Single dedupe method.

litecoder/data/city-alt-names.yml

@@ -1,6 +1,7 @@
 ---
 
 # TODO: Separate neighborhoods list, for eg Hollywood / Bronx?
+# TODO: Switch to WOF ids, since some don't have Wikidata?
 
 # https://en.wikipedia.org/wiki/List_of_city_nicknames_in_the_United_States
 # https://web.archive.org/web/20080701040406/http://www.taglineguru.com:80/citymottosmonikers.html
@@ -43,6 +44,7 @@ Q1297:
 
 # Houston
 Q16555:
+  - HTX
   - Space City
   - H-Town
 
@@ -109,14 +111,11 @@ Q23556:
   - The ATL
   - Hotlanta
 
+# Denver
 Q16554:
   - Mile High City
   - The Mile High City
 
-# Houston
-Q16555:
-  - HTX
-
 # Richmond
 Q43421:
   - RVA
@@ -125,7 +124,7 @@ Q43421:
 Q38022:
   - STL
 
-# San Antonia
+# San Antonio
 Q975:
   - SATX
 

litecoder/models/wof_locality_dup.py

@@ -12,6 +12,22 @@
 from ..db import session
 
 
+ID_COLS = (
+    'dbp_id',
+    'fb_id',
+    'fct_id',
+    'fips_code',
+    'gn_id',
+    'gp_id',
+    'loc_id',
+    'nyt_id',
+    'qs_id',
+    'qs_pg_id',
+    'wd_id',
+    'wk_page',
+)
+
+
 class WOFLocalityDup(BaseModel):
 
     __tablename__ = 'wof_locality_dup'
@@ -28,7 +44,35 @@ def update(cls, wof_ids):
         session.commit()
 
     @classmethod
-    def dedupe_by_proximity(cls, buffer=0.1):
+    def dedupe_id_col(cls, col_name):
+        """Dedupe localities via shared external identifier.
+        """
+        dup_col = getattr(WOFLocality, col_name)
+
+        logger.info('Mapping `%s` -> rows' % col_name)
+
+        id_rows = defaultdict(list)
+        for row in tqdm(WOFLocality.query.filter(dup_col != None)):
+            id_rows[getattr(row, col_name)].append(row)
+
+        logger.info('Deduping rows with shared `%s`' % col_name)
+
+        dupes = set()
+        for rows in tqdm(id_rows.values()):
+            if len(rows) > 1:
+
+                # Sort by completeness.
+                rows = sorted(rows, key=lambda r: r.field_count, reverse=True)
+
+                # Add all but most complete to dupes.
+                for row in rows[1:]:
+                    dupes.add(row.wof_id)
+
+        cls.update(dupes)
+        return len(dupes)
+
+    @classmethod
+    def dedupe_proximity(cls, buffer=0.1):
         """For each locality, get neighbors within N degrees. If any of these
         (a) has the same name and (b) has more complete metadata, set dupe.
         """
@@ -56,29 +100,16 @@ def dedupe_by_proximity(cls, buffer=0.1):
         return len(dupes)
 
     @classmethod
-    def dedupe_shared_id_col(cls, col_name):
-        """Dedupe localities via shared external identifier.
+    def dedupe(cls):
+        """Dedupe on all id cols + proximity.
         """
-        dup_col = getattr(WOFLocality, col_name)
-
-        logger.info('Mapping `%s` -> rows' % col_name)
-
-        id_rows = defaultdict(list)
-        for row in tqdm(WOFLocality.query.filter(dup_col != None)):
-            id_rows[getattr(row, col_name)].append(row)
-
-        logger.info('Deduping rows with shared `%s`' % col_name)
-
-        dupes = set()
-        for rows in tqdm(id_rows.values()):
-            if len(rows) > 1:
+        for name in ID_COLS:
+            cls.dedupe_id_col(name)
 
-                # Sort by completeness.
-                rows = sorted(rows, key=lambda r: r.field_count, reverse=True)
+        cls.dedupe_proximity()
 
-                # Add all but most complete to dupes.
-                for row in rows[1:]:
-                    dupes.add(row.wof_id)
-
-        cls.update(dupes)
-        return len(dupes)
+    @classmethod
+    def count_unique(cls):
+        """Count unique duplicate rows.
+        """
+        return session.query(cls.wof_id.distinct()).count()