use ogr to convert gml more robustly - my solution was a hack that di…

…dn't work

.deployment/prod_environment.yml

@@ -10,6 +10,7 @@ dependencies:
   - google-cloud-logging
   - rioxarray
   - stackstac
+  - ogr
   - gdal
   - numpy
   - geopandas

.devcontainer/dev_environment.yml

@@ -11,6 +11,7 @@ dependencies:
   - ipykernel
   - rioxarray
   - stackstac
+  - ogr
   - contextily
   - rich
   - rich-with-jupyter

src/lib/query_soil.py

@@ -5,6 +5,7 @@
 from shapely.ops import transform
 import xml.etree.ElementTree as ET
 import tempfile
+import ogr
 
 SDM_ENDPOINT_TABULAR = "https://SDMDataAccess.sc.egov.usda.gov/Tabular/post.rest"
 SDM_ENDPOINT_SPATIAL = "https://SDMDataAccess.sc.egov.usda.gov/Spatial/SDMWGS84Geographic.wfs"
@@ -90,17 +91,33 @@ def sdm_get_esa_mapunitid_poly(geojson):
             with tempfile.NamedTemporaryFile(suffix='.gml') as tmp:
                 tmp.write(response.content)
                 tmp.seek(0)
-                gdf = gpd.read_file(tmp.name)
 
-                # GML is in lon/lat, so we need to transform to lat/lon
-                gdf['geometry'] = gdf['geometry'].apply(lambda geom: transform(lambda x, y: (y, x), geom))
+                # gdf = gpd.read_file(tmp.name)
+                # # GML is in lon/lat, so we need to transform to lat/lon
+                # gdf['geometry'] = gdf['geometry'].apply(lambda geom: transform(lambda x, y: (y, x), geom))
+
+                gdf = gml_to_gpd(tmp.name)
 
                 mapunitpoly_geojson = gdf.to_json()
                 return mapunitpoly_geojson
-        else: 
+        elif response.status_code == 400:
             print("Error:", response.status_code)
             return None
 
     except Exception as e:
         print("Error:", str(e))
-        return None
+        return None
+
+def gml_to_gpd(gml_file):
+    gml = ogr.Open(gml_file)
+    layer = gml.GetLayer(0)
+
+    # Get the features and create a list to put geometries
+    features=[]
+    for i in range(0,layer.GetFeatureCount()):
+        feature = layer.GetFeature(i)
+        geom = feature.GetGeometryRef()
+        features.append(wkt.loads(geom.ExportToWkt()))
+
+    # convert this list into a geopandas dataframe  
+    gdf = gpd.GeoDataFrame(geometry=features)