Standard_Intelligence_Dev / scrape_3gpp.py
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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
def scrape(url, excel_file, folder_name):
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')]
# Télécharger chaque fichier zip
for zip_link in zip_links:
# 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):
folder_name = url.split("/")[-2]
result, message = scrape(url, excel_file, folder_name)
if result:
print("Success:", message)
else:
return(None, message)
extractZip(folder_name)
excel3gpp(url)
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"]
}
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):
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"