scrape_3gpp.py

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 <a> 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"