highcharts-maps
High-end Map Data Visualization for the Python Ecosystem
Decision gist · record as of 2026-08-14
Yes, with conditions. Install if you need interactive map visualizations in Python and are comfortable with the Highcharts ecosystem. However, verify the license terms first (they are unclear in the metadata), and be aware that the package has not been updated in 724 days—test compatibility with your target Highcharts JS version and Python environment before relying on it for production. No known security vulnerabilities exist.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or higher and Highcharts Maps (JS) v.10.2 or higher in your JavaScript environment
- Installation is straightforward with low friction.
- The package is in production/stable status but dormant—last release was 724 days ago with no recent commits.
License · maintenance · safety
(unclear) — License treatment is unclear: no SPDX identifier or raw license text is available in the metadata. Before installing, verify the actual license terms directly from the project documentation or repository to understand any restrictions.
last release 2024-08-20 (724 days) · last repo commit 2024-08-20 · 12 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 88,585 downloads/mo, #13,714 on PyPI
Alternatives
Verify before relying
pip install highcharts-maps
from highcharts_maps import Chart
import geojson
chart = Chart()
# Configure with geojson or topojson map data
chart.to_html_file()- Whether the unclear license is proprietary, commercial, or open-source and what restrictions it imposes
- Whether the dormant maintenance status affects compatibility with current Highcharts JS versions or Python ecosystem changes
- Specific version compatibility requirements between this package and highcharts-core beyond the stated minimum
What it is and what it does
Highcharts Maps for Python is a Python wrapper around the Highcharts Maps JavaScript visualization library, designed to let you build interactive geospatial and map-based charts without writing JavaScript. It translates Python objects into the JavaScript configuration format that Highcharts Maps expects, handling the serialization complexity automatically. The library supports over 70 chart types from Highcharts Core plus four core map visualizations, and it integrates directly with Jupyter notebooks, Pandas dataframes, PySpark dataframes, and GeoPandas GeoDataFrames so you can visualize geographic data alongside your Python workflows.
The package requires Python 3.10 or higher and depends on six runtime libraries: esprima for JavaScript parsing, geojson and topojson for map geometry handling, highcharts-core for the underlying visualization engine, requests for HTTP operations, and validator-collection for data validation. It also requires Highcharts Maps (JS) v.10.2 or higher to be available in your JavaScript environment. The library is classified as production/stable but has not been updated in 724 days, so you should verify that it remains compatible with your target Highcharts JS version and current Python ecosystem before committing to it.
Use it for
- Build interactive choropleth maps in Jupyter notebooks that visualize regional or country-level data from Pandas dataframes without writing JavaScript.
- Create geospatial dashboards that combine GIS data from GeoPandas GeoDataFrames with Highcharts' interactive map and chart capabilities.
- Render TopoJSON or GeoJSON map geometries as interactive visualizations with data overlays, suitable for geographic analysis and reporting.
- Generate downloadable static map visualizations programmatically via the Highcharts Export Server for reports or automated pipelines.
- Visualize time-series or multi-dimensional data on maps using PySpark dataframes in large-scale data science workflows.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, with conditions.
Install if you need interactive map visualizations in Python and are comfortable with the Highcharts ecosystem. However, verify the license terms first (they are unclear in the metadata), and be aware that the package has not been updated in 724 days—test compatibility with your target Highcharts JS version and Python environment before relying on it for production. No known security vulnerabilities exist.
Install
highcharts-maps on PyPI
Before you install
Installation is straightforward with low friction. The package is in production/stable status but dormant—last release was 724 days ago with no recent commits. Six runtime dependencies are all established libraries, so the dependency chain is manageable.
Requires Python 3.10 or higher and Highcharts Maps (JS) v.10.2 or higher in your JavaScript environment
License in practice
License treatment is unclear: no SPDX identifier or raw license text is available in the metadata. Before installing, verify the actual license terms directly from the project documentation or repository to understand any restrictions.
Quickstart
pip install highcharts-maps
from highcharts_maps import Chart
import geojson
chart = Chart()
# Configure with geojson or topojson map data
chart.to_html_file()Verify before relying
- Whether the unclear license is proprietary, commercial, or open-source and what restrictions it imposes
- Whether the dormant maintenance status affects compatibility with current Highcharts JS versions or Python ecosystem changes
- Specific version compatibility requirements between this package and highcharts-core beyond the stated minimum
Package facts
| License | Not declared unclear |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 6 packagesesprimageojsonhighcharts-corerequeststopojsonvalidator-collection |
| Maintenance | Dormant 724 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 88,585 / month, #13,714 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableEnvironment :: Web EnvironmentFramework :: JupyterIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Financial and Insurance IndustryIntended Audience :: Healthcare IndustryIntended Audience :: ManufacturingIntended Audience :: Science/ResearchLicense :: Other/Proprietary LicenseOperating System :: OS IndependentTopic :: Internet :: WWW/HTTP :: Dynamic ContentTopic :: Office/BusinessTopic :: Scientific/Engineering :: GISTopic :: Scientific/Engineering :: Information AnalysisTopic :: Scientific/Engineering :: VisualizationTopic :: Software Development :: Code GeneratorsTopic :: Software Development :: LibrariesTopic :: Utilities |
Evidence: highcharts_maps-1.7.1-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “highcharts maps wrapper”
- highcharts-mapsHighcharts Maps for Python wraps the Highcharts Maps JavaScript…
- highcharts-coreGenerates interactive Highcharts data visualizations from Python,…
- googlemapsPython client library that wraps Google Maps Platform web service…
Give your agent the search over MCP, or paste the wish link into any chat.
More Libraries packages
urllib3 is an HTTP client library that provides thread-safe connection pooling, SSL/TLS verification, multipart file uploads, request retries, compression support, and proxy handling for Python applications.
Requests is a Python HTTP library that simplifies sending HTTP/1.1 requests with automatic handling of headers, authentication, cookies, and response parsing.
Pluggy provides a plugin system that lets you define hook specifications and register implementations to be called in sequence, enabling extensible Python applications without tight coupling.
Install it if you're building an extensible application or framework.
Provides parsing, arithmetic, and recurrence rule computation for dates and times, with timezone support and iCalendar RFC compliance.
Install it if you need to parse flexible date strings, compute relative dates, handle timezones, or work with recurrence rules—it's the de facto choice for these tasks.
Six provides utility functions to write Python code that runs on both Python 2.7 and Python 3.3+, smoothing over language differences between the two versions.
pytest is a testing framework that lets you write test functions using plain assert statements and automatically discovers and runs them, with detailed failure reporting.
See also highcharts-core · overturemaps · pydeck · plotbin · jupyter-leaflet · folium · leafmap · splot · pyvis · pyecharts