Parsing metrics for the dynamics component

ERFormatConstants.py

 #File contains constants from the CSV export format of the entity relationship tool
 
 #Generic fields for all rows in the CSV file  
-componentID = "Id"              # LucidChart ID 
 Id = "Id"                       # The id of the entity 
 
 textArea1 = "Text Area 1"
@@ -76,3 +75,4 @@ ThreatDynamic = "Threat"                 # The threat dynamics
 ConsequenceDynamic = "Consequence"       # The consequence dynamics
 AttackDynamic = "Attack"                 # The attack dynamics
 ERDynamic = "ER"                         # The ER dynamics
+BowtieDynamicType = textArea3                 # The bowtie dynamics

diagramParser.py

@@ -21,6 +21,7 @@ def parseDiagramFile(csvFile):
     #List containing all attacks
     attacks = []
     
+        
     parseDynamic(df)
     
     
@@ -68,29 +69,46 @@ def parseAttacks(df, attackDict):
     return attackDict
         
 #Parses metrics components and adds it to list
-def parseDynamic(df):
+def parseDynamic(df, metricList):
     for i in range(len(df)):                                            # Iterates through the dataframe
         if df[const.textArea1][i] == const.Dynamics:                    # If the component is a dynamic component
             
             if df[const.textArea3][i] == const.ThreatDynamic:           # If the dynamic component is a threat
-                print("Found threat dynamic")
+                threatDynamic = dynamic.BowtieDynamic(
+                    df[const.Id][i],                                    # Component ID LucidChart
+                    df[const.textArea3][i]
+                )
+                extractMetrics(df, i, 4)
+    
+                
             elif df[const.textArea3][i] == const.ConsequenceDynamic:
-                print("Found consequence dynamic") 
+                consequenceDynamic = dynamic.BowtieDynamic()
+                extractMetrics(df, i, 4)
+                
             elif df[const.textArea3][i] == const.AttackDynamic:
-                print("Found attack dynamic")
+                attackDynamic = dynamic.BowtieDynamic()
+                extractMetrics(df, i, 4)
                                                     
             elif df[const.textArea3][i] == const.ERDynamic:
-                print("Found ER dynamic")
-                
-                for j in range(8, len(df.columns),2):                         # Parse all text areas to find metrics 
-                    metric = "Text Area "+str(j)
-                    metricDescription = "Text Area "+str(j+1)
-                    if pd.isnull(df[metric][i]) == False:             # If the text area is not
-                        print(df["Id"][i])
-                        print(f"Found Metric with type: {df[metric][i]}")
-                        print(f"Metric description: {df[metricDescription][i]}")  
+                erDynamic = dynamic.ERDynamic()
+                extractMetrics(df, i, 8)
+
+def extractMetrics(df, index, startRange, metricList):
+    for j in range(startRange, len(df.columns),2):                   # Parse all text areas to find metrics 
+        metricID = "Text Area "+str(j)
+        metricName = "Text Area "+str(j+1)
+        
+        if pd.isnull(df[metric][index]) == False:               # If the text area is not empty
+            print("Metric: ID", df[metricID][index], "Name: ", df[metricName][index])
+            metric = dynamic.Metric(df[metricID][index], df[metricName][index])
+            metricList.append(metric)
         else:
+            j=0
             break                                           # First empty field indicates no more metrics
         
+        return metricList                                   # Returns metric found in the dynamic component
+        
+        
+
             
             

dynamics.py

@@ -3,7 +3,7 @@ import logging as log
 # Dynamics class parent class for both the bowtie dynamics and the architecture dynamics
 class DynamicComponent:
 
-    def __init__(self, componentID, type) -> None:
+    def __init__(self, componentID) -> None:
         self.componentID = componentID
         self.metrics = [Metric]             # List of metrics for the dynamic
         self.DynamicsRow = None             # The row in the dynamics table the dynamic is associated with
@@ -39,18 +39,25 @@ class DynamicComponent:
     
 #Metric class, will be used for all dynamics
 class Metric:
-    def __init__(self, name, type, description) -> None:
+    def __init__(self, ID, name) -> None:
+        
+        #Metrics found in the dynamics tables 
+        self.ID = ID                    # ID of the metric used to locate in dynamics matrics
         self.name = name                # Name of the metric
-        self.description = description  # Description of the metric
-        self.type = type                # Four types of dynamic metrics: process, devteam, opensource and vendor
+        
+                
+        # Metrics found in the metric table 
+        
+        
 
     def __str__(self) -> str:
         return f"Metric: {self.name}, {self.description}"
             
 class BowtieDynamic(DynamicComponent):
     def __init__(self, componentID, type) -> None:
-        super().__init__(componentID, type)
+        super().__init__(componentID)
         
+        self.type = type                # Type of dynamicM
         self.associatedThreat = None     # List of threats associated with the dynamic
         self.associatedAttack = None     # List of attacks associated with the dynamic
         

tempCodeRunnerFile.py

+i
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