chore: sync project files
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Gilles Soulier
133
analyze_backmarket.py
Executable file
133
analyze_backmarket.py
Executable file
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#!/usr/bin/env python3
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"""Analyse du HTML Backmarket pour identifier les sélecteurs."""
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from bs4 import BeautifulSoup
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import json
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import re
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# Lire le HTML
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with open("scraped/backmarket_pw.html", "r", encoding="utf-8") as f:
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html = f.read()
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soup = BeautifulSoup(html, "lxml")
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print("=" * 80)
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print("ANALYSE HTML BACKMARKET.FR")
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print("=" * 80)
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# 1. Titre
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print("\n1. TITRE")
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print("-" * 80)
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h1_tags = soup.find_all("h1")
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print(f"Nombre de h1: {len(h1_tags)}")
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for i, h1 in enumerate(h1_tags[:3]):
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print(f" [{i+1}] Classes: {h1.get('class')}")
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print(f" Texte: {h1.get_text().strip()[:100]}")
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# 2. Prix
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print("\n2. PRIX")
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print("-" * 80)
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# Chercher dans JSON-LD
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json_ld_scripts = soup.find_all("script", {"type": "application/ld+json"})
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print(f"Scripts JSON-LD trouvés: {len(json_ld_scripts)}")
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for i, script in enumerate(json_ld_scripts[:3]):
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try:
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data = json.loads(script.string)
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if isinstance(data, dict):
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print(f"\n Script [{i+1}] @type: {data.get('@type')}")
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if data.get("@type") == "Product":
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print(f" name: {data.get('name')}")
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offers = data.get('offers', {})
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if isinstance(offers, dict):
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print(f" price: {offers.get('price')}")
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print(f" priceCurrency: {offers.get('priceCurrency')}")
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except Exception as e:
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print(f" Script [{i+1}] Erreur parsing JSON: {e}")
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# Chercher les divs/spans avec prix
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price_elements = soup.find_all(["div", "span", "p"], class_=lambda x: x and ("price" in str(x).lower()))
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print(f"\nÉléments avec 'price' dans la classe: {len(price_elements)}")
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for i, elem in enumerate(price_elements[:5]):
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text = elem.get_text().strip()[:80]
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print(f" [{i+1}] {elem.name} {elem.get('class')} → {text}")
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# Regex prix
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matches = re.findall(r'(\d{2,4})[,\s]?(\d{2})\s*€', html)
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print(f"\nPrix trouvés par regex: {len(matches)} matches")
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unique_prices = list(set([f"{m[0]},{m[1]} €" for m in matches[:10]]))
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for price in unique_prices[:5]:
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print(f" - {price}")
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# 3. Images
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print("\n3. IMAGES")
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print("-" * 80)
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img_product = soup.find_all("img", alt=True)
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print(f"Images avec alt: {len(img_product)}")
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for i, img in enumerate(img_product[:5]):
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alt = img.get("alt", "")
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src = img.get("src", "")
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if "iphone" in alt.lower() or "apple" in alt.lower():
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print(f" [{i+1}] alt: {alt[:60]}")
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print(f" src: {src[:80]}")
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# 4. État/Condition
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print("\n4. ÉTAT / CONDITION")
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print("-" * 80)
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condition_elements = soup.find_all(["div", "span", "button"], class_=lambda x: x and ("condition" in str(x).lower() or "grade" in str(x).lower() or "état" in str(x).lower()))
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print(f"Éléments avec condition/grade/état: {len(condition_elements)}")
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for i, elem in enumerate(condition_elements[:5]):
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text = elem.get_text().strip()[:80]
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print(f" [{i+1}] {elem.name} {elem.get('class')} → {text}")
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# 5. SKU / Référence
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print("\n5. SKU / RÉFÉRENCE PRODUIT")
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print("-" * 80)
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# Chercher dans l'URL
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print("Dans l'URL: /fr-fr/p/iphone-15-pro")
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print("Possible SKU: iphone-15-pro")
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# Chercher dans JSON-LD
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for script in json_ld_scripts:
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try:
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data = json.loads(script.string)
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if isinstance(data, dict) and data.get("@type") == "Product":
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print(f"\nDans JSON-LD:")
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print(f" sku: {data.get('sku')}")
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print(f" mpn: {data.get('mpn')}")
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print(f" productID: {data.get('productID')}")
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except:
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pass
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# 6. Breadcrumb / Catégorie
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print("\n6. CATÉGORIE / BREADCRUMB")
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print("-" * 80)
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breadcrumbs = soup.find_all(["nav", "ol", "ul"], class_=lambda x: x and "breadcrumb" in str(x).lower())
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for bc in breadcrumbs[:2]:
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print(f"Tag: {bc.name}, Classes: {bc.get('class')}")
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links = bc.find_all("a")
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for link in links[:5]:
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print(f" - {link.get_text().strip()}")
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# 7. Spécifications
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print("\n7. CARACTÉRISTIQUES TECHNIQUES")
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print("-" * 80)
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specs_sections = soup.find_all(["div", "dl", "table"], class_=lambda x: x and ("spec" in str(x).lower() or "characteristic" in str(x).lower() or "feature" in str(x).lower()))
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print(f"Sections de specs: {len(specs_sections)}")
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for i, section in enumerate(specs_sections[:3]):
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print(f" [{i+1}] {section.name} {section.get('class')}")
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text = section.get_text().strip()[:150]
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print(f" {text}")
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# 8. Meta tags
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print("\n8. META TAGS")
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print("-" * 80)
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og_title = soup.find("meta", property="og:title")
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og_price = soup.find("meta", property="og:price:amount")
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if og_title:
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print(f"og:title: {og_title.get('content')}")
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if og_price:
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print(f"og:price:amount: {og_price.get('content')}")
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print("\n" + "=" * 80)
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print("FIN DE L'ANALYSE")
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print("=" * 80)
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