Implemntation is done

dashboards/adding_instances.py

@@ -1,67 +1,75 @@
+# The scrpit below is used to add instances to the ontology 
+# It generates mock data for the asset management and risk management classes
+# The mock data is then added to the ontology
+
+# Import required libraries
 import pandas as pd
 import numpy as np
 import random
 import string
-from owlready2 import *
+from owlready2 import get_ontology
 import uuid
 
 # Helper functions for generating mock data
-#def random_string(length=10, chars=string.ascii_uppercase + string.digits):
-   # return ''.join(random.choice(chars) for _ in range(length))
+def random_string(length=10, chars=string.ascii_uppercase + string.digits):
+    return ''.join(random.choice(chars) for _ in range(length))
 
-#def random_city(cities):
- #   return random.choice(cities)
+# Function to randomly select a city from the list
+def random_city(cities):
+    return random.choice(cities)
 
 # List of cities for 'LastKnownLocation' and 'OriginalPlace'
-#cities = ['New York', 'London', 'Tokyo', 'Sydney', 'Paris', 'Berlin', 'Singapore', 'Dubai', 'San Francisco', 'Sao Paulo']
+cities = ['New York', 'London', 'Tokyo', 'Sydney', 'Paris', 'Berlin', 'Singapore', 'Dubai', 'San Francisco', 'Sao Paulo']
 
 # Generate mock data
-#num_assets = 100  # Number of assets to generate
-#data = {
-   # 'AssetID': [random_string(8) for _ in range(num_assets)],
-   # 'Name': [f"{asset_type}-{random_string(5)}" for asset_type in np.random.choice(['Server', 'Workstation', 'Router', 'Switch', 'Firewall'], size=num_assets)],
-  #  'TypeOfAsset': np.random.choice(['Hardware', 'Software', 'Network Device'], size=num_assets),
-  #  'LastKnownLocation': [random_city(cities) for _ in range(num_assets)],
-   # 'OriginalPlace': [random_city(cities) for _ in range(num_assets)]
-#}
+num_assets = 100  # Number of assets to generate
+data = {
+    'AssetID': [random_string(8) for _ in range(num_assets)],
+    'Name': [f"{asset_type}-{random_string(5)}" for asset_type in np.random.choice(['Server', 'Workstation', 'Router', 'Switch', 'Firewall'], size=num_assets)],
+    'TypeOfAsset': np.random.choice(['Hardware', 'Software', 'Network Device'], size=num_assets),
+    'LastKnownLocation': [random_city(cities) for _ in range(num_assets)],
+    'OriginalPlace': [random_city(cities) for _ in range(num_assets)]
+}
 
 # Create DataFrame from mock data
-#asset_management_df = pd.DataFrame(data)
+asset_management_df = pd.DataFrame(data)
 
 # Load the ontology
 onto = get_ontology("/workspaces/csonto/dashboards/csonto-edit.rdf").load()
 
 # Access the AssetsList class using the provided IRI
-#AssetsList = onto.search_one(iri="http://FYP-ASHS21/csonto#AssetsList")
+AssetsList = onto.search_one(iri="http://FYP-ASHS21/csonto#AssetsList")
 
 # Verify the AssetsList class was found
-#if not AssetsList:
-    #raise ValueError("AssetsList class not found in the ontology")
+if not AssetsList:
+    raise ValueError("AssetsList class not found in the ontology")
 
-#for index, row in asset_management_df.iterrows():
-   # asset_instance = AssetsList()
+# Iterate over the DataFrame rows and create instances of the AssetsList class
+for index, row in asset_management_df.iterrows():
+    asset_instance = AssetsList()
 
     # Assign properties to the instance, ensuring they are treated as data properties
     # Since the properties are not functional, you cannot assign directly.
     # Instead, you need to use append or set method.
-    #getattr(asset_instance, "originalPlace").append(str(row['OriginalPlace']))
-    #getattr(asset_instance, "typeOfAsset").append(str(row['TypeOfAsset']))
-    #getattr(asset_instance, "lastKnownLocation").append(str(row['LastKnownLocation']))
+    getattr(asset_instance, "originalPlace").append(str(row['OriginalPlace']))
+    getattr(asset_instance, "typeOfAsset").append(str(row['TypeOfAsset']))
+    getattr(asset_instance, "lastKnownLocation").append(str(row['LastKnownLocation']))
 
     # For functional properties, you can assign directly
-    #asset_instance.name = str(row['Name'])  # Assuming 'name' is a functional property
-    #asset_instance.AssetID = str(row['AssetID'])  # Assuming 'AssetID' is a functional property
-
+    asset_instance.name = str(row['Name'])  # Assuming 'name' is a functional property
+    asset_instance.AssetID = str(row['AssetID'])  # Assuming 'AssetID' is a functional property
 
+# Function to create instances of RiskManagementCases
 def create_risk_management_cases(n_instances):
-    RiskManagementCases = onto.search_one(iri="http://FYP-ASHS21/csonto#RiskManagementCases")
+    risk_management_cases = onto.search_one(iri="http://FYP-ASHS21/csonto#RiskManagementCases")
 
     for i in range(n_instances):
-        new_case = RiskManagementCases(f"RiskManagementCase_{uuid.uuid4()}")
+        new_case = risk_management_cases(f"RiskManagementCase_{uuid.uuid4()}")
 
         # Assuming CaseID and other properties can have only a single value per individual
         # and are correctly modeled as functional properties in your ontology
         new_case.CaseID.append(str(uuid.uuid4()))
+
          # Single value for functional property
         new_case.CaseName.append(f"CaseName_{i}")
         new_case.Consequences.append(random.choice(["Low", "Medium", "High"]))
@@ -76,7 +84,7 @@ def create_risk_management_cases(n_instances):
         new_case.RiskSolutions.append(f"Solution_{random.randint(1, 3)}")
 
 
-
+# Function to create instances of VulnerabilityList and PatchList
 def create_mock_data(num_vulnerabilities=100, num_patches=35):
     # Create Vulnerability instances
     for i in range(1, num_vulnerabilities + 1):
@@ -115,8 +123,8 @@ def create_mock_data(num_vulnerabilities=100, num_patches=35):
             else:
                 vulnerability.hasPatch.append(patch)
 
-
-create_mock_data()
 # Call the function to create mock
+create_mock_data()
+
 # Save the updated ontology
 onto.save(file="/workspaces/csonto/dashboards/csonto-edit.rdf")