BE-WAL: the crops were in the table all along, under their names

CHANGELOG.md

@@ -11,6 +11,7 @@ and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.
 - ES-CL: the ITACyL server is https-only, the 2025 shapefiles sit in province subfolders, and C_REFREC is the identifier
 - A test refuses a fixture above 5 MB, committed or merely lying in the fixture folder, because a failing convert test downloads the real source there
 - ES-MD: find RECINTO.shp wherever the archive puts it
+- BE-WAL: match the crop by name where EuroCrops' table leaves the code empty, which covered 6.79% of the collection
 - Update vecorel-cli to v0.2.17:
   - GeoJSON is read as UTF-8 as the format mandates, instead of the platform locale (cp1252 on Windows mangled umlauts)
   - GeoJSON files with a byte order mark no longer fail to read

fiboa_cli/datasets/be_wal.py

@@ -38,6 +38,9 @@ class Converter(AdminConverterMixin, AddHCATMixin, FiboaBaseConverter):
         "determination:datetime": "determination:datetime",
     }
     ec_mapping_csv = "be_wal_all_years.csv"
+    # 208 of that table's 298 rows carry no code, only the crop name, so every
+    # crop whose coded row is missing went unmapped: 23,216 fields over 59 codes.
+    ec_mapping_name_fallback = True
     column_additions = {
         "determination:datetime": "2022-01-01T00:00:00Z",
     }

fiboa_cli/datasets/commons/hcat.py

@@ -18,6 +18,9 @@ class AddHCATMixin:
     """
 
     ec_mapping_csv: Optional[str] = None  # TODO rename to hcat_mapping_csv
+    # Match on the crop name where the table has no row for the code:
+    # be_wal_all_years.csv leaves original_code empty in 208 of its 298 rows.
+    ec_mapping_name_fallback = False
     mapping_file = None
     ec_mapping: Optional[list[dict]] = None  # TODO rename to hcat_mapping
 
@@ -70,12 +73,26 @@ def add_hcat(self, gdf):
             def map_to(attribute):
                 return {e[from_code]: e[attribute] or None for e in self.ec_mapping}
 
+            name_col = None
+            if self.ec_mapping_name_fallback and from_code == "original_code":
+                name_col = self.get_code_column(gdf, "crop:name")
+
+            def map_by_name(attribute):
+                # Three Walloon crops carry a trailing space in the table.
+                return {
+                    (e["original_name"] or "").strip(): e[attribute] or None
+                    for e in self.ec_mapping
+                    if not (e["original_code"] or "").strip()
+                }
+
             col = None
             for k, v in zip(
                 self.hcat_columns.keys(), ("translated_name", "HCAT3_name", "HCAT3_code")
             ):
                 if v in self.ec_mapping[0]:
                     col = crop_code_col.map(map_to(v))
+                    if name_col is not None:
+                        col = col.fillna(name_col.str.strip().map(map_by_name(v)))
                     gdf[k] = col
                     assert np.unique(col[~col.isna()]).size > 1, "No HCAT crops mapped"