ipympl

library0.10.0pypypi✓ verified 22d ago

ipympl is a Matplotlib Jupyter Extension that leverages the Jupyter interactive widgets framework to enable interactive features of Matplotlib within Jupyter Notebooks, JupyterLab, Google Colab, and VSCode notebooks. It provides a proper Jupyter interactive widget for figure canvases, allowing them to be positioned in interactive widget layouts. The library is actively maintained with regular releases, currently at version 0.10.0.

ai-ml web-framework

pip install ipympl

github ↗package ↗homepage ↗

INSTALL

IMPORT

SIG · IPYMPL

ipympl

ai-mlpythonv0.10.0

Install

11.2s avg

Import

—

Disk

245MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.10.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 0.000s · 247.4MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 11.2s · import 0.000s · 239MB

245MB installed

● package 245MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

%matplotlib ipympl

✓ %matplotlib ipympl

✗ import ipympl

ipympl is activated via a Jupyter magic command, not a direct Python import. '%matplotlib widget' also works.

This quickstart demonstrates how to activate the ipympl backend using the Jupyter magic command and create a basic interactive Matplotlib plot. Run this code in a Jupyter Notebook or JupyterLab environment to see the interactive features.

import matplotlib.pyplot as plt import numpy as np %matplotlib ipympl fig, ax = plt.subplots() x = np.linspace(0, 2 * np.pi, 100) y = np.sin(3 * x) ax.plot(x, y) plt.show()

Debug

Known issues

breakingFor JupyterLab versions 1 or 2, `ipympl` requires manual installation of the `jupyter-matplotlib` labextension and specific version compatibility. For JupyterLab >= 3, installation via pip/conda is usually sufficient as the extension is automatically handled. Ensure your `ipympl` and `jupyter-matplotlib` versions are compatible.

fix

Upgrade to JupyterLab 3+ or refer to the official ipympl documentation's 'Compatibility Table' for specific `jupyter-matplotlib` versions required for older JupyterLab installations. For older JupyterLab versions, e.g., `conda install -c conda-forge nodejs jupyter labextension install @jupyter-widgets/jupyterlab-manager jupyter-matplotlib` might be needed.

affects: < 0.9.4 (JupyterLab 1/2 support), all versions with non-standard setups

gotchaipympl comprises both a Python (backend) and a JavaScript (frontend) component. In certain complex environments (e.g., custom Jupyter deployments, mixing environments), a version mismatch between these components can lead to non-interactive plots or errors. Always ensure both frontend and backend are from the same installation environment.

fix

Verify that `pip list` or `conda list` shows `ipympl` in your active kernel's environment. If issues persist, check the browser's developer console for JavaScript errors related to Jupyter widgets.

affects: All versions

gotchaWhen using `ipympl` in Google Colab, you must explicitly enable the custom widget manager before activating the Matplotlib backend, otherwise plots will not be interactive.

fix

Add `from google.colab import output; output.enable_custom_widget_manager()` at the beginning of your Colab notebook, before `%matplotlib ipympl`.

affects: All versions

Upgrade

Version history

0.10.0latest on PyPI · released Jan 21, 2026

Audit

Dependencies

matplotlibrequiredCore plotting library that ipympl extends.

ipywidgetsrequiredJupyter interactive widgets framework for interactivity.

ipykernelrequiredRequired for Jupyter kernel interaction.

Agent activity

36 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/matplotlib/ipympl ↗

packagehttps://pypi.org/project/ipympl/ ↗

homepagehttp://matplotlib.org/ipympl ↗