clean

generate_keys.py

@@ -0,0 +1,100 @@
+"""
+HELPER SCRIPT: generate_keys.py
+-------------------------------
+This script generates a list of 'Quadkeys' (map tiles) that intersect a specific
+geographic area (WKT Geometry). This list is used to seed the scraper in 'power2.py'
+so it knows exactly where to look for outages without scanning the whole world.
+
+PREREQUISITES:
+   pip install shapely mercantile
+
+USAGE INSTRUCTIONS:
+1. Obtain the WKT (Well-Known Text) geometry for your target area from your database.
+   
+   Example SQL to get WKT for a specific county:
+      SELECT ST_AsText(geom) FROM county WHERE countyname = 'Kanawha' AND state = 'WV';
+
+   Example SQL to get WKT for a whole NWS Warning Area (Union of counties):
+      SELECT ST_AsText(ST_Union(geom)) FROM county WHERE cwa = 'RLX';
+
+2. Run this script:
+      python generate_keys.py
+
+3. Paste the huge text string returned by your SQL query into the prompt and hit Enter.
+
+4. Copy the resulting 'KEY_LIST = [...]' output and paste it into the configuration 
+   section of 'power2.py' (e.g., replace AEP_WV_KEYS).
+"""
+
+import mercantile
+from shapely import wkt
+from shapely.geometry import box
+import sys
+
+# --- CONFIGURATION ---
+# The zoom level to generate keys for. 
+# Level 7 is standard for the "entry" lists in your scraper (e.g. '0320001').
+# If the utility uses a different zoom level for its top-level clusters, adjust this.
+TARGET_ZOOM = 7 
+
+# Increase the CSV field size limit to handle massive WKT strings
+import csv
+csv.field_size_limit(sys.maxsize)
+
+def generate_keys_from_wkt(wkt_string):
+    """
+    Takes a WKT geometry string, finds the bounding box, generates all tiles
+    within that box, and filters them to keep only those that actually 
+    intersect the geometry.
+    """
+    try:
+        print("Parsing WKT...")
+        # 1. Parse the WKT
+        service_area = wkt.loads(wkt_string)
+        
+        # 2. Get the Bounding Box (minx, miny, maxx, maxy)
+        bounds = service_area.bounds
+        
+        # 3. Generate all tiles covering the bounding box at the target zoom
+        # mercantile.tiles(west, south, east, north, zooms)
+        candidate_tiles = list(mercantile.tiles(bounds[0], bounds[1], bounds[2], bounds[3], zooms=[TARGET_ZOOM]))
+        
+        valid_keys = []
+        
+        print(f"Scanning {len(candidate_tiles)} candidate tiles...")
+
+        for tile in candidate_tiles:
+            # 4. Create a geometry for the tile itself
+            # mercantile.bounds returns (west, south, east, north)
+            t_bounds = mercantile.bounds(tile)
+            tile_geom = box(t_bounds.west, t_bounds.south, t_bounds.east, t_bounds.north)
+            
+            # 5. Intersection Check: Does this tile actually touch the service area?
+            # We use intersects() because contains() might miss tiles that only partially overlap.
+            if service_area.intersects(tile_geom):
+                valid_keys.append(mercantile.quadkey(tile))
+
+        # 6. Output formatted for Python list
+        valid_keys.sort()
+        print(f"\nFound {len(valid_keys)} intersecting tiles.")
+        print("-" * 30)
+        print(f"KEY_LIST = {valid_keys}")
+        print("-" * 30)
+
+    except Exception as e:
+        print(f"Error processing geometry: {e}")
+
+if __name__ == "__main__":
+    print("Paste your PostGIS WKT (Well-Known Text) string below and press Enter:")
+    
+    # Use standard input reading to handle potentially large inputs better than input()
+    try:
+        user_wkt = input().strip()
+        if user_wkt:
+            generate_keys_from_wkt(user_wkt)
+        else:
+            print("No input provided.")
+    except EOFError:
+        print("Error reading input.")
+    except KeyboardInterrupt:
+        print("\nCancelled.")