van location finished and integrasted into child location upload

prepared_steps/1_extract_data/queries.json

@@ -32,7 +32,7 @@
             "query": "SELECT Id, Article__r.Name, Price__c, PriceUnit__c, Pricelist__c, ValidFrom__c, ValidTo__c, Article__r.EANCode__c, Pricelist__r.Brand__r.Name, Pricelist__r.Country__c  FROM SCPriceListItem__c WHERE Country__c = '{country}' AND PriceList__c != null AND (ValidTo__c >= TODAY OR ValidFrom__c >= TODAY) AND Article__c = 'a0Gw000001R9slpEAB'"
         },{
             "sobject": "SCResourceAssignment__c",
-            "query": "SELECT Id, ValidTo__c, ValidFrom__c, Country__c, City__c, District__c, Street__c, HouseNo__c, Extension__c, FlatNo__c, Floor__c, GeoY__c, GeoX__c, Resource__c, Stock__c FROM SCResourceAssignment__c WHERE Country__c = '{country}' AND ValidTo__c >= TODAY"
+            "query": "SELECT Id, ValidTo__c, ValidFrom__c, Country__c, City__c, PostalCode__c, District__c, Street__c, HouseNo__c, Extension__c, FlatNo__c, Floor__c, GeoY__c, GeoX__c, Resource__c, Resource__r.Employee__r.Name, Stock__c FROM SCResourceAssignment__c WHERE Country__c = '{country}' AND ValidTo__c >= TODAY"
         }
     ]
 }

prepared_steps/2_transform_via_script/TransformScript.py

@@ -2,8 +2,27 @@ import pandas as pd
 from tqdm import tqdm
 
 country_mapping = {
-    'NL': 'Netherlands'
+    'NL': 'Netherlands',
-    }   
+    'GB': 'United Kingdom',
+    'UK': 'United Kingdom',
+    'IE': 'Ireland',
+    'DE': 'Germany',
+    'FR': 'France',
+    'IT': 'Italy',
+    'ES': 'Spain',
+    'PT': 'Portugal',
+    'BE': 'Belgium',
+    'AT': 'Austria',
+    'CH': 'Switzerland',
+    'NO': 'Norway',
+    'FI': 'Finland',
+    'SE': 'Sweden',
+    'DK': 'Denmark',
+    'PL': 'Poland',
+    'CZ': 'Czech Republic',
+    'HU': 'Hungary',
+    'RO': 'Romania'
+}   
 
 # Read the input CSV file, assuming the second row is the header
 read_df = pd.read_csv('../1_extract_data/results/SCInstalledBaseLocation__c.csv', header=0, keep_default_na=False, dtype=str)
@@ -23,7 +42,7 @@ reindex_columns_product2 = ['Id','Main_Product_Group__c','Family','MaterialType_
 reindex_columns_ibr = ['Id', 'InstalledBaseLocation__c', 'Role__c', 'ValidFrom__c', 'ValidTo__c', 'Account__c']
 reindex_columns_pricelist = ['Id', 'Name', 'Brand__r.Name', 'Country__c']
 reindex_columns_pricelistitem = ['Id', 'Article__r.Name', 'Article__r.EANCode__c', 'Price__c', 'PriceUnit__c', 'Pricelist__c', 'ValidFrom__c', 'ValidTo__c', 'Pricelist__r.Brand__r.Name', 'Pricelist__r.Country__c']
-reindex_columns_resourceassignment = ['Id', 'ValidTo__c', 'ValidFrom__c', 'Country__c', 'City__c', 'District__c', 'Street__c', 'HouseNo__c', 'Extension__c', 'FlatNo__c', 'Floor__c', 'GeoY__c', 'GeoX__c', 'Resource__c', 'Stock__c']
+reindex_columns_resourceassignment = ['Id', 'ValidTo__c', 'ValidFrom__c', 'Country__c', 'City__c', 'PostalCode__c', 'District__c', 'Street__c', 'HouseNo__c', 'Extension__c', 'FlatNo__c', 'Floor__c', 'GeoY__c', 'GeoX__c', 'Resource__c', 'Resource__r.Employee__r.Name', 'Stock__c']
 reindex_columns_address_iot = ['Id', 'Country', 'CountryCode', 'Street', 'City', 'ParentId', 'PostalCode']
 reindex_columns_location_iot = ['Id', 'Name']
 
@@ -156,6 +175,9 @@ child_columns = ['Id', 'Extension__c', 'FlatNo__c', 'Floor__c', 'City__c', 'Coun
 # Modify child_df by explicitly creating a new DataFrame
 child_df = df[child_columns].copy()  # Add .copy() to create an explicit copy
 
+child_df.columns = ['Id', 'Extension__c', 'FlatNo__c', 'Floor__c', 'City', 'Country', 
+                    'PostalCode', 'Street', 'ExternalReference']
+
 # Create the 'Name' column with simplified logic
 child_df['Name'] = (
     # Check if all three fields are not null; if so, concatenate them
@@ -168,8 +190,8 @@ child_df['Name'] = (
 child_df.replace({'Name': {'--': 'HOME'}}, inplace=True)
 
 # Create the 'ExternalReference' column for Asset assignment
-child_df['ExternalReference'] = (
+child_df['PKey__c'] = (
-    child_df['PKey__c'].astype(str) + ';' +
+    child_df['ExternalReference'].astype(str) + ';' +
     child_df['Extension__c'].astype(str) + ';' +
     child_df['FlatNo__c'].astype(str) + ';' +
     child_df['Floor__c'].astype(str)
@@ -177,7 +199,7 @@ child_df['ExternalReference'] = (
 
 # Rename columns to match the desired format
 child_df.columns = ['Id', 'Extension__c', 'Flat__c', 'Floor__c', 'City', 'Country',
-                     'PostalCode', 'Street', 'PKey__c', 'Name', 'ExternalReference']
+                     'PostalCode', 'Street', 'ExternalReference', 'Name', 'PKey__c']
 
 child_df = child_df.drop_duplicates(subset=['Extension__c', 'Flat__c', 'Floor__c','City', 'Country', 'PostalCode', 'Street'], keep='first')
 
@@ -314,8 +336,6 @@ df_pricelistitem = df_pricelistitem.drop('Article__r.EANCode__c', axis=1)
 
 df_pricelistitem.insert(0, 'IsActive', 'true')
 
-print(df_pricelistitem)
-
 columns_pricebookentry = ['IsActive', 'Product2.Product_Code__c', 'UnitPrice', 'Pricebook2.Name']
 
 df_pricelistitem.columns = columns_pricebookentry
@@ -324,8 +344,33 @@ df_pricelistitem.columns = columns_pricebookentry
 ## Location (Van)
 ##--------------------------------------------------------------------------##
 
+# Create van locations from resource assignments
+van_columns = ['Id', 'City__c', 'Country__c', 'Street__c', 'PostalCode__c', 'GeoY__c', 'GeoX__c', 'Resource__r.Employee__r.Name']
+van_df = df_resourceassignment[van_columns].copy()
 
+# Create PKey__c for vans
+van_df['ExternalReference'] = (
+    van_df['Street__c'].astype(str) + ', ' +
+    van_df['PostalCode__c'].astype(str) + ' ' +
+    van_df['City__c'].astype(str) + ', ' +
+    van_df['Country__c'].astype(str)
+)
 
+# Filter vans where ExternalReference does not exist in parent_df
+van_df = van_df[~van_df['ExternalReference'].isin(parent_df['Name'])]
+
+# Add van records to child_df
+if not van_df.empty:
+    van_records = pd.DataFrame({
+        'Name': van_df['Resource__r.Employee__r.Name'],
+        'ExternalReference': van_df['ExternalReference'],
+        'PKey__c': van_df['ExternalReference'] + ';' + 'VAN',
+        'DuplicateCheck__c': 'false',
+        'IsInventoryLocation': 'true',
+        'IsMobile': 'true',
+        'LocationType': 'Van'
+    })
+    child_df = pd.concat([child_df, van_records], ignore_index=True)
 
 # Write each DataFrame to a separate CSV file
 address_df.to_csv('../4_upsert_address_and_parent_location/Address.csv', index=False)

prepared_steps/6_upsert_child_location/export.json

@@ -3,7 +3,7 @@
     "excludeIdsFromCSVFiles": true,
     "objects": [
         {
-            "query": "SELECT Extension,Flat,Floor,Name,DuplicateCheck__c,IsInventoryLocation,IsMobile,LocationType,PKey__c, ExternalReference FROM Location",
+            "query": "SELECT Id,Extension__c,Flat__c,Floor__c,ExternalReference,Name,PKey__c,DuplicateCheck__c,IsInventoryLocation,IsMobile,LocationType FROM Location",
             "operation": "Insert",
             "useSourceCSVFile": true
         }

prepared_steps/7_build_lookup_child_to_parent_location/export.json

@@ -2,7 +2,7 @@
     "allOrNone": true,
     "objects": [
         {
-            "query": "SELECT Id, Name, Pkey__c, ParentLocationId FROM Location WHERE Pkey__c != null AND PKey__c like '%NL' AND ParentLocationId = null AND VisitorAddressId = null",
+            "query": "SELECT Id, Name, ExternalReference, ParentLocationId FROM Location WHERE ExternalReference != null AND ExternalReference LIKE '%NL' AND ParentLocationId = null AND VisitorAddressId = null",
             "operation": "Update",
             "beforeUpdateAddons": [
                 {
@@ -14,7 +14,7 @@
                                 "alias": "sourceAddressParentIdFromPkey",
                                 "sourceObject": "Address",
                                 "sourceField": "ParentId",
-                                "lookupExpression": "source.PKey__c == target.Pkey__c",
+                                "lookupExpression": "source.PKey__c == target.ExternalReference",
                                 "lookupSource": "source"
                             }
                         ],