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Ofure:Ashby_agent
Ofure:amazon_agent
Ofure:llm_agent
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compare: Ofure:e49860faae3eb3f9c63001b7bd53ac05845447bb
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Ofure:amazon_agent
Ofure:llm_agent
Ofure:Headless
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235
amazon_job_scraper.py
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"Specifically for scraping job postings from Amazon Jobs."
import asyncio
import random
import re
from typing import Optional, Dict
from playwright.async_api import async_playwright, TimeoutError as PlaywrightTimeoutError
from browserforge.injectors.playwright import AsyncNewContext
from llm_agent import LLMJobRefiner
from fetcher import StealthyFetcher
from datetime import datetime
class AmazonJobScraper:
def __init__(
self,
engine,
db_path: str = "amazon_jobs.db",
human_speed: float = 1.0,
user_request: str = "Extract all standard job details"
):
self.engine = engine
self.db_path = db_path
self.human_speed = human_speed
self.user_request = user_request
self.llm_agent = LLMJobRefiner()
async def _human_click(self, page, element, wait_after: bool = True):
if not element:
return False
await element.scroll_into_view_if_needed()
await asyncio.sleep(random.uniform(0.3, 0.8) * self.human_speed)
try:
await element.click()
if wait_after:
await asyncio.sleep(random.uniform(1.0, 2.0) * self.human_speed)
return True
except:
return False
def _extract_location_from_keywords(self, search_keywords: str) -> str:
location_match = re.search(r'location:\s*([^,]+)', search_keywords, re.IGNORECASE)
return location_match.group(1).strip() if location_match else ""
def _build_amazon_search_url(self, keywords: str) -> str:
clean_keywords = re.sub(r'location:\s*[^,]+', '', keywords, flags=re.IGNORECASE).strip()
location = self._extract_location_from_keywords(keywords)
base_url = "https://www.amazon.jobs/en/search?"
params = []
if clean_keywords:
params.append(f"base_query={clean_keywords.replace(' ', '+')}")
if location:
params.append(f"loc_query={location.replace(' ', '+')}")
params.append("offset=0")
params.append("result_limit=10")
return base_url + "&".join(params)
async def _extract_page_content_for_llm(self, page) -> str:
await asyncio.sleep(2 * self.human_speed)
await self.engine._human_like_scroll(page)
await asyncio.sleep(2 * self.human_speed)
return await page.content()
async def _scrape_job_links_from_page(self, page, seen_job_ids, all_job_links):
job_cards = await page.query_selector_all('div.job-tile a[href^="/en/jobs/"]')
new_jobs = 0
for card in job_cards:
href = await card.get_attribute("href")
if not href:
continue
full_url = f"https://www.amazon.jobs{href}" if href.startswith("/") else href
job_id = href.split("/")[-1] if href.split("/")[-1] else "unknown"
if job_id in seen_job_ids:
continue
title_element = await card.query_selector('h3')
title = await title_element.inner_text() if title_element else "Unknown Title"
seen_job_ids.add(job_id)
all_job_links.append((full_url, title))
new_jobs += 1
return new_jobs
async def _scroll_and_collect_jobs(self, page, seen_job_ids, all_job_links, max_pages=5):
offset = 0
jobs_per_page = 10
for page_num in range(max_pages):
print(f"📄 Fetching Amazon job page {page_num + 1} (offset: {offset})")
current_url = page.url
if "offset=" in current_url:
base_url = current_url.split("offset=")[0]
new_url = base_url + f"offset={offset}&result_limit={jobs_per_page}"
else:
new_url = current_url + f"&offset={offset}&result_limit={jobs_per_page}"
await page.goto(new_url, wait_until='domcontentloaded', timeout=120000)
await asyncio.sleep(random.uniform(3.0, 5.0) * self.human_speed)
new_jobs = await self._scrape_job_links_from_page(page, seen_job_ids, all_job_links)
print(f" ➕ Found {new_jobs} new job(s) on page {page_num + 1} (total: {len(all_job_links)})")
if new_jobs == 0 and page_num > 0:
print("🔚 No new jobs — stopping pagination.")
break
offset += jobs_per_page
async def scrape_jobs(
self,
search_keywords: Optional[str],
max_pages: int = 5,
credentials: Optional[Dict] = None # Not used for Amazon
):
search_url = self._build_amazon_search_url(search_keywords)
print(f"🔍 Amazon search URL: {search_url}")
profile = self.engine._select_profile()
renderer = random.choice(self.engine.common_renderers[self.engine.os])
vendor = random.choice(self.engine.common_vendors)
spoof_script = self.engine._get_spoof_script(renderer, vendor)
async with async_playwright() as pw:
browser = await pw.chromium.launch(
headless=False,
args=['--disable-blink-features=AutomationControlled']
)
context = await AsyncNewContext(browser, fingerprint=profile)
await context.add_init_script(f"""
Object.defineProperty(navigator, 'hardwareConcurrency', {{ get: () => {profile.navigator.hardwareConcurrency} }});
Object.defineProperty(navigator, 'deviceMemory', {{ get: () => {profile.navigator.deviceMemory} }});
Object.defineProperty(navigator, 'platform', {{ get: () => '{profile.navigator.platform}' }});
""")
await context.add_init_script(spoof_script)
page = await context.new_page()
temp_fetcher = StealthyFetcher(self.engine, browser, context)
# Amazon doesn't require login
print("🌐 Navigating to Amazon Jobs (no login required)...")
await page.goto(search_url, wait_until='domcontentloaded', timeout=120000)
await asyncio.sleep(random.uniform(3.0, 5.0) * self.human_speed)
# Protection check
protection_type = await temp_fetcher._detect_protection(page)
if protection_type:
print(f"🛡️ Protection detected: {protection_type}")
content_accessible = await temp_fetcher._is_content_accessible(page)
if not content_accessible:
handled = await self.engine._handle_cloudflare(page) if protection_type == "cloudflare" else False
if not handled:
await browser.close()
self.engine.report_outcome("protection_block")
return
else:
print("✅ Protection present but content accessible.")
all_job_links = []
seen_job_ids = set()
print("🔄 Collecting job links via pagination...")
await self._scroll_and_collect_jobs(page, seen_job_ids, all_job_links, max_pages=max_pages)
print(f"✅ Collected {len(all_job_links)} unique Amazon job links.")
scraped_count = 0
for idx, (job_url, title) in enumerate(all_job_links):
try:
print(f" → Opening job {idx+1}/{len(all_job_links)}: {job_url}")
fetcher = StealthyFetcher(self.engine, browser, context)
job_page = await fetcher.fetch_url(job_url, wait_for_selector="h1.job-title")
if not job_page:
print(f" ❌ Failed to fetch job page: {job_url}")
self.engine.report_outcome("fetch_failure", url=job_url)
continue
# Extract raw HTML for LLM
await self.engine._human_like_scroll(job_page)
await asyncio.sleep(2 * self.human_speed)
page_content = await self._extract_page_content_for_llm(job_page)
job_id = job_url.split("/")[-1] if job_url.split("/")[-1] else "unknown"
raw_data = {
"page_content": page_content,
"url": job_url,
"job_id": job_id,
"search_keywords": search_keywords
}
refined_data = await self.llm_agent.refine_job_data(raw_data, self.user_request)
if refined_data and refined_data.get("title", "N/A") != "N/A":
# Ensure compulsory fields
compulsory_fields = ['company_name', 'job_id', 'url']
for field in compulsory_fields:
if not refined_data.get(field) or refined_data[field] in ["N/A", "", "Unknown"]:
if field == 'job_id':
refined_data[field] = job_id
elif field == 'url':
refined_data[field] = job_url
elif field == 'company_name':
refined_data[field] = "Amazon"
refined_data['scraped_at'] = datetime.now().isoformat()
refined_data['category'] = re.sub(r'location:\s*[^,]+', '', search_keywords, flags=re.IGNORECASE).strip()
await self.llm_agent.save_job_data(refined_data, search_keywords)
scraped_count += 1
print(f" ✅ Scraped and refined: {refined_data['title'][:50]}...")
self.engine.report_outcome("success", url=job_url)
else:
print(f" 🟡 LLM could not extract valid data from: {job_url}")
self.engine.report_outcome("llm_failure", url=job_url)
await job_page.close()
except Exception as e:
print(f" ⚠️ Failed on job {idx+1}: {str(e)[:100]}")
if 'job_page' in locals() and job_page:
await job_page.close()
continue
await browser.close()
if scraped_count > 0:
self.engine.report_outcome("success")
print(f"✅ Completed! Processed {scraped_count} Amazon jobs for '{search_keywords}'.")
else:
self.engine.report_outcome("no_jobs")
print("⚠️ No Amazon jobs processed successfully.")

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amazon_main.py
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from scraping_engine import FingerprintScrapingEngine
from amazon_job_scraper import AmazonJobScraper # Updated class name
from dotenv import load_dotenv
import asyncio
import random
import time
load_dotenv()
async def main():
engine = FingerprintScrapingEngine(
seed="amazon_job_scraping_12",
target_os="windows",
db_path="amazon_jobs.db",
markdown_path="amazon_jobs.md"
)
scraper = AmazonJobScraper(
engine,
human_speed=1.4,
user_request="Extract title, company, location, description, basic qualifications, preferred qualifications, job ID, and job type (full-time, part-time, etc.)"
)
job_titles = [
"Software Development Engineer",
"Data Scientist",
"Product Manager",
"UX Designer",
"Solutions Architect",
"Machine Learning Engineer",
"Frontend Engineer",
"Backend Engineer",
"Full Stack Engineer",
"Data Engineer"
]
fixed_location = "United States" # Amazon uses country/region, not city
while True:
random.shuffle(job_titles)
for job_title in job_titles:
search_keywords = f"{job_title} location:{fixed_location}"
print(f"\n{'='*60}")
print(f"Starting Amazon scrape for: {search_keywords}")
print(f"{'='*60}")
await scraper.scrape_jobs(
search_keywords=search_keywords,
max_pages=3 # Amazon loads 10 per page; 3 pages = ~30 jobs
)
print(f"\n✅ Completed scraping for: {job_title}")
print(f"⏳ Waiting 90 seconds before next job title...")
time.sleep(90)
print(f"\n✅ Completed full cycle. Restarting...")
if __name__ == "__main__":
asyncio.run(main())