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Domain-specific narrative examples using multiple PyViz projects
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README.md

PyViz Topics Examples

Domain-specific narrative examples using multiple PyViz projects. Isolated fully described projects, runnable locally and deployable to Anaconda Enterprise. Each project is expected to have an author, a created-date, and a canonical URL that can be sent around to send someone to this particular project.

Running Locally

To run an example locally first download it from https://examples.pyviz.org, unzip it, and cd into it. Then install anaconda-project and run the command defined in the anaconda-project file:

conda install anaconda-project tornado<5.0
anaconda-project run

Don't want to use anaconda-project?

If you don't want to use anaconda-project, you can create a regular conda environment using:

conda env create --file anaconda-project.yml

Activate the environment (be sure to replace env-name with the real name of the environment you created):

conda activate <env-name>

Then start a jupyter notebook as usual:

jupyter notebook

NOTE: If the notebook depends on data files, you will need to download them explicitly if you don't use anaconda-project, by extracting the URLs defined in anaconda-project.yml and saving the file(s) to this directory.

Uploading to AE

In addition to running examples locally you can upload and share them using Anaconda Enterprise, which is the platform we use for publishing our public deployments. If you've already installed anaconda-project, then for an example named "bears" just do:

cd bears
anaconda-project archive bears.zip

Then in the AE interface select "Create", "Upload Project" and navigate to the zip file. Once your project has been created, you can deploy it.

Running on Binder

To experiment in a running environment, you can use binder:

Binder

Since the data involved is sometime rather large, full datasets are not available on binder, but small versions of the datasets are included in the environment so that you can test things out.

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