Spaces:
Running
Running
File size: 10,969 Bytes
7fcb613 a49b92f 7fcb613 a49b92f 7fcb613 a49b92f 7fcb613 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 |
import os
import time
import warnings
from dotenv import load_dotenv
import numpy as np
import requests
import pandas as pd
warnings.filterwarnings("ignore")
os.environ["CURL_CA_BUNDLE"] = ""
load_dotenv()
from huggingface_hub import configure_http_backend
def backend_factory() -> requests.Session:
session = requests.Session()
session.verify = False
return session
configure_http_backend(backend_factory=backend_factory)
from datasets import load_dataset, Dataset
from datasets.data_files import EmptyDatasetError
import threading
import zipfile
import sys
import fitz
import re
import json
import traceback
import io
import concurrent.futures
import hashlib
CHARS = "0123456789abcdefghijklmnopqrstuvwxyz"
DICT_LOCK = threading.Lock()
DOCUMENT_LOCK = threading.Lock()
STOP_EVENT = threading.Event()
documents_by_spec_num = {}
try:
spec_contents = load_dataset("OrganizedProgrammers/ETSISpecContent", token=os.environ.get("HF_TOKEN"))
spec_contents = spec_contents["train"].to_list()
for section in spec_contents:
if section["doc_id"] not in documents_by_spec_num.keys():
documents_by_spec_num[section["doc_id"]] = {"content": {section["section"]: section["content"]}, "hash": section["hash"]}
else:
documents_by_spec_num[section["doc_id"]]["content"][section["section"]] = section["content"]
except EmptyDatasetError as e:
print("Base de données vide !")
indexed_specifications = {}
specifications_passed = set()
processed_count = 0
total_count = 0
session = requests.Session()
req = session.post("https://portal.etsi.org/ETSIPages/LoginEOL.ashx", verify=False, headers={"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/136.0.0.0 Safari/537.36"}, data=json.dumps({"username": os.environ.get("EOL_USER"), "password": os.environ.get("EOL_PASSWORD")}))
print("Récupération des spécifications depuis ETSI...", req.status_code)
url_ts = "https://www.etsi.org/?option=com_standardssearch&view=data&format=csv&includeScope=1&page=1&search=&title=1&etsiNumber=1&content=0&version=0&onApproval=0&published=1&withdrawn=0&historical=0&isCurrent=1&superseded=0&harmonized=0&keyword=&TB=&stdType=TS&frequency=&mandate=&collection=&sort=1"
url_tr = url_ts.replace("stdType=TS", "stdType=TR")
data_ts = requests.get(url_ts, verify=False).content
data_tr = requests.get(url_tr, verify=False).content
df_ts = pd.read_csv(io.StringIO(data_ts.decode('utf-8')), sep=";", skiprows=1, index_col=False)
df_tr = pd.read_csv(io.StringIO(data_tr.decode('utf-8')), sep=";", skiprows=1, index_col=False)
backup_ts = df_ts["ETSI deliverable"]
backup_tr = df_tr["ETSI deliverable"]
df_ts["ETSI deliverable"] = df_ts["ETSI deliverable"].str.extract(r"\s*ETSI TS (\d+ \d+(?:-\d+(?:-\d+)?)?)")
df_tr["ETSI deliverable"] = df_tr["ETSI deliverable"].str.extract(r"\s*ETSI TR (\d+ \d+(?:-\d+(?:-\d+)?)?)")
version1 = backup_ts.str.extract(r"\s*ETSI TS \d+ \d+(?:-\d+(?:-\d+)?)? V(\d+\.\d+\.\d+)")
version2 = backup_tr.str.extract(r"\s*ETSI TR \d+ \d+(?:-\d+(?:-\d+)?)? V(\d+\.\d+\.\d+)")
df_ts["Version"] = version1[0]
df_tr["Version"] = version2[0]
def ver_tuple(v):
return tuple(map(int, v.split(".")))
df_ts["temp"] = df_ts["Version"].apply(ver_tuple)
df_tr["temp"] = df_tr["Version"].apply(ver_tuple)
df_ts["Type"] = "TS"
df_tr["Type"] = "TR"
df = pd.concat([df_ts, df_tr])
unique_df = df.loc[df.groupby("ETSI deliverable")["temp"].idxmax()]
unique_df = unique_df.drop(columns="temp")
unique_df = unique_df[(~unique_df["title"].str.contains("3GPP", case=True, na=False))]
df = df.drop(columns="temp")
df = df[(~df["title"].str.contains("3GPP", case=True, na=False))]
def get_text(specification: str):
if STOP_EVENT.is_set():
return None, []
print(f"\n[INFO] Tentative de récupération de la spécification {specification}", flush=True)
response = session.get(
unique_df[unique_df["ETSI deliverable"] == specification].iloc[0]["PDF link"],
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:
print(f"\n[ERREUR] Echec du téléchargement du PDF pour {specification}. {req.status_code}", flush=True)
return None, []
pdf = fitz.open(stream=response.content, filetype="pdf")
return pdf, pdf.get_toc()
def get_spec_content(specification: str):
def extract_sections(text, titles):
sections = {}
# On trie les titres selon leur position dans le texte
sorted_titles = sorted(titles, key=lambda t: text.find(t))
for i, title in enumerate(sorted_titles):
start = text.find(title)
if i + 1 < len(sorted_titles):
end = text.find(sorted_titles[i + 1])
sections[re.sub(r"\s+", " ", title)] = re.sub(r"\s+", " ", text[start:end].replace(title, "").strip().rstrip())
else:
sections[re.sub(r"\s+", " ", title)] = re.sub(r"\s+", " ", text[start:].replace(title, "").strip().rstrip())
return sections
if STOP_EVENT.is_set():
return {}
print("\n[INFO] Tentative de récupération du texte", flush=True)
pdf, doc_toc = get_text(specification)
text = []
first = 0
for level, title, page in doc_toc:
first = page - 1
break
for page in pdf[first:]:
text.append("\n".join([line.strip() for line in page.get_text().splitlines()]))
text = "\n".join(text)
if not text or STOP_EVENT.is_set() or not doc_toc:
print("\n[ERREUR] Pas de texte/table of contents trouvé !")
return {}
print(f"\n[INFO] Texte {specification} récupéré", flush=True)
titles = []
for level, title, page in doc_toc:
if STOP_EVENT.is_set():
return {}
if title[0].isnumeric() and '\n'.join(title.strip().split(" ", 1)) in text:
titles.append('\n'.join(title.strip().split(" ", 1)))
return extract_sections(text, titles)
def hasher(specification: str, version: str):
return hashlib.md5(f"{specification}{version}".encode()).hexdigest()
def get_scope(content):
for title, text in content.items():
if title.lower().endswith("scope"):
return text
return ""
def process_specification(spec):
global processed_count, indexed_specifications, documents_by_spec_num
if STOP_EVENT.is_set():
return
try:
version = spec.get('Version')
if not version: return
doc_id = str(spec.get("ETSI deliverable"))
document = None
with DOCUMENT_LOCK:
if doc_id in documents_by_spec_num and documents_by_spec_num[doc_id]["hash"] == hasher(doc_id, version) and not doc_id in specifications_passed:
document = documents_by_spec_num[doc_id]
specifications_passed.add(doc_id)
print(f"\n[INFO] Document déjà présent pour {doc_id} (version {spec['Version']})", flush=True)
elif doc_id in specifications_passed:
document = documents_by_spec_num[doc_id]
print(f"\n[INFO] Document déjà présent pour {doc_id} [dernière version présent]")
else:
print(f"\n[INFO] Tentative de récupération du document {doc_id} (version {spec['Version']})", flush=True)
document = get_spec_content(doc_id)
if document:
documents_by_spec_num[doc_id] = {"content": document, "hash": hasher(doc_id, version)}
document = {"content": document, "hash": hasher(doc_id, version)}
specifications_passed.add(doc_id)
print(f"\n[INFO] Document extrait pour {doc_id} (version {spec['Version']})", flush=True)
string_key = f"{doc_id}+-+{spec['title']}+-+{spec['Type']}+-+{spec['Version']}"
metadata = {
"id": str(doc_id),
"title": spec["title"],
"type": spec["Type"],
"version": version,
"url": spec["PDF link"],
"scope": "" if not document else get_scope(document["content"])
}
with DICT_LOCK:
indexed_specifications[string_key] = metadata
processed_count += 1
sys.stdout.write(f"\rTraitement: {processed_count}/{total_count} spécifications...")
sys.stdout.flush()
except Exception as e:
traceback.print_exception(e)
print(f"\n[ERREUR] Échec du traitement de {doc_id} {version}: {e}", flush=True)
def sauvegarder(indexed_specifications, documents_by_spec_num):
print("\nSauvegarde en cours...", flush=True)
flat_metadata = [metadata for _, metadata in indexed_specifications.items()]
flat_docs = []
for doc_id, data in documents_by_spec_num.items():
for title, content in data["content"].items():
flat_docs.append({"hash": data["hash"], "doc_id": doc_id, "section": title, "content": content})
push_spec_content = Dataset.from_list(flat_docs)
push_spec_metadata = Dataset.from_list(flat_metadata)
push_spec_content.push_to_hub("OrganizedProgrammers/ETSISpecContent", token=os.environ["HF_TOKEN"])
push_spec_metadata.push_to_hub("OrganizedProgrammers/ETSISpecMetadata", token=os.environ["HF_TOKEN"])
print("Sauvegarde terminée.", flush=True)
def main():
global total_count
start_time = time.time()
specifications = df.to_dict(orient="records")
total_count = len(specifications)
print(f"Traitement de {total_count} spécifications avec multithreading...")
try:
with concurrent.futures.ThreadPoolExecutor(max_workers=16) as executor:
futures = [executor.submit(process_specification, spec) for spec in specifications]
while True:
if all(f.done() for f in futures):
break
if STOP_EVENT.is_set():
break
time.sleep(0.35)
except Exception as e:
print(f"\nErreur inattendue dans le ThreadPool : {e}", flush=True)
print("\nSauvegarde des résultats...", flush=True)
sauvegarder(indexed_specifications, documents_by_spec_num)
elapsed_time = time.time() - start_time
print(f"\nTraitement terminé en {elapsed_time:.2f} secondes.", flush=True)
if __name__ == "__main__":
try:
main()
except KeyboardInterrupt:
print("\nInterruption détectée (Ctrl+C). Arrêt des tâches en cours...", flush=True)
STOP_EVENT.set()
time.sleep(2)
sauvegarder(indexed_specifications, documents_by_spec_num)
print("Arrêt propre du script.", flush=True)
sys.exit(0)
except Exception as e:
print(f"\nErreur inattendue : {e}", flush=True)
sauvegarder(indexed_specifications, documents_by_spec_num)
sys.exit(1)
# print(get_spec_content("188 005-1")) |