antimeridian
Correct GeoJSON geometries that cross the 180th meridian
Decision gist · record as of 2026-08-14
Yes. The package solves a specific but real problem in geospatial work with minimal dependencies and active maintenance. It is Production/Stable, has no known vulnerabilities, and is permissively licensed. Install it if you work with global geographic data or need to handle geometries near the antimeridian.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Note: fix_geojson mutates the input dictionary in-place; pass a deepcopy if you need to preserve the original.
- Low friction: pure Python wheel with only numpy and shapely as runtime dependencies.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 is permissive; you can use, modify, and distribute this package freely in commercial and private projects with minimal restrictions.
last release 2026-06-22 (53 days) · last repo commit 2026-08-10 · 110 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 154,936 downloads/mo, #10,837 on PyPI
Alternatives
Verify before relying
pip install antimeridian
import antimeridian
fixed = antimeridian.fix_geojson(geojson)- Performance characteristics with large or complex geometries (number of vertices, coordinate density).
- Behavior with edge cases like geometries exactly on the antimeridian or with multiple crossings.
What it is and what it does
Antimeridian is a geometry correction library for handling shapes that cross the 180th meridian (antimeridian), a common problem in global geospatial data. It works with Shapely geometry objects and GeoJSON dictionaries, transforming coordinates so that geometries that span the date line are properly represented in standard geographic systems. The library depends on numpy and shapely for its core operations.
The package is useful when working with global maps or datasets that include features near the poles or spanning the international date line. It provides not only the core fix function but also utilities for computing bounding boxes and centroids from antimeridian-crossing polygons. An optional CLI is available for batch processing GeoJSON files from the command line.
Use it for
- Correct GeoJSON features from global mapping APIs that include territories crossing the date line.
- Prepare Shapely geometries for rendering on web maps without distortion artifacts at the antimeridian.
- Batch-process GeoJSON files to fix meridian-crossing boundaries before loading into a spatial database.
- Compute accurate bounding boxes and centroids for polygons that span the 180th meridian.
- Normalize geographic data from sources that represent date-line-crossing regions inconsistently.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package solves a specific but real problem in geospatial work with minimal dependencies and active maintenance. It is Production/Stable, has no known vulnerabilities, and is permissively licensed. Install it if you work with global geographic data or need to handle geometries near the antimeridian.
Install
antimeridian on PyPI
Before you install
Low friction: pure Python wheel with only numpy and shapely as runtime dependencies. Actively maintained with recent releases; last commit 2026-08-10 and marked Production/Stable.
Requires Python 3.10 or later. Note: fix_geojson mutates the input dictionary in-place; pass a deepcopy if you need to preserve the original.
License in practice
Apache-2.0 is permissive; you can use, modify, and distribute this package freely in commercial and private projects with minimal restrictions.
Quickstart
pip install antimeridian
import antimeridian
fixed = antimeridian.fix_geojson(geojson)Verify before relying
- Performance characteristics with large or complex geometries (number of vertices, coordinate density).
- Behavior with edge cases like geometries exactly on the antimeridian or with multiple crossings.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesnumpyshapely |
| Maintenance | Actively maintained 53 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 154,936 / month, #10,837 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/StableProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14 |
Evidence: antimeridian-0.4.8-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 › “antimeridian geometry fix”
- antimeridianFixes Shapely geometries and GeoJSON features that cross the…
- pymeshfixPyMeshFix repairs triangular meshes by removing defects like…
- trimeshTrimesh loads, manipulates, and analyzes triangular mesh geometry in…
Give your agent the search over MCP, or paste the wish link into any chat.
More Scientific/Engineering packages
NumPy provides an N-dimensional array object and a comprehensive suite of mathematical, linear algebra, Fourier transform, and random number functions for scientific computing in Python.
pandas provides fast, flexible data structures (Series and DataFrame) for loading, cleaning, transforming, and analyzing labeled or relational data in Python.
scipy provides numerical algorithms for mathematics, science, and engineering—including optimization, integration, linear algebra, Fourier transforms, signal and image processing, and ODE solvers—built on numpy arrays.
scikit-learn provides a comprehensive Python library for supervised and unsupervised machine learning, including classification, regression, clustering, dimensionality reduction, and model evaluation tools built on NumPy and SciPy.
Install it if you need to train, evaluate, or deploy supervised or unsupervised learning models.
dill extends Python's pickle module to serialize and deserialize a much wider range of Python objects, including functions, lambdas, classes, and interpreter sessions, to byte streams for storage or network transmission.
Multiprocess is an enhanced fork of Python's standard multiprocessing library that uses dill for better serialization, allowing you to spawn processes with a threading-like API and share complex objects between them.
Install it if you use multiprocessing and encounter pickle serialization limits with lambdas or complex objects.
See also shapely · geopandas · osm2geojson · descartes · pydantic-geojson · plpygis · geomet · reproj · quadrilateral-fitter · geojson-pydantic