GeoJSON Objects | Status |
---|---|
Point | β |
MultiPoint | β |
LineString | β |
MultiLineString | β |
Polygon | β |
MultiPolygon | β |
GeometryCollection | β |
Feature | β |
FeatureCollection | β |
pydantic-geojson is compatible with Python 3.7 and up. The recommended way to install is via poetry:
poetry add pydantic_geojson
Using pip to install is also possible.
pip install pydantic_geojson
GeoJSON is a format for encoding a variety of geographic data structures.
{
"type": "Feature",
"geometry": {
"type": "Point",
"coordinates": [125.6, 10.1]
},
"properties": {
"name": "Dinagat Islands"
}
}
GeoJSON supports the following geometry types: Point, LineString, Polygon, MultiPoint, MultiLineString, and MultiPolygon. Geometric objects with additional properties are Feature objects. Sets of features are contained by FeatureCollection objects.
Custom properties:
from pydantic import BaseModel
from pydantic_geojson import FeatureModel
class MyPropertiesModel(BaseModel):
name: str
class MyFeatureModel(FeatureModel):
properties: MyPropertiesModel
data = {
"type": "Feature",
"properties": {
"name": "foo name",
},
"geometry": {
"type": "Polygon",
"coordinates": [
[
[-80.724878, 35.265454],
[-80.722646, 35.260338]
]
]
}
}
>>> MyFeatureModel(**data)
>>> type='Feature' geometry=PolygonModel(type='Polygon', coordinates=[[Coordinates(lon=-80.724878, lat=35.265454), Coordinates(lon=-80.722646, lat=35.260338)]]) properties=MyPropertiesModel(name='foo name')
Simple example data:
from pydantic_geojson import PointModel
data = {
"type": "Point",
"coordinates": [-105.01621, 39.57422]
}
>>> PointModel(**data)
>>> type='Point' coordinates=Coordinates(lon=-105.01621, lat=39.57422)
Simple example data:
from pydantic_geojson import MultiPointModel
data = {
"type": "MultiPoint",
"coordinates": [
[-105.01621, 39.57422],
[-80.666513, 35.053994]
]
}
>>> PointModel(**data)
>>> type='MultiPoint' coordinates=[Coordinates(lon=-105.01621, lat=39.57422), Coordinates(lon=-80.666513, lat=35.053994)]
Simple example data:
from pydantic_geojson import LineStringModel
data = {
"type": "LineString",
"coordinates": [
[-99.113159, 38.869651],
[-99.0802, 38.85682],
[-98.822021, 38.85682],
[-98.448486, 38.848264]
]
}
>>> LineStringModel(**data)
>>> type='LineString' coordinates=[Coordinates(lon=-99.113159, lat=38.869651), Coordinates(lon=-99.0802, lat=38.85682), Coordinates(lon=-98.822021, lat=38.85682), Coordinates(lon=-98.448486, lat=38.848264)]
Simple example data:
from pydantic_geojson import MultiLineStringModel
data = {
"type": "MultiLineString",
"coordinates": [
[
[-105.019898, 39.574997],
[-105.019598, 39.574898],
[-105.019061, 39.574782]
],
[
[-105.017173, 39.574402],
[-105.01698, 39.574385],
[-105.016636, 39.574385],
[-105.016508, 39.574402],
[-105.01595, 39.57427]
],
[
[-105.014276, 39.573972],
[-105.014126, 39.574038],
[-105.013825, 39.57417],
[-105.01331, 39.574452]
]
]
}
>>> MultiLineStringModel(**data)
>>> type='MultiLineString' coordinates=[[Coordinates(lon=-105.019898, lat=39.574997), Coordinates(lon=-105.019598, lat=39.574898), Coordinates(lon=-105.019061, lat=39.574782)], [Coordinates(lon=-105.017173, lat=39.574402), Coordinates(lon=-105.01698, lat=39.574385), Coordinates(lon=-105.016636, lat=39.574385), Coordinates(lon=-105.016508, lat=39.574402), Coordinates(lon=-105.01595, lat=39.57427)], [Coordinates(lon=-105.014276, lat=39.573972), Coordinates(lon=-105.014126, lat=39.574038), Coordinates(lon=-105.013825, lat=39.57417), Coordinates(lon=-105.01331, lat=39.574452)]]
Simple example data:
from pydantic_geojson import PolygonModel
data = {
"type": "Polygon",
"coordinates": [
[
[100, 0],
[101, 0],
[101, 1],
[100, 1],
[100, 0]
]
]
}
>>> PolygonModel(**data)
>>> type='Polygon' coordinates=[[Coordinates(lon=100.0, lat=0.0), Coordinates(lon=101.0, lat=0.0), Coordinates(lon=101.0, lat=1.0), Coordinates(lon=100.0, lat=1.0), Coordinates(lon=100.0, lat=0.0)]]
Simple example data:
from pydantic_geojson import MultiPolygonModel
data = {
"type": "MultiPolygon",
"coordinates": [
[
[
[107, 7],
[108, 7],
[108, 8],
[107, 8],
[107, 7]
]
],
[
[
[100, 0],
[101, 0],
[101, 1],
[100, 1],
[100, 0]
]
]
]
}
>>> MultiPolygonModel(**data)
>>> type='MultiPolygon' coordinates=[[[Coordinates(lon=107.0, lat=7.0), Coordinates(lon=108.0, lat=7.0), Coordinates(lon=108.0, lat=8.0), Coordinates(lon=107.0, lat=8.0), Coordinates(lon=107.0, lat=7.0)]], [[Coordinates(lon=100.0, lat=0.0), Coordinates(lon=101.0, lat=0.0), Coordinates(lon=101.0, lat=1.0), Coordinates(lon=100.0, lat=1.0), Coordinates(lon=100.0, lat=0.0)]]]
Simple example data:
from pydantic_geojson import GeometryCollectionModel
data = {
"type": "GeometryCollection",
"geometries": [
{
"type": "Point",
"coordinates": [-80.660805, 35.049392]
},
{
"type": "Polygon",
"coordinates": [
[
[-80.664582, 35.044965],
[-80.663874, 35.04428],
[-80.662586, 35.04558],
[-80.663444, 35.046036],
[-80.664582, 35.044965]
]
]
},
{
"type": "LineString",
"coordinates": [
[-80.662372, 35.059509],
[-80.662693, 35.059263],
[-80.662844, 35.05893]
]
}
]
}
>>> GeometryCollectionModel(**data)
>>> type='GeometryCollection' geometries=[PointModel(type='Point', coordinates=Coordinates(lon=-80.660805, lat=35.049392)), PolygonModel(type='Polygon', coordinates=[[Coordinates(lon=-80.664582, lat=35.044965), Coordinates(lon=-80.663874, lat=35.04428), Coordinates(lon=-80.662586, lat=35.04558), Coordinates(lon=-80.663444, lat=35.046036), Coordinates(lon=-80.664582, lat=35.044965)]]), LineStringModel(type='LineString', coordinates=[Coordinates(lon=-80.662372, lat=35.059509), Coordinates(lon=-80.662693, lat=35.059263), Coordinates(lon=-80.662844, lat=35.05893)])]
Simple example data:
from pydantic_geojson import FeatureModel
data = {
"type": "Feature",
"geometry": {
"type": "Polygon",
"coordinates": [
[
[-80.724878, 35.265454],
[-80.722646, 35.260338],
[-80.720329, 35.260618],
[-80.71681, 35.255361],
[-80.704793, 35.268397],
[-82.715179, 35.267696],
[-80.721359, 35.267276],
[-80.724878, 35.265454]
]
]
}
}
>>> FeatureModel(**data)
>>> type='Feature' geometry=PolygonModel(type='Polygon', coordinates=[[Coordinates(lon=-80.724878, lat=35.265454), Coordinates(lon=-80.722646, lat=35.260338), Coordinates(lon=-80.720329, lat=35.260618), Coordinates(lon=-80.71681, lat=35.255361), Coordinates(lon=-80.704793, lat=35.268397), Coordinates(lon=-82.715179, lat=35.267696), Coordinates(lon=-80.721359, lat=35.267276), Coordinates(lon=-80.724878, lat=35.265454)]])
Simple example data:
from pydantic_geojson import FeatureCollectionModel
data = {
"type": "FeatureCollection",
"features": [
{
"type": "Feature",
"geometry": {
"type": "Point",
"coordinates": [-80.870885, 35.215151]
}
},
{
"type": "Feature",
"geometry": {
"type": "Polygon",
"coordinates": [
[
[-80.724878, 35.265454],
[-80.722646, 35.260338],
[-80.720329, 35.260618],
[-80.704793, 35.268397],
[-80.724878, 35.265454]
]
]
}
}
]
}
>>> FeatureCollectionModel(**data)
>>> type='FeatureCollection' features=[FeatureModel(type='Feature', geometry=PointModel(type='Point', coordinates=Coordinates(lon=-80.870885, lat=35.215151))), FeatureModel(type='Feature', geometry=PolygonModel(type='Polygon', coordinates=[[Coordinates(lon=-80.724878, lat=35.265454), Coordinates(lon=-80.722646, lat=35.260338), Coordinates(lon=-80.720329, lat=35.260618), Coordinates(lon=-80.704793, lat=35.268397), Coordinates(lon=-80.724878, lat=35.265454)]]))]