s output, and where you’ll be rapidly tweaking and rewriting your code based on what you learn.

Bionic uses dependency injection to let you specify your workflow with a minimal amount of code. You define the entities you care about: dataframes, parameters, models, plots. Bionic then handles the tedious glue work of stitching your components together, adding caching and execution logic, and wrapping it up in a nice API. This means you can make progress faster; you can refactor your code more confidently; and your colleagues can understand and reuse your work more easily.

Contents

• Why Should I Use Bionic?
  • When Should I Use It?
  • Why Not Just Use…?
• Get Started
  • Installation
  • Tutorials
• Concepts and Features
  • Flows, FlowBuilders, and Entities
  • Caching and Protocols
  • Multiplicity
  • Other Features
• Warnings and Pitfalls
  • This is Alpha Software
  • Avoid Global State
  • Don’t Modify Your Arguments
  • Watch Out For Stale Data
• API Reference
  • Flow and FlowBuilder
  • Decorators
  • Protocols
• Get Help
• Contributing to Bionic
  • Setting Up Your Development Environment
  • Running the Tests
  • Updating the Documentation
• The Future of Bionic
  • Development Status
  • Future Work