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Calkit is an open source framework and toolkit for reproducible research projects. It acts as a top-level layer to integrate and simplify the use of enabling technologies such as Git, DVC, Conda, and Docker. Calkit also adds a domain-specific data model such that all aspects of the research process can be fully described in a single repository and therefore easily consumed by others.

Our goal is to make reproducibility easier so it becomes more common. To do this, we try to make it easy for users to follow two simple rules:

1. Keep everything in version control. This includes large files like datasets, enabled by DVC. The Calkit Cloud, hosted at calkit.io, serves as a simple default DVC remote storage location for those who do not want to manage their own infrastructure.
2. Generate all important artifacts with a single pipeline. There should be no special instructions required to reproduce a project's artifacts. It should be as simple as calling calkit run. The DVC pipeline (in a project's dvc.yaml file) is therefore the main thing to "build" throughout a research project. Calkit provides helper functionality to build pipeline stages that keep computational environments up-to-date and label their outputs for convenient reuse.

Features

• A version control interface that unifies and simplifies interaction with Git and DVC.
• Automated environment management.
• A project metadata model to declare global dependencies, environments, and artifacts like datasets, figures, notebooks, and publications to facilitate searchability and reuse.
• A complementary cloud platform to interact with the project and its artifacts, which also serves as a DVC remote.
• Templates for projects, publications, and more.
• The ability to declare, execute, and track manual procedures and pipeline stages with manual steps.
• A Jupyter cell magic to use notebook cells as pipeline stages.
• Tools to help improve the reproducibility of workflows that depend on Microsoft Office.