Update imports_utils.py

imports_utils.py

@@ -17,10 +17,6 @@ import json
 from notion_client import Client
 import os
 
-notionToken = os.getenv('notionToken')
-notion = Client(auth=notionToken)
-speckleToken = os.getenv('speckleToken')
-
 from config import landuseColumnName 
 from config import subdomainColumnName 
 from config import sqmPerEmployeeColumnName
@@ -33,6 +29,14 @@ from config import landuseDatabaseId , streamId,  dmBranchName, dmCommitId, luBr
 import speckle_utils
 import data_utils
 
+
+notionToken = os.getenv('notionToken')
+notion = Client(auth=notionToken)
+speckleToken = os.getenv('speckleToken')
+
+
+
+
 # ----------------------------------------------------------------------------------
 
 
@@ -127,7 +131,7 @@ def get_page_by_id(notion_db_pages, page_id):
     if pg["id"] == page_id:
       return pg
 
-
+"""
 
 def fetchDomainMapper (luAttributePages):
         
@@ -175,7 +179,7 @@ def fetchSubdomainMapper (livabilityAttributePages):
     #domains_unique = list(set(domains_unique))
     return attribute_mapper
 
-
+"""
 # --------------------------------------------------------------------------------------------- #
 
 
@@ -266,59 +270,51 @@ def getDataFromSpeckle(
 
 
 
-"""
-def fetchDistanceMatrices (streamObj):
-
-    matrices = {}
-    isDict = False
- 
-    try:
-        data_part = streamObj["@Data"]["@{0}"]
-        for matrix in data_part:
-            # Find the matrix name
-            matrix_name = next((attr for attr in dir(matrix) if "matrix" in attr), None)
- 
-            if not matrix_name:
-                continue
- 
-            matrix_data = getattr(matrix, matrix_name)
-            originUUID = matrix_data["@originUUID"]
-            destinationUUID = matrix_data["@destinationUUID"]
- 
-            processed_rows = []
-            for chunk in matrix_data["@chunks"]:
-                for row in chunk["@rows"]:
-                    processed_rows.append(row["@row"])
- 
-            matrix_array = np.array(processed_rows)
-            matrix_df = pd.DataFrame(matrix_array, index=originUUID, columns=destinationUUID)
-            matrices[matrix_name] = matrix_df
-    except KeyError:
-        data_part = streamObj["@Data"].__dict__
-        print(data_part.keys())
- 
-        for k, v in data_part.items():
-            if "matrix" in k:
-                matrix_name = k
-                matrix_data = v
-                originUUID = matrix_data["@originUUID"]
-                destinationUUID = matrix_data["@destinationUUID"]
- 
-                processed_rows = []
-                for chunk in matrix_data["@chunks"]:
-                    for row in chunk["@rows"]:
-                        processed_rows.append(row["@row"])
- 
-                matrix_array = np.array(processed_rows)
-                matrix_df = pd.DataFrame(matrix_array, index=originUUID, columns=destinationUUID)
-                matrices[matrix_name] = matrix_df
- 
-    return matrices
+def getDataFromNotion(
+        notion,
+		notionToken,
+		landuseDatabaseID,
+		subdomainDatabaseID,
+		landuseColumnName ="LANDUSE",
+		subdomainColumnName ="SUBDOMAIN_LIVABILITY",
+		sqmPerEmployeeColumnName = "SQM PER EMPL",
+		thresholdsColumnName="MANHATTAN THRESHOLD"
+		maxPointsColumnName = "LIVABILITY MAX POINT",
+		domainColumnName = "DOMAIN_LIVABILITY",
+		
+		):
 
+    landuse_attributes  = fetch_all_database_pages(notion, landuseDatabaseID)
+    livability_attributes  = fetch_all_database_pages(notion, subdomainDatabaseID)
 
+    landuseMapperDict ={}
+    livabilityMapperDict ={}
+
+    for page in landuse_attributes:
+        value_landuse = get_property_value(page, landuseColumnName)
+        value_subdomain = get_property_value(page, subdomainColumnName)
+        origin =  "false" if not get_property_value(page, "is_origin_mask") else get_property_value(page, "is_origin_mask")
+        if value_subdomain and value_landuse:
+            landuseMapperDict[value_landuse] = {
+            'subdomain livability': value_subdomain,
+            'is origin': origin
+            }
     
-    
-"""
+    for page in livability_attributes:
+        subdomain = get_property_value(page, subdomainColumnName)
+        sqm_per_employee = get_property_value(page, sqmPerEmployeeColumnName)
+        thresholds = get_property_value(page, thresholdsColumnName)
+        max_points = get_property_value(page, maxPointsColumnName)
+        domain = get_property_value(page, domainColumnName)
+        if  thresholds:   
+            livabilityMapperDict[subdomain] = {
+            'sqmPerEmpl': sqm_per_employee if sqm_per_employee != "" else 0,
+            'thresholds': thresholds,
+            'max_points': max_points,
+            'domain': [domain if domain != "" else 0]
+            }    
+        
+	return landuseMapperDict, livabilityMapperDict,