Files
anonymisation/anonymisation_cli_onefile.spec
Domi31tls 4b7c8db9a8 build: retirer torch/docTR du frozen + hiddenimports OnnxTR (pré-audit Qwen GO)
Suite à la migration OCR docTR→OnnxTR (8d683bc) et au verdict pré-audit Qwen
(GO technique, 2026-06-21), préparation des 3 specs PyInstaller pour le prochain
rebuild Windows :

- Retrait de "torch", "torchvision", "doctr.*" des hiddenimports des 3 specs
  (anonymisation_onefile, _cli_onefile, _gui_v6_onefile) → -~2 Go EXE attendu,
  suppression définitive de la classe de bug oneDNN sur CPU contraint.
- Ajout des hiddenimports transitifs OnnxTR manquants (réserve R1 Qwen) :
  "pyclipper", "scipy.cluster.hierarchy", "scipy.special" → anti-omission
  PyInstaller (évite un crash OCR en frozen).
- Retrait de python-doctr[torch]>=0.9.0 de requirements.txt (transitoire levé).

_configure_torch_threads() conservé en code (lazy import torch sous try/except,
no-op si torch absent) pour future réactivation EDS-Pseudo/GLiNER.

Aucun rebuild ni diffusion (gate Dom). 3 specs compilent (py_compile).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-22 16:49:03 +02:00

180 lines
4.6 KiB
Python

import os
from pathlib import Path
from PyInstaller.utils.hooks import collect_all, copy_metadata
# Spec CLI frozen — EXE de PRODUCTION (anonymisation fichier unique sans GUI).
# Même moteur / mêmes datas que anonymisation_onefile.spec, mais :
# - entrypoint = scripts/anonymize_cli.py (CLI production, pas launcher.py)
# Contrat : Anonymisation-CLI.exe <fichier> <dossier_sortie>
# Modèle CamemBERT-bio ONNX OBLIGATOIRE (fail-closed, code 3 si absent).
# - console=True (CLI), pas de Splash
# - name = Anonymisation-CLI -> ne remplace pas dist/Anonymisation.exe
# (Le harnais perf D-19 reste scripts/anonymize_batch_cli.py, non buildé ici.)
block_cipher = None
project_dir = Path(globals().get("SPECPATH", os.getcwd())).resolve()
def _data_entry(relative_path: str, target_dir: str | None = None):
src = project_dir / relative_path
if not src.exists():
return None
return (str(src), target_dir or relative_path)
binaries = []
datas = []
for relative_path, target_dir in [
("config", "config"),
("data/bdpm", "data/bdpm"),
("data/finess", "data/finess"),
("data/insee", "data/insee"),
("models/camembert-bio-deid/onnx", "models/camembert-bio-deid/onnx"),
("detectors", "detectors"),
("scripts", "scripts"),
("assets", "assets"),
]:
entry = _data_entry(relative_path, target_dir)
if entry is not None:
datas.append(entry)
for relative_path in [
"data/stopwords_manuels.txt",
"data/villes_blacklist.txt",
"data/dpi_labels_blacklist.txt",
"data/companion_blacklist.txt",
]:
entry = _data_entry(relative_path, "data")
if entry is not None:
datas.append(entry)
onnxtr_cache_dir = Path(os.environ.get("ONNXTR_CACHE_DIR", Path.home() / ".cache" / "onnxtr"))
required_onnxtr_weights = [
"db_resnet50-69ba0015.onnx",
"crnn_vgg16_bn-743599aa.onnx",
]
missing_onnxtr_weights = []
for filename in required_onnxtr_weights:
src = onnxtr_cache_dir / "models" / filename
if src.exists():
datas.append((str(src), "models/onnxtr/models"))
else:
missing_onnxtr_weights.append(str(src))
if missing_onnxtr_weights:
raise FileNotFoundError(
"Poids OCR OnnxTR manquants pour le build frozen : "
+ ", ".join(missing_onnxtr_weights)
+ ". Précharger OnnxTR (lancer une OCR une fois) ou définir ONNXTR_CACHE_DIR avant PyInstaller."
)
hiddenimports = [
"anonymizer_core_refactored_onnx",
"admin_rules",
"config_defaults",
"profile_defaults",
"gui_batch_paths",
"manual_masking",
"pdf_mask_designer",
"format_converter",
"ner_manager_onnx",
"camembert_ner_manager",
"eds_pseudo_manager",
"gliner_manager",
"vlm_manager",
"build_info",
# OCR OnnxTR (ONNX Runtime, remplace docTR — sans torch ni doctr)
"onnxtr",
"onnxtr.io",
"onnxtr.models",
"onnxtr.models.detection",
"onnxtr.models.recognition",
"onnxtr.utils",
"onnxtr.utils.data",
# Dépendances transitives OnnxTR (hiddenimports défensifs vs omission PyInstaller)
"pyclipper",
"scipy.cluster.hierarchy",
"scipy.special",
"cv2",
"edsnlp",
"edsnlp.pipes",
"edsnlp.pipes.ner",
"edsnlp.pipes.ner.pseudo",
"spacy",
"spacy.lang.fr",
"gliner",
"onnxruntime",
"transformers",
"tokenizers",
"pdfplumber",
"fitz",
"PIL",
"yaml",
"loguru",
"regex",
"optimum",
"optimum.onnxruntime",
"optimum.pipelines",
"optimum.modeling_base",
"optimum.exporters.onnx",
]
def _collect_optional_package(package_name: str):
try:
package_datas, package_binaries, package_hiddenimports = collect_all(package_name)
datas.extend(package_datas)
binaries.extend(package_binaries)
hiddenimports.extend(package_hiddenimports)
try:
datas.extend(copy_metadata(package_name, recursive=True))
except Exception:
pass
except Exception:
pass
for _package_name in [
"edsnlp",
"spacy",
"thinc",
"blis",
"srsly",
"catalogue",
"confection",
"cymem",
"preshed",
"murmurhash",
"gliner",
"loguru",
]:
_collect_optional_package(_package_name)
a = Analysis(
[str(project_dir / "scripts" / "anonymize_cli.py")],
pathex=[str(project_dir)],
binaries=binaries,
datas=datas,
hiddenimports=hiddenimports,
cipher=block_cipher,
noarchive=False,
)
pyz = PYZ(a.pure, a.zipped_data, cipher=block_cipher)
exe = EXE(
pyz,
a.scripts,
a.binaries,
a.zipfiles,
a.datas,
[],
name="Anonymisation-CLI",
debug=False,
strip=False,
upx=False,
console=True,
)