Python bindings and utilities for GeoJSON

Overview

geojson

GitHub Actions Codecov Jazzband

This Python library contains:

Table of Contents

Installation

geojson is compatible with Python 3.6, 3.7 and 3.8. The recommended way to install is via pip:

pip install geojson

GeoJSON Objects

This library implements all the GeoJSON Objects described in The GeoJSON Format Specification.

All object keys can also be used as attributes.

The objects contained in GeometryCollection and FeatureCollection can be indexed directly.

Point

>>> from geojson import Point

>>> Point((-115.81, 37.24))  # doctest: +ELLIPSIS
{"coordinates": [-115.8..., 37.2...], "type": "Point"}

Visualize the result of the example above here. General information about Point can be found in Section 3.1.2 and Appendix A: Points within The GeoJSON Format Specification.

MultiPoint

>>> from geojson import MultiPoint

>>> MultiPoint([(-155.52, 19.61), (-156.22, 20.74), (-157.97, 21.46)])  # doctest: +ELLIPSIS
{"coordinates": [[-155.5..., 19.6...], [-156.2..., 20.7...], [-157.9..., 21.4...]], "type": "MultiPoint"}

Visualize the result of the example above here. General information about MultiPoint can be found in Section 3.1.3 and Appendix A: MultiPoints within The GeoJSON Format Specification.

LineString

>>> from geojson import LineString

>>> LineString([(8.919, 44.4074), (8.923, 44.4075)])  # doctest: +ELLIPSIS
{"coordinates": [[8.91..., 44.407...], [8.92..., 44.407...]], "type": "LineString"}

Visualize the result of the example above here. General information about LineString can be found in Section 3.1.4 and Appendix A: LineStrings within The GeoJSON Format Specification.

MultiLineString

>>> from geojson import MultiLineString

>>> MultiLineString([
...     [(3.75, 9.25), (-130.95, 1.52)],
...     [(23.15, -34.25), (-1.35, -4.65), (3.45, 77.95)]
... ])  # doctest: +ELLIPSIS
{"coordinates": [[[3.7..., 9.2...], [-130.9..., 1.52...]], [[23.1..., -34.2...], [-1.3..., -4.6...], [3.4..., 77.9...]]], "type": "MultiLineString"}

Visualize the result of the example above here. General information about MultiLineString can be found in Section 3.1.5 and Appendix A: MultiLineStrings within The GeoJSON Format Specification.

Polygon

>>> from geojson import Polygon

>>> # no hole within polygon
>>> Polygon([[(2.38, 57.322), (23.194, -20.28), (-120.43, 19.15), (2.38, 57.322)]])  # doctest: +ELLIPSIS
{"coordinates": [[[2.3..., 57.32...], [23.19..., -20.2...], [-120.4..., 19.1...]]], "type": "Polygon"}

>>> # hole within polygon
>>> Polygon([
...     [(2.38, 57.322), (23.194, -20.28), (-120.43, 19.15), (2.38, 57.322)],
...     [(-5.21, 23.51), (15.21, -10.81), (-20.51, 1.51), (-5.21, 23.51)]
... ])  # doctest: +ELLIPSIS
{"coordinates": [[[2.3..., 57.32...], [23.19..., -20.2...], [-120.4..., 19.1...]], [[-5.2..., 23.5...], [15.2..., -10.8...], [-20.5..., 1.5...], [-5.2..., 23.5...]]], "type": "Polygon"}

Visualize the results of the example above here. General information about Polygon can be found in Section 3.1.6 and Appendix A: Polygons within The GeoJSON Format Specification.

MultiPolygon

>>> from geojson import MultiPolygon

>>> MultiPolygon([
...     ([(3.78, 9.28), (-130.91, 1.52), (35.12, 72.234), (3.78, 9.28)],),
...     ([(23.18, -34.29), (-1.31, -4.61), (3.41, 77.91), (23.18, -34.29)],)
... ])  # doctest: +ELLIPSIS
{"coordinates": [[[[3.7..., 9.2...], [-130.9..., 1.5...], [35.1..., 72.23...]]], [[[23.1..., -34.2...], [-1.3..., -4.6...], [3.4..., 77.9...]]]], "type": "MultiPolygon"}

Visualize the result of the example above here. General information about MultiPolygon can be found in Section 3.1.7 and Appendix A: MultiPolygons within The GeoJSON Format Specification.

GeometryCollection

>>> from geojson import GeometryCollection, Point, LineString

>>> my_point = Point((23.532, -63.12))

>>> my_line = LineString([(-152.62, 51.21), (5.21, 10.69)])

>>> geo_collection = GeometryCollection([my_point, my_line])

>>> geo_collection  # doctest: +ELLIPSIS
{"geometries": [{"coordinates": [23.53..., -63.1...], "type": "Point"}, {"coordinates": [[-152.6..., 51.2...], [5.2..., 10.6...]], "type": "LineString"}], "type": "GeometryCollection"}

>>> geo_collection[1]
{"coordinates": [[-152.62, 51.21], [5.21, 10.69]], "type": "LineString"}

>>> geo_collection[0] == geo_collection.geometries[0]
True

Visualize the result of the example above here. General information about GeometryCollection can be found in Section 3.1.8 and Appendix A: GeometryCollections within The GeoJSON Format Specification.

Feature

>>> from geojson import Feature, Point

>>> my_point = Point((-3.68, 40.41))

>>> Feature(geometry=my_point)  # doctest: +ELLIPSIS
{"geometry": {"coordinates": [-3.68..., 40.4...], "type": "Point"}, "properties": {}, "type": "Feature"}

>>> Feature(geometry=my_point, properties={"country": "Spain"})  # doctest: +ELLIPSIS
{"geometry": {"coordinates": [-3.68..., 40.4...], "type": "Point"}, "properties": {"country": "Spain"}, "type": "Feature"}

>>> Feature(geometry=my_point, id=27)  # doctest: +ELLIPSIS
{"geometry": {"coordinates": [-3.68..., 40.4...], "type": "Point"}, "id": 27, "properties": {}, "type": "Feature"}

Visualize the results of the examples above here. General information about Feature can be found in Section 3.2 within The GeoJSON Format Specification.

FeatureCollection

>>> from geojson import Feature, Point, FeatureCollection

>>> my_feature = Feature(geometry=Point((1.6432, -19.123)))

>>> my_other_feature = Feature(geometry=Point((-80.234, -22.532)))

>>> feature_collection = FeatureCollection([my_feature, my_other_feature])

>>> feature_collection # doctest: +ELLIPSIS
{"features": [{"geometry": {"coordinates": [1.643..., -19.12...], "type": "Point"}, "properties": {}, "type": "Feature"}, {"geometry": {"coordinates": [-80.23..., -22.53...], "type": "Point"}, "properties": {}, "type": "Feature"}], "type": "FeatureCollection"}

>>> feature_collection.errors()
[]

>>> (feature_collection[0] == feature_collection['features'][0], feature_collection[1] == my_other_feature)
(True, True)

Visualize the result of the example above here. General information about FeatureCollection can be found in Section 3.3 within The GeoJSON Format Specification.

GeoJSON encoding/decoding

All of the GeoJSON Objects implemented in this library can be encoded and decoded into raw GeoJSON with the geojson.dump, geojson.dumps, geojson.load, and geojson.loads functions. Note that each of these functions is a wrapper around the core json function with the same name, and will pass through any additional arguments. This allows you to control the JSON formatting or parsing behavior with the underlying core json functions.

>>> import geojson

>>> my_point = geojson.Point((43.24, -1.532))

>>> my_point  # doctest: +ELLIPSIS
{"coordinates": [43.2..., -1.53...], "type": "Point"}

>>> dump = geojson.dumps(my_point, sort_keys=True)

>>> dump  # doctest: +ELLIPSIS
'{"coordinates": [43.2..., -1.53...], "type": "Point"}'

>>> geojson.loads(dump)  # doctest: +ELLIPSIS
{"coordinates": [43.2..., -1.53...], "type": "Point"}

Custom classes

This encoding/decoding functionality shown in the previous can be extended to custom classes using the interface described by the __geo_interface__ Specification.

>>> import geojson

>>> class MyPoint():
...     def __init__(self, x, y):
...         self.x = x
...         self.y = y
...
...     @property
...     def __geo_interface__(self):
...         return {'type': 'Point', 'coordinates': (self.x, self.y)}

>>> point_instance = MyPoint(52.235, -19.234)

>>> geojson.dumps(point_instance, sort_keys=True)  # doctest: +ELLIPSIS
'{"coordinates": [52.23..., -19.23...], "type": "Point"}'

Default and custom precision

GeoJSON Object-based classes in this package have an additional precision attribute which rounds off coordinates to 6 decimal places (roughly 0.1 meters) by default and can be customized per object instance.

>>> from geojson import Point

>>> Point((-115.123412341234, 37.123412341234))  # rounded to 6 decimal places by default
{"coordinates": [-115.123412, 37.123412], "type": "Point"}

>>> Point((-115.12341234, 37.12341234), precision=8)  # rounded to 8 decimal places
{"coordinates": [-115.12341234, 37.12341234], "type": "Point"}

Helpful utilities

coords

geojson.utils.coords yields all coordinate tuples from a geometry or feature object.

>>> import geojson

>>> my_line = LineString([(-152.62, 51.21), (5.21, 10.69)])

>>> my_feature = geojson.Feature(geometry=my_line)

>>> list(geojson.utils.coords(my_feature))  # doctest: +ELLIPSIS
[(-152.62..., 51.21...), (5.21..., 10.69...)]

map_coords

geojson.utils.map_coords maps a function over all coordinate values and returns a geometry of the same type. Useful for scaling a geometry.

>>> import geojson

>>> new_point = geojson.utils.map_coords(lambda x: x/2, geojson.Point((-115.81, 37.24)))

>>> geojson.dumps(new_point, sort_keys=True)  # doctest: +ELLIPSIS
'{"coordinates": [-57.905..., 18.62...], "type": "Point"}'

map_tuples

geojson.utils.map_tuples maps a function over all coordinates and returns a geometry of the same type. Useful for changing coordinate order or applying coordinate transforms.

>>> import geojson

>>> new_point = geojson.utils.map_tuples(lambda c: (c[1], c[0]), geojson.Point((-115.81, 37.24)))

>>> geojson.dumps(new_point, sort_keys=True)  # doctest: +ELLIPSIS
'{"coordinates": [37.24..., -115.81], "type": "Point"}'

map_geometries

geojson.utils.map_geometries maps a function over each geometry in the input.

>>> import geojson

>>> new_point = geojson.utils.map_geometries(lambda g: geojson.MultiPoint([g["coordinates"]]), geojson.GeometryCollection([geojson.Point((-115.81, 37.24))]))

>>> geojson.dumps(new_point, sort_keys=True)
'{"geometries": [{"coordinates": [[-115.81, 37.24]], "type": "MultiPoint"}], "type": "GeometryCollection"}'

validation

is_valid property provides simple validation of GeoJSON objects.

>>> import geojson

>>> obj = geojson.Point((-3.68,40.41,25.14,10.34))
>>> obj.is_valid
False

errors method provides collection of errors when validation GeoJSON objects.

>>> import geojson

>>> obj = geojson.Point((-3.68,40.41,25.14,10.34))
>>> obj.errors()
'a position must have exactly 2 or 3 values'

generate_random

geojson.utils.generate_random yields a geometry type with random data

>>> import geojson

>>> geojson.utils.generate_random("LineString")  # doctest: +ELLIPSIS
{"coordinates": [...], "type": "LineString"}

>>> geojson.utils.generate_random("Polygon")  # doctest: +ELLIPSIS
{"coordinates": [...], "type": "Polygon"}

Development

To build this project, run python setup.py build. To run the unit tests, run python setup.py test. To run the style checks, run flake8 (install flake8 if needed).

Credits

This is a simple python code to get IP address and its location using python

IP address & Location finder @DEV/ED : Pavan Ananth Sharma Dependencies: ip2geotools Note: use pip install ip2geotools to install this in your termin

Pavan Ananth Sharma 2 Jul 05, 2022
A python package that extends Google Earth Engine.

A python package that extends Google Earth Engine GitHub: https://github.com/davemlz/eemont Documentation: https://eemont.readthedocs.io/ PyPI: https:

David Montero Loaiza 307 Jan 01, 2023
a Geolocator made in python

Geolocator A Geolocator made in python ✨ Features locates ur location using ur ip thats it! 💁‍♀️ How to use first download the locator.py file instal

Portgas D Ace 1 Oct 27, 2021
A bot that tweets info and location map for new bicycle parking added to OpenStreetMap within a GeoJSON boundary.

Bike parking tweepy bot app A twitter bot app that searches for bicycle parking added to OpenStreetMap. Relies on AWS Lambda/S3, Python3, Tweepy, Flas

Angelo Trivisonno 1 Dec 19, 2021
Python script that can be used to generate latitude/longitude coordinates for GOES-16 full-disk extent.

goes-latlon Python script that can be used to generate latitude/longitude coordinates for GOES-16 full-disk extent. 🌎 🛰️ The grid files can be acces

Douglas Uba 3 Apr 06, 2022
A ninja python package that unifies the Google Earth Engine ecosystem.

A Python package that unifies the Google Earth Engine ecosystem. EarthEngine.jl | rgee | rgee+ | eemont GitHub: https://github.com/r-earthengine/ee_ex

47 Dec 27, 2022
iNaturalist observations along hiking trails

This tool reads the route of a hike and generates a table of iNaturalist observations along the trails. It also shows the observations and the route of the hike on a map. Moreover, it saves waypoints

7 Nov 11, 2022
Google maps for Jupyter notebooks

gmaps gmaps is a plugin for including interactive Google maps in the IPython Notebook. Let's plot a heatmap of taxi pickups in San Francisco: import g

Pascal Bugnion 747 Dec 19, 2022
GeoNode is an open source platform that facilitates the creation, sharing, and collaborative use of geospatial data.

Table of Contents What is GeoNode? Try out GeoNode Install Learn GeoNode Development Contributing Roadmap Showcase Most useful links Licensing What is

GeoNode Development Team 1.2k Dec 26, 2022
A trivia questions about Europe

EUROPE TRIVIA QUIZ IN PYTHON Project Outline Ask user if he / she knows more about Europe. If yes show the Trivia main screen, else show the end Trivi

David Danso 1 Nov 17, 2021
ProjPicker (projection picker) is a Python module that allows the user to select all coordinate reference systems (CRSs)

ProjPicker ProjPicker (projection picker) is a Python module that allows the user to select all coordinate reference systems (CRSs) whose extent compl

Huidae Cho 4 Feb 06, 2022
h3-js provides a JavaScript version of H3, a hexagon-based geospatial indexing system.

h3-js The h3-js library provides a pure-JavaScript version of the H3 Core Library, a hexagon-based geographic grid system. It can be used either in No

Uber Open Source 648 Jan 07, 2023
Yet Another Time Series Model

Yet Another Timeseries Model (YATSM) master v0.6.x-maintenance Build Coverage Docs DOI | About Yet Another Timeseries Model (YATSM) is a Python packag

Chris Holden 60 Sep 13, 2022
:earth_asia: Python Geocoder

Python Geocoder Simple and consistent geocoding library written in Python. Table of content Overview A glimpse at the API Forward Multiple results Rev

Denis 1.5k Jan 02, 2023
List of Land Cover datasets in the GEE Catalog

List of Land Cover datasets in the GEE Catalog A list of all the Land Cover (or discrete) datasets in Google Earth Engine. Values, Colors and Descript

David Montero Loaiza 5 Aug 24, 2022
Summary statistics of geospatial raster datasets based on vector geometries.

rasterstats rasterstats is a Python module for summarizing geospatial raster datasets based on vector geometries. It includes functions for zonal stat

Matthew Perry 437 Dec 23, 2022
Geospatial Image Processing for Python

GIPPY Gippy is a Python library for image processing of geospatial raster data. The core of the library is implemented as a C++ library, libgip, with

GIPIT 83 Aug 19, 2022
OSMnx: Python for street networks. Retrieve, model, analyze, and visualize street networks and other spatial data from OpenStreetMap.

OSMnx OSMnx is a Python package that lets you download geospatial data from OpenStreetMap and model, project, visualize, and analyze real-world street

Geoff Boeing 4k Jan 08, 2023
ArcGIS Python Toolbox for WhiteboxTools

WhiteboxTools-ArcGIS ArcGIS Python Toolbox for WhiteboxTools. This repository is related to the ArcGIS Python Toolbox for WhiteboxTools, which is an A

Qiusheng Wu 190 Dec 30, 2022
Blender addons to make the bridge between Blender and geographic data

Blender GIS Blender minimal version : 2.8 Mac users warning : currently the addon does not work on Mac with Blender 2.80 to 2.82. Please do not report

5.9k Jan 02, 2023