add tests and enforce type property

stac-utils · Feb 15, 2024 · ac8e143 · ac8e143
1 parent 6d5da29
commit ac8e143
Show file tree

Hide file tree

Showing 13 changed files with 250 additions and 72 deletions.
diff --git a/.github/workflows/cicd.yml b/.github/workflows/cicd.yml
@@ -14,7 +14,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.8", "3.9", "3.10", "3.11"]
+        python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
 
     steps:
       - uses: actions/checkout@v4
@@ -27,11 +27,14 @@ jobs:
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          python -m pip install tox pre-commit
+          python -m pip install '.[lint]'
           pre-commit install
 
+      - name: Lint
+        run: pre-commit run --all
+
       # Run tox using the version of Python in `PATH`
-      - name: Run Tox
+      - name: Test
         run: tox -e py
 
       - name: Upload Results

diff --git a/pyproject.toml b/pyproject.toml
@@ -46,7 +46,7 @@ lint = ["types-requests>=2.31.0.5",
         "isort>=5.12.0",
         "flake8>=6.1.0",
         "Flake8-pyproject>=1.2.3",
-        "mypy>=1.8.0",
+        "mypy==1.4.1",
         "pre-commit>=3.4.0",
         "tox>=4.11.3"]
 

diff --git a/stac_pydantic/catalog.py b/stac_pydantic/catalog.py
@@ -1,6 +1,6 @@
-from typing import List, Literal, Optional
+from typing import Any, List, Literal, Optional
 
-from pydantic import AnyUrl, ConfigDict, Field
+from pydantic import AnyUrl, ConfigDict, Field, model_validator
 
 from stac_pydantic.links import Links
 from stac_pydantic.shared import SEMVER_REGEX, StacBaseModel
@@ -14,13 +14,23 @@ class _Catalog(StacBaseModel):
 
     id: str = Field(..., alias="id", min_length=1)
     description: str = Field(..., alias="description", min_length=1)
-    stac_version: str = Field(STAC_VERSION, pattern=SEMVER_REGEX)
-    links: Links = Links(root=[])
-    stac_extensions: Optional[List[AnyUrl]] = []
+    stac_version: str = Field(..., pattern=SEMVER_REGEX)
+    links: Links
+    stac_extensions: Optional[List[AnyUrl]] = None
     title: Optional[str] = None
     type: str
     model_config = ConfigDict(use_enum_values=True, extra="allow")
 
+    @model_validator(mode="before")
+    @classmethod
+    def set_default_links(cls, data: Any) -> Any:
+        if isinstance(data, dict):
+            if data.get("links") is None:
+                data["links"] = []
+            if data.get("stac_version") is None:
+                data["stac_version"] = STAC_VERSION
+        return data
+
 
 class Catalog(_Catalog):
-    type: Literal["Catalog"] = "Catalog"
+    type: Literal["Catalog"]
diff --git a/stac_pydantic/collection.py b/stac_pydantic/collection.py
@@ -52,4 +52,4 @@ class Collection(_Catalog):
     keywords: Optional[List[str]] = None
     providers: Optional[List[Provider]] = None
     summaries: Optional[Dict[str, Union[Range, List[Any], Dict[str, Any]]]] = None
-    type: Literal["Collection"] = "Collection"
+    type: Literal["Collection"]
diff --git a/stac_pydantic/item.py b/stac_pydantic/item.py
@@ -1,25 +1,11 @@
-from datetime import datetime as dt
 from typing import Any, Dict, List, Optional
 
 from ciso8601 import parse_rfc3339
 from geojson_pydantic import Feature
-from pydantic import (
-    AnyUrl,
-    ConfigDict,
-    Field,
-    field_serializer,
-    model_serializer,
-    model_validator,
-)
+from pydantic import AnyUrl, ConfigDict, Field, model_serializer, model_validator
 
 from stac_pydantic.links import Links
-from stac_pydantic.shared import (
-    DATETIME_RFC339,
-    SEMVER_REGEX,
-    Asset,
-    StacBaseModel,
-    StacCommonMetadata,
-)
+from stac_pydantic.shared import SEMVER_REGEX, Asset, StacBaseModel, StacCommonMetadata
 from stac_pydantic.version import STAC_VERSION
 
 
@@ -60,19 +46,25 @@ class Item(Feature, StacBaseModel):
     """
 
     id: str = Field(..., alias="id", min_length=1)
-    stac_version: str = Field(STAC_VERSION, pattern=SEMVER_REGEX)
+    stac_version: str = Field(..., pattern=SEMVER_REGEX)
     properties: ItemProperties
-    assets: Dict[str, Asset] = {}
-    links: Links = Links(root=[])
+    assets: Dict[str, Asset]
+    links: Links
     stac_extensions: Optional[List[AnyUrl]] = None
     collection: Optional[str] = None
 
     @model_validator(mode="before")
     @classmethod
-    def validate_bbox(cls, data: Any) -> Any:
+    def validate_defaults(cls, data: Any) -> Any:
         if isinstance(data, dict):
+            if data.get("stac_version") is None:
+                data["stac_version"] = STAC_VERSION
             if data.get("geometry") and data.get("bbox") is None:
                 raise ValueError("bbox is required if geometry is not null")
+            if data.get("assets") is None:
+                data["assets"] = {}
+            if data.get("links") is None:
+                data["links"] = []
         return data
 
     # https://github.com/developmentseed/geojson-pydantic/issues/147

diff --git a/tests/api/examples/v1.0.0/example-collection-list.json b/tests/api/examples/v1.0.0/example-collection-list.json
@@ -13,7 +13,8 @@
     ],
     "collections":[
        {
-          "id":"aster-l1t",
+         "type":"Collection",
+         "id":"aster-l1t",
           "description":"The [ASTER](https://terra.nasa.gov/about/terra-instruments/aster) instrument, launched on-board NASA's [Terra](https://terra.nasa.gov/) satellite in 1999, provides multispectral images of the Earth at 15m-90m resolution.  ASTER images provide information about land surface temperature, color, elevation, and mineral composition.\n\nThis dataset represents ASTER [L1T](https://lpdaac.usgs.gov/products/ast_l1tv003/) data from 2000-2006.  L1T images have been terrain-corrected and rotated to a north-up UTM projection.  Images are in [cloud-optimized GeoTIFF](https://www.cogeo.org/) format.\n",
           "stac_version":"1.0.0",
           "links":[
@@ -405,6 +406,7 @@
           }
        },
        {
+          "type":"Collection",
           "id":"landsat-8-c2-l2",
           "description":"The [Landsat](https://landsat.gsfc.nasa.gov/) program has been imaging the Earth since 1972; it provides a comprehensive, continuous archive of the Earth's surface.  [Landsat 8](https://www.usgs.gov/core-science-systems/nli/landsat/landsat-8) is the most recent satellite in the Landsat series.  Launched in 2013, Landsat 8 captures data in eleven spectral bands: ten optical/IR bands from the [Operational Land Imager](https://landsat.gsfc.nasa.gov/landsat-8/operational-land-imager) (OLI) instrument, and two thermal bands from the [Thermal Infrared Sensor](https://landsat.gsfc.nasa.gov/landsat-8/thermal-infrared-sensor-tirs) (TIRS) instrument.\n\nThis dataset represents the global archive of Level-2 Landsat 8 data from [Landsat Collection 2](https://www.usgs.gov/core-science-systems/nli/landsat/landsat-collection-2).  Because there is some latency before Level-2 data is available, a rolling window of recent Level-1 data is available as well.  Images are stored in [cloud-optimized GeoTIFF](https://www.cogeo.org/) format.\n",
           "stac_version":"1.0.0",
@@ -871,6 +873,7 @@
           }
        },
        {
+         "type":"Collection",
           "id":"sentinel-2-l2a",
           "description":"The [Sentinel-2](https://sentinel.esa.int/web/sentinel/missions/sentinel-2) program provides global imagery in thirteen spectral bands at 10m-60m resolution and a revisit time of approximately five days.  This dataset represents the global Sentinel-2 archive, from 2016 to the present, processed to L2A (bottom-of-atmosphere) using [Sen2Cor](https://step.esa.int/main/snap-supported-plugins/sen2cor/) and converted to [cloud-optimized GeoTIFF](https://www.cogeo.org/) format.",
           "stac_version":"1.0.0",
@@ -1496,7 +1499,8 @@
           }
        },
        {
-          "id":"naip",
+         "type":"Collection",
+         "id":"naip",
           "description":"The [National Agriculture Imagery Program](https://www.fsa.usda.gov/programs-and-services/aerial-photography/imagery-programs/naip-imagery/) (NAIP) provides US-wide, high-resolution aerial imagery, with four spectral bands (R, G, B, IR).  NAIP is administered by the [Aerial Field Photography Office](https://www.fsa.usda.gov/programs-and-services/aerial-photography/) (AFPO) within the [US Department of Agriculture](https://www.usda.gov/) (USDA).  Data are captured at least once every three years for each state.  This dataset represents NAIP data from 2010-present, in [cloud-optimized GeoTIFF](https://www.cogeo.org/) format.\n",
           "stac_version":"1.0.0",
           "links":[

diff --git a/tests/api/test_landing_page.py b/tests/api/test_landing_page.py
@@ -71,6 +71,7 @@ def test_schema(example_url, schema_url):
 
 def test_api_landing_page():
     LandingPage(
+        type="Catalog",
         id="test-landing-page",
         description="stac-api landing page",
         stac_extensions=[
@@ -100,6 +101,7 @@ def test_api_landing_page():
 
 def test_api_landing_page_is_catalog():
     landing_page = LandingPage(
+        type="Catalog",
         id="test-landing-page",
         description="stac-api landing page",
         stac_extensions=[

diff --git a/tests/example_stac/example-collection-list.json b/tests/example_stac/example-collection-list.json
@@ -8,6 +8,7 @@
     ],
     "collections":[
        {
+         "type":"Collection",
           "id":"aster-l1t",
           "description":"The [ASTER](https://terra.nasa.gov/about/terra-instruments/aster) instrument, launched on-board NASA's [Terra](https://terra.nasa.gov/) satellite in 1999, provides multispectral images of the Earth at 15m-90m resolution.  ASTER images provide information about land surface temperature, color, elevation, and mineral composition.\n\nThis dataset represents ASTER [L1T](https://lpdaac.usgs.gov/products/ast_l1tv003/) data from 2000-2006.  L1T images have been terrain-corrected and rotated to a north-up UTM projection.  Images are in [cloud-optimized GeoTIFF](https://www.cogeo.org/) format.\n",
           "stac_version":"1.0.0",
@@ -400,7 +401,8 @@
           }
        },
        {
-          "id":"landsat-8-c2-l2",
+         "type":"Collection",
+         "id":"landsat-8-c2-l2",
           "description":"The [Landsat](https://landsat.gsfc.nasa.gov/) program has been imaging the Earth since 1972; it provides a comprehensive, continuous archive of the Earth's surface.  [Landsat 8](https://www.usgs.gov/core-science-systems/nli/landsat/landsat-8) is the most recent satellite in the Landsat series.  Launched in 2013, Landsat 8 captures data in eleven spectral bands: ten optical/IR bands from the [Operational Land Imager](https://landsat.gsfc.nasa.gov/landsat-8/operational-land-imager) (OLI) instrument, and two thermal bands from the [Thermal Infrared Sensor](https://landsat.gsfc.nasa.gov/landsat-8/thermal-infrared-sensor-tirs) (TIRS) instrument.\n\nThis dataset represents the global archive of Level-2 Landsat 8 data from [Landsat Collection 2](https://www.usgs.gov/core-science-systems/nli/landsat/landsat-collection-2).  Because there is some latency before Level-2 data is available, a rolling window of recent Level-1 data is available as well.  Images are stored in [cloud-optimized GeoTIFF](https://www.cogeo.org/) format.\n",
           "stac_version":"1.0.0",
           "links":[
@@ -866,7 +868,8 @@
           }
        },
        {
-          "id":"sentinel-2-l2a",
+         "type":"Collection",
+         "id":"sentinel-2-l2a",
           "description":"The [Sentinel-2](https://sentinel.esa.int/web/sentinel/missions/sentinel-2) program provides global imagery in thirteen spectral bands at 10m-60m resolution and a revisit time of approximately five days.  This dataset represents the global Sentinel-2 archive, from 2016 to the present, processed to L2A (bottom-of-atmosphere) using [Sen2Cor](https://step.esa.int/main/snap-supported-plugins/sen2cor/) and converted to [cloud-optimized GeoTIFF](https://www.cogeo.org/) format.",
           "stac_version":"1.0.0",
           "links":[
@@ -1491,7 +1494,8 @@
           }
        },
        {
-          "id":"naip",
+         "type":"Collection",
+         "id":"naip",
           "description":"The [National Agriculture Imagery Program](https://www.fsa.usda.gov/programs-and-services/aerial-photography/imagery-programs/naip-imagery/) (NAIP) provides US-wide, high-resolution aerial imagery, with four spectral bands (R, G, B, IR).  NAIP is administered by the [Aerial Field Photography Office](https://www.fsa.usda.gov/programs-and-services/aerial-photography/) (AFPO) within the [US Department of Agriculture](https://www.usda.gov/) (USDA).  Data are captured at least once every three years for each state.  This dataset represents NAIP data from 2010-present, in [cloud-optimized GeoTIFF](https://www.cogeo.org/) format.\n",
           "stac_version":"1.0.0",
           "links":[

diff --git a/tests/example_stac/example-collection_version-extension.json b/tests/example_stac/example-collection_version-extension.json
@@ -1,36 +1,51 @@
 {
-    "stac_version": "1.0.0",
-    "stac_extensions": ["https://stac-extensions.github.io/version/v1.0.0/schema.json"],
-    "id": "merraclim",
-    "title": "MERRAclim",
-    "description": "A high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling.",
-    "license": "CC0-1.0",
-    "version": "1",
-    "deprecated": true,
-    "extent": {
-      "spatial": {
-        "bbox": [[-180,-90,180,90]]
-      },
-      "temporal": {
-        "interval": [["1980-01-01T00:00:00Z","2009-12-31T23:59:59Z"]]
-      }
+  "type": "Collection",
+  "stac_version": "1.0.0",
+  "stac_extensions": [
+    "https://stac-extensions.github.io/version/v1.0.0/schema.json"
+  ],
+  "id": "merraclim",
+  "title": "MERRAclim",
+  "description": "A high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling.",
+  "license": "CC0-1.0",
+  "version": "1",
+  "deprecated": true,
+  "extent": {
+    "spatial": {
+      "bbox": [
+        [
+          -180,
+          -90,
+          180,
+          90
+        ]
+      ]
     },
-    "links": [
-      {
-        "rel": "self",
-        "href": "https://datadryad.org/resource/doi:10.5061/dryad.s2v81/v1/collection.json"
-      },
-      {
-        "rel": "item",
-        "href": "https://datadryad.org/resource/doi:10.5061/dryad.s2v81/v1/item.json"
-      },
-      {
-        "rel": "root",
-        "href": "https://datadryad.org/resource/doi:10.5061/dryad.s2v81/catalog.json"
-      },
-      {
-        "rel": "latest-version",
-        "href": "https://datadryad.org/resource/doi:10.5061/dryad.s2v81/v2/collection.json"
-      }
-    ]
-  }
+    "temporal": {
+      "interval": [
+        [
+          "1980-01-01T00:00:00Z",
+          "2009-12-31T23:59:59Z"
+        ]
+      ]
+    }
+  },
+  "links": [
+    {
+      "rel": "self",
+      "href": "https://datadryad.org/resource/doi:10.5061/dryad.s2v81/v1/collection.json"
+    },
+    {
+      "rel": "item",
+      "href": "https://datadryad.org/resource/doi:10.5061/dryad.s2v81/v1/item.json"
+    },
+    {
+      "rel": "root",
+      "href": "https://datadryad.org/resource/doi:10.5061/dryad.s2v81/catalog.json"
+    },
+    {
+      "rel": "latest-version",
+      "href": "https://datadryad.org/resource/doi:10.5061/dryad.s2v81/v2/collection.json"
+    }
+  ]
+}
diff --git a/tests/example_stac/example-landsat8_item-assets-extension.json b/tests/example_stac/example-landsat8_item-assets-extension.json
@@ -1,5 +1,6 @@
 {
-    "id": "landsat-8-l1",
+  "type": "Collection",
+  "id": "landsat-8-l1",
     "title": "Landsat 8 L1",
     "description": "Landat 8 imagery radiometrically calibrated and orthorectified using gound points and Digital Elevation Model (DEM) data to correct relief displacement.",
     "keywords": [

diff --git a/tests/example_stac/landsat-collection.json b/tests/example_stac/landsat-collection.json
@@ -1,5 +1,6 @@
 {
-    "stac_version": "1.0.0",
+  "type":"Collection",
+  "stac_version": "1.0.0",
     "stac_extensions": [],
     "id": "landsat-8-l1",
     "title": "Landsat 8 L1",

diff --git a/tests/test_catalog.py b/tests/test_catalog.py
@@ -0,0 +1,22 @@
+from stac_pydantic.catalog import Catalog
+
+
+def test_catalog():
+    # Create a valid Catalog instance
+    catalog = Catalog(
+        type="Catalog",
+        id="my-catalog",
+        description="My STAC catalog",
+    )
+
+    catalog_json = catalog.model_dump(mode="json")
+
+    # Make default all values are set
+    assert catalog_json["id"] == "my-catalog"
+    assert catalog_json["description"] == "My STAC catalog"
+    assert catalog_json["stac_version"] == "1.0.0"
+    assert catalog_json["links"] == []
+    assert catalog_json["type"] == "Catalog"
+
+    assert "stac_extensions" not in catalog_json
+    assert "title" not in catalog_json