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folium

Make beautiful maps with Leaflet.js & Python

folium v0.20.0 7.2M downloads/30d#1,773 on PyPI7,396
Permissive license MIT Active released

What it is and what it does

folium is a Python library that bridges data analysis and web mapping by wrapping Leaflet.js, a popular JavaScript mapping library. You write Python code to define map features—markers, polygons, popups, layers—and folium generates interactive HTML maps that can be embedded in web pages, Jupyter notebooks, or saved as standalone files. The library integrates with the Python data ecosystem through dependencies like numpy and jinja2, and uses xyzservices to access basemap tile providers.

Typical workflows involve loading geographic data in Python, processing it with standard tools, then using folium to visualize the results as an interactive web map. The library handles the translation from Python objects to Leaflet.js configuration, so you don't write JavaScript directly. It's designed for exploratory analysis, dashboard building, and sharing geographic insights in a format that works in any web browser.

Use it for:

  • Visualize GPS traces, sensor locations, or field survey points on an interactive map in a Jupyter notebook
  • Build a web dashboard showing real-time or historical geographic data with markers, heatmaps, and layer controls
  • Create choropleth maps from GeoJSON boundaries and pandas DataFrames to show regional statistics
  • Generate static map images or interactive HTML files for reports, presentations, or web embedding
  • Prototype geographic applications before committing to a full mapping framework

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

folium builds interactive web maps by combining Python data manipulation with Leaflet.js, letting you create and customize maps programmatically and render them as HTML.

Yes. folium is production-stable, actively maintained, has no known vulnerabilities, and installs with minimal friction. It's the standard choice for Python developers who need interactive web maps without learning JavaScript or deploying a mapping server. Use it if you're working with geographic data in Python and want to visualize it interactively.

Install

folium on PyPI

pip

pip install folium

uv

uv add folium

poetry

poetry add folium

Installing folium

Before you install

Low install friction with a pure-Python wheel and five common runtime dependencies. The project is actively maintained with recent commits and has been stable since its early releases.

License in practice

MIT license is permissive; you can use, modify, and distribute folium freely in commercial and private projects with minimal restrictions.

Quickstart

pip install folium

import folium
m = folium.Map(location=[0, 0], zoom_start=13)
m.save('map.html')

Verify before relying

  • Whether folium's map rendering works offline or requires internet access for tile providers
  • Performance characteristics when handling large GeoJSON datasets or many markers
  • Specific coordinate examples and typical zoom levels for common use cases

Package facts

License MIT (permissive)
Python support supports the current Python release (>=3.9)
Install friction low — pure-Python wheel
Runtime dependencies 5 — branca, jinja2, numpy, requests, xyzservices
Maintenance actively maintained — 424 days since the last release
Last repo commit
First released
Downloads 7,186,642/month — #1,773 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: folium-0.20.0-py2.py3-none-any.whl

Keywords: data, visualization

Development Status :: 5 - Production/StableLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.9Topic :: Scientific/Engineering :: GISTopic :: Scientific/Engineering :: Visualization

Tags

python interactive mapsleaflet.js python wrappergeospatial data visualizationweb map generation pythongeographic data mappingpython mapping libraryleaflet map builder
geospatialweb-visualizationjupyter-friendly

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