Getting Set Up

The hvPlot library is a complex project which provides a wide range of data interfaces and an extensible set of plotting backends, which means the development and testing process involves a wide set of libraries.

Preliminaries

Git

The hvPlot source code is stored in a Git source control repository. The first step to working on hvPlot is to install Git on to your system. There are different ways to do this depending on whether, you are using Windows, OSX, or Linux.

To install Git on any platform, refer to the Installing Git section of the Pro Git Book.

Conda

Developing hvPlot requires a wide range of packages that are not easily and quickly available using pip. To make this more manageable, core developers rely heavily on the conda package manager for the free Anaconda Python distribution. However, conda can also install non-Python package dependencies, which helps streamline hvPlot development greatly. It is strongly recommended that anyone developing hvPlot also use conda, and the remainder of the instructions will assume that conda is available.

To install Conda on any platform, see the Download conda section of the conda documentation.

Cloning the Repository

The source code for the hvPlot project is hosted on GitHub. To clone the source repository, issue the following command:

git clone https://github.com/pyviz/hvplot.git

This will create a hvplot directory at your file system location. This hvplot directory is referred to as the source checkout for the remainder of this document.

Installing Dependencies

hvPlot requires many additional packages for development and testing. Many of these are on the main Anaconda default channel.

Conda Environments

Since hvPlot interfaces with a large range of different libraries the full test suite requires a wide range of dependencies. To make it easier to install and run different parts of the test suite across different platforms hvPlot uses a library called pyctdev to make things more consistent and general.

conda create -n hvplot_dev -c pyviz pyctdev python=3.6

Specify the desired Python version, currently hvPlot officially supports Python 2.7, 3.5, 3.6 and 3.7. Once the environment has been created you can activate it with:

conda activate hvplot_dev

Finally to install the dependencies required to run the full unit test suite and all the examples:

doit develop_install -c pyviz/label/dev -o all

Next Steps

If you have any problems with the steps here, please contact the developers.