Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/matplotlib/ipympl

Matplotlib Jupyter Integration
https://github.com/matplotlib/ipympl

interactive ipywidgets jupyter-widgets jupyterlab-extension matplotlib

Last synced: 25 days ago
JSON representation

Matplotlib Jupyter Integration

Awesome Lists containing this project

README 

        
# ipympl



[![Test Status](https://github.com/matplotlib/ipympl/actions/workflows/main.yml/badge.svg)](https://github.com/matplotlib/ipympl/actions/workflows/main.yml?query=branch%3Amain)

[![Latest PyPI version](https://img.shields.io/pypi/v/ipympl?logo=pypi)](https://pypi.python.org/pypi/ipympl)

[![Latest conda-forge version](https://img.shields.io/conda/vn/conda-forge/ipympl?logo=conda-forge)](https://anaconda.org/conda-forge/ipympl)

[![Latest npm version](https://img.shields.io/npm/v/jupyter-matplotlib?logo=npm)](https://www.npmjs.com/package/jupyter-matplotlib)

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/matplotlib/ipympl/main?urlpath=notebooks/docs/examples/full-example.ipynb)

[![Gitter](https://img.shields.io/badge/gitter-Join_chat-blue?logo=gitter)](https://gitter.im/jupyter-widgets/Lobby)



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

```

## Documentation

See the documentation at: https://matplotlib.org/ipympl/

## Example

See the [example notebook](https://github.com/matplotlib/ipympl/blob/main/docs/examples/full-example.ipynb) for more!



![matplotlib screencast](matplotlib.gif)



## Installation



### With conda:



```bash

conda install -c conda-forge ipympl

```



### With pip:



```bash

pip install ipympl

```



### Use in JupyterLab



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



If you use JupyterLab 2, you still need to install the labextension manually:



```bash

conda install -c conda-forge nodejs

jupyter labextension install @jupyter-widgets/jupyterlab-manager jupyter-matplotlib

```



#### 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`.



```bash

conda install -c conda-forge ipympl==0.5.1

jupyter labextension install @jupyter-widgets/jupyterlab-manager [email protected]

```



Versions lookup table:



| `ipympl` | `jupyter-matplotlib` | `JupyterLab` | `Matplotlib` |

|----------|----------------------|--------------|--------------|

| 0.9.3+   | 0.11.3+              | >=2,<5       | 3.4.0>=      |

| 0.9.0-2  | 0.11.0-2             | >=2,<5       | 3.4.0>=  <3.7|

| 0.8.8    | 0.10.x               | >=2,<5       | 3.3.1>=  <3.7|

| 0.8.0-7  | 0.10.x               | >=2,<5       | 3.3.1>=, <3.6|

| 0.7.0    | 0.9.0                | >=2,<5       | 3.3.1>=      |

| 0.6.x    | 0.8.x                | >=2,<5       | 3.3.1>=, <3.4|

| 0.5.8    | 0.7.4                | >=1,<3       | 3.3.1>=, <3.4|

| 0.5.7    | 0.7.3                | >=1,<3       | 3.2.*        |

| ...      | ...                  | ...          |              |

| 0.5.3    | 0.7.2                | >=1,<3       |              |

| 0.5.2    | 0.7.1                | >=1,<2       |              |

| 0.5.1    | 0.7.0                | >=1,<2       |              |

| 0.5.0    | 0.6.0                | >=1,<2       |              |

| 0.4.0    | 0.5.0                | >=1,<2       |              |

| 0.3.3    | 0.4.2                | >=1,<2       |              |

| 0.3.2    | 0.4.1                | >=1,<2       |              |

| 0.3.1    | 0.4.0                | >=0<2        |              |



### For a development installation (requires nodejs):



Create a dev environment that has nodejs installed. The instructions here use

[mamba](https://github.com/mamba-org/mamba#the-fast-cross-platform-package-manager) but you

can also use conda.



```bash

mamba env create --file dev-environment.yml

conda activate ipympl-dev

```



Install the Python Packge

```bash

pip install -e .

```



When developing your extensions, you need to manually enable your extensions with the

notebook / lab frontend. For lab, this is done by the command:



```bash

jupyter labextension develop --overwrite .

jlpm build

```



For classic notebook, you need to run:

```bash

jupyter nbextension install --py --symlink --sys-prefix --overwrite ipympl

jupyter nbextension enable --py --sys-prefix ipympl

```



#### How to see your changes



**Typescript**:



If you use JupyterLab to develop then you can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the widget.



```bash

# Watch the source directory in one terminal, automatically rebuilding when needed

jlpm watch

# Run JupyterLab in another terminal

jupyter lab

```



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.