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LifeOmic’s PHC Python SDK

In my last post, I introduced Jupyter Notebook support for the PHC. I briefly mentioned the new PHC Python SDK. The SDK came out of a hackathon that our company sponsored with one of our business partners last year. I wanted to follow up with another post to quickly highlight it.

This is the first SDK for the PHC. We have a CLI application that has been around for a while and is heavily used both internally and externally by our customers. While the CLI works really well and can be incorporated into scripts for automation purposes, we wanted to provide something that had a nicer developer experience. We decided that Python would be a good candidate for the SDK language given that a lot of our initial use cases involved performing analysis on data that is stored in the PHC. Python has become the language of choice for data scientists. So it felt like the right one to start with.

Getting started with the SDK is pretty easy. You just need to first install it using pip.

pip install phc

The code below shows an example of how to query the clinical FHIR resources that are stored in a PHC project. The nice thing about the SDK being written in Python is that it is really easy to utilize popular packages like pandas. The SDK is still very young. We do not expose all of the platform functionality at this point.

More Info

The SDK is open source, hosted on GitHub, and deployed to PyPI. We welcome contributions from anyone wanting to add improvements or new features. Read the docs for more information.

It comes installed on the notebook environments that are available in the PHC. The SDK plus notebooks have proven to be a powerful combination for those wanting to perform advanced data analysis. Contact us if you are interested in learning more about the LifeOmic Precision Health Cloud.