Domi31tls
8339069c83
- GUI v5 : vue unique épurée (tkinter), 2 étapes visuelles - Core ONNX : anonymisation regex + NER optionnel - Extraction globale des noms depuis champs structurés (Patient, Rédigé par, MME/Madame, DR) - Génération simultanée PDF Image + PDF Anonymisé (structure préservée) - Build Windows via Nuitka (script batch + GitHub Actions CI) - install.sh pour setup/run Linux Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
423 lines
16 KiB
Python
423 lines
16 KiB
Python
# ==========================
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# FILE 1/2 — anonymizer_core_refactored.py (FIXED)
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# ==========================
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from __future__ import annotations
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import io
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import json
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import re
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import List, Dict, Tuple, Optional, Any
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import pdfplumber
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from pdfminer.high_level import extract_text as pdfminer_extract_text
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from pdfminer.layout import LAParams
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from PIL import Image, ImageDraw
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# Optional deps
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try:
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import fitz # PyMuPDF
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except Exception:
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fitz = None
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try:
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import yaml # PyYAML for dictionaries
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except Exception:
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yaml = None
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# ----------------- Defaults & Config -----------------
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DEFAULTS_CFG = {
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"version": 1,
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"encoding": "utf-8",
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"normalization": "NFKC",
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"whitelist": {
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"sections_titres": ["DIM", "GHM", "GHS", "RUM", "COMPTE", "RENDU", "DIAGNOSTIC"],
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"noms_maj_excepts": ["Médecin DIM", "Praticien conseil"],
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"org_gpe_keep": True,
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},
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"blacklist": {
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"force_mask_terms": [],
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"force_mask_regex": [],
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},
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"kv_labels_preserve": ["FINESS", "IPP", "N° OGC", "Etablissement"],
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"regex_overrides": [
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{
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"name": "OGC_court",
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"pattern": r"\b(?:N°\s*)?OGC\s*[:\-]?\s*([A-Za-z0-9\-]{1,3})\b",
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"placeholder": "[OGC]",
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"flags": ["IGNORECASE"],
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}
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],
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"flags": {
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"case_insensitive": True,
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"unicode_word_boundaries": True,
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"regex_engine": "python",
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},
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}
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PLACEHOLDERS = {
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"EMAIL": "[EMAIL]",
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"TEL": "[TEL]",
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"IBAN": "[IBAN]",
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"NIR": "[NIR]",
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"IPP": "[IPP]",
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"FINESS": "[FINESS]",
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"OGC": "[OGC]",
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"NOM": "[NOM]",
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"VILLE": "[VILLE]",
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"ETAB": "[ETABLISSEMENT]",
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"MASK": "[MASK]",
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}
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CRITICAL_PII_KEYS = {"EMAIL", "TEL", "IBAN", "NIR", "IPP"}
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# Baseline regex
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RE_EMAIL = re.compile(r"[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}")
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RE_TEL = re.compile(r"(?<!\d)(?:\+33\s?|0)\d(?:[ .-]?\d){8}(?!\d)")
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RE_IBAN = re.compile(r"\b[A-Z]{2}\d{2}[A-Z0-9]{11,30}\b")
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RE_IPP = re.compile(r"\bIPP\s*[:\-]?\s*([A-Za-z0-9]{6,})\b", re.IGNORECASE)
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RE_FINESS = re.compile(r"\bFINESS\s*[:\-]?\s*(\d{9})\b", re.IGNORECASE)
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RE_OGC = re.compile(r"\b(?:N°\s*)?OGC\s*[:\-]?\s*([A-Za-z0-9\-]{1,})\b", re.IGNORECASE) # élargi
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RE_NIR = re.compile(r"\b(\d{13})\s*([0-9]{2})\b")
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RE_PERSON_CONTEXT = re.compile(
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r"(?:(?:Dr\.?|Docteur|Mme|M\.|Monsieur|Nom\s*:\s*|Praticien|Médecin)\s*)([A-ZÉÈÀÙÂÊÎÔÛÄËÏÖÜÇ\-\' ]{2,})"
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)
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SPLITTER = re.compile(r"\s*[:|;\t]\s*")
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@dataclass
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class PiiHit:
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page: int
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kind: str
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original: str
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placeholder: str
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bbox_hint: Optional[Tuple[float, float, float, float]] = None
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@dataclass
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class AnonResult:
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text_out: str
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tables_block: str
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audit: List[PiiHit] = field(default_factory=list)
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# ----------------- Config loader -----------------
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def load_dictionaries(config_path: Optional[Path]) -> Dict[str, Any]:
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cfg = DEFAULTS_CFG.copy()
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if config_path and config_path.exists() and yaml is not None:
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try:
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user = yaml.safe_load(config_path.read_text(encoding="utf-8")) or {}
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# shallow-merge for top-level keys
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for k, v in user.items():
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cfg[k] = v
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except Exception:
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pass
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return cfg
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# ----------------- Extraction -----------------
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def extract_text_two_passes(pdf_path: Path):
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pages_text: List[str] = []
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tables_lines: List[List[str]] = []
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with pdfplumber.open(pdf_path) as pdf:
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for p in pdf.pages:
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t = p.extract_text(x_tolerance=2.5, y_tolerance=4.0) or ""
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pages_text.append(t)
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rows: List[str] = []
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try:
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tables = p.extract_tables()
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for tbl in tables or []:
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for row in tbl:
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clean = [c if c is not None else "" for c in row]
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rows.append("\t".join(clean).strip())
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except Exception:
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pass
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tables_lines.append(rows)
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total_chars = sum(len(x or "") for x in pages_text)
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if total_chars < 500:
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text_all = pdfminer_extract_text(
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str(pdf_path),
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laparams=LAParams(char_margin=2.0, word_margin=0.1, line_margin=0.8, boxes_flow=0.5),
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)
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pages_text = [x for x in text_all.split("\f") if x]
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return pages_text, tables_lines
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# ----------------- Helpers (with dictionaries) -----------------
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def _compile_user_regex(pattern: str, flags_list: List[str]):
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flags = 0
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for f in flags_list or []:
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if f.upper() == "IGNORECASE":
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flags |= re.IGNORECASE
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if f.upper() == "MULTILINE":
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flags |= re.MULTILINE
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if f.upper() == "DOTALL":
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flags |= re.DOTALL
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return re.compile(pattern, flags)
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def _apply_overrides(line: str, audit: List[PiiHit], page_idx: int, cfg: Dict[str, Any]) -> str:
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for ov in cfg.get("regex_overrides", []) or []:
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pattern = ov.get("pattern"); placeholder = ov.get("placeholder", PLACEHOLDERS["MASK"]) ; name = ov.get("name", "override")
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flags_list = ov.get("flags", [])
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try:
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rx = _compile_user_regex(pattern, flags_list)
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except Exception:
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continue
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def _rep(m: re.Match):
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audit.append(PiiHit(page_idx, name, m.group(0), placeholder))
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return placeholder
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line = rx.sub(_rep, line)
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# force-mask literals
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for term in (cfg.get("blacklist", {}).get("force_mask_terms", []) or []):
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if not term:
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continue
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word_rx = re.compile(rf"\b{re.escape(term)}\b", re.IGNORECASE)
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if word_rx.search(line):
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audit.append(PiiHit(page_idx, "force_term", term, PLACEHOLDERS["MASK"]))
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line = word_rx.sub(PLACEHOLDERS["MASK"], line)
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# force-mask regex
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for pat in (cfg.get("blacklist", {}).get("force_mask_regex", []) or []):
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try:
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rx = re.compile(pat, re.IGNORECASE)
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except Exception:
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continue
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if rx.search(line):
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audit.append(PiiHit(page_idx, "force_regex", pat, PLACEHOLDERS["MASK"]))
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line = rx.sub(PLACEHOLDERS["MASK"], line)
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return line
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def _mask_admin_label(line: str, audit: List[PiiHit], page_idx: int) -> str:
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m = RE_FINESS.search(line)
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if m:
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val = m.group(1); audit.append(PiiHit(page_idx, "FINESS", val, PLACEHOLDERS["FINESS"]))
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return RE_FINESS.sub(lambda _: f"FINESS : {PLACEHOLDERS['FINESS']}", line)
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m = RE_OGC.search(line)
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if m:
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val = m.group(1); audit.append(PiiHit(page_idx, "OGC", val, PLACEHOLDERS["OGC"]))
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return RE_OGC.sub(lambda _: f"N° OGC : {PLACEHOLDERS['OGC']}", line)
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m = RE_IPP.search(line)
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if m:
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val = m.group(1); audit.append(PiiHit(page_idx, "IPP", val, PLACEHOLDERS["IPP"]))
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return RE_IPP.sub(lambda _: f"IPP : {PLACEHOLDERS['IPP']}", line)
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return line
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def _mask_line_by_regex(line: str, audit: List[PiiHit], page_idx: int, cfg: Dict[str, Any]) -> str:
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# Apply user overrides & force-masks first
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line = _apply_overrides(line, audit, page_idx, cfg)
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# EMAIL
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def _repl_email(m: re.Match) -> str:
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audit.append(PiiHit(page_idx, "EMAIL", m.group(0), PLACEHOLDERS["EMAIL"]))
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return PLACEHOLDERS["EMAIL"]
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line = RE_EMAIL.sub(_repl_email, line)
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# TEL
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def _repl_tel(m: re.Match) -> str:
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audit.append(PiiHit(page_idx, "TEL", m.group(0), PLACEHOLDERS["TEL"]))
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return PLACEHOLDERS["TEL"]
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line = RE_TEL.sub(_repl_tel, line)
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# IBAN
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def _repl_iban(m: re.Match) -> str:
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audit.append(PiiHit(page_idx, "IBAN", m.group(0), PLACEHOLDERS["IBAN"]))
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return PLACEHOLDERS["IBAN"]
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line = RE_IBAN.sub(_repl_iban, line)
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# NIR
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def _repl_nir(m: re.Match) -> str:
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audit.append(PiiHit(page_idx, "NIR", m.group(0), PLACEHOLDERS["NIR"]))
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return PLACEHOLDERS["NIR"]
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line = RE_NIR.sub(_repl_nir, line)
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# PERSON uppercase with context, but with whitelist/short-token guards
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wl_sections = set((cfg.get("whitelist", {}) or {}).get("sections_titres", []) or [])
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wl_phrases = set((cfg.get("whitelist", {}) or {}).get("noms_maj_excepts", []) or [])
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def _repl_person_ctx(m: re.Match) -> str:
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span = m.group(1).strip()
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raw = m.group(0)
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if span in wl_sections or raw in wl_phrases:
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return raw
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tokens = [t for t in span.split() if t]
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if len(tokens) == 1 and len(tokens[0]) <= 3:
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return raw # acronym short (DIM/DR/DP...)
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# Otherwise mask
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audit.append(PiiHit(page_idx, "NOM", span, PLACEHOLDERS["NOM"]))
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return raw.replace(span, PLACEHOLDERS["NOM"]) # keep prefix (Dr/Mme/etc.)
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line = RE_PERSON_CONTEXT.sub(_repl_person_ctx, line)
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return line
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def _kv_value_only_mask(line: str, audit: List[PiiHit], page_idx: int, cfg: Dict[str, Any]) -> str:
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line = _mask_admin_label(line, audit, page_idx)
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parts = SPLITTER.split(line, maxsplit=1)
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if len(parts) == 2:
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key, value = parts
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masked_val = _mask_line_by_regex(value, audit, page_idx, cfg)
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return f"{key.strip()} : {masked_val.strip()}"
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else:
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return _mask_line_by_regex(line, audit, page_idx, cfg)
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# ----------------- Anonymisation -----------------
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def anonymise_document(pages_text: List[str], tables_lines: List[List[str]], cfg: Dict[str, Any]) -> AnonResult:
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audit: List[PiiHit] = []
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out_pages: List[str] = []
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for i, page_txt in enumerate(pages_text):
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lines = [ln for ln in (page_txt or "").splitlines()]
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masked = [_kv_value_only_mask(ln, audit, i, cfg) for ln in lines]
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out_pages.append("\n".join(masked))
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table_blocks: List[str] = []
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for i, rows in enumerate(tables_lines):
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mbuf: List[str] = []
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for r in rows:
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masked = _kv_value_only_mask(r, audit, i, cfg)
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mbuf.append(masked)
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if mbuf:
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table_blocks.append("\n".join(mbuf))
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tables_block = "\n\n".join(table_blocks)
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text_out = "\n\n".join(out_pages)
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if tables_block.strip():
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text_out += "\n\n[TABLES]\n" + tables_block + "\n[/TABLES]"
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return AnonResult(text_out=text_out, tables_block=tables_block, audit=audit)
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# ----------------- Selective safety rescan -----------------
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def selective_rescan(text: str) -> str:
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# remove TABLES from scope
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def strip_tables(s: str):
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kept = []
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out = []
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i = 0
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pattern = re.compile(r"\[TABLES\](.*?)\[/TABLES\]", re.DOTALL)
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for m in pattern.finditer(s):
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out.append(s[i:m.start()])
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kept.append((len("".join(out)), len("".join(out)) + len(m.group(1)), m.group(1)))
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out.append("\x00" * (m.end() - m.start()))
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i = m.end()
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out.append(s[i:])
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return "".join(out), kept
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protected, kept = strip_tables(text)
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protected = RE_EMAIL.sub(PLACEHOLDERS["EMAIL"], protected)
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protected = RE_TEL.sub(PLACEHOLDERS["TEL"], protected)
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protected = RE_IBAN.sub(PLACEHOLDERS["IBAN"], protected)
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protected = RE_NIR.sub(PLACEHOLDERS["NIR"], protected)
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res = list(protected)
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for start, end, payload in kept:
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res[start:end] = list(payload)
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return "".join(res)
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# ----------------- PDF Redaction -----------------
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def redact_pdf_vector(original_pdf: Path, audit: List[PiiHit], out_pdf: Path) -> None:
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if fitz is None:
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raise RuntimeError("PyMuPDF not disponible – installez pymupdf.")
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doc = fitz.open(str(original_pdf))
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by_page: Dict[int, List[PiiHit]] = {}
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for h in audit:
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by_page.setdefault(h.page, []).append(h)
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for pno, hits in by_page.items():
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if pno >= len(doc):
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continue
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page = doc[pno]
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for h in hits:
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token = h.original.strip()
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if not token:
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continue
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rects = page.search_for(token)
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if not rects and h.kind in {"NIR", "IBAN", "TEL"}:
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compact = re.sub(r"\s+", "", token)
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if compact != token:
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rects = page.search_for(compact)
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for r in rects:
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page.add_redact_annot(r, fill=(0,0,0))
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try:
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page.apply_redactions()
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except Exception:
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pass
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doc.save(str(out_pdf), deflate=True, garbage=4, clean=True, incremental=False)
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doc.close()
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def redact_pdf_raster(original_pdf: Path, audit: List[PiiHit], out_pdf: Path, dpi: int = 300) -> None:
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if fitz is None:
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raise RuntimeError("PyMuPDF not disponible – installez pymupdf.")
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doc = fitz.open(str(original_pdf))
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out = fitz.open()
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# search rects per page
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all_rects: Dict[int, List["fitz.Rect"]] = {}
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for pno in range(len(doc)):
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page = doc[pno]
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rects = []
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for h in [x for x in audit if x.page == pno]:
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token = h.original.strip()
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if not token:
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continue
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found = page.search_for(token)
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if not found and h.kind in {"NIR", "IBAN", "TEL"}:
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compact = re.sub(r"\s+", "", token)
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found = page.search_for(compact)
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rects.extend(found)
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all_rects[pno] = rects
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# render + compose
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for pno in range(len(doc)):
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src_page = doc[pno]
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page_rect = src_page.rect
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zoom = dpi / 72.0
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mat = fitz.Matrix(zoom, zoom)
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pix = src_page.get_pixmap(matrix=mat, annots=False)
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img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
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draw = ImageDraw.Draw(img)
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for r in all_rects.get(pno, []):
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draw.rectangle([r.x0 * zoom, r.y0 * zoom, r.x1 * zoom, r.y1 * zoom], fill=(0, 0, 0))
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buf = io.BytesIO(); img.save(buf, format="PNG"); buf.seek(0)
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dst_page = out.new_page(width=page_rect.width, height=page_rect.height)
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dst_page.insert_image(page_rect, stream=buf.getvalue())
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out.save(str(out_pdf), deflate=True, garbage=4, clean=True)
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out.close(); doc.close()
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# ----------------- Orchestration -----------------
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def process_pdf(pdf_path: Path, out_dir: Path, make_vector_redaction: bool = True, also_make_raster_burn: bool = False, config_path: Optional[Path] = None) -> Dict[str, str]:
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out_dir.mkdir(parents=True, exist_ok=True)
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cfg = load_dictionaries(config_path)
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pages_text, tables_lines = extract_text_two_passes(pdf_path)
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anon = anonymise_document(pages_text, tables_lines, cfg)
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final_text = selective_rescan(anon.text_out)
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base = pdf_path.stem
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txt_path = out_dir / f"{base}.pseudonymise.txt"
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audit_path = out_dir / f"{base}.audit.jsonl"
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txt_path.write_text(final_text, encoding="utf-8")
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with audit_path.open("w", encoding="utf-8") as f:
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for hit in anon.audit:
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f.write(json.dumps(hit.__dict__, ensure_ascii=False) + "\n")
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outputs = {"text": str(txt_path), "audit": str(audit_path)}
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if make_vector_redaction and fitz is not None:
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vec_path = out_dir / f"{base}.redacted_vector.pdf"
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try:
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redact_pdf_vector(pdf_path, anon.audit, vec_path)
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outputs["pdf_vector"] = str(vec_path)
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except Exception:
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pass
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if also_make_raster_burn and fitz is not None:
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ras_path = out_dir / f"{base}.redacted_raster.pdf"
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redact_pdf_raster(pdf_path, anon.audit, ras_path)
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outputs["pdf_raster"] = str(ras_path)
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return outputs
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||
if __name__ == "__main__":
|
||
import argparse
|
||
ap = argparse.ArgumentParser(description="Anonymiser PDF avec dictionnaires YAML + PDF redactions")
|
||
ap.add_argument("pdf", type=str)
|
||
ap.add_argument("--out", type=str, default="out")
|
||
ap.add_argument("--no-vector", action="store_true")
|
||
ap.add_argument("--raster", action="store_true")
|
||
ap.add_argument("--config", type=str, default=str(Path("config/dictionnaires.yml")))
|
||
args = ap.parse_args()
|
||
outs = process_pdf(Path(args.pdf), Path(args.out), make_vector_redaction=not args.no_vector, also_make_raster_burn=args.raster, config_path=Path(args.config))
|
||
print(json.dumps(outs, indent=2, ensure_ascii=False))
|