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Priceflow/app/services/cataloguemate_scraper.py
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286 lines
9.6 KiB
Python

"""
Cataloguemate.fr Scraper Service
Scrapes promotional catalogs from Cataloguemate.fr.
Replaces Tiendeo scraper due to better reliability and simpler structure.
Refactored to use BrowserlessService for robust containerized scraping.
"""
import asyncio
import logging
import re
from datetime import datetime, timedelta
from typing import Any, Optional
from bs4 import BeautifulSoup
from sqlalchemy.orm import Session
from app.models import Enseigne, Catalogue, CataloguePage, ScrapingLog
from app.services.browserless_service import browserless_service
logger = logging.getLogger(__name__)
BASE_URL = "https://www.cataloguemate.fr"
async def scrape_catalog_list(enseigne: Enseigne) -> list[dict[str, Any]]:
"""
Scrape the list of catalogs for an enseigne.
We use a default city (Paris) because the main page often doesn't list catalogs directly.
URL format: https://www.cataloguemate.fr/offres/paris/{enseigne_slug}/
"""
slug = enseigne.slug_bonial.lower()
# Handle specific slug mapping
if enseigne.nom.lower() == "b&m":
slug = "bm"
elif enseigne.nom.lower() == "la foir'fouille":
slug = "la-foirfouille"
# Use Paris as default city to find national catalogs
url = f"{BASE_URL}/offres/paris/{slug}/"
logger.info(f"Scraping catalog list from: {url}")
# Use browserless service to get content
html_content, _ = await browserless_service.get_page_content(url)
if not html_content:
logger.error(f"Failed to fetch list {url}")
return []
soup = BeautifulSoup(html_content, 'html.parser')
catalogs = []
# Find all links that might be catalogs
links = soup.find_all('a', href=True)
seen_urls = set()
logger.info(f"Found {len(links)} links on page {url}")
for link in links:
href = link['href']
text = link.get_text(strip=True)
# Normalize href
if href.startswith(BASE_URL):
href = href.replace(BASE_URL, "")
# Debug log for potential candidates
if slug in href:
logger.debug(f"Checking link: {href}")
# Filter:
# 1. Must contain the slug (or be a catalog link for this enseigne)
# 2. Must NOT be a city search page (/offres/)
# 3. Must NOT be a product search (/rechercher/)
# 4. Should usually have a numeric ID at the end
if f"/{slug}/" in href:
if any(x in href for x in ["/offres/", "/magasins/", "/rechercher/", "page="]):
logger.debug(f" -> Rejected (invalid pattern): {href}")
continue
full_url = f"{BASE_URL}{href}"
if full_url in seen_urls:
continue
# Check for numeric ID pattern which is typical for catalogs
# e.g. -61130/
if re.search(r'-\d+/?$', href) or "catalogue" in href.lower():
catalogs.append({
'url': full_url,
'title': text or "Catalogue",
})
seen_urls.add(full_url)
logger.info(f"Found catalog: {full_url}")
else:
logger.debug(f" -> Rejected (no ID/catalogue keyword): {href}")
logger.info(f"Total catalogs found: {len(catalogs)}")
return catalogs
async def scrape_catalog_pages(catalog_url: str) -> list[dict[str, Any]]:
"""
Scrape pages from a specific catalog.
Iterates through ?page=1, ?page=2 etc.
"""
pages = []
page_num = 1
max_pages = 100 # Safety limit
while page_num <= max_pages:
# Construct URL for specific page
current_url = catalog_url if page_num == 1 else f"{catalog_url}?page={page_num}"
logger.info(f"Scraping page {page_num}: {current_url}")
# Use browserless service
html_content, _ = await browserless_service.get_page_content(current_url)
if not html_content:
logger.warning(f"Failed to fetch page {page_num}")
break
soup = BeautifulSoup(html_content, 'html.parser')
# Find the main catalog image
main_image_url = None
max_area = 0
all_imgs = soup.find_all('img')
for img in all_imgs:
src = img.get('src')
if not src: continue
# Skip common UI elements
if any(x in src.lower() for x in ['logo', 'icon', 'facebook', 'twitter', 'instagram']):
continue
# Calculate area if dimensions exist
width = img.get('width')
height = img.get('height')
area = 0
if width and height:
try:
area = int(width) * int(height)
except:
pass
# Heuristic: Catalog pages are usually large vertical images
# Check src for keywords
is_likely_catalog = any(k in src.lower() for k in ['page', 'flyer', 'catalog', 'upload', 'images'])
# Logic:
# 1. If keyword match AND decent size -> Strong candidate
# 2. If no keyword match but HUGE size -> Candidate
if is_likely_catalog:
if area > max_area:
max_area = area
main_image_url = src
elif area == 0 and not main_image_url:
main_image_url = src
elif area > 100000: # Arbitrary large size (e.g. 300x333)
if area > max_area:
max_area = area
main_image_url = src
if main_image_url:
# Ensure absolute URL
if main_image_url.startswith("//"):
main_image_url = "https:" + main_image_url
elif main_image_url.startswith("/"):
main_image_url = BASE_URL + main_image_url
pages.append({
'page_number': page_num,
'image_url': main_image_url
})
logger.info(f"Found image for page {page_num}: {main_image_url}")
else:
logger.warning(f"No catalog image found on page {page_num}")
# If we can't find an image, we might have reached the end or it's a bad page
if page_num > 1:
break
# Check for pagination "Next" to know if we should continue
if not main_image_url:
break
page_num += 1
# Small delay handled by browserless service already, but adding a tiny one here
await asyncio.sleep(0.5)
return pages
async def scrape_enseigne(enseigne: Enseigne, db: Session) -> ScrapingLog:
"""Main entry point for scraping an enseigne"""
start_time = datetime.now()
log = ScrapingLog(
enseigne_id=enseigne.id,
statut="running",
date_debut=start_time,
catalogues_trouves=0,
catalogues_nouveaux=0,
catalogues_mis_a_jour=0
)
db.add(log)
db.commit()
try:
# 0. Test connection (Implicit in get_page_content, but good to log)
logger.info(f"Starting scraping for {enseigne.nom} using Browserless...")
# 1. Get list of catalogs
catalogs_list = await scrape_catalog_list(enseigne)
log.catalogues_trouves = len(catalogs_list)
for cat_info in catalogs_list:
# Check if catalog exists
existing = db.query(Catalogue).filter(
Catalogue.catalogue_url == cat_info['url']
).first()
if existing:
continue
# 2. Scrape pages for new catalog
pages = await scrape_catalog_pages(cat_info['url'])
if not pages:
continue
# Create catalog entry
new_cat = Catalogue(
enseigne_id=enseigne.id,
titre=cat_info['title'],
catalogue_url=cat_info['url'],
date_debut=datetime.now(), # Todo: extract real dates
date_fin=datetime.now() + timedelta(days=14),
image_couverture_url=pages[0]['image_url']
)
db.add(new_cat)
db.commit()
db.refresh(new_cat)
# Add pages
for page_data in pages:
new_page = CataloguePage(
catalogue_id=new_cat.id,
numero_page=page_data['page_number'],
image_url=page_data['image_url'],
)
db.add(new_page)
db.commit()
log.catalogues_nouveaux += 1
logger.info(f"Saved catalog '{new_cat.titre}' with {len(pages)} pages")
log.statut = "success"
except Exception as e:
logger.error(f"Scraping failed: {e}")
log.statut = "error"
log.message_erreur = str(e)
finally:
log.date_fin = datetime.now()
db.commit()
return log
async def scrape_all_enseignes(db: Session) -> list[ScrapingLog]:
"""
Scrape catalogs for all active enseignes.
"""
logger.info("Starting scraping for all enseignes...")
logs = []
enseignes = db.query(Enseigne).filter(Enseigne.is_active == True).all()
for enseigne in enseignes:
try:
log = await scrape_enseigne(enseigne, db)
logs.append(log)
except Exception as e:
logger.error(f"Error scraping enseigne {enseigne.nom}: {e}")
return logs