This project contains self-contained, typically domain-specific examples illustrating how to use one or more HoloViz visualization tools to explore data or understand a topic. Each project is fully reproducible by downloading and running it locally, and can also be deployed automatically using an Anaconda Enterprise server.
To run an example locally first download it from https://examples.holoviz.org, unzip it, and cd into it.
Install anaconda-project and run the command defined in the anaconda-project.yml file:
conda install anaconda-project=0.11.1
anaconda-project runanaconda-project is a handy way to automate a project, but if you don't want to use it, you can create a regular conda environment using:
conda env create --file anaconda-project.ymlThen 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 notebookNOTE: 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 the appropriate location in this directory.
In addition to running examples locally you can upload and share them using Anaconda Enterprise, which is the platform we use for publishing the 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.
To experiment in a running environment, you can use binder:
Since the data involved is sometimes 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.
Shield:
This work is licensed under a Creative Commons Attribution 4.0 International License.
