Pydantic models for STAC Catalogs, Collections, Items, and the STAC API spec. Initially developed by arturo-ai.
The main purpose of this library is to provide reusable request/response models for tools such as fastapi. For more comprehensive schema validation and robust extension support, use pystac.
pip install stac-pydanticFor local development:
pip install -e '.[dev,lint]'| stac-pydantic | STAC Version | STAC API Version | Pydantic Version |
|---|---|---|---|
| 1.2.x | 1.0.0-beta.1 | <1* | ^1.6 |
| 1.3.x | 1.0.0-beta.2 | <1* | ^1.6 |
| 2.0.x | 1.0.0 | <1* | ^1.6 |
| 3.0.x | 1.0.0 | 1.0.0 | ^2.4 |
* various beta releases, specs not fully implemented
Install the pre-commit hooks:
pre-commit installEnsure you have all Python versions installed that the tests will be run against. If using pyenv, run:
pyenv install 3.8.18
pyenv install 3.9.18
pyenv install 3.10.13
pyenv install 3.11.5
pyenv local 3.8.18 3.9.18 3.10.13 3.11.5Run the entire test suite:
toxRun a single test case using the standard pytest convention:
pytest -v tests/test_models.py::test_item_extensionsLoad data into models with standard pydantic:
from stac_pydantic import Catalog
stac_catalog = {
"type": "Catalog",
"stac_version": "1.0.0",
"id": "sample",
"description": "This is a very basic sample catalog.",
"links": [
{
"href": "item.json",
"rel": "item"
}
]
}
catalog = Catalog(**stac_catalog)
assert catalog.id == "sample"
assert catalog.links[0].href == "item.json"STAC defines many extensions which let the user customize the data in their catalog. stac-pydantic.extensions.validate_extensions will validate a dict, Item, Collection or Catalog against the schema urls provided in the stac_extensions property:
from stac_pydantic import Item
from stac_pydantic.extensions import validate_extensions
stac_item = {
"id": "12345",
"type": "Feature",
"stac_extensions": [
"https://stac-extensions.github.io/eo/v1.0.0/schema.json"
],
"geometry": { "type": "Point", "coordinates": [0, 0] },
"bbox": [0.0, 0.0, 0.0, 0.0],
"properties": {
"datetime": "2020-03-09T14:53:23.262208+00:00",
"eo:cloud_cover": 25,
},
"links": [],
"assets": {},
}
model = Item(**stac_item)
validate_extensions(model, reraise_exception=True)
assert getattr(model.properties, "eo:cloud_cover") == 25The complete list of current STAC Extensions can be found here.
The same procedure described above works for any STAC Extension schema as long as it can be loaded from a public url.
The STAC API Specs extent the core STAC specification for implementing dynamic catalogs. STAC Objects used in an API context should always import models from the api subpackage. This package extends
Catalog, Collection, and Item models with additional fields and validation rules and introduces Collections and ItemCollections models and Pagination/ Search Links.
It also implements models for defining ItemSeach queries.
from stac_pydantic.api import Item, ItemCollection
stac_item = Item(**{
"id": "12345",
"type": "Feature",
"stac_extensions": [],
"geometry": { "type": "Point", "coordinates": [0, 0] },
"bbox": [0.0, 0.0, 0.0, 0.0],
"properties": {
"datetime": "2020-03-09T14:53:23.262208+00:00",
},
"collection": "CS3",
"links": [
{
"rel": "self",
"href": "http://stac.example.com/catalog/collections/CS3-20160503_132130_04/items/CS3-20160503_132130_04.json"
},
{
"rel": "collection",
"href": "http://stac.example.com/catalog/CS3-20160503_132130_04/catalog.json"
},
{
"rel": "root",
"href": "http://stac.example.com/catalog"
}],
"assets": {},
})
stac_item_collection = ItemCollection(**{
"type": "FeatureCollection",
"features": [stac_item],
"links": [
{
"rel": "self",
"href": "http://stac.example.com/catalog/search?collection=CS3",
"type": "application/geo+json"
},
{
"rel": "root",
"href": "http://stac.example.com/catalog",
"type": "application/json"
}],
})Most STAC extensions are namespaced with a colon (ex eo:gsd) to keep them distinct from other extensions. Because
Python doesn't support the use of colons in variable names, we use Pydantic aliasing
to add the namespace upon model export. This requires exporting
the model with the by_alias = True parameter. Export methods (model_dump() and model_dump_json()) for models in this library have by_alias and exclude_unset st to True by default:
item_dict = item.model_dump()
assert item_dict['properties']['landsat:row'] == item.properties.row == 250Usage: stac-pydantic [OPTIONS] COMMAND [ARGS]...
stac-pydantic cli group
Options:
--help Show this message and exit.
Commands:
validate-item Validate STAC Item
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