import os import requests from bs4 import BeautifulSoup from urllib.parse import urljoin import pandas as pd import numpy as np import zipfile import textract import gradio as gr def scrape(url, excel_file, folder_name,progress=gr.Progress()): filenames = [] # Check if the excel_file argument is provided and if the file exists. if excel_file and os.path.exists(excel_file): try: df = pd.read_excel(excel_file) # If 'Actions' in df.columns and filter based on it, and construct URLs from 'TDoc' or 'URL' columns if 'Actions' in df.columns: df = df[df['Actions'] == 'x'] elif 'File' in df.columns: filenames = [f"{url}/{row['File']}.zip" for index, row in df.iterrows()] elif 'URL' in df.columns: filenames = df['URL'].tolist() except Exception as e: print(f"Error reading Excel file: {e}") # Optionally, handle the error or return a message if needed # If no Excel file is provided or found, or if it lacks 'TDoc'/'URL', the function can still continue with predefined URLs or other logic download_directory = folder_name if not os.path.exists(download_directory): os.makedirs(download_directory) if not filenames: print("No Excel file provided, or no valid URLs found in the file.") # You can either return here or continue with other predefined logic response = requests.get(url) # Analyser le contenu HTML de la page soup = BeautifulSoup(response.content, "html.parser") # Trouver tous les balises avec des attributs href (liens) links = soup.find_all("a", href=True) # Filtrer les liens se terminant par ".zip" zip_links = [link['href'] for link in links if link['href'].endswith('.zip')] download_num = 0 pourcentss = 0.1 # Télécharger chaque fichier zip for zip_link in zip_links: if download_num%10 == 0: pourcentss = pourcentss + download_num/500 progress(pourcentss,desc='Telechargement') download_num = 0 download_num+=1 # Construire l'URL absolue du fichier zip absolute_url = urljoin(url, zip_link) # Extraire le nom de fichier de l'URL filename = os.path.basename(absolute_url) # Chemin où le fichier sera enregistré save_path = os.path.join(download_directory, filename) # Envoyer une requête GET pour télécharger le fichier with requests.get(absolute_url, stream=True) as r: r.raise_for_status() with open(save_path, 'wb') as f: for chunk in r.iter_content(chunk_size=8192): f.write(chunk) else: # Proceed with downloading files using the filenames list for file_url in filenames: filename = os.path.basename(file_url) save_path = os.path.join(download_directory, filename) try: with requests.get(file_url, stream=True) as r: r.raise_for_status() with open(save_path, 'wb') as f: for chunk in r.iter_content(chunk_size=8192): f.write(chunk) except requests.exceptions.HTTPError as e: print(f"HTTP error occurred: {file_url}: {e}") return False, "Il n'y a pas de colonne action ou alors celle ci n'est pas bien écrite, format attendu: 'Actions'" return True, "Téléchargement terminé !" def extractZip(folder_name): # Répertoire où les fichiers zip sont déjà téléchargés download_directory = folder_name extract_directory = folder_name + " extraction" # Répertoire où le contenu des fichiers zip sera extrait # Extraire le contenu de tous les fichiers zip dans le répertoire de téléchargement for zip_file in os.listdir(download_directory): zip_path = os.path.join(download_directory, zip_file) # Vérifier si le fichier est un fichier zip if zip_file.endswith(".zip"): extract_dir = os.path.join(extract_directory, os.path.splitext(zip_file)[0]) # Supprimer l'extension .zip # Vérifier si le fichier zip existe if os.path.exists(zip_path): # Créer un répertoire pour extraire le contenu s'il n'existe pas if not os.path.exists(extract_dir): os.makedirs(extract_dir) # Extraire le contenu du fichier zip print(f"Extraction en cours pour {zip_file}") with zipfile.ZipFile(zip_path, 'r') as zip_ref: zip_ref.extractall(extract_dir) print(f"Extraction terminée pour {zip_file}") else: print(f"Fichier zip {zip_file} introuvable") print("Toutes les extractions sont terminées !") def excel3gpp(url): response = requests.get(url) response.raise_for_status() # This will raise an exception if there's an error # Use BeautifulSoup to parse the HTML content soup = BeautifulSoup(response.text, 'html.parser') # Look for Excel file links; assuming they have .xlsx or .xls extensions excel_links = [a['href'] for a in soup.find_all('a', href=True) if a['href'].endswith(('.xlsx', '.xls'))] # Download the first Excel file found (if any) if excel_links: excel_url = excel_links[0] # Assuming you want the first Excel file if not excel_url.startswith('http'): excel_url = os.path.join(url, excel_url) # Handle relative URLs # Download the Excel file excel_response = requests.get(excel_url) excel_response.raise_for_status() # Define the path where you want to save the file filename = excel_url.split('/')[-1] filepath = os.path.join('path_to_save_directory', filename) # Replace 'path_to_save_directory' with your desired path # Write the content of the Excel file to a local file # Write the content of the Excel file to a local file named 'guide.xlsx' filepath = 'guide.xlsx' # Directly specify the filename with open(filepath, 'wb') as f: f.write(excel_response.content) print(f'Excel file downloaded and saved as: {filepath}') def replace_line_breaks(text): return text.replace("\n", "/n") def remod_text(text): return text.replace("/n", "\n") def extractionPrincipale(url, excel_file=None,progress=gr.Progress()): folder_name = url.split("/")[-2] progress(0.1,desc='Telechargement') result, message = scrape(url, excel_file, folder_name) if result: print("Success:", message) else: return(None, message) progress(0.4,desc='Extraction') extractZip(folder_name) progress(0.5,desc='Extraction 2') excel3gpp(url) progress(0.6,desc='Mise en forme Excel') extract_directory = folder_name +" extraction" categories = { "Other": ["URL", "File", "Type", "Title", "Source", "Content"], "CR": ["URL", "File", "Type", "Title", "Source", "Content"], "pCR":["URL", "File", "Type", "Title", "Source", "Content"], "LS": ["URL", "File", "Type", "Title", "Source", "Content"], "WID": ["URL", "File", "Type", "Title", "Source", "Content"], "SID": ["URL", "File", "Type", "Title", "Source", "Content"], "DISCUSSION": ["URL", "File", "Type", "Title", "Source", "Content"], "pdf": ["URL", "File", "Type", "Title", "Source", "Content"], "ppt": ["URL", "File", "Type", "Title", "Source", "Content"], "pptx": ["URL", "File", "Type", "Title", "Source", "Content"] } nouv=0 num=0.6 data = [] errors_count = 0 pre_title_section = None for folder in os.listdir(extract_directory): folder_path = os.path.join(extract_directory, folder) if os.path.isdir(folder_path): for file in os.listdir(folder_path): num=num + nouv/400 progress(num,desc='Mise en forme Excel') nouv+=1 if file == "__MACOSX": continue file_path = os.path.join(folder_path, file) if file.endswith((".pptx", ".ppt", ".pdf", ".docx", ".doc", ".DOCX")): try: text = textract.process(file_path).decode('utf-8') except Exception as e: print(f"Error processing {file_path}: {e}") errors_count += 1 continue cleaned_text_lines = text.split('\n') cleaned_text = '\n'.join([line.strip('|').strip() for line in cleaned_text_lines if line.strip()]) title = "" debut = "" sections = cleaned_text.split("Title:") if len(sections) > 1: pre_title_section = sections[0].strip().split() title = sections[1].strip().split("\n")[0].strip() debut = sections[0].strip() category = "Other" if file.endswith(".pdf"): category = "pdf" elif file.endswith((".ppt", ".pptx")): category = "ppt" # assuming all ppt and pptx files go into the same category elif "CHANGE REQUEST" in debut: category = "CR" elif "Discussion" in title: category = "DISCUSSION" elif "WID" in title: category = "WID" elif "SID" in title: category = "SID" elif "LS" in title: category = "LS" elif pre_title_section and pre_title_section[-1] == 'pCR': category = "pCR" elif "Pseudo-CR" in title: category = "pCR" contenu = "" # This will hold the concatenated content for 'Contenu' column if category in categories: columns = categories[category] extracted_content = [] if category == "CR": reason_for_change = "" summary_of_change = "" if len(sections) > 1: reason_for_change = sections[1].split("Reason for change", 1)[-1].split("Summary of change")[0].strip() summary_of_change = sections[1].split("Summary of change", 1)[-1].split("Consequences if not")[0].strip() extracted_content.append(f"Reason for change: {reason_for_change}") extracted_content.append(f"Summary of change: {summary_of_change}") elif category == "pCR": if len(sections) > 1:# Handle 'pCR' category-specific content extraction pcr_specific_content = sections[1].split("Introduction", 1)[-1].split("First Change")[0].strip() extracted_content.append(f"Introduction: {pcr_specific_content}") elif category == "LS": overall_review = "" if len(sections) > 1: overall_review = sections[1].split("Overall description", 1)[-1].strip() extracted_content.append(f"Overall review: {overall_review}") elif category in ["WID", "SID"]: objective = "" start_index = cleaned_text.find("Objective") end_index = cleaned_text.find("Expected Output and Time scale") if start_index != -1 and end_index != -1: objective = cleaned_text[start_index + len("Objective"):end_index].strip() extracted_content.append(f"Objective: {objective}") elif category == "DISCUSSION": Discussion = "" extracted_text = replace_line_breaks(cleaned_text) start_index_doc_for = extracted_text.find("Document for:") if start_index_doc_for != -1: start_index_word_after_doc_for = start_index_doc_for + len("Document for:") end_index_word_after_doc_for = start_index_word_after_doc_for + extracted_text[start_index_word_after_doc_for:].find("/n") word_after_doc_for = extracted_text[start_index_word_after_doc_for:end_index_word_after_doc_for].strip() result_intro = '' result_conclusion = '' result_info = '' if word_after_doc_for.lower() == "discussion": start_index_intro = extracted_text.find("Introduction") end_index_intro = extracted_text.find("Discussion", start_index_intro) intro_text = "" if start_index_intro != -1 and end_index_intro != -1: intro_text = extracted_text[start_index_intro + len("Introduction"):end_index_intro].strip() result_intro = remod_text(intro_text) # Convert back line breaks else: result_intro = "Introduction section not found." # Attempt to find "Conclusion" start_index_conclusion = extracted_text.find("Conclusion", end_index_intro) end_index_conclusion = extracted_text.find("Proposal", start_index_conclusion if start_index_conclusion != -1 else end_index_intro) conclusion_text = "" if start_index_conclusion != -1 and end_index_conclusion != -1: conclusion_text = extracted_text[start_index_conclusion + len("Conclusion"):end_index_conclusion].strip() result_conclusion = remod_text(conclusion_text) elif start_index_conclusion == -1: # Conclusion not found, look for Proposal directly start_index_proposal = extracted_text.find("Proposal", end_index_intro) if start_index_proposal != -1: end_index_proposal = len(extracted_text) # Assuming "Proposal" section goes till the end if present proposal_text = extracted_text[start_index_proposal + len("Proposal"):end_index_proposal].strip() result_conclusion = remod_text(proposal_text) # Using "Proposal" content as "Conclusion" else: result_conclusion = "Conclusion/Proposal section not found." else: # Handle case where "Conclusion" exists but no "Proposal" to mark its end conclusion_text = extracted_text[start_index_conclusion + len("Conclusion"):].strip() result_conclusion = remod_text(conclusion_text) Discussion=f"Introduction: {result_intro}\nConclusion/Proposal: {result_conclusion}" elif word_after_doc_for.lower() == "information": start_index_info = extracted_text.find(word_after_doc_for) if start_index_info != -1: info_to_end = extracted_text[start_index_info + len("Information"):].strip() result_info = remod_text(info_to_end) Discussion = f"Discussion:{result_info}" else: Discussion = "The word after 'Document for:' is not 'Discussion', 'DISCUSSION', 'Information', or 'INFORMATION'." else: Discussion = "The phrase 'Document for:' was not found." # Since DISCUSSION category handling requires more specific processing, adapt as necessary # Here's a simplified example discussion_details = Discussion extracted_content.append(discussion_details) # Add more categories as needed contenu = "\n".join(extracted_content) # Assuming 'source' needs to be filled from the guide.xlsx mapping # Placeholder for source value calculation source = "" # Update this with actual source determination logic status = "" data.append([url+ "/" + folder + '.zip', folder , category, title, source,status, contenu]) # After processing all files and directories # Read the guide.xlsx file into a DataFrame to map 'TDoc' to 'Source' guide_df = pd.read_excel('guide.xlsx', usecols=['Source', 'TDoc','TDoc Status']) tdoc_source_map = {row['TDoc']: row['Source'] for index, row in guide_df.iterrows()} tdoc_status_map = {row['TDoc']: row['TDoc Status'] for index, row in guide_df.iterrows()} # Update the 'Source' in your data based on matching 'Nom du fichier' with 'TDoc' for item in data: nom_du_fichier = item[1] # Assuming 'Nom du fichier' is the first item in your data list if nom_du_fichier in tdoc_source_map: item[4] = tdoc_source_map[nom_du_fichier] # Update the 'Source' field, assuming it's the fourth item item[5] = tdoc_status_map[nom_du_fichier] new_df_columns = ["URL", "File", "Type", "Title", "Source", "Status", "Content"] # Create a DataFrame with the updated data new_df = pd.DataFrame(data, columns=new_df_columns) try: old_df = pd.read_excel(excel_file) # Check if 'Actions' column exists in the old DataFrame if 'Actions' in old_df.columns: # Assuming you want to update 'Content' in old_df for matching 'TDoc' values in 'File' for index, new_row in new_df.iterrows(): # Find matching rows in old_df where 'TDoc' matches 'File' from new_df match_indices = old_df[old_df['TDoc'] == new_row['File']].index # Update 'Content' in old_df for matching rows for i in match_indices: old_df.at[i, 'Content'] = new_row['Content'] old_df.at[i, 'URL'] = new_row['URL'] df = old_df ###placer la colonne content en 4eme position # current_columns = df.columns.tolist() # current_columns.remove('URL') # # Insert 'Content' at the desired position # new_columns_order = current_columns[:1] + ['URL'] + current_columns[3:] # df = df[new_columns_order] else: # If 'Actions' column doesn't exist, simply concatenate the DataFrames df = pd.concat([old_df, new_df], axis=0, ignore_index=True) except Exception as e: print("The provided excel file seems invalid:", e) df = new_df file_name = url.split("/")[-2] + ".xlsx" # Save the updated DataFrame to Excel df.to_excel(file_name, index=False) return file_name, "Téléchargement réussi"