cloud-bids-layout 0.1.dev2464353510

Cloud-BIDS-Layout: Use pybids with Amazon S3

Cloud-BIDS-Layout

Cloud-BIDS-Layout is a lightweight wrapper for pybids' BIDS.Layout that can grab BIDS studies from Amazon S3.

Motivation

The Brain Imaging Data Structure (BIDS) is an intuitive, accessible, and community-driven data specification for neuroimaging data. Pybids is an exceptionally written Python library that makes it easy for researchers to query, summarize, and manipulate BIDS-compliant data. However, it's workhorse BIDSLayout class doesn't index remote datasets stored in the cloud. That's where Cloud-BIDS-Layout comes in.

Cloud-BIDS-Layout allows its user to specify a remote location for a BIDS-Compliant dataset. Currently only Amazon S3 locations are supported but support for Google Cloud Storage and others is coming soon. Cloud-BIDS-Layout creates a lightweight semblance of the remote dataset, just enough to pass to pybids' BIDSLayout for indexing. The user can then use pybids' familiar .get() method to select a subset of the study that they wish to download to the host. See the documentation for more details.

This is the Cloud-BIDS-Layout development site. You can view the source code, file new issues, and contribute to Cloud-BIDS-Layouts's development. If you are just getting started, you should look at the Cloud-BIDS-Layout documentation

Contributing

We love contributions! Cloud-BIDS-Layout is open source, built on open source, and we'd love to have you hang out in our community.

We have developed some guidelines for contributing to Cloud-BIDS-Layout.

Imposter syndrome disclaimer: We want your help. No, really.

There may be a little voice inside your head that is telling you that you're not ready to be an open source contributor; that your skills aren't nearly good enough to contribute. What could you possibly offer a project like this one?

We assure you - the little voice in your head is wrong. If you can write code at all, you can contribute code to open source. Contributing to open source projects is a fantastic way to advance one's coding skills. Writing perfect code isn't the measure of a good developer (that would disqualify all of us!); it's trying to create something, making mistakes, and learning from those mistakes. That's how we all improve, and we are happy to help others learn.

Being an open source contributor doesn't just mean writing code, either. You can help out by writing documentation, tests, or even giving feedback about the project (and yes - that includes giving feedback about the contribution process). Some of these contributions may be the most valuable to the project as a whole, because you're coming to the project with fresh eyes, so you can see the errors and assumptions that seasoned contributors have glossed over.

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

The imposter syndrome disclaimer was originally written by Adrienne Lowe for a PyCon talk, and was adapted based on its use in the README file for the MetPy project.