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receipt_parser.py

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"""

Parsing de tickets de caisse exportés depuis les applis des enseignes.

Objectif : zéro IA, 100 % Python. Les applis (Mon E.Leclerc, etc.) exportent

des PDF avec une couche texte propre — on lit ce texte et on extrait les lignes.

Point d'entrée : parse_receipt(raw: bytes, filename: str) -> dict

Retourne {items: [{category, name, price}], ticket_store, ticket_date, total, warning?}

"""

import io

import csv

import re

from typing import Optional

# ---------------------------------------------------------------------------

# CSV (format E.Leclerc "Export Ticket de Caisse")

# ---------------------------------------------------------------------------

def parse_csv(raw: bytes) -> dict:

text = _decode(raw)

reader = csv.reader(io.StringIO(text))

items = []

ticket_date = ""

ticket_store = ""

SKIP_STARTS = ("rayon", "export", "date", "total", "bon", "reste", "sous")

for row in reader:

if len(row) >= 1:

cell = row[0].strip()

if cell.lower().startswith("export ticket"):

ticket_store = cell.replace("Export Ticket de Caisse - ", "").strip()

if cell.lower().startswith("date du ticket"):

ticket_date = cell.split(":", 1)[-1].strip()

if len(row) < 5:

continue

rayon = row[0].strip()

article = row[1].strip()

total = row[4].strip().replace(",", ".")

if not rayon or not article:

continue

if any(rayon.lower().startswith(s) for s in SKIP_STARTS):

continue

if any(article.lower().startswith(s) for s in SKIP_STARTS):

continue

try:

price = float(total)

except ValueError:

continue

if price <= 0:

continue

items.append({"category": rayon.strip(), "name": article.strip(), "price": price})

return {

"items": items,

"ticket_store": ticket_store,

"ticket_date": ticket_date,

"total": round(sum(i["price"] for i in items), 2),

}

# ---------------------------------------------------------------------------

# PDF

# ---------------------------------------------------------------------------

def parse_pdf(raw: bytes) -> dict:

import pdfplumber # imported lazily so the app runs even if absent

pages_text = []

with pdfplumber.open(io.BytesIO(raw)) as pdf:

for page in pdf.pages:

pages_text.append(page.extract_text() or "")

text = "\n".join(pages_text)

if not text.strip():

raise ValueError(

"Ce PDF ne contient pas de texte lisible (probablement une image scannée). "

"Exportez un PDF depuis l'appli de l'enseigne."

)

store = _detect_store(text)

if store == "leclerc":

return _parse_leclerc(text)

return _parse_generic(text)

def _detect_store(text: str) -> Optional[str]:

low = text.lower()

if "leclerc" in low:

return "leclerc"

if "lidl" in low:

return "lidl"

if "carrefour" in low:

return "carrefour"

if "auchan" in low:

return "auchan"

return None

# E.Leclerc: lignes "[* ]NOM PRIX CODE_TVA" entre l'en-tête "TTC TVA" et "Total N articles"

_LECLERC_ITEM = re.compile(r"^(?:\*\s+)?(.+?)\s+(\d+[.,]\d{2})\s+(\d)$")

_LECLERC_TOTAL = re.compile(r"Total\s+\d+\s+articles?\s+(\d+[.,]\d{2})", re.IGNORECASE)

# code TVA E.Leclerc -> libellé de rayon approximatif (1 = alimentaire 5.5%, 3 = 20%)

_LECLERC_TVA_CAT = {"1": "Alimentaire", "3": "Autres"}

def _parse_leclerc(text: str) -> dict:

lines = text.split("\n")

items = []

in_items = False

for ln in lines:

s = ln.strip()

if re.search(r"\bTTC\b.*\bTVA\b", s):

in_items = True

continue

if not in_items:

continue

if s.startswith("---") or s.lower().startswith("total") or s.startswith("CB"):

break

m = _LECLERC_ITEM.match(s)

if not m:

continue

name = m.group(1).strip()

price = float(m.group(2).replace(",", "."))

tva = m.group(3)

if price <= 0:

continue

items.append({

"category": _LECLERC_TVA_CAT.get(tva, "Divers"),

"name": name,

"price": price,

})

date = ""

dm = re.search(r"(\d{1,2}\s+\w+\s+\d{4}\s+\d{1,2}:\d{2})", text)

if dm:

date = dm.group(1)

result = {

"items": items,

"ticket_store": "E.Leclerc",

"ticket_date": date,

"total": round(sum(i["price"] for i in items), 2),

}

# Cross-check against the printed total

tm = _LECLERC_TOTAL.search(text)

if tm:

printed = float(tm.group(1).replace(",", "."))

result["printed_total"] = printed

if abs(printed - result["total"]) > 0.01:

result["warning"] = (

f"Somme des articles ({result['total']:.2f}€) "

f"≠ total du ticket ({printed:.2f}€). Vérifiez les lignes."

)

return result

# Generic best-effort: any "NAME .... 12,34" line, skipping obvious non-items.

_GENERIC_ITEM = re.compile(r"^(.+?)\s+(\d+[.,]\d{2})(?:\s*[A-Z€]?)?$")

_GENERIC_SKIP = re.compile(

r"total|sous.?total|^cb$|carte|montant|tva|espece|rendu|monnaie|"

r"remise|reduction|rabais|^ht$|^ttc$|caisse|ticket|siret|^code|^total",

re.IGNORECASE,

)

def _parse_generic(text: str) -> dict:

items = []

for ln in text.split("\n"):

s = ln.strip()

if not s or _GENERIC_SKIP.search(s):

continue

m = _GENERIC_ITEM.match(s)

if not m:

continue

name = m.group(1).strip(" .-")

try:

price = float(m.group(2).replace(",", "."))

except ValueError:

continue

# Filter noise: name must have a couple letters and a plausible price

if price <= 0 or price > 2000 or len(re.sub(r"[^A-Za-zÀ-ÿ]", "", name)) < 2:

continue

items.append({"category": "Divers", "name": name, "price": price})

return {

"items": items,

"ticket_store": _detect_store(text) or "",

"ticket_date": "",

"total": round(sum(i["price"] for i in items), 2),

"warning": "Format non reconnu — extraction générique, vérifiez les lignes.",

}

# ---------------------------------------------------------------------------

# Dispatch

# ---------------------------------------------------------------------------

_IMAGE_MAGIC = (b"\x89PNG", b"\xff\xd8\xff", b"GIF8", b"RIFF", b"BM")

def parse_receipt(raw: bytes, filename: str) -> dict:

name = (filename or "").lower()

if name.endswith(".pdf") or raw[:5] == b"%PDF-":

return parse_pdf(raw)

is_image = (

name.endswith((".png", ".jpg", ".jpeg", ".webp", ".gif", ".bmp"))

or raw[:4] in _IMAGE_MAGIC

or raw[:2] == b"BM"

)

if is_image:

try:

import receipt_ocr

except ImportError:

raise ValueError(

"L'OCR image n'est pas disponible (easyocr non installé). "

"Utilisez un export PDF ou CSV."

)

return receipt_ocr.parse_image(raw)

return parse_csv(raw)

def _decode(raw: bytes) -> str:

for enc in ("utf-8-sig", "utf-8", "latin-1", "cp1252"):

try:

return raw.decode(enc)

except UnicodeDecodeError:

continue

raise ValueError("Encodage du fichier non reconnu")