Update google_sheet_Legend.py

google_sheet_Legend.py

@@ -578,6 +578,7 @@ def deletefromlegend(deletedrows, SimilarAreaDictionarycopy, section, areaPermAr
     myDict = eval(SimilarAreaDictionarycopy)
     SimilarAreaDictionarycopy = pd.DataFrame(myDict)
     strings = deletedrows['content']
+    print('content',deletedrows)
     colors = deletedrows['color']
     indicies_toDelete=[]
     # print(colors)
@@ -601,18 +602,23 @@ def deletefromlegend(deletedrows, SimilarAreaDictionarycopy, section, areaPermAr
                
             # print('eee',existing_color,color)
             if is_color_within_tolerance(existing_color, color, tolerance):
-                # print(f'Color {color} found close to {existing_color} at index {idx}')
+                print(f'Color {color} found close to {existing_color} at index {idx}')
                 found = True
                 # print('strings',strings[j])
-                matchA = re.search(r"Area=(\d+\.\d+)", strings[j])
-                matchP = re.search(r"Perimeter=(\d+\.\d+)", strings[j])
-                matchL = re.search(r"Length=(\d+\.\d+)", strings[j])
+                # matchA = re.search(r"Area=(\d+\.\d+)", strings[j])
+                # matchP = re.search(r"Perimeter=(\d+\.\d+)", strings[j])
+
+
+                # else:
+                #   matchL = re.search(r"(\d+\.\d+)\s*m(?![a-zA-Z])", strings[j])
 
                 comment = SimilarAreaDictionarycopy.iloc[int(idx), SimilarAreaDictionarycopy.columns.get_loc('Comments')]
                 occ = SimilarAreaDictionarycopy.iloc[int(idx), SimilarAreaDictionarycopy.columns.get_loc('Occurences')]
 
                 # Only subtract area if the area value is found
-                if matchA:
+                if "Area" in deletedrows['subject'][j]:
+                    matchA = re.search(r"(\d+\.\d+)\s*sq\s*m",strings[j])
+                    print('matchA')
                     # print(' SimilarAreaDictionaryArea',  float(matchA.group(1)),   SimilarAreaDictionarycopy.iloc[int(idx), SimilarAreaDictionarycopy.columns.get_loc('Total Area')])
                     SimilarAreaDictionarycopy.iloc[int(idx), SimilarAreaDictionarycopy.columns.get_loc('Total Area')] =SimilarAreaDictionarycopy.iloc[int(idx), SimilarAreaDictionarycopy.columns.get_loc('Total Area')] - float(matchA.group(1))
                     # Update area occurrences
@@ -625,8 +631,9 @@ def deletefromlegend(deletedrows, SimilarAreaDictionarycopy, section, areaPermAr
                         perimeter_occurrences = SimilarAreaDictionarycopy.iloc[int(idx), SimilarAreaDictionarycopy.columns.get_loc('Occurences')]
 
                     SimilarAreaDictionarycopy.iloc[int(idx), SimilarAreaDictionarycopy.columns.get_loc('Comments')] = f'Area occurrences: {area_occurrences}, Perimeter occurrences: {perimeter_occurrences}'
-                if matchP:
-
+                if "Perimeter" in deletedrows['subject'][j]:
+                    matchP = re.search(r"(\d+\.\d+)\s*m(?![a-zA-Z])", strings[j])
+                    print('matchP')
                     SimilarAreaDictionarycopy.iloc[int(idx), SimilarAreaDictionarycopy.columns.get_loc('Total Perimeter')] =SimilarAreaDictionarycopy.iloc[int(idx), SimilarAreaDictionarycopy.columns.get_loc('Total Perimeter')]  - float(matchP.group(1))# Replace 'Area' with the actual column name
                     if pd.notna(comment) and 'Perimeter' in str(comment):
                       matches = re.findall(r'\b\d+\b', str(comment))
@@ -638,7 +645,8 @@ def deletefromlegend(deletedrows, SimilarAreaDictionarycopy, section, areaPermAr
                       perimeter_occurrences = SimilarAreaDictionarycopy.iloc[int(idx), SimilarAreaDictionarycopy.columns.get_loc('Occurences')]-1
                       # print(area_occurrences,perimeter_occurrences)
                       SimilarAreaDictionarycopy.iloc[int(idx), SimilarAreaDictionarycopy.columns.get_loc('Comments')] = f'Area occurrences: {area_occurrences}, Perimeter occurrences: {perimeter_occurrences}'
-                  
+                else:
+                      matchL = re.search(r"(\d+\.\d+)\s*m(?![a-zA-Z])", strings[j])