---
id: jupyter-leaflet
version: "0.20.0"
license: The MIT License (MIT) Copyright (c) 2014-2018, Project Jupyter Contributors Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation… (full text in the JSON record)
license_treatment: permissive
maintenance: active
---

# jupyter-leaflet — ipyleaflet extensions for JupyterLab and Jupyter Notebook

License: permissive · Maintenance: active · Downloads: 448.5K/mo

## What it is and what it does

jupyter-leaflet is a Python package that brings interactive Leaflet.js maps into Jupyter notebooks and JupyterLab as interactive widgets. It lets you create, manipulate, and display geographic data—basemaps, GeoJSON overlays, markers, and custom Leaflet primitives—directly in notebook cells without leaving your computational environment.

The package acts as a bridge between the Jupyter widget ecosystem and Leaflet's JavaScript mapping library. You define maps and layers in Python, and jupyter-leaflet renders them as interactive web maps in the notebook output. It supports geospatial workflows like choropleth visualization, velocity data overlay, and split-map comparison, making it useful for exploratory geographic analysis, data journalism, and educational notebooks.

Use it for:

- Explore and visualize GeoJSON datasets interactively within a notebook during data analysis.
- Create choropleth maps to show regional statistics or aggregated geographic data.
- Build interactive dashboards combining map layers with Python-computed analysis.
- Compare two map layers side-by-side using the split-map control for change detection.
- Prototype geospatial applications and share them as executable notebooks.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

jupyter-leaflet provides interactive map widgets for Jupyter notebooks and JupyterLab, bridging Jupyter and Leaflet.js to render geospatial data and controls directly in notebook cells.

Yes. Low install friction, active maintenance, no runtime dependencies, and MIT licensing make it a straightforward choice for anyone doing geospatial work in Jupyter. The main caveat is that the frontend widget extension must be available in your Jupyter environment; verify that before installing if you're using a non-standard Jupyter setup.

## Install

pip install jupyter-leaflet
uv add jupyter-leaflet
poetry add jupyter-leaflet

## Installing jupyter-leaflet

Before you install: Low install friction; pure Python wheel with no runtime dependencies. Actively maintained with recent commits and 1537 repository stars. Supports Python 3.8 through 3.12.

License in practice: MIT license (permissive); you may use, modify, and distribute the package freely, including in commercial projects, provided you include the license notice.

Quickstart:

pip install jupyter-leaflet

In a Jupyter notebook:
from jupyter_leaflet import Map

m = Map()
m

Requires Jupyter notebook or JupyterLab environment; the widget frontend must be installed in your Jupyter installation for maps to render.

Verify before relying:

- Whether the frontend widget extension is automatically installed with the pip package or requires separate JupyterLab extension installation.
- Performance characteristics when rendering large GeoJSON files or many map layers.
- Compatibility with specific Jupyter versions beyond the Python version support stated.
- Specific basemap options, layer types, and interactive controls available through the API.

## Package facts

- License: The MIT License (MIT) Copyright (c) 2014-2018, Project Jupyter Contributors Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation… (full text in the JSON record) (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 448.5K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

jupyter interactive maps, leaflet maps in notebooks, geospatial visualization jupyter, jupyter map widgets, interactive cartography notebooks, leaflet.js jupyter bridge, notebook GIS visualization, geospatial, jupyter-widget, cartography

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