Update InitialMarkups.py

InitialMarkups.py

@@ -1933,68 +1933,63 @@ def extract_section_under_header_tobebilled2marthe(multiplePDF_Paths):
     print(arrayofPDFS)
     df = pd.DataFrame(columns=["PDF Name","NBSLink","Subject","Page","Author","Creation Date","Layer",'Code', 'head above 1', "head above 2","BodyText"])
     for pdf_path in arrayofPDFS:
-        print(pdf_path)
         headertoContinue1 = False
         headertoContinue2=False
         Alltexttobebilled=''
-        
-
-        
         parsed_url = urlparse(pdf_path)
         filename = os.path.basename(parsed_url.path)
         filename = unquote(filename)  # decode URL-encoded characters
-        
-
+    
         # Optimized URL handling
         if pdf_path and ('http' in pdf_path or 'dropbox' in pdf_path):
             pdf_path = pdf_path.replace('dl=0', 'dl=1')
-
+    
         # Cache frequently used values
         response = requests.get(pdf_path)
         pdf_content = BytesIO(response.content)
         if not pdf_content:
             raise ValueError("No valid PDF content found.")
-
+    
         doc = fitz.open(stream=pdf_content, filetype="pdf")
         docHighlights = fitz.open(stream=pdf_content, filetype="pdf")
         most_common_font_size, most_common_color, most_common_font = get_regular_font_size_and_color(doc)
-
+    
         # Precompute regex patterns
         dot_pattern = re.compile(r'\.{3,}')
         url_pattern = re.compile(r'https?://\S+|www\.\S+')
-
+    
         def get_toc_page_numbers(doc, max_pages_to_check=15):
             toc_pages = []
             for page_num in range(min(len(doc), max_pages_to_check)):
                 page = doc.load_page(page_num)
                 blocks = page.get_text("dict")["blocks"]
-
+    
                 dot_line_count = 0
                 for block in blocks:
                     for line in block.get("lines", []):
                         line_text = get_spaced_text_from_spans(line["spans"]).strip()
                         if dot_pattern.search(line_text):
                             dot_line_count += 1
-
+    
                 if dot_line_count >= 3:
                     toc_pages.append(page_num)
-
+    
             return list(range(0, toc_pages[-1] +1)) if toc_pages else toc_pages
-
+    
         toc_pages = get_toc_page_numbers(doc)
-
+    
         headers, top_3_font_sizes, smallest_font_size, headersSpans = extract_headers(
             doc, toc_pages, most_common_font_size, most_common_color, most_common_font, top_margin, bottom_margin
         )
-
+    
         hierarchy = build_header_hierarchy(doc, toc_pages, most_common_font_size, most_common_color, most_common_font)
         listofHeaderstoMarkup = get_leaf_headers_with_paths(hierarchy)
         
         # Precompute all children headers once
         allchildrenheaders = [normalize_text(item['text']) for item, p in listofHeaderstoMarkup]
         allchildrenheaders_set = set(allchildrenheaders)  # For faster lookups
-
-        
+    
+        df = pd.DataFrame(columns=["NBSLink","Subject","Page","Author","Creation Date","Layer",'Code', 'head above 1', "head above 2","BodyText"])
         dictionaryNBS={}
         data_list_JSON = []
         currentgroupname=''
@@ -2004,16 +1999,16 @@ def extract_section_under_header_tobebilled2marthe(multiplePDF_Paths):
             mainHeaderFontSize= top_3_font_sizes[0]
             subHeaderFontSize= top_3_font_sizes[1]
             subsubheaderFontSize= top_3_font_sizes[1]
-
+    
         
-
+    
         # Preload all pages to avoid repeated loading
         # pages = [doc.load_page(page_num) for page_num in range(len(doc)) if page_num not in toc_pages]
-
+    
         for heading_to_searchDict, paths in listofHeaderstoMarkup:
             heading_to_search = heading_to_searchDict['text']
             heading_to_searchPageNum = heading_to_searchDict['page']
-
+    
             # Initialize variables
             headertoContinue1 = False
             headertoContinue2 = False
@@ -2031,45 +2026,45 @@ def extract_section_under_header_tobebilled2marthe(multiplePDF_Paths):
             heading_norm = normalize_text(heading_to_search)
             paths_norm = [normalize_text(p) for p in paths[0]] if paths and paths[0] else []
             for page_num in range(heading_to_searchPageNum,len(doc)):
-                # print(heading_to_search)
+                print(heading_to_search)
                 if paths[0].strip().lower() != currentgroupname.strip().lower():
                     Alltexttobebilled+= paths[0] +'\n'
                     currentgroupname=paths[0]
-                    # print(paths[0])
-
+                    print(paths[0])
+    
                     
                 if page_num in toc_pages:
-                    continue
+                  continue
                 if break_collecting:
                     break
                 page=doc[page_num]
                 page_height = page.rect.height
                 blocks = page.get_text("dict")["blocks"]
-
+    
                 for block in blocks:
                     if break_collecting:
                         break
-
+    
                     lines = block.get("lines", [])
                     i = 0
                     while i < len(lines):
                         if break_collecting:
                             break
-
+    
                         spans = lines[i].get("spans", [])
                         if not spans:
                             i += 1
                             continue
-
+    
                         y0 = spans[0]["bbox"][1]
                         y1 = spans[0]["bbox"][3]
                         if y0 < top_margin or y1 > (page_height - bottom_margin):
                             i += 1
                             continue
-
+    
                         line_text = get_spaced_text_from_spans(spans).lower()
                         line_text_norm = normalize_text(line_text)
-
+    
                         # Combine with next line if available
                         if i + 1 < len(lines):
                             next_spans = lines[i + 1].get("spans", [])
@@ -2077,7 +2072,7 @@ def extract_section_under_header_tobebilled2marthe(multiplePDF_Paths):
                             combined_line_norm = normalize_text(line_text + " " + next_line_text)
                         else:
                             combined_line_norm = line_text_norm
-
+    
                         # Check if we should continue processing
                         if combined_line_norm and combined_line_norm in paths[0]:
                             
@@ -2086,24 +2081,14 @@ def extract_section_under_header_tobebilled2marthe(multiplePDF_Paths):
                         
                             headertoContinue2 = combined_line_norm
                         # if  'installation' in paths[-2].lower() or 'execution' in paths[-2].lower() or 'miscellaneous items' in paths[-2].lower() :
-                        # last_path = paths[-2].lower()
-                        flagstring=False
-                        last_word = paths[-2].lower()
-                                        
+                        last_path = paths[-2].lower()
                         # if any(word in paths[-2].lower() for word in keywordstoSkip):
                         # if  'installation' in paths[-2].lower() or 'execution' in paths[-2].lower() or 'miscellaneous items' in paths[-2].lower() or 'workmanship' in paths[-2].lower() or 'testing' in paths[-2].lower() or 'labeling' in paths[-2].lower():
-                        # if any(keyword in last_word for keyword in keywords):
-                        # Precompile regex for faster repeated checks
-                        pattern = re.compile(r'installation|execution|miscellaneous items|workmanship|testing|labeling', re.IGNORECASE)
-
-                        if pattern.search(last_word):
-                            stringtowrite = 'Not to be billed'
-                            flagstring = False
+                        if any(keyword in last_path for keyword in keywords):
+                          stringtowrite='Not to be billed'
                         else:
-                            stringtowrite = 'To be billed'
-                            flagstring = True
-
-                        if flagstring:
+                          stringtowrite='To be billed'
+                        if stringtowrite=='To be billed':
                             # Alltexttobebilled+= combined_line_norm  #################################################
                             if matched_header_line_norm in combined_line_norm:
                                 Alltexttobebilled+='\n'
@@ -2113,12 +2098,12 @@ def extract_section_under_header_tobebilled2marthe(multiplePDF_Paths):
                             ( combined_line_norm in allchildrenheaders_set or
                             combined_line_norm in allchildrenheaders ) and heading_to_search in combined_line_norm
                         )
-
+    
                         # New word-based matching
                         current_line_words = set(combined_line_norm.split())
                         heading_words = set(heading_norm.split())
                         all_words_match = current_line_words.issubset(heading_words) and len(current_line_words) > 0
-
+    
                         substring_match = (
                             heading_norm in combined_line_norm or
                             combined_line_norm in heading_norm or
@@ -2128,10 +2113,10 @@ def extract_section_under_header_tobebilled2marthe(multiplePDF_Paths):
                         #     heading_norm in combined_line_norm or
                         #     combined_line_norm in heading_norm
                         # )
-
+    
                         if (substring_match and existsfull and not collecting and
                             len(combined_line_norm) > 0 ):#and (headertoContinue1 or headertoContinue2) ):
-
+    
                             # Check header conditions more efficiently
                             header_spans = [
                                 span for span in spans
@@ -2139,23 +2124,23 @@ def extract_section_under_header_tobebilled2marthe(multiplePDF_Paths):
                                     # and span['size'] >= subsubheaderFontSize
                                     and span['size'] < mainHeaderFontSize)
                             ]
-                            if header_spans and flagstring:
+                            if header_spans and stringtowrite.startswith('To'):
                                 collecting = True
                                 # if stringtowrite=='To be billed':
                                 #     Alltexttobebilled+='\n'
                                 matched_header_font_size = max(span["size"] for span in header_spans)
-
+    
                                 # collected_lines.append(line_text)
                                 valid_spans = [span for span in spans if span.get("bbox")]
-
+    
                                 if valid_spans:
                                     x0s = [span["bbox"][0] for span in valid_spans]
                                     x1s = [span["bbox"][2] for span in valid_spans]
                                     y0s = [span["bbox"][1] for span in valid_spans]
                                     y1s = [span["bbox"][3] for span in valid_spans]
-
+    
                                     header_bbox = [min(x0s), min(y0s), max(x1s), max(y1s)]
-
+    
                                     if page_num in current_bbox:
                                         cb = current_bbox[page_num]
                                         current_bbox[page_num] = [
@@ -2168,36 +2153,36 @@ def extract_section_under_header_tobebilled2marthe(multiplePDF_Paths):
                                         current_bbox[page_num] = header_bbox
                                     last_y1s[page_num] = header_bbox[3]
                                     x0, y0, x1, y1 = header_bbox
-
+    
                                     zoom = 200
                                     left = int(x0)
                                     top = int(y0)
                                     zoom_str = f"{zoom},{left},{top}"
                                     pageNumberFound = page_num + 1
-
-                                # Build the query parameters
+    
+                                  # Build the query parameters
                                     params = {
                                         'pdfLink': pdf_path,  # Your PDF link
                                         'keyword': heading_to_search,  # Your keyword (could be a string or list)
                                     }
-
+    
                                     # URL encode each parameter
                                     encoded_params = {key: urllib.parse.quote(value, safe='') for key, value in params.items()}
-
+    
                                     # Construct the final encoded link
                                     encoded_link = '&'.join([f"{key}={value}" for key, value in encoded_params.items()])
-
+    
                                     # Correctly construct the final URL with page and zoom
                                     final_url = f"{baselink}{encoded_link}#page={str(pageNumberFound)}&zoom={zoom_str}"
-
+    
                                     # Get current date and time
                                     now = datetime.now()
-
+    
                                     # Format the output
                                     formatted_time = now.strftime("%d/%m/%Y %I:%M:%S %p")
                                     # Optionally, add the URL to a DataFrame
-
-
+    
+    
                                     data_entry = {
                                             "PDF Name":filename,
                                             "NBSLink": final_url,
@@ -2213,22 +2198,22 @@ def extract_section_under_header_tobebilled2marthe(multiplePDF_Paths):
                                             "MC Connnection": 'Go to ' +  paths[0].strip().split()[0] +'/'+ heading_to_search.strip().split()[0] + ' in '+ filename
                                         }
                                     data_list_JSON.append(data_entry)
-
+    
                                     # Convert list to JSON
                                     json_output = json.dumps(data_list_JSON, indent=4)
-
+    
                                     i += 2
                                     continue
                         else:
                             if (substring_match and not collecting and
                                 len(combined_line_norm) > 0): # and (headertoContinue1 or headertoContinue2) ):
-
+    
                                 # Calculate word match percentage
                                 word_match_percent = words_match_ratio(heading_norm, combined_line_norm) * 100
-
+    
                                 # Check if at least 70% of header words exist in this line
                                 meets_word_threshold = word_match_percent >= 100
-
+    
                                 # Check header conditions (including word threshold)
                                 header_spans = [
                                     span for span in spans
@@ -2236,26 +2221,26 @@ def extract_section_under_header_tobebilled2marthe(multiplePDF_Paths):
                                         # and span['size'] >= subsubheaderFontSize
                                         and span['size'] < mainHeaderFontSize)
                                 ]
-
-                                if header_spans and (meets_word_threshold or same_start_word(heading_to_search, combined_line_norm) ) and flagstring:
+    
+                                if header_spans and (meets_word_threshold or same_start_word(heading_to_search, combined_line_norm) ) and stringtowrite.startswith('To'):
                                     collecting = True
-                                    if flagstring:
+                                    if stringtowrite=='To be billed':
                                         Alltexttobebilled+='\n'
                                     # if stringtowrite=='To be billed':
                                     #     Alltexttobebilled+= ' '+ combined_line_norm
                                     matched_header_font_size = max(span["size"] for span in header_spans)
-                                
+                                 
                                     collected_lines.append(line_text)
                                     valid_spans = [span for span in spans if span.get("bbox")]
-
+    
                                     if valid_spans:
                                         x0s = [span["bbox"][0] for span in valid_spans]
                                         x1s = [span["bbox"][2] for span in valid_spans]
                                         y0s = [span["bbox"][1] for span in valid_spans]
                                         y1s = [span["bbox"][3] for span in valid_spans]
-
+    
                                         header_bbox = [min(x0s), min(y0s), max(x1s), max(y1s)]
-
+    
                                         if page_num in current_bbox:
                                             cb = current_bbox[page_num]
                                             current_bbox[page_num] = [
@@ -2266,7 +2251,7 @@ def extract_section_under_header_tobebilled2marthe(multiplePDF_Paths):
                                             ]
                                         else:
                                             current_bbox[page_num] = header_bbox
-
+    
                                         last_y1s[page_num] = header_bbox[3]
                                         x0, y0, x1, y1 = header_bbox
                                         zoom = 200
@@ -2274,32 +2259,32 @@ def extract_section_under_header_tobebilled2marthe(multiplePDF_Paths):
                                         top = int(y0)
                                         zoom_str = f"{zoom},{left},{top}"
                                         pageNumberFound = page_num + 1
-
-                                    # Build the query parameters
+    
+                                      # Build the query parameters
                                         params = {
                                             'pdfLink': pdf_path,  # Your PDF link
                                             'keyword': heading_to_search,  # Your keyword (could be a string or list)
                                         }
-
+    
                                         # URL encode each parameter
                                         encoded_params = {key: urllib.parse.quote(value, safe='') for key, value in params.items()}
-
+    
                                         # Construct the final encoded link
                                         encoded_link = '&'.join([f"{key}={value}" for key, value in encoded_params.items()])
-
+    
                                         # Correctly construct the final URL with page and zoom
                                         final_url = f"{baselink}{encoded_link}#page={str(pageNumberFound)}&zoom={zoom_str}"
-
+    
                                         # Get current date and time
                                         now = datetime.now()
-
+    
                                         # Format the output
                                         formatted_time = now.strftime("%d/%m/%Y %I:%M:%S %p")
                                         # Optionally, add the URL to a DataFrame
-
-
+    
+    
                                         data_entry = {
-                                                "PDF Name": filename,
+                                                "PDF Name":filename,
                                                 "NBSLink": final_url,
                                                 "Subject": heading_to_search,
                                                 "Page": str(pageNumberFound),
@@ -2313,22 +2298,22 @@ def extract_section_under_header_tobebilled2marthe(multiplePDF_Paths):
                                                 "MC Connnection": 'Go to ' +  paths[0].strip().split()[0] +'/'+ heading_to_search.strip().split()[0] + ' in '+ filename
                                             }
                                         data_list_JSON.append(data_entry)
-
+    
                                         # Convert list to JSON
                                         json_output = json.dumps(data_list_JSON, indent=4)
-
+    
                     
                                         i += 2
                                         continue
                         if collecting:
                             norm_line = normalize_text(line_text)
-
+    
                             # Optimized URL check
                             if url_pattern.match(norm_line):
                                 line_is_header = False
                             else:
                                 line_is_header = any(is_header(span, most_common_font_size, most_common_color, most_common_font) for span in spans)
-
+    
                             if line_is_header:
                                 header_font_size = max(span["size"] for span in spans)
                                 is_probably_real_header = (
@@ -2336,26 +2321,26 @@ def extract_section_under_header_tobebilled2marthe(multiplePDF_Paths):
                                     is_header(spans[0], most_common_font_size, most_common_color, most_common_font) and
                                     len(line_text.strip()) > 2
                                 )
-
+    
                                 if (norm_line != matched_header_line_norm and
                                     norm_line != heading_norm and
                                     is_probably_real_header):
                                     if line_text not in heading_norm:
-                                        collecting = False
-                                        done = True
-                                        headertoContinue1 = False
-                                        headertoContinue2=False
-                                        for page_num, bbox in current_bbox.items():
-                                            bbox[3] = last_y1s.get(page_num, bbox[3])
-                                            page_highlights[page_num] = bbox
-                                        highlight_boxes(docHighlights, page_highlights,stringtowrite)
-
-                                        break_collecting = True
-                                        break
-
+                                      collecting = False
+                                      done = True
+                                      headertoContinue1 = False
+                                      headertoContinue2=False
+                                      for page_num, bbox in current_bbox.items():
+                                          bbox[3] = last_y1s.get(page_num, bbox[3])
+                                          page_highlights[page_num] = bbox
+                                      highlight_boxes(docHighlights, page_highlights,stringtowrite)
+    
+                                      break_collecting = True
+                                      break
+    
                             if break_collecting:
                                 break
-
+    
                             collected_lines.append(line_text)
                             valid_spans = [span for span in spans if span.get("bbox")]
                             if valid_spans:
@@ -2363,9 +2348,9 @@ def extract_section_under_header_tobebilled2marthe(multiplePDF_Paths):
                                 x1s = [span["bbox"][2] for span in valid_spans]
                                 y0s = [span["bbox"][1] for span in valid_spans]
                                 y1s = [span["bbox"][3] for span in valid_spans]
-
+    
                                 line_bbox = [min(x0s), min(y0s), max(x1s), max(y1s)]
-
+    
                                 if page_num in current_bbox:
                                     cb = current_bbox[page_num]
                                     current_bbox[page_num] = [
@@ -2376,30 +2361,25 @@ def extract_section_under_header_tobebilled2marthe(multiplePDF_Paths):
                                     ]
                                 else:
                                     current_bbox[page_num] = line_bbox
-
+    
                                 last_y1s[page_num] = line_bbox[3]
                         i += 1
-
+    
             if not done:
                 for page_num, bbox in current_bbox.items():
                     bbox[3] = last_y1s.get(page_num, bbox[3])
                     page_highlights[page_num] = bbox
-                if flagstring:
-                # if  'installation' in paths[-2].lower() or 'execution' in paths[-2].lower() or 'miscellaneous items' in paths[-2].lower() :
-                    stringtowrite='To be billed'
-                else:
+                if  'installation' in paths[-2].lower() or 'execution' in paths[-2].lower() or 'miscellaneous items' in paths[-2].lower() :
                     stringtowrite='Not to be billed'
+                else:
+                    stringtowrite='To be billed'
                 highlight_boxes(docHighlights, page_highlights,stringtowrite)
-
-    # docHighlights.save("highlighted_output.pdf", garbage=4, deflate=True)
-
-    pdf_bytes = BytesIO()
-    docHighlights.save(pdf_bytes)
-
-    return pdf_bytes.getvalue(), docHighlights , json_output, Alltexttobebilled , filename
-
-
-
-
-
-
+    
+        # docHighlights.save("highlighted_output.pdf", garbage=4, deflate=True)
+    
+        pdf_bytes = BytesIO()
+        docHighlights.save(pdf_bytes)
+    
+        return pdf_bytes.getvalue(), docHighlights , json_output, Alltexttobebilled , filename
+    
+