Document script helpers

src/data/scripts/find_cha_buildings.py

@@ -2,6 +2,11 @@
 
 found = []
 
+# Reads from cha_building_names, which is sourced from:
+# https://www.thecha.org/residents/public-housing/find-public-housing
+#
+# This script will then log the correctly formatted data, and you can copy that into
+# buildings-custom-info.constant
 with open("src/data/scripts/cha_building_names.txt") as f:
     looking_for = f.read().splitlines()
     with open("src/data/source/ChicagoEnergyBenchmarking.csv") as a:
@@ -15,4 +20,4 @@
 
 for place in found:
     print('// '+place[1])
-    print("'" + place[0] + "'" + ": { owner: BuildingOwners.cha.key },")
+    print("'" + place[0] + "'" + ": { owner: BuildingOwners.cha.key },")

src/data/scripts/find_city_buildings.py

@@ -2,30 +2,41 @@
 
 found = []
 
+# Read through an export of the City of Chicago Land Inventory, filtering to only buildings with
+# the status 'Owned by City' and Managing Organization = 'AIS'
+#
+# Source: https://data.cityofchicago.org/Community-Economic-Development/City-Owned-Land-Inventory/aksk-kvfp
+#
+# This script will then log the correctly formatted data, and you can copy that into
+# buildings-custom-info.constant
 def find_addresses():
     with open('src/data/source/City-Owned_Land_Inventory.csv') as source_file:
         city_file = csv.DictReader(source_file)
         MAIN_FILE_ADDRESS_INDEX = 4
         MAIN_FILE_ID_INDEX = 1
-        
+
         with open('src/data/source/ChicagoEnergyBenchmarking.csv', newline='') as all_data:
             whole_file = all_data.read().splitlines()
             for i, line in enumerate(city_file):
                 if line["Address"].strip() == "" or line["Property Status"] != "Owned by City":
                     continue
+
                 for j, whole_file_line in enumerate(whole_file):
                     print(i, j)
                     address = whole_file_line.split(",")[MAIN_FILE_ADDRESS_INDEX]
+
+                    # Only include buildings that are owned AND managed by the city. Some buildings
+                    # are on land that appears to be owned by the city from their inventory
                     if line["Address"].lower().strip().replace(" ", "") == address.lower().strip().replace(" ", "") and line["Managing Organization"] == "AIS":
                         found.append(whole_file_line.split(",")[MAIN_FILE_ID_INDEX])
                         break
-                
+
                 if i%50 == 49:
                     with open("temp.txt", "w") as f:
                         f.write(str(len(found)))
                         f.write("/n")
                         f.write(", ".join(found))
-            
+
             print("found addresses: ", found.__str__(), len(found))
 
 def print_tags():
@@ -39,4 +50,4 @@ def print_tags():
                 found.remove(line["ID"])
 
 find_addresses()
-print_tags()
+print_tags()

src/data/scripts/find_cps_schools.py

@@ -2,13 +2,22 @@
 
 cps_schools:[str, str] = {}
 
+# Find CPS (Chicago Public Schools) properties by searching specifically for the term CPS in the
+# property name.
+#
+# NOTE: This does not include ALL buildings, so we manually tagged selective enrollment schools
+#
+# This script will then log the correctly formatted data, and you can copy that into
+# buildings-custom-info.constant
 with open('src/data/source/ChicagoEnergyBenchmarking.csv', newline='') as csvfile:
     whole_file = csv.DictReader(csvfile)
+
     for row in whole_file:
         if "CPS" in row["Property Name"]:
             cps_schools[row["ID"]] = row["Property Name"]
 
     for id, school in cps_schools.items():
-        cleaned_school_name = school.removesuffix("-CPS").strip()  
-        print("// "+cleaned_school_name)
-        print('"' + id + '"' + ": { owner: BuildingOwners.cps.key },")
+        cleaned_school_name = school.removesuffix("-CPS").strip()
+
+        print("// " + cleaned_school_name)
+        print('"' + id + '"' + ": { owner: BuildingOwners.cps.key },")