Edr feature collection #7
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Jeffrey-Vervoort-KNMI
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| from edr_pydantic.base_model import EdrBaseModel | ||
| from edr_pydantic.parameter import Parameter | ||
| from geojson_pydantic import FeatureCollection # type: ignore |
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Why do we need a # type: ignore here?
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Because mypy is not able to find the stubs for the external packages. I would have to look into it, but I think that there are two possible fixes:
- add
py.typedto the library and ensure it is distributed by adding it to pytoml or setup.py:
[tool.setuptools.package-data]
"<package_name>" = ["py.typed"]
- Ignore it.
| from typing import Dict | ||
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| from edr_pydantic.base_model import EdrBaseModel | ||
| from edr_pydantic.parameter import Parameter |
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It should be covjson_pydantic.parameter!
I think the parameter inconsistency between EDR and CovJSON should be corrected in EDR v1.2:
opengeospatial/ogcapi-environmental-data-retrieval#427
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Fixed
| "parameters": { | ||
| "tx_dryb_10": { | ||
| "type": "Parameter", | ||
| "description": "Temperature, air, maximum, 10", |
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Should use i18n here and in several other places.
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Fixed
| @@ -19,8 +19,8 @@ classifiers = [ | |||
| "Topic :: Scientific/Engineering :: GIS", | |||
| "Typing :: Typed", | |||
| ] | |||
| version = "0.2.1" | |||
| dependencies = ["pydantic>=2.3,<3"] | |||
| version = "0.3.0" | |||
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Is this a breaking change?
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No, when upgrading you can still use the FeatureCollection of geojson-pydantic. It is not mandatory to use the model or implement the parameters.
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Then why bump minor version?
Co-authored-by: Paul van Schayck <[email protected]>
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The focus of regular GeoJSON is representing spatial data. EDR GeoJSON adds custom properties that help users discover what is available in the request. See here for the optional requirements.
The GeoJSON package implements the GeoJSON standards. The models inside the package ignore extra properties. Therefore it cannot be used to add the optional properties of EDR Feature Collection GeoJSON. In addition, I think it is nice to have validation on the parameters which a custom model makes possible.