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README.md

ipympl

TravisCI build status Latest PyPI version Latest conda-forge version Latest npm version Binder Gitter

Leveraging the Jupyter interactive widgets framework, ipympl enables the interactive features of matplotlib in the Jupyter notebook and in JupyterLab.

Besides, the figure canvas element is a proper Jupyter interactive widget which can be positioned in interactive widget layouts.

Usage

To enable the ipympl backend, simply use the matplotlib Jupyter magic:

%matplotlib widget

Example

See the example notebook for more!

matplotlib screencast

Installation

With conda:

conda install -c conda-forge ipympl

With pip:

pip install ipympl

Use in JupyterLab

If you want to use ipympl in JupyterLab, we recommend using JupyterLab >= 3.

Install an old JupyterLab extension

If you are using JupyterLab 1 or 2, you will need to install the right jupyter-matplotlib version, according to the ipympl and jupyterlab versions you installed. For example, if you installed ipympl 0.5.1, you need to install jupyter-matplotlib 0.7.0, and this version is only compatible with JupyterLab 1.

conda install -c conda-forge ipympl==0.5.1
jupyter labextension install @jupyter-widgets/jupyterlab-manager jupyter-matplotlib@0.7.0

Versions lookup table:

ipympl jupyter-matplotlib JupyterLab Matplotlib
0.5.8 0.7.4 1 or 2 3.3.1
0.5.7 0.7.3 1 or 2 3.2.*
... ... ...
0.5.3 0.7.2 1 or 2
0.5.2 0.7.1 1
0.5.1 0.7.0 1
0.5.0 0.6.0 1
0.4.0 0.5.0 1
0.3.3 0.4.2 1
0.3.2 0.4.1 1
0.3.1 0.4.0 0 or 1

For a development installation (requires nodejs):

git clone https://github.com/matplotlib/ipympl.git
cd ipympl
pip install -e .

# If using classic Jupyter Notebook
jupyter nbextension install --py --symlink --sys-prefix ipympl
jupyter nbextension enable --py --sys-prefix ipympl

# If using JupyterLab
jupyter labextension install @jupyter-widgets/jupyterlab-manager --no-build
jupyter labextension install ./js

How to see your changes

Javascript:

To continuously monitor the project for changes and automatically trigger a rebuild, start Jupyter in watch mode:

jupyter lab --watch

After a change wait for the build to finish and then refresh your browser and the changes should take effect.

Python:

If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.

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