Here's what you need to run SAS with Jupyter: This allows you to move easily between Python and SAS in a single environment.

From within a Python language notebook, you can inject your SAS program code and pull in SAS results. These magic commands look almost just like SAS macro calls (imagine that!). The second way that you can run SAS code is by using special Jupyter 'magics' supported by the sas_kernel. nbextensions/showSASLog) that can show you the SAS log. The most natural method is to create a new SAS notebook, available from the New menu in the Jupyter Home window and from the File menu in an active notebook:įrom a SAS notebook, you can enter and run SAS code directly from a cell: Within Jupyter, the sas_kernel provides multiple ways to access SAS programming methods. Visit the project on GitHub: sas_kernel by sassoftware

If you want to learn more about Jupyter and see the SAS support in action, then you can watch the video here. My colleague Amy Peters announced this during a SAS Tech Talk show at SAS Global Forum 2016. With this new project on the /sassoftware page, SAS contributes new support for running SAS from within Jupyter Notebooks - a popular browser-based environment used by professors and data scientists. It does, however, take quite some time to rebuild the docker image after the repository is updated.We've just celebrated Earth Day, but I'm here to talk about Jupyter - and the SAS open source project that opens the door for more learning. Then push your changes, and point to your repository.Ĭompared to adding packages within a notebook, an advantage of this approach is that package installation and precompilation happens only when the docker the image for the repository is built (or rebuilt after each commit), instead of each time a user opens the notebook.Pkg.activate('path/to/repo') # modify this Probably easiest to just delete them and then recreate them by running something like Modify the Project.toml and Manifest.toml files.Modify the version of Julia in the Dockerfile if you want something other than 1.5.3.Replace the contents of the notebooks folder with your notebooks (or maybe just delete it and leave your notebooks in a separate place, so that you can update the notebooks without triggering a rebuild of the binder docker image).Clone GitHub - UBCECON567/ioplutonotebooks: Pluto.jl notebooks about empirical industrial organization.I created this setup by making some minor changes to GitHub - pankgeorg/pluto-on-jupyterlab I don’t know if it’s the best way to do it, but I have a working setup at GitHub - UBCECON567/ioplutonotebooks: Pluto.jl notebooks about empirical industrial organization. You can run Pluto on binder with a custom package environment by creating an appropriate github repository.

Hosting a jupyter notebook online