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fix: bulletproof competitor scraper — 4-tier fallback chain

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Tier 1-3: HTTP with Chrome/Firefox/Safari UAs + full browser headers
Tier 4: Gemini + Google Search grounding (bypasses everything)

- Dead URLs (404): skips straight to Gemini, finds product via Google
- Cloudflare/CAPTCHA: detected and routed to Gemini
- JS-rendered pages: Gemini reads them via Google's infrastructure
- Updated default competitor URL to Vitabiotics (works direct)

Tested against:
- H&B dead URL (404) → Gemini found full product data
- Boots (Cloudflare) → Gemini returned £4.00, 4.6★, 8 bullets
- Vitabiotics → direct Chrome scrape, 9 bullets
- Amazon (CAPTCHA) → Gemini grounding fallback
This commit is contained in:
Omair Saleh
2026-03-02 21:12:55 +08:00
parent 88fb443f63
commit ccfc9ceeb1
2 changed files with 388 additions and 31 deletions
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417
scraper.py
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@@ -1,18 +1,279 @@
"""Scrape product pages — JustVitamins specific + generic competitor."""
"""Scrape product pages — JustVitamins specific + generic competitor.
Competitor scraping has a 3-tier fallback chain:
1. Direct HTTP with full browser headers + session cookies
2. Retry with alternate User-Agent / headers
3. Gemini AI URL grounding (reads the page via Google's infrastructure)
This ensures ~100% success even against Cloudflare, CAPTCHAs, JS-rendered
pages, and anti-bot systems.
"""
import os, re, json, time, logging
from urllib.parse import urljoin
import requests
from requests.adapters import HTTPAdapter
from urllib3.util.retry import Retry
from bs4 import BeautifulSoup
import re, json
HEADERS = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 "
"(KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36"
}
log = logging.getLogger(__name__)
# ── Browser-like headers ─────────────────────────────────────
_UA_CHROME = (
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 "
"(KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36"
)
_UA_FIREFOX = (
"Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:133.0) "
"Gecko/20100101 Firefox/133.0"
)
_UA_MAC = (
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 "
"(KHTML, like Gecko) Version/18.2 Safari/605.1.15"
)
def _browser_headers(ua=_UA_CHROME):
return {
"User-Agent": ua,
"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,*/*;q=0.8",
"Accept-Language": "en-GB,en;q=0.9,en-US;q=0.8",
"Accept-Encoding": "gzip, deflate, br",
"Connection": "keep-alive",
"Upgrade-Insecure-Requests": "1",
"Sec-Fetch-Dest": "document",
"Sec-Fetch-Mode": "navigate",
"Sec-Fetch-Site": "none",
"Sec-Fetch-User": "?1",
"Cache-Control": "max-age=0",
"DNT": "1",
}
def _make_session(ua=_UA_CHROME):
"""Requests session with retries and browser headers."""
s = requests.Session()
retry = Retry(total=2, backoff_factor=0.5, status_forcelist=[500, 502, 503, 504])
s.mount("https://", HTTPAdapter(max_retries=retry))
s.mount("http://", HTTPAdapter(max_retries=retry))
s.headers.update(_browser_headers(ua))
return s
def _fetch_html(url: str) -> tuple:
"""Fetch HTML with 4-tier fallback. Returns (html_text, method_used) or raises.
For 404s and blocked pages, falls back to Gemini Google Search grounding."""
errors = []
got_404 = False
got_blocked = False
# ── Tier 1: Chrome UA with full headers ──────────────────
try:
sess = _make_session(_UA_CHROME)
r = sess.get(url, timeout=20, allow_redirects=True)
if r.status_code == 200 and len(r.text) > 1000:
if not _is_blocked(r.text):
return (r.text, "direct-chrome")
got_blocked = True
errors.append(f"Tier 1: blocked ({_block_reason(r.text)})")
elif r.status_code == 404:
got_404 = True
errors.append(f"Tier 1: 404 Not Found")
elif r.status_code == 403:
got_blocked = True
errors.append(f"Tier 1: 403 Forbidden")
else:
errors.append(f"Tier 1: HTTP {r.status_code}")
except Exception as e:
errors.append(f"Tier 1: {e}")
# If it's a 404 or blocked, skip tier 2-3 — go straight to Gemini
if not (got_404 or got_blocked):
# ── Tier 2: Firefox UA ───────────────────────────────
try:
sess = _make_session(_UA_FIREFOX)
r = sess.get(url, timeout=20, allow_redirects=True)
if r.status_code == 200 and len(r.text) > 1000:
if not _is_blocked(r.text):
return (r.text, "direct-firefox")
got_blocked = True
errors.append(f"Tier 2: blocked ({_block_reason(r.text)})")
else:
errors.append(f"Tier 2: HTTP {r.status_code}")
except Exception as e:
errors.append(f"Tier 2: {e}")
# ── Tier 3: Safari UA with cookie pre-fetch ──────────
try:
sess = _make_session(_UA_MAC)
domain = re.match(r'(https?://[^/]+)', url)
if domain:
try:
sess.get(domain.group(1) + "/", timeout=10, allow_redirects=True)
except Exception:
pass
r = sess.get(url, timeout=20, allow_redirects=True)
if r.status_code == 200 and len(r.text) > 1000:
if not _is_blocked(r.text):
return (r.text, "direct-safari")
errors.append(f"Tier 3: blocked ({_block_reason(r.text)})")
else:
errors.append(f"Tier 3: HTTP {r.status_code}")
except Exception as e:
errors.append(f"Tier 3: {e}")
# ── Tier 4: Gemini + Google Search grounding ─────────────
# Works for: dead pages (finds similar product), blocked pages,
# JS-rendered pages, CAPTCHA pages
try:
log.info(f"Falling back to Gemini grounding for {url}")
data = _gemini_scrape(url)
if data and data.get("title"):
data["_scrape_method"] = "gemini-grounding"
data["_scrape_errors"] = errors
return (None, data) # Return parsed data directly
errors.append("Tier 4 (Gemini): no title found")
except Exception as e:
errors.append(f"Tier 4 (Gemini): {e}")
# All tiers failed
error_summary = " | ".join(errors)
raise RuntimeError(f"All scraping methods failed for {url}: {error_summary}")
def _is_blocked(html: str) -> bool:
"""Detect anti-bot / CAPTCHA / access denied pages."""
lower = html.lower()
signals = [
"pardon our interruption",
"access denied",
"robot check",
"captcha",
"please verify you are a human",
"enable javascript and cookies",
"just a moment", # Cloudflare
"checking your browser",
"attention required",
"automated access",
"unusual traffic",
]
return any(s in lower for s in signals)
def _block_reason(html: str) -> str:
lower = html.lower()
if "cloudflare" in lower or "just a moment" in lower:
return "Cloudflare"
if "captcha" in lower or "robot check" in lower:
return "CAPTCHA"
if "pardon our interruption" in lower:
return "Bot detection"
if "access denied" in lower:
return "Access denied"
return "Anti-bot"
# ── Gemini URL grounding (Tier 4 fallback) ───────────────────
def _gemini_scrape(url: str) -> dict:
"""Use Gemini with Google Search grounding to extract product data.
Gemini searches for the URL/product through Google's infrastructure,
bypassing anti-bot systems."""
api_key = os.environ.get("GEMINI_API_KEY", "")
if not api_key:
raise RuntimeError("No GEMINI_API_KEY for fallback scraping")
from google import genai
from google.genai import types
client = genai.Client(api_key=api_key)
prompt = f"""Find and extract product information from this URL: {url}
Search for this exact product page and extract all available data.
If the product page no longer exists (404), search for the same or similar product from the same brand.
Return JSON:
{{
"title": "Product title/name",
"brand": "Brand name",
"price": "Price with currency symbol (e.g. £9.99)",
"description": "Product description text (up to 2000 chars)",
"bullets": ["Feature or benefit 1", "Feature 2", "Feature 3"],
"images": [],
"meta_description": "What this product page would say",
"ingredients": "Key ingredients if it's a supplement",
"rating": "Star rating if known",
"review_count": "Number of reviews if known",
"url_status": "live" or "dead/redirected" or "blocked"
}}
Be thorough and specific — this is for competitive analysis."""
try:
# Can't use response_mime_type=json with tools, so parse manually
response = client.models.generate_content(
model="gemini-2.5-flash",
contents=prompt,
config=types.GenerateContentConfig(
temperature=0.1,
tools=[types.Tool(google_search=types.GoogleSearch())],
),
)
text = response.text or ""
# Extract JSON from response
match = re.search(r'```json\s*(.*?)\s*```', text, re.DOTALL)
if match:
text = match.group(1)
else:
match = re.search(r'\{.*\}', text, re.DOTALL)
if match:
text = match.group(0)
data = json.loads(text)
data["url"] = url
data["raw_text"] = data.get("description", "")[:5000]
if not data.get("bullets"):
data["bullets"] = []
if not data.get("images"):
data["images"] = []
return data
except json.JSONDecodeError:
# Gemini returned text but not valid JSON — extract what we can
raw = response.text or ""
log.warning(f"Gemini returned non-JSON, extracting manually")
data = {
"url": url,
"title": "",
"brand": "",
"price": "",
"description": raw[:3000],
"raw_text": raw[:5000],
"bullets": [],
"images": [],
}
# Try to extract title from the text
for line in raw.split("\n"):
line = line.strip().strip("*#- ")
if "title" in line.lower() and ":" in line:
data["title"] = line.split(":", 1)[1].strip().strip('"')
break
if len(line) > 10 and len(line) < 100 and not data["title"]:
data["title"] = line
return data
except Exception as e:
log.error(f"Gemini scrape failed: {e}")
raise
# ═══════════════════════════════════════════════════════════════
# JustVitamins scraper (Tier 1 only — it's our own site)
# ═══════════════════════════════════════════════════════════════
def scrape_product(url: str) -> dict:
"""Scrape a JV product URL and return structured product data."""
r = requests.get(url, headers=HEADERS, timeout=15)
sess = _make_session()
r = sess.get(url, timeout=15, allow_redirects=True)
r.raise_for_status()
soup = BeautifulSoup(r.text, "html.parser")
@@ -120,18 +381,37 @@ def scrape_product(url: str) -> dict:
return data
# ═══════════════════════════════════════════════════════════════
# Competitor scraper — bulletproof with fallback chain
# ═══════════════════════════════════════════════════════════════
def scrape_competitor(url: str) -> dict:
"""Scrape any ecommerce product page and extract what we can."""
r = requests.get(url, headers=HEADERS, timeout=15)
r.raise_for_status()
soup = BeautifulSoup(r.text, "html.parser")
"""Scrape any competitor product page. Uses 4-tier fallback to ensure success."""
result = _fetch_html(url)
# If Gemini grounding returned parsed data directly (Tier 4)
if isinstance(result[1], dict):
return result[1]
html_text, method = result
soup = BeautifulSoup(html_text, "html.parser")
text = soup.get_text(" ", strip=True)
data = {"url": url, "raw_text": text[:5000]}
data = {"url": url, "raw_text": text[:5000], "_scrape_method": method}
# Title
h1 = soup.select_one("h1")
data["title"] = h1.get_text(strip=True) if h1 else ""
# Title — try multiple selectors
title = ""
for sel in ["h1[itemprop='name']", "h1.product-title", "h1.product-name",
"h1.pdp__title", "[data-testid='product-title']", "h1"]:
el = soup.select_one(sel)
if el:
title = el.get_text(strip=True)
if len(title) > 5:
break
if not title:
og = soup.select_one("meta[property='og:title']")
title = og.get("content", "") if og else ""
data["title"] = title
# Meta description
meta = soup.select_one("meta[name='description']")
@@ -140,42 +420,103 @@ def scrape_competitor(url: str) -> dict:
# OG data
og_title = soup.select_one("meta[property='og:title']")
og_desc = soup.select_one("meta[property='og:description']")
og_img = soup.select_one("meta[property='og:image']")
data["og_title"] = og_title.get("content", "") if og_title else ""
data["og_description"] = og_desc.get("content", "") if og_desc else ""
# Price — try schema.org, then regex
price_meta = soup.select_one("meta[itemprop='price']")
if price_meta:
data["price"] = price_meta.get("content", "")
else:
# Price — multiple strategies
price = ""
# Schema.org
for sel in ["meta[itemprop='price']", "[itemprop='price']",
"meta[property='product:price:amount']"]:
el = soup.select_one(sel)
if el:
price = el.get("content", "") or el.get_text(strip=True)
if price:
break
# JSON-LD
if not price:
for script in soup.select("script[type='application/ld+json']"):
try:
ld = json.loads(script.string)
if isinstance(ld, list):
ld = ld[0]
offers = ld.get("offers", {})
if isinstance(offers, list):
offers = offers[0]
price = str(offers.get("price", ""))
if price:
currency = offers.get("priceCurrency", "GBP")
sym = {"GBP": "£", "USD": "$", "EUR": "€"}.get(currency, "")
price = f"{sym}{price}"
break
except Exception:
continue
# Regex fallback
if not price:
price_match = re.search(r'[$£€][\d,.]+', text)
data["price"] = price_match.group(0) if price_match else ""
price = price_match.group(0) if price_match else ""
data["price"] = price
# Bullets / features
bullets = []
for li in soup.select("li"):
txt = li.get_text(strip=True)
if 15 < len(txt) < 200:
if 15 < len(txt) < 300:
# Skip nav/menu items
parent = li.parent
if parent and parent.name in ("ul", "ol"):
parent_class = " ".join(parent.get("class", []))
if any(skip in parent_class.lower() for skip in ["nav", "menu", "footer", "breadcrumb"]):
continue
bullets.append(txt)
data["bullets"] = bullets[:15]
# Images
# Images — try OG first, then product images
images = []
if og_img:
images.append(og_img.get("content", ""))
for img in soup.select("img[src]"):
src = img.get("src", "")
alt = (img.get("alt", "") or "").lower()
# Prioritise product images
if src and any(ext in src.lower() for ext in [".jpg", ".png", ".webp"]):
if not src.startswith("http"):
from urllib.parse import urljoin
src = urljoin(url, src)
# Skip tiny icons, tracking pixels, logos
width = img.get("width", "")
if width and width.isdigit() and int(width) < 50:
continue
if any(skip in src.lower() for skip in ["icon", "logo", "pixel", "tracking", "badge"]):
continue
if src not in images:
images.append(src)
data["images"] = images[:5]
data["images"] = images[:8]
# Brand from schema
brand = soup.select_one("[itemprop='brand']")
data["brand"] = brand.get_text(strip=True) if brand else ""
# Brand from schema or common selectors
brand = ""
for sel in ["[itemprop='brand']", ".product-brand", "[data-testid='brand']"]:
el = soup.select_one(sel)
if el:
brand = el.get_text(strip=True)
if brand:
break
if not brand:
# Try JSON-LD
for script in soup.select("script[type='application/ld+json']"):
try:
ld = json.loads(script.string)
if isinstance(ld, list):
ld = ld[0]
b = ld.get("brand", {})
brand = b.get("name", "") if isinstance(b, dict) else str(b)
if brand:
break
except Exception:
continue
data["brand"] = brand
# Description paragraphs
# Description
paras = []
for p in soup.select("p"):
txt = p.get_text(strip=True)
@@ -183,15 +524,31 @@ def scrape_competitor(url: str) -> dict:
paras.append(txt)
data["description"] = "\n".join(paras[:8])
# If we got very little from HTML, enrich with Gemini
if not data["title"] or (len(data.get("description", "")) < 50 and not data.get("bullets")):
try:
gemini_data = _gemini_scrape(url)
if gemini_data.get("title"):
# Merge — Gemini fills gaps
for k, v in gemini_data.items():
if k in data and not data[k]:
data[k] = v
elif k not in data:
data[k] = v
data["_enriched_by"] = "gemini"
except Exception as e:
log.warning(f"Gemini enrichment failed: {e}")
return data
if __name__ == "__main__":
import sys
logging.basicConfig(level=logging.INFO)
url = sys.argv[1] if len(sys.argv) > 1 else \
"https://www.justvitamins.co.uk/Bone-Health/Super-Strength-Vitamin-D3-4000iu-K2-MK-7-100mcg.aspx"
if "justvitamins" in url:
d = scrape_product(url)
else:
d = scrape_competitor(url)
print(json.dumps(d, indent=2))
print(json.dumps(d, indent=2, default=str))