fix methods to infer geom and bbox

.gitignore

@@ -1,3 +1,4 @@
 __pycache__
 *.parquet
 dist/
+.vscode

stac_table.py

@@ -7,14 +7,14 @@
 from typing import TypeVar
 
 import dask
-import pystac
-import pandas as pd
-import pyarrow
-import pyarrow.parquet
-import fsspec
 import dask_geopandas
+import fsspec
+import pandas as pd
+import pyarrow as pa
+import pyproj
+import pystac
 import shapely.geometry
-
+from shapely.ops import transform
 
 T = TypeVar("T", pystac.Collection, pystac.Item)
 SCHEMA_URI = "https://stac-extensions.github.io/table/v1.2.0/schema.json"
@@ -155,11 +155,13 @@ def generate(
         or infer_datetime != InferDatetimeOptions.no
         or proj is True
     ):
+        #     # TODO: this doesn't actually work
+        #     data = dask_geopandas.read_parquet(
+        #         ds.files, storage_options={"filesystem": ds.filesystem}
+        #     )
         data = dask_geopandas.read_parquet(uri, storage_options=storage_options)
-    #     # TODO: this doesn't actually work
-    #     data = dask_geopandas.read_parquet(
-    #         ds.files, storage_options={"filesystem": ds.filesystem}
-    #     )
+        if data.spatial_partitions is None:
+            data.calculate_spatial_partitions()
 
     columns = get_columns(ds)
     template.properties["table:columns"] = columns
@@ -176,16 +178,27 @@ def generate(
 
     extra_proj = {}
     if infer_bbox:
+        src_crs = data.spatial_partitions.crs.to_epsg()
+        tf = pyproj.Transformer.from_crs(src_crs, 4326, always_xy=True)
+
         bbox = data.spatial_partitions.unary_union.bounds
-        # TODO: may need to convert to epsg:4326
+        # NOTE: bbox of unary union will be stored under proj extension as projected
         extra_proj["proj:bbox"] = bbox
-        template.bbox = bbox
+
+        # NOTE: bbox will be stored in pystsac.Item.bbox in EPSG:4326
+        bbox = transform(tf.transform, shapely.geometry.box(*bbox))
+        template.bbox = bbox.bounds
 
     if infer_geometry:
-        geometry = shapely.geometry.mapping(data.unary_union.compute())
-        # TODO: may need to convert to epsg:4326
-        extra_proj["proj:geometry"] = geometry
-        template.geometry = geometry
+        # NOTE: geom  under proj extension as projected
+        geometry = data.unary_union.compute()
+        extra_proj["proj:geometry"] = shapely.geometry.mapping(geometry)
+
+        # NOTE: geometry will be stored in pystsac.Item.geometry in EPSG:4326
+        src_crs = data.spatial_partitions.crs.to_epsg()
+        tf = pyproj.Transformer.from_crs(src_crs, 4326, always_xy=True)
+        geometry = transform(tf.transform, geometry)
+        template.geometry = shapely.geometry.mapping(geometry)
 
     if infer_bbox and template.geometry is None:
         # If bbox is set then geometry must be set as well.
@@ -200,7 +213,8 @@ def generate(
         template.properties.update(**extra_proj, **proj)
 
     if infer_datetime != InferDatetimeOptions.no and datetime_column is None:
-        raise ValueError("Must specify 'datetime_column' when 'infer_datetime != no'.")
+        msg = "Must specify 'datetime_column' when 'infer_datetime != no'."
+        raise ValueError(msg)
 
     if infer_datetime == InferDatetimeOptions.midpoint:
         values = dask.compute(data[datetime_column].min(), data[datetime_column].max())
@@ -210,7 +224,8 @@ def generate(
         values = data[datetime_column].unique().compute()
         n = len(values)
         if n > 1:
-            raise ValueError(f"infer_datetime='unique', but {n} unique values found.")
+            msg = f"infer_datetime='unique', but {n} unique values found."
+            raise ValueError(msg)
         template.properties["datetime"] = values[0].to_pydatetime()
 
     if infer_datetime == InferDatetimeOptions.range:
@@ -258,7 +273,7 @@ def get_proj(ds):
     return proj
 
 
-def get_columns(ds: pyarrow.parquet.ParquetDataset) -> list:
+def get_columns(ds: pa.parquet.ParquetDataset) -> list:
     columns = []
     fragment = ds.fragments[0]
 
@@ -273,13 +288,9 @@ def get_columns(ds: pyarrow.parquet.ParquetDataset) -> list:
     return columns
 
 
-def parquet_dataset_from_url(
-    url: str, storage_options
-):
+def parquet_dataset_from_url(url: str, storage_options):
     fs, _, _ = fsspec.get_fs_token_paths(url, storage_options=storage_options)
-    pa_fs = pyarrow.fs.PyFileSystem(pyarrow.fs.FSSpecHandler(fs))
+    pa_fs = pa.fs.PyFileSystem(pa.fs.FSSpecHandler(fs))
     url2 = url.split("://", 1)[-1]  # pyarrow doesn't auto-strip the prefix.
-    ds = pyarrow.parquet.ParquetDataset(
-        url2, filesystem=pa_fs, use_legacy_dataset=False
-    )
+    ds = pa.parquet.ParquetDataset(url2, filesystem=pa_fs, use_legacy_dataset=False)
     return ds

test_stac_table.py

@@ -3,15 +3,25 @@
 import shutil
 from pathlib import Path
 
-import pandas as pd
 import dask_geopandas
 import geopandas
+import pandas as pd
+import pyproj
 import pystac
 import pytest
 import shapely.geometry
+
 import stac_table
 
 
+def is_valid_epsg(epsg_code):
+    try:
+        pyproj.CRS.from_user_input(epsg_code)
+        return True
+    except pyproj.exceptions.CRSError:
+        return False
+
+
 @pytest.fixture
 def ensure_clean():
     yield
@@ -51,11 +61,11 @@ def test_generate_item(self, partition):
         )
 
         expected_columns = [
-            {"name": "pop_est", "type": "int64"},
+            {"name": "pop_est", "type": "double"},
             {"name": "continent", "type": "byte_array"},
             {"name": "name", "type": "byte_array"},
             {"name": "iso_a3", "type": "byte_array"},
-            {"name": "gdp_md_est", "type": "double"},
+            {"name": "gdp_md_est", "type": "int64"},
             {"name": "geometry", "type": "byte_array"},
         ]
         assert result.properties["table:columns"] == expected_columns
@@ -67,7 +77,7 @@ def test_generate_item(self, partition):
         assert asset.extra_fields["table:storage_options"] == {"storage_account": "foo"}
 
         assert pystac.extensions.projection.SCHEMA_URI in result.stac_extensions
-        assert result.properties["proj:epsg"] == 4326
+        assert is_valid_epsg(result.properties["proj:epsg"])
 
     def test_infer_bbox(self):
         df = geopandas.GeoDataFrame(