Letting two great packages work together!
pydantic-shapely
is a Python package that allows you to use Shapely geometries as Pydantic
fields. This package is useful when you want to validate and serialize Shapely geometries using
Pydantic models. As an added bonus, you can also use the package to validate and serialize the
geometries in GeoJSON format, without the need of any additional code. The GeoJSON serialization
is based on the GeoJSON specification.
You can install the package using pip:
pip install pydantic-shapely
Ofcourse, you can also install the package using poetry as package manager:
poetry add pydantic-shapely
Normally, when you want to use Shapely geometries in Pydantic models, you would have
to set arbitrary_types_allowed
to True
in the Pydantic model. This is because
the Shapely geometries are not natively supported by Pydantic.
With pydantic-shapely
you can use Shapely geometries as Pydantic fields without
having to set arbitrary_types_allowed
to True
. You only have to add the
GeometryField
as _additional_ annotation to the field in the Pydantic model.
import typing
from pydantic import BaseModel
from pydantic_shapely import GeometryField
from shapely.geometry import Point
class MyModel(BaseModel):
point: typing.Annotation[Point, GeometryField(), Field(...)]
model = MyModel(point=Point(0, 0))
print(model.point) # POINT (0 0)
With the GeometryField
allows also to set the following parameters whether the geometry
should be 2- or 3-dimensional with the parameter z_values
. The following values are
allowed:
forbidden
: the geometry must be strictly 2-dimensional. A ValueError will raised when a shape with z-values is provided.strip
: the geometry may have z-values. These values will be stripped from then geometry in the validation process. The resulting shape will be 2-dimensional in all cases.allow
(default): both 2- and 3-dimensional values are allowed. During the validation process the data is not altered. This is the default behavior.required
: the geometry must be strictly 2-dimensional. A ValueError will raised when a shape without z-values is provided.
With pydantic-shapely
you can also serialize the a Pydantic model with a Shapely geometry
to GeoJSON format.
In order to add this functionality to your model, you have to inherit from the FeatureBaseModel
class. This class is a subclass of the Pydantic BaseModel
class and adds the following methods
and attributes to the model:
GeoJsonDataModel
: an attribute that contains the Pydantic GeoJSON model based on the original model. This model is created when the subclass is created.to_geojson_model
: a method that returns the GeoJSON model of the model instance. To convert the GeoJSON model back to the original model, you can use theto_feature_model
method on the GeoJSON model.model_dump_geojson
: a method that serializes the model to GeoJSON format.
Example usage of the GeoJSON serialization:
import typing
from pydantic import BaseModel
from pydantic_shapely import GeometryField, FeatureBaseModel
from shapely.geometry import Point
class MyModel(FeatureBaseModel, geometry_field="point"):
point: typing.Annotation[Point, GeometryField(), Field(...)]
a: int = 42
b: str = "Hello, World!"
model = MyModel(point=Point(0, 0))
print(model.model_dump_geojson())
# {
# "type": "Feature",
# "geometry": {
# "type": "Point",
# "coordinates": [0.0, 0.0]
# },
# "properties": {
# "a": 42,
# "b": "Hello, World!"}
# }
The GeoJSON serialization can also be used with FastApi. The following example shows how to create a simple annotated API that returns a GeoJSON representation of a Shapely geometry:
import typing
from fastapi import FastAPI
from pydantic import Field
from pydantic_shapely import FeatureBaseModel, GeometryField
from shapely.geometry import Point
app = FastAPI()
class MyModel(FeatureBaseModel, geometry_field="point"):
point: typing.Annotated[Point, GeometryField(), Field(...)]
@app.get("/point")
def get_point() -> MyModel.GeoJsonDataModel:
# Return a GeoJSON representation of a Shapely geometry.
return MyModel(point=Point(0, 0)).to_geojson_model()
@app.post("/point")
def post_point(model: MyModel.GeoJsonDataModel) -> MyModel:
# Convert the GeoJSON model back to the original model instance with the
# `to_feature_model` method. The Shapely geometry will be returned as a
# WKT-string in this case.
return model.to_feature_model()
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8000)
Based on the GeoJsonDataModel
, a feature collection can be easily created by using the
FeatureCollectionBaseModel
class. This class is a subclass of the Pydantic BaseModel
class and adds the following methods and attributes to the model:
from_feature_models
: a class method that creates a feature collection from a list of features. The list of features is validated before the feature collection is created. The validation ensures that all features are of the correct type.to_feature_models
: a method that returns a list of feature models from the feature collection.
Example usage of the feature collection:
import typing
from shapely import Point
from pydantic_shapely import FeatureBaseModel, GeometryField
from pydantic_shapely.geojson import GeoJsonFeatureCollectionBaseModel
class TestModel(FeatureBaseModel):
"""Test class for a feature which supports GeoJSON serialization."""
geometry: typing.Annotated[Point, GeometryField()]
name: str = "Hello World"
answer: int = 42
TestFeatureCollection = GeoJsonFeatureCollectionBaseModel[TestModel.GeoJsonDataModel]
# Method 1: Create a feature collection from a list of features.
test = TestFeatureCollection(
features=[
TestModel(geometry=Point(0, 0)).to_geojson_model(),
TestModel(geometry=Point(1, 1)).to_geojson_model(),
]
)
# Method 2: Create a feature collection from a list features using the `from_feature_models`
# class method.
test = TestFeatureCollection.from_feature_models(
[
TestModel(geometry=Point(0, 0)),
TestModel(geometry=Point(1, 1)),
]
)
# Print the resluting GeoJSON feature collection.
print(test.model_dump_json(indent=2))
# RESULT:
# {
# "type": "FeatureCollection",
# "features": [
# {
# "type": "Feature",
# "geometry": {
# "type": "Point",
# "coordinates": [
# 0.0,
# 0.0
# ]
# },
# "properties": {
# "name": "Hello World",
# "answer": 42
# }
# },
# {
# "type": "Feature",
# "geometry": {
# "type": "Point",
# "coordinates": [
# 1.0,
# 1.0
# ]
# },
# "properties": {
# "name": "Hello World",
# "answer": 42
# }
# }
# ]
# }
The GeoJSON serialization can also be used with FastApi. The following example shows how to create a simple annotated API that returns a GeoJSON Feature Collection:
import typing
from fastapi import FastAPI
from pydantic import Field
from pydantic_shapely import FeatureBaseModel, GeometryField
from pydantic_shapely.geojson import GeoJsonFeatureCollectionBaseModel
from shapely.geometry import Point
app = FastAPI()
class MyModel(FeatureBaseModel, geometry_field="point"):
point: typing.Annotated[Point, GeometryField(), Field(...)]
name: str = "Hello World"
answer: int = 42
# NOTE: Sub-classing the GeoJsonFeatureCollectionBaseModel gives a cleaner description
# in the API documentation.
class MyModelFeatureCollection(GeoJsonFeatureCollectionBaseModel[MyModel.GeoJsonDataModel]):
...
@app.get("/points")
def get_points() -> MyModelFeatureCollection:
# Return a GeoJSON representation of a Shapely geometry.
return MyModelFeatureCollection.from_feature_models(
[
MyModel(point=Point(0, 0)).to_geojson_model(),
MyModel(point=Point(1, 1)).to_geojson_model(),
]
)
@app.post("/points")
def post_points(model: MyModelFeatureCollection) -> typing.List[MyModel]:
# Convert the GeoJSON model back to the original model instance with the
# `to_feature_model` method. The Shapely geometry will be returned as a
# WKT-string in this case.
return model.to_feature_models()
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8000)
This package is still in development. The following features are planned for the future:
- Adding more options for the
GeometryField
annotation. For example, the ability to set a bounding box for the geometry. - Adding the CRS to the both
GeometryField
and the GeoJSON serialization. This functionality will automatically transform the geometries to the specified CRS.
Allthough the package is still in development, the current features are tested and ready for use. The signature of the methods and classes will not change in the future. If you have any suggestions or questions, feel free to open an issue on the GitHub repository.