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This post is an overview for reviewers that are using Gigantum to inspect code for a manuscript.

Gigantum is a browser base application that integrates with Jupyter &  RStudio to streamline the creation and sharing of reproducible work in Python & R. 

This post is an overview for how to use Gigantum to create and submit reproducible code.

Working exclusively in a single cloud isn't possible for most people, and that is not just because it is expensive. Real work requires significantly flexibility around deployment.

For example, sensitive data typically can't go in the cloud. Or maybe each of your three clients uses a different cloud, or maybe you spend significant time on a laptop. 

It would be nice if things would "just work" wherever you want them to, but the barriers are many and large. Git & Docker skills are table stakes. Typos & hard coded variables rule the day. No matter how careful you are, stuff goes wrong. Maybe your collaborators don't have the same level of care and technical skill you do.

Who knows? The possibilities are endless.

Well, it used to be hard. There is a new container native system that moves reproducible work between machines (virtual or bare metal) with a few clicks.

No need to know Docker or Git. No need to be obsessive about best practices. No need to worry who is on what machine. 

We will demo it here using Dask and DigitalOcean for context. In the demo we:

1. Create a 32-core Droplet (i.e. instance) on Digital Ocean
2. Install the open source Gigantum Client on the Droplet
3. Import a Dask Project from Gigantum Hub and run it
4. Sync your work to Gigantum Hub to save it for later.

Computational reproducibility should be trivial but it is not. Though code and data are increasingly shared, the community has realised that many other factors affect reproducibility, a typical example of which is the difficulty in reconstructing a work’s original library dependencies and software versions. The required level of detail documenting such aspects scales with the complexity of the problem, making the creation of user-friendly solutions very challenging.