HoloViews+Bokeh Viz to Dashboards Tutorial at Jupytercon 2017
This document explains how to get your computer set up for the tutorial, including how to install the software libraries and data files that we will be working with. Because some of the data files are large, it's best to run through these steps before you leave on your trip, using a good internet connection.
jupytercon-2017-holoviews-tutorial repositoryStep 1: Clone the
- Any Linux, Mac OS X, or Windows computer with a web browser should work. We recommend Chrome, but typically also test Firefox and Safari.
- 16GB of RAM is required for some of the examples, but most will run fine in 4GB.
- Clone this repository, e.g. using
git clone https://github.com/ioam/jupytercon2017-holoviews-tutorial.git
- Open a terminal window inside the repository.
You should plan to do a "git pull" on your clone of this repository sometime in the 48 hours before the tutorial, in case we need to make any fixes or improvements in the meantime.
Step 2: Create a conda environment from
The easiest way to get an environment set up for the tutorial is
installing it using the
environment.yml we have provided. If you
don't already have it, install conda,
and then create the
hvtutorial environment by executing:
> conda env create --force -f environment.yml
When installation is complete you may activate the environment by writing:
> activate hvtutorial
(for Windows) or:
$ source activate hvtutorial
(for Linux and Mac).
Later, when you are ready to exit the environment after the tutorial, you can type:
If for some reason you want to remove the environment entirely, you can do so by writing:
> conda env remove --name hvtutorial
Step 3: Downloading the sample data
In this tutorial we will be showing you how to work with some fairly large datasets. Unfortunately, that also means that you have to download this data. To make this as easy as possible we have provided a script that will download the data for you. Simply execute in the root of your clone of this repository:
> python download_sample_data.py
Step 4: Launch Jupyter Notebook
You can then launch the notebook server and client:
(hvtutorial)> cd notebooks (hvtutorial)> jupyter notebook --NotebookApp.iopub_data_rate_limit=100000000
A browser window with a Jupyter Notebook instance should now open, letting you select and execute each notebook. (Increasing the rate limit in this way is required for the current 5.0 Jupyter version, but should not be needed in earlier or later Jupyter releases.)
If you don't see the notebook appear (e.g. on some OS X versions), you'll 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
00-welcome.ipynb notebook 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 HoloViews logo after it runs
Preparing for the Tutorial
If you want to get familiar with HoloViews before the tutorial (which is not a requirement), you can have a look at our new website at holoviews.org, browsing through the getting started and user guides. If you want to run these examples yourself, you can get ahold of them by typing this command inside your conda environment:
(hvtutorial)> holoviews --install-examples (hvtutorial)> cd holoviews-examples
You should then be inside a new folder named "holoviews-examples" in your current directory. Now launch a Jupyter notebook server and dive into the examples:
(hvtutorial)> jupyter notebook --NotebookApp.iopub_data_rate_limit=100000000