Any Linux, Mac OS X, or Windows computer with a web browser (preferably Google Chrome) should be suitable. 16GB of RAM is required for some of the examples, but most will run fine in 4GB.
If you don’t already have conda on your machine, you can get it from conda.io , and then open a terminal window.
If you do have conda already, it’s a good idea to update it (running it twice to get the very latest) to ensure you have the latest version:
> conda update conda > conda update conda
You should then create a separate Conda environment to work in for this tutorial:
> conda create -n pyviz-tutorial python=3.6 > conda activate pyviz-tutorial
Depending on how your conda is set up, you may need to use “source” instead of “conda” activate, or sometimes just “activate” on Windows.
Step 2: Install
and other required libraries
> conda install -c pyviz/label/dev pyviz
Step 3: Install the tutorials in your current working directory and download data ¶
> pyviz examples
This will (a) create a copy of the notebooks and related files needed for the tutorial in a new subdirectory
, and (b) download larger sample datasets such as NYC Taxi.
If you only want to get a copy of the examples, or only want to download the data, there are individual commands pyviz copy-examples and pyviz fetch-data ; run e.g. pyviz copy-examples –help for more info.
Step 4: Launch Jupyter Notebook ¶
You can then launch the notebook server and client:
> cd pyviz-examples > jupyter notebook
A browser window with a Jupyter Notebook instance should now open, letting you select and execute each notebook. You can start with the ones in the
subdirectory, as these show how to use the others in the
directory along with the applications in the
directory. The first notebook to load is
, which makes it simple to subsequently load each of the others.
If you don’t see the notebook appear (e.g. on some OS X versions), you may need to cut and paste the URL from the console output manually.
Step 5: Test that everything is working ¶
You can see if everything has installed correctly by selecting the
notebook from the index and doing “Cell/Run All” in the menus. There may be warnings on some platforms, but you’ll know it is working if you see the orange HoloViews logo after it runs