ETSISpecSplitter / spec_indexer_multi_doc.py
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First version
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import datetime
import time
import sys
import json
import traceback
import requests
import zipfile
import uuid
import os
import re
import subprocess
import concurrent.futures
import threading
from io import StringIO, BytesIO
from typing import List, Dict, Any
import pandas as pd
import numpy as np
import warnings
warnings.filterwarnings("ignore")
# Caractères pour le formatage des versions
chars = "0123456789abcdefghijklmnopqrstuvwxyz"
# Verrous pour les opérations thread-safe
print_lock = threading.Lock()
dict_lock = threading.Lock()
scope_lock = threading.Lock()
# Dictionnaires globaux
indexed_specifications = {}
documents_by_spec_num = {}
processed_count = 0
total_count = 0
def get_text(specification: str, version: str):
"""Récupère les bytes du PDF à partir d'une spécification et d'une version."""
doc_id = specification
series = doc_id.split(".")[0]
response = requests.get(
f"https://www.3gpp.org/ftp/Specs/archive/{series}_series/{doc_id}/{doc_id.replace('.', '')}-{version}.zip",
verify=False,
headers={"User-Agent": 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'}
)
if response.status_code != 200:
raise Exception(f"Téléchargement du ZIP échoué pour {specification}-{version}")
zip_bytes = BytesIO(response.content)
with zipfile.ZipFile(zip_bytes) as zf:
for file_name in zf.namelist():
if file_name.endswith("zip"):
print("Another ZIP !")
zip_bytes = BytesIO(zf.read(file_name))
zf = zipfile.ZipFile(zip_bytes)
for file_name2 in zf.namelist():
if file_name2.endswith("doc") or file_name2.endswith("docx"):
if "cover" in file_name2.lower():
print("COVER !")
continue
ext = file_name2.split(".")[-1]
doc_bytes = zf.read(file_name2)
temp_id = str(uuid.uuid4())
input_path = f"/tmp/{temp_id}.{ext}"
output_path = f"/tmp/{temp_id}.txt"
with open(input_path, "wb") as f:
f.write(doc_bytes)
subprocess.run([
"libreoffice",
"--headless",
"--convert-to", "txt",
"--outdir", "/tmp",
input_path
], check=True)
with open(output_path, "r") as f:
txt_data = [line.strip() for line in f if line.strip()]
os.remove(input_path)
os.remove(output_path)
return txt_data
elif file_name.endswith("doc") or file_name.endswith("docx"):
if "cover" in file_name.lower():
print("COVER !")
continue
ext = file_name.split(".")[-1]
doc_bytes = zf.read(file_name)
temp_id = str(uuid.uuid4())
input_path = f"/tmp/{temp_id}.{ext}"
output_path = f"/tmp/{temp_id}.txt"
print("Ecriture")
with open(input_path, "wb") as f:
f.write(doc_bytes)
print("Convertissement")
subprocess.run([
"libreoffice",
"--headless",
"--convert-to", "txt",
"--outdir", "/tmp",
input_path
], check=True)
print("Ecriture TXT")
with open(output_path, "r", encoding="utf-8") as f:
txt_data = [line.strip() for line in f if line.strip()]
os.remove(input_path)
os.remove(output_path)
return txt_data
raise Exception(f"Aucun fichier .doc/.docx trouvé dans le ZIP pour {specification}-{version}")
def get_spec_content(specification: str, version: str):
text = get_text(specification, version)
forewords = []
for x in range(len(text)):
line = text[x]
if "Foreword" in line:
forewords.append(x)
if len(forewords) >= 2:
break
toc_brut = text[forewords[0]:forewords[1]]
chapters = []
for line in toc_brut:
x = line.split("\t")
if re.search(r"^\d+\t[\ \S]+", line):
chapters.append(x[0] if len(x) == 1 else "\t".join(x[:2]))
if re.search(r"^\d+\.\d+\t[\ \S]+", line):
chapters.append(x[0] if len(x) == 1 else "\t".join(x[:2]))
if re.search(r"^\d+\.\d+\.\d+\t[\ \S]+", line):
chapters.append(x[0] if len(x) == 1 else "\t".join(x[:2]))
if re.search(r"^\d+\.\d+\.\d+.\d+\t[\ \S]+", line):
chapters.append(x[0] if len(x) == 1 else "\t".join(x[:2]))
if re.search(r"^\d+\.\d+\.\d+.\d+.\d+\t[\ \S]+", line):
chapters.append(x[0] if len(x) == 1 else "\t".join(x[:2]))
real_toc_indexes = {}
for chapter in chapters:
try:
x = text.index(chapter)
real_toc_indexes[chapter] = x
except ValueError as e:
try:
number = chapter.split("\t")[0] + "\t"
for line in text[forewords[1]:]:
if number in line:
x = text.index(line)
real_toc_indexes[line] = x
break
except:
real_toc_indexes[chapter] = -float("inf")
document = {}
toc = list(real_toc_indexes.keys())
index_toc = list(real_toc_indexes.values())
curr_index = 0
for x in range(1, len(toc)):
document[toc[curr_index].replace("\t", " ")] = re.sub(r"[\ \t]+", " ", "\n".join(text[index_toc[curr_index]+1:index_toc[x]]))
curr_index = x
document[toc[curr_index].replace("\t"," ")] = re.sub(r"\s+", " ", " ".join(text[index_toc[curr_index]+1:]))
return document
def process_specification(spec: Dict[str, Any], columns: List[str]) -> None:
"""Traite une spécification individuelle avec multithreading."""
global processed_count, indexed_specifications, documents_by_spec_num
try:
if spec.get('vers', None) is None:
return
doc_id = str(spec["spec_num"])
series = doc_id.split(".")[0]
a, b, c = str(spec["vers"]).split(".")
# Formatage de l'URL selon la version
if not (int(a) > 35 or int(b) > 35 or int(c) > 35):
version_code = f"{chars[int(a)]}{chars[int(b)]}{chars[int(c)]}"
spec_url = f"https://www.3gpp.org/ftp/Specs/archive/{series}_series/{doc_id}/{doc_id.replace('.', '')}-{version_code}.zip"
else:
x, y, z = str(a), str(b), str(c)
while len(x) < 2:
x = "0" + x
while len(y) < 2:
y = "0" + y
while len(z) < 2:
z = "0" + z
version_code = f"{x}{y}{z}"
spec_url = f"https://www.3gpp.org/ftp/Specs/archive/{series}_series/{doc_id}/{doc_id.replace('.', '')}-{version_code}.zip"
string = f"{spec['spec_num']}+-+{spec['title']}+-+{spec['type']}+-+{spec['vers']}+-+{spec['WG']}+-+Rel-{spec['vers'].split('.')[0]}"
metadata = {
"id": str(spec["spec_num"]),
"title": spec["title"],
"type": spec["type"],
"release": str(spec["vers"].split(".")[0]),
"version": str(spec["vers"]),
"working_group": spec["WG"],
"url": spec_url
}
# Vérification si le scope existe déjà pour ce numéro de spécification
spec_num = str(spec["spec_num"])
with scope_lock:
if spec_num in documents_by_spec_num:
# Réutilisation du scope existant
metadata["content"] = documents_by_spec_num[spec_num]
with print_lock:
print(f"\nRéutilisation du document (dernier release) pour {spec_num}")
else:
# Extraction du scope seulement si nécessaire
if not (int(a) > 35 or int(b) > 35 or int(c) > 35):
version_for_document = f"{chars[int(a)]}{chars[int(b)]}{chars[int(c)]}"
else:
version_for_document = version_code
with print_lock:
print(f"\nExtraction du contenu pour {spec_num} (version {version_for_document})")
try:
document = get_spec_content(metadata["id"], version_for_document)
documents_by_spec_num[spec_num] = document
metadata["content"] = document
except Exception as e:
error_msg = f"Erreur lors de l'extraction du scope: {str(e)}"
metadata["content"] = error_msg
documents_by_spec_num[spec_num] = error_msg
# Mise à jour du dictionnaire global avec verrou
with dict_lock:
indexed_specifications[string] = metadata
processed_count += 1
# Affichage de la progression avec verrou
with print_lock:
sys.stdout.write(f"\rTraitement: {processed_count}/{total_count} spécifications")
sys.stdout.flush()
except Exception as e:
with print_lock:
print(f"\nErreur lors du traitement de {spec.get('spec_num', 'inconnu')}: {str(e)}")
def main():
global total_count
start_time = time.time()
# Récupération des spécifications depuis le site 3GPP
print("Récupération des spécifications depuis 3GPP...")
response = requests.get(
f'https://www.3gpp.org/dynareport?code=status-report.htm',
headers={"User-Agent": 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'},
verify=False
)
# Analyse des tableaux HTML
dfs = pd.read_html(
StringIO(response.text),
storage_options={'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'},
encoding="utf-8"
)
for x in range(len(dfs)):
dfs[x] = dfs[x].replace({np.nan: None})
# Extraction des colonnes nécessaires
columns_needed = [0, 1, 2, 3, 4]
extracted_dfs = [df.iloc[:, columns_needed] for df in dfs]
columns = [x.replace("\xa0", "_") for x in extracted_dfs[0].columns]
# Préparation des spécifications
specifications = []
for df in extracted_dfs:
for index, row in df.iterrows():
doc = row.to_list()
doc_dict = dict(zip(columns, doc))
specifications.append(doc_dict)
total_count = len(specifications)
print(f"Traitement de {total_count} spécifications avec multithreading...")
try:
# Vérification si un fichier de documents existe déjà
if os.path.exists("indexed_docs_content.zip"):
with zipfile.ZipFile(open("indexed_docs_content.zip", "rb")) as zf:
for file_name in zf.namelist():
if file_name.endswith(".json"):
doc_bytes = zf.read(file_name)
global documents_by_spec_num
documents_by_spec_num = json.loads(doc_bytes.decode("utf-8"))
print(f"Chargement de {len(documents_by_spec_num)} documents depuis le cache.")
# Utilisation de ThreadPoolExecutor pour le multithreading
with concurrent.futures.ThreadPoolExecutor(max_workers=100) as executor:
futures = [executor.submit(process_specification, spec, columns) for spec in specifications]
concurrent.futures.wait(futures)
finally:
# Sauvegarde des résultats
result = {
"specs": indexed_specifications,
"last_indexed_date": datetime.datetime.today().strftime("%d-%m-%Y")
}
with open("indexed_documents.json", "w", encoding="utf-8") as f:
json.dump(documents_by_spec_num, f, indent=4, ensure_ascii=False)
with open("indexed_specifications.json", "w", encoding="utf-8") as f:
json.dump(result, f, indent=4, ensure_ascii=False)
elapsed_time = time.time() - start_time
print(f"\nTraitement terminé en {elapsed_time:.2f} secondes")
print(f"Résultats sauvegardés dans indexed_specifications.json")
if __name__ == "__main__":
main()