Installing HoloViews ¶
The quickest and easiest way to get the latest version of all the recommended packages for working with HoloViews on Linux, Windows, or Mac systems is via the conda command provided by the Anaconda or Miniconda scientific Python distributions:
conda install -c ioam holoviews bokeh
A similar set of packages can be installed using
, if that
command is available on your system:
pip install "holoviews[recommended]"
also supports other installation options, including a minimal
install of only the packages necessary to generate and manipulate
HoloViews objects without visualization:
pip install holoviews
This minimal install includes only the two required libraries Param and Numpy , neither of which has any required dependencies, which makes it very easy to integrate HoloViews into your workflow or as part of another project.
Alternatively, you can ask
to install a larger set of
packages that provide additional functionality in HoloViews:
pip install "holoviews[extras]"
pip install "holoviews[all]"
Between releases, development snapshots are made available on conda and can be installed using:
conda install -c ioam/label/dev holoviews
To get the very latest development version using
, you can use:
pip install git+https://github.com/ioam/holoviews.git
The alternative approach using git archive (e.g
recommended as you will have incomplete version strings.
Anyone interested in following development can get the very latest version by cloning the git repository:
git clone https://github.com/ioam/holoviews.git
To make this code available for import you then need to run:
python setup.py develop
And you can then update holoviews at any time to the latest version by running:
Once you’ve installed HoloViews, you can get started by launching Jupyter Notebook:
To work with JupyterLab you will also need the PyViz 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:
Now you can download the tutorial notebooks . unzip them somewhere Jupyter Notebook can find them, and then open the Homepage.ipynb tutorial or any of the others in the Notebook. Enjoy exploring your data!