Installing and Configuring HoloViews¶

HoloViews can be installed on any platform where NumPy and Python 2.7 or 3 are available.

That said, HoloViews is designed to work closely with many other libraries, which can make installation and configuration more complicated. This user guide page describes some of these less-common or not-required options that may be helpful for some users.

Other installation options¶

The main installation instructions should be sufficient for most users, but you may also want the Matplotlib and Plotly backends, which are required for some of the examples:

conda install matplotlib plotly

HoloViews can also be installed using one of these pip commands:

pip install holoviews
pip install 'holoviews[recommended]'
pip install 'holoviews[extras]'
pip install 'holoviews[all]'

The first option installs just the bare library and the NumPy and Param libraries, which is all you need on your system to generate and work with HoloViews objects without visualizing them. The other options install additional libraries that are often useful, with the recommended option being similar to the conda install command above.

Between releases, development snapshots are made available as conda packages:

conda install -c pyviz/label/dev holoviews

To get the very latest development version you can clone our git repository and put it on the Python path:

git clone git://github.com/ioam/holoviews.git
cd holoviews
pip install -e .

JupyterLab configuration¶

To work with JupyterLab you will also need the HoloViews JupyterLab extension:

conda install -c conda-forge jupyterlab
jupyter labextension install @pyviz/jupyterlab_pyviz

Once you have installed JupyterLab and the extension launch it with:

jupyter-lab

hv.config settings¶

The default HoloViews installation will use the latest defaults and options available, which is appropriate for new users. If you want to work with code written for older HoloViews versions, you can use the top-level hv.config object to control various backwards-compatibility options:

• future_deprecations: Enables warnings about future deprecations (introduced in 1.11).
• warn_options_call: Warn when using the to-be-deprecated __call__ syntax for specifying options, instead of the recommended .opts method.

It is recommended you set warn_options_call to True in your holoviews.rc file (see section below).

It is possible to set the configuration using hv.config directly:

However, because in some cases this configuration needs to be declared before the plotting extensions are imported, the recommended way of setting configuration options is:

In addition to backwards-compatibility options, hv.config holds some global options:

• image_rtol: The tolerance used to enforce regular sampling for regular, gridded data. Used to validate Image data.

This option allows you to set the rtol parameter of Image elements globally.

Improved tab-completion¶

Both Layout and Overlay are designed around convenient tab-completion, with the expectation of upper-case names being listed first. In recent versions of Jupyter/IPython there has been a regression whereby the tab-completion is no longer case-sensitive. This can be fixed with:

The holoviews.rc file¶

HoloViews searches for the first rc file it finds in the following places (in order):

1. holoviews.rc in the parent directory of the top-level __init__.py file (useful for developers working out of the HoloViews git repo)
2. ~/.holoviews.rc
3. ~/.config/holoviews/holoviews.rc

The rc file location can be overridden via the HOLOVIEWSRC environment variable.

The rc file is a Python script, executed as HoloViews is imported. An example rc file to include various options discussed above might look like this:

import holoviews as hv
hv.config(warn_options_call=True)
hv.extension.case_sensitive_completion=True