modification du clean csv et du makefile
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8
makefile
8
makefile
@ -36,10 +36,18 @@ import:
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@until docker exec -i $(PG_CONTAINER) pg_isready -U $(PG_USER) -d $(PG_DB); do \
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sleep 2; \
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done
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@echo "🧹 Nettoyage des CSV avant import (local -> in-place)..."
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@python3 scripts/clean_csv.py
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@if [ $$? -ne 0 ]; then echo "❌ Erreurs lors du nettoyage des CSV - corrige les fichiers avant import"; exit 1; fi
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@echo "📥 Import des données de démo..."
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@docker exec -i $(PG_CONTAINER) psql -U $(PG_USER) -d $(PG_DB) -f $(IMPORT_SQL)
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@echo "✅ Données importées."
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set-dev-admin-pw:
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@echo "🔐 Définir mot de passe dev pour admin@ptits-pas.fr (admin123)"
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@docker exec -i $(PG_CONTAINER) psql -U $(PG_USER) -d $(PG_DB) -c "UPDATE utilisateurs SET password = crypt('admin123', gen_salt('bf')) WHERE email = 'admin@ptits-pas.fr';"
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@echo "✅ Mot de passe admin dev mis à jour."
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verify:
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@echo "⏳ Attente que Postgres démarre pour vérifier..."
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@until docker exec -i $(PG_CONTAINER) pg_isready -U $(PG_USER) -d $(PG_DB); do \
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@ -1,59 +1,123 @@
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#!/usr/bin/env python3
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"""scripts/clean_csv.py
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Usage:
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python3 scripts/clean_csv.py [input_dir] [--out-dir OUT] [--dry-run]
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This script cleans CSV files (trim, remove 'NULL', fix column count) and
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performs simple validations (UUID-looking columns, date columns).
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"""
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import csv
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import sys
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from pathlib import Path
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from datetime import datetime
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import argparse
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import re
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def clean_csv_file(file_path: Path):
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"""
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Nettoie un CSV directement en place :
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- remplace "NULL" par ""
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- supprime les espaces parasites
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- force le même nombre de colonnes que l'en-tête
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"""
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UUID_RE = re.compile(r'^[0-9a-fA-F-]{36}$')
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def is_uuid(s: str) -> bool:
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return bool(UUID_RE.match(s))
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def looks_like_date(s: str) -> bool:
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if not s:
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return False
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# try ISO-like detection
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try:
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datetime.fromisoformat(s)
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return True
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except Exception:
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return False
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def clean_csv_file(file_path: Path, out_path: Path = None, dry_run: bool = False):
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cleaned_rows = []
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errors = []
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with open(file_path, "r", encoding="utf-8-sig", newline="") as infile:
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with file_path.open("r", encoding="utf-8-sig", newline="") as infile:
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reader = csv.reader(infile)
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try:
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header = next(reader)
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except StopIteration:
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print(f"[⚠️] Fichier vide : {file_path}")
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return
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return {'file': str(file_path), 'error': 'empty', 'errors': []}
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nb_cols = len(header)
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cleaned_rows.append([h.strip() for h in header])
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# Heuristics for validations
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uuid_cols = [i for i, h in enumerate(header) if h.lower() == 'id' or h.lower().endswith('_id')]
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date_cols = [i for i, h in enumerate(header) if any(k in h.lower() for k in ('date', '_le', '_at'))]
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for i, row in enumerate(reader, start=2):
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# Ajuste le nombre de colonnes
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if len(row) < nb_cols:
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row.extend([""] * (nb_cols - len(row)))
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elif len(row) > nb_cols:
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row = row[:nb_cols]
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# Nettoyage cellule par cellule
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row = [cell.strip().replace("NULL", "") for cell in row]
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row = [cell.strip().replace('NULL', '') for cell in row]
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# Validations simples
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for ci in uuid_cols:
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if ci < len(row) and row[ci]:
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if not is_uuid(row[ci]):
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errors.append(f"Line {i}: column {header[ci]} not UUID-like: {row[ci]!r}")
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for ci in date_cols:
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if ci < len(row) and row[ci]:
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if not looks_like_date(row[ci]):
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errors.append(f"Line {i}: column {header[ci]} not ISO-like date: {row[ci]!r}")
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cleaned_rows.append(row)
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# Réécriture dans le même fichier
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with open(file_path, "w", encoding="utf-8", newline="") as outfile:
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writer = csv.writer(outfile)
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writer.writerows(cleaned_rows)
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# Write output if not dry-run
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if not dry_run:
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target = out_path if out_path else file_path
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with target.open('w', encoding='utf-8', newline='') as outfile:
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writer = csv.writer(outfile)
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writer.writerows(cleaned_rows)
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print(f"[✔] Nettoyé : {file_path}")
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return {'file': str(file_path), 'errors': errors}
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def main():
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if len(sys.argv) > 1:
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base_dir = Path(sys.argv[1])
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parser = argparse.ArgumentParser()
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parser.add_argument('input_dir', nargs='?', default='bdd/data_test')
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parser.add_argument('--out-dir', '-o', help='Optional output directory for cleaned files')
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parser.add_argument('--dry-run', action='store_true', help='Do not write files, just report')
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args = parser.parse_args()
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base_dir = Path(args.input_dir)
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out_dir = Path(args.out_dir) if args.out_dir else None
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if out_dir and not out_dir.exists():
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out_dir.mkdir(parents=True)
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results = []
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for file_path in sorted(base_dir.glob('*.csv')):
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out_path = out_dir / file_path.name if out_dir else None
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res = clean_csv_file(file_path, out_path, args.dry_run)
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results.append(res)
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# Report
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any_errors = False
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for r in results:
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if 'error' in r:
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print(f"[WARN] {r['file']}: {r['error']}")
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if r.get('errors'):
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any_errors = True
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print(f"[ERR] {r['file']} ->")
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for e in r['errors'][:20]:
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print(' -', e)
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else:
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print(f"[OK] {r['file']}")
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if any_errors:
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print('\nSome files have validation issues. Fix them or run with --dry-run to inspect.')
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sys.exit(2)
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else:
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base_dir = Path("bdd/data_test")
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print(f"🔎 Nettoyage des CSV dans : {base_dir}")
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for file_path in base_dir.glob("*.csv"):
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clean_csv_file(file_path)
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print(f"✅ Terminé. Les fichiers CSV ont été écrasés (nettoyés en place).")
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print('\nAll files cleaned successfully.')
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if __name__ == "__main__":
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if __name__ == '__main__':
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main()
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