562 lines
27 KiB
Python
562 lines
27 KiB
Python
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import asyncio
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import random
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from typing import Optional, Dict
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from playwright.async_api import async_playwright, TimeoutError as PlaywrightTimeoutError
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from browserforge.injectors.playwright import AsyncNewContext
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from llm_agent import LLMJobRefiner
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import re
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from fetcher import StealthyFetcher
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from datetime import datetime
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import json
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import redis
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class LinkedInJobScraper:
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def __init__(
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self,
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engine,
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db_path: str = "linkedin_jobs.db",
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human_speed: float = 1.0,
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user_request: str = "Extract all standard job details"
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):
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self.engine = engine
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self.db_path = db_path
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self.human_speed = human_speed
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self.user_request = user_request
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self._init_db()
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self.llm_agent = LLMJobRefiner()
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# Initialize Redis connection
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self.redis_client = redis.Redis(host='localhost', port=6379, db=0, decode_responses=True)
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def _init_db(self):
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# This method is kept for backward compatibility but LLMJobRefiner handles PostgreSQL now
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pass
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async def _human_click(self, page, element, wait_after: bool = True):
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if not element:
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return False
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await element.scroll_into_view_if_needed()
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await asyncio.sleep(random.uniform(0.3, 0.8) * self.human_speed)
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try:
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await element.click()
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if wait_after:
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await asyncio.sleep(random.uniform(2, 4) * self.human_speed)
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return True
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except:
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return False
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async def _login(self, page, credentials: Dict) -> bool:
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print("🔐 Navigating to LinkedIn login page...")
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await page.goto("https://www.linkedin.com/login", timeout=120000)
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await asyncio.sleep(random.uniform(2.0, 3.5) * self.human_speed)
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email_field = await page.query_selector('input[name="session_key"]')
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if not email_field:
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print("❌ Email field not found.")
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return False
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print("✍️ Typing username...")
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await email_field.click()
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await asyncio.sleep(random.uniform(0.4, 0.9) * self.human_speed)
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for char in credentials["email"]:
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await page.keyboard.type(char)
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await asyncio.sleep(random.uniform(0.06, 0.14) * self.human_speed)
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await asyncio.sleep(random.uniform(1.0, 1.8) * self.human_speed)
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password_field = await page.query_selector('input[name="session_password"]')
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if not password_field:
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print("❌ Password field not found.")
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return False
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print("🔒 Typing password...")
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await password_field.click()
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await asyncio.sleep(random.uniform(0.3, 0.7) * self.human_speed)
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for char in credentials["password"]:
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await page.keyboard.type(char)
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await asyncio.sleep(random.uniform(0.08, 0.16) * self.human_speed)
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await asyncio.sleep(random.uniform(0.8, 1.5) * self.human_speed)
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print("✅ Submitting login form...")
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await page.keyboard.press("Enter")
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for _ in range(15):
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current_url = page.url
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if "/feed" in current_url or "/jobs" in current_url:
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if "login" not in current_url:
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print("✅ Login successful!")
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await asyncio.sleep(random.uniform(2.0, 3.0) * self.human_speed)
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return True
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await asyncio.sleep(1)
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print("❌ Login may have failed.")
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return False
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async def _extract_page_content_for_llm(self, page) -> str:
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"""
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Extract raw page content as HTML/text for LLM processing
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The LLM will handle all extraction logic, not specific selectors
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"""
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await asyncio.sleep(2 * self.human_speed)
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await self.engine._human_like_scroll(page)
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await asyncio.sleep(2 * self.human_speed)
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page_content = await page.content()
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return page_content
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def _calculate_keyword_match(self, title: str, keywords: str) -> float:
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if not title or not keywords:
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return 0.0
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title_lower = title.lower()
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keyword_list = [kw.strip().lower() for kw in keywords.split()]
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matches = sum(1 for kw in keyword_list if kw in title_lower)
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return matches / len(keyword_list) if keyword_list else 0.0
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def _extract_location_from_keywords(self, search_keywords: str) -> str:
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location_match = re.search(r'location:\s*([^,]+)', search_keywords, re.IGNORECASE)
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return location_match.group(1).strip().lower() if location_match else ""
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async def _scrape_jobs_from_current_page(self, page, search_keywords: str, seen_job_ids, all_job_links):
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current_links = await page.query_selector_all("a[href*='/jobs/view/']")
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new_jobs = 0
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location_from_keywords = self._extract_location_from_keywords(search_keywords)
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for link in current_links:
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href = await link.get_attribute("href")
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if href:
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full_url = href if href.startswith("http") else f"https://www.linkedin.com{href}"
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job_id = href.split("/view/")[-1].split("/")[0] if "/view/" in href else href
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if job_id and job_id not in seen_job_ids:
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title_element = await link.query_selector("span.job-title, h3, .job-card-title")
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if title_element:
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title = await title_element.inner_text()
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match_percentage = self._calculate_keyword_match(title, search_keywords)
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location_match = True
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if location_from_keywords:
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location_element = await link.query_selector("span.job-location, .job-card-location, .location")
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if location_element:
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location_text = await location_element.inner_text()
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location_match = location_from_keywords in location_text.lower()
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if match_percentage >= 0.7 and location_match:
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seen_job_ids.add(job_id)
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all_job_links.append((href, title))
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new_jobs += 1
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elif match_percentage < 0.7:
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print(f" ⚠️ Skipping job due to low keyword match: {title[:50]}... (match: {match_percentage:.2%})")
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elif not location_match:
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print(f" ⚠️ Skipping job due to location mismatch: {title[:50]}... (expected: {location_from_keywords})")
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else:
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seen_job_ids.add(job_id)
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all_job_links.append((href, "Unknown Title"))
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new_jobs += 1
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return new_jobs
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async def _handle_pagination(self, page, search_keywords: str, seen_job_ids, all_job_links):
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current_page = 1
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while True:
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print(f"📄 Processing page {current_page}")
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new_jobs = await self._scrape_jobs_from_current_page(page, search_keywords, seen_job_ids, all_job_links)
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print(f" ➕ Found {new_jobs} new job(s) on page {current_page} (total: {len(all_job_links)})")
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next_btn = await page.query_selector("button[aria-label='Next']")
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if next_btn and await next_btn.is_enabled():
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await self._human_click(page, next_btn)
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await asyncio.sleep(random.uniform(4.0, 6.0) * self.human_speed)
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try:
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await page.wait_for_function("() => window.location.href.includes('start=')", timeout=120000)
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except:
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pass
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current_page += 1
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else:
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print("🔚 'Next' button not available — stopping pagination.")
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break
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async def _handle_infinite_scroll(self, page, search_keywords: str, seen_job_ids, all_job_links):
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last_height = await page.evaluate("document.body.scrollHeight")
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no_new_jobs_count = 0
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max_no_new = 3
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while no_new_jobs_count < max_no_new:
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await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
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await asyncio.sleep(random.uniform(3.0, 5.0) * self.human_speed)
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new_jobs_found = await self._scrape_jobs_from_current_page(page, search_keywords, seen_job_ids, all_job_links)
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print(f" ➕ Found {new_jobs_found} new job(s) (total: {len(all_job_links)})")
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new_height = await page.evaluate("document.body.scrollHeight")
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if new_height == last_height:
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no_new_jobs_count += 1
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else:
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no_new_jobs_count = 0
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last_height = new_height
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if new_jobs_found == 0 and no_new_jobs_count >= 1:
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print("🔚 No new jobs loaded. Stopping scroll.")
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break
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async def _extract_job_posted_date(self, page) -> str:
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"""
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Extract the job posted date from LinkedIn job page
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Returns date in MM/DD/YY format
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"""
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try:
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# Try multiple selectors for the posted date
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selectors = [
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"span[class*='posted-date']",
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"span:has-text('ago')",
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"span:has-text('Posted')",
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"span.job-details-jobs-unified-top-card__job-insight-view-model-secondary"
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]
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for selector in selectors:
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date_element = await page.query_selector(selector)
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if date_element:
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date_text = await date_element.inner_text()
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if date_text:
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# Clean the text
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date_text = date_text.strip()
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# Check if it contains "ago" (e.g., "2 hours ago", "1 day ago")
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if "ago" in date_text.lower():
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# Use current date since it's relative
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current_date = datetime.now()
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return current_date.strftime("%m/%d/%y")
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elif "Posted" in date_text:
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# Extract date from "Posted X days ago" or similar
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current_date = datetime.now()
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return current_date.strftime("%m/%d/%y")
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else:
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# Try to parse actual date formats
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# Common LinkedIn format: "Mar 15, 2025"
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import re
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date_match = re.search(r'([A-Za-z]+)\s+(\d{1,2}),\s+(\d{4})', date_text)
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if date_match:
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month_name = date_match.group(1)
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day = date_match.group(2)
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year = date_match.group(3)
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# Convert month name to number
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months = {
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'Jan': '01', 'Feb': '02', 'Mar': '03', 'Apr': '04',
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'May': '05', 'Jun': '06', 'Jul': '07', 'Aug': '08',
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'Sep': '09', 'Oct': '10', 'Nov': '11', 'Dec': '12'
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}
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month_num = months.get(month_name[:3], '01')
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return f"{month_num}/{day.zfill(2)}/{year[-2:]}"
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# If no date found, use current date
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current_date = datetime.now()
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return current_date.strftime("%m/%d/%y")
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except Exception as e:
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print(f" ⚠️ Error extracting posted date: {str(e)}")
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# Return current date as fallback
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current_date = datetime.now()
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return current_date.strftime("%m/%d/%y")
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async def _add_job_to_redis_cache(self, job_url: str, job_id: str, error_type: str):
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"""Add failed job to Redis cache for later retry"""
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try:
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job_data = {
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"job_url": job_url,
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"job_id": job_id,
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"error_type": error_type,
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"timestamp": datetime.now().isoformat()
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}
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# Use job_id as the key to avoid duplicates
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self.redis_client.hset("failed_jobs", job_id, json.dumps(job_data))
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print(f" 📦 Added failed job to Redis cache: {job_id} (Error: {error_type})")
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except Exception as e:
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print(f" ❌ Failed to add job to Redis cache: {str(e)}")
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async def scrape_jobs(
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self,
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search_keywords: Optional[str],
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max_pages: int = 1,
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credentials: Optional[Dict] = None
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):
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location_match = re.search(r'location:\s*([^,]+)', search_keywords, re.IGNORECASE)
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location = location_match.group(1).strip() if location_match else ""
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clean_keywords = re.sub(r'location:\s*[^,]+', '', search_keywords, flags=re.IGNORECASE).strip()
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encoded_keywords = clean_keywords.replace(" ", "%20")
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search_url = f"https://www.linkedin.com/jobs/search/?keywords={encoded_keywords}"
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if location:
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search_url += f"&location={location.replace(' ', '%20')}"
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profile = self.engine._select_profile()
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renderer = random.choice(self.engine.common_renderers[self.engine.os])
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vendor = random.choice(self.engine.common_vendors)
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spoof_script = self.engine._get_spoof_script(renderer, vendor)
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async with async_playwright() as pw:
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browser = await pw.chromium.launch(
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headless=False,
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args=['--disable-blink-features=AutomationControlled']
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)
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context = await AsyncNewContext(browser, fingerprint=profile)
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await context.add_init_script(f"""
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Object.defineProperty(navigator, 'hardwareConcurrency', {{ get: () => {profile.navigator.hardwareConcurrency} }});
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Object.defineProperty(navigator, 'deviceMemory', {{ get: () => {profile.navigator.deviceMemory} }});
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Object.defineProperty(navigator, 'platform', {{ get: () => '{profile.navigator.platform}' }});
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""")
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await context.add_init_script(spoof_script)
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page = await context.new_page()
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# Create a temporary fetcher for protection checks on main page
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temp_fetcher = StealthyFetcher(self.engine, browser, context)
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session_loaded = await self.engine.load_session(context)
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login_successful = False
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if session_loaded:
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print("🔁 Using saved session — verifying login...")
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await page.goto("https://www.linkedin.com/feed/", timeout=120000)
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if "feed" in page.url and "login" not in page.url:
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print("✅ Session still valid.")
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login_successful = True
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else:
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print("⚠️ Saved session expired — re-authenticating.")
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session_loaded = False
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if not session_loaded and credentials:
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print("🔐 Performing fresh login...")
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login_successful = await self._login(page, credentials)
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if login_successful:
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await self.engine.save_session(context)
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else:
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print("❌ Login failed. Exiting.")
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await browser.close()
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self.engine.report_outcome("block")
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return
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elif not credentials:
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print("ℹ️ No credentials — proceeding as guest.")
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login_successful = True
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await page.wait_for_load_state("load", timeout=120000)
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print("✅ Post-login page fully loaded. Starting search...")
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# >>> PROTECTION CHECK USING FETCHER LOGIC <<<
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protection_type = await temp_fetcher._detect_protection(page)
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if protection_type:
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print(f"🛡️ Protection detected on initial page: {protection_type}")
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content_accessible = await temp_fetcher._is_content_accessible(page)
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if not content_accessible:
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print("🔒 Content not accessible.")
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handled = False
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if protection_type == "cloudflare":
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handled = await self.engine._handle_cloudflare(page)
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elif protection_type == "captcha":
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handled = False
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if not handled:
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await browser.close()
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self.engine.report_outcome("protection_block")
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return
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else:
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print("✅ Protection present but content accessible — proceeding.")
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print(f"🔍 Searching for: {search_keywords}")
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await page.goto(search_url, wait_until='load', timeout=120000)
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await asyncio.sleep(random.uniform(4.0, 6.0) * self.human_speed)
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# >>> PROTECTION CHECK ON SEARCH PAGE <<<
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protection_type = await temp_fetcher._detect_protection(page)
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if protection_type:
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print(f"🛡️ Protection detected on search page: {protection_type}")
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content_accessible = await temp_fetcher._is_content_accessible(page)
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if not content_accessible:
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print("🔒 Content not accessible.")
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handled = False
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if protection_type == "cloudflare":
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handled = await self.engine._handle_cloudflare(page)
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elif protection_type == "captcha":
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handled = False
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if not handled:
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await browser.close()
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self.engine.report_outcome("protection_block")
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return
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else:
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print("✅ Protection present but content accessible — proceeding.")
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all_job_links = []
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seen_job_ids = set()
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print("🔄 Collecting initial job links...")
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initial_jobs = await self._scrape_jobs_from_current_page(page, search_keywords, seen_job_ids, all_job_links)
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print(f" ➕ Found {initial_jobs} initial job(s) (total: {len(all_job_links)})")
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iteration = 1
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while iteration <= 5: # Fixed the condition - was "iteration >= 5" which never runs
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print(f"🔄 Iteration {iteration}: Checking for new jobs...")
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prev_job_count = len(all_job_links)
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await self._handle_infinite_scroll(page, search_keywords, seen_job_ids, all_job_links)
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new_jobs_count = len(all_job_links) - prev_job_count
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if new_jobs_count > 0:
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print(f" ➕ Found {new_jobs_count} new jobs via infinite scroll")
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iteration += 1
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continue
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pagination_exists = await page.query_selector("button[aria-label='Next']")
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if pagination_exists:
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print("⏭️ Pagination detected. Processing pages...")
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await self._handle_pagination(page, search_keywords, seen_job_ids, all_job_links)
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iteration += 1
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continue
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else:
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print("🔄 Refreshing page to check for new results...")
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await page.reload(wait_until='load')
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await asyncio.sleep(random.uniform(3.0, 5.0) * self.human_speed)
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new_jobs_after_refresh = await self._scrape_jobs_from_current_page(page, search_keywords, seen_job_ids, all_job_links)
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if new_jobs_after_refresh > 0:
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print(f" ➕ Found {new_jobs_after_refresh} new job(s) after refresh")
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iteration += 1
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continue
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else:
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print("🔚 No new jobs found after refresh. Stopping.")
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break
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print(f"✅ Collected {len(all_job_links)} unique job links.")
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scraped_count = 0
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for idx, (href, title) in enumerate(all_job_links):
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try:
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full_url = href if href.startswith("http") else f"https://www.linkedin.com{href}"
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print(f" → Opening job {idx+1}/{len(all_job_links)}: {full_url}")
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fetcher = StealthyFetcher(self.engine, browser, context)
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job_page = await fetcher.fetch_url(full_url, wait_for_selector="h1.t-24")
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if not job_page:
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print(f" ❌ Failed to fetch job page {full_url} after retries.")
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await self._add_job_to_redis_cache(full_url, full_url.split("/")[-2] if "/jobs/view/" in full_url else "unknown", "fetch_failure")
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self.engine.report_outcome("fetch_failure", url=full_url)
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continue
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# Extract posted date from the job page
|
||
posted_date = await self._extract_job_posted_date(job_page)
|
||
print(f" 📅 Posted date extracted: {posted_date}")
|
||
|
||
apply_btn = None
|
||
apply_selectors = [
|
||
"button[aria-label*='Apply']",
|
||
"button:has-text('Apply')",
|
||
"a:has-text('Apply')",
|
||
"button:has-text('Easy Apply')"
|
||
]
|
||
for selector in apply_selectors:
|
||
apply_btn = await job_page.query_selector(selector)
|
||
if apply_btn:
|
||
break
|
||
|
||
final_url = full_url
|
||
external_url = None
|
||
page_content = None
|
||
|
||
if apply_btn:
|
||
print(" → Clicking 'Apply' / 'Easy Apply' button...")
|
||
|
||
page_waiter = asyncio.create_task(context.wait_for_event("page"))
|
||
await self._human_click(job_page, apply_btn, wait_after=False)
|
||
|
||
external_page = None
|
||
try:
|
||
external_page = await asyncio.wait_for(page_waiter, timeout=5.0)
|
||
print(" 🌐 External job site opened in new tab.")
|
||
await external_page.wait_for_load_state("load", timeout=120000)
|
||
await asyncio.sleep(2 * self.human_speed)
|
||
await self.engine._human_like_scroll(external_page)
|
||
await asyncio.sleep(2 * self.human_speed)
|
||
|
||
# Extract raw content from external page for LLM processing
|
||
external_url = external_page.url
|
||
final_url = external_url
|
||
page_content = await self._extract_page_content_for_llm(external_page)
|
||
|
||
if not external_page.is_closed():
|
||
await external_page.close()
|
||
|
||
except asyncio.TimeoutError:
|
||
print(" 🖥️ No external tab — scraping LinkedIn job page directly.")
|
||
await job_page.wait_for_timeout(60000)
|
||
try:
|
||
await job_page.wait_for_selector("div.jobs-apply-button--fixed, div.jobs-easy-apply-modal", timeout=80000)
|
||
except PlaywrightTimeoutError:
|
||
pass
|
||
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)
|
||
else:
|
||
print(" ⚠️ No 'Apply' button found — scraping job details directly.")
|
||
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 = full_url.split("/")[-2] if "/jobs/view/" in full_url else "unknown"
|
||
|
||
raw_data = {
|
||
"page_content": page_content,
|
||
"url": final_url,
|
||
"job_id": job_id,
|
||
"search_keywords": search_keywords,
|
||
"posted_date": posted_date # Add the posted date to raw data
|
||
}
|
||
|
||
# LLM agent is now fully responsible for extraction and validation
|
||
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 are present (fallback if LLM missed them)
|
||
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] = final_url
|
||
elif field == 'company_name':
|
||
refined_data[field] = "Unknown Company"
|
||
|
||
refined_data['scraped_at'] = datetime.now().isoformat()
|
||
refined_data['category'] = clean_keywords
|
||
refined_data['posted_date'] = posted_date # Add posted date to refined data
|
||
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=raw_data["url"])
|
||
else:
|
||
print(f" 🟡 Could not extract meaningful data from: {final_url}")
|
||
await self._add_job_to_redis_cache(final_url, job_id, "llm_failure")
|
||
self.engine.report_outcome("llm_failure", url=raw_data["url"])
|
||
|
||
await job_page.close()
|
||
|
||
except Exception as e:
|
||
error_msg = str(e)[:100]
|
||
print(f" ⚠️ Failed on job {idx+1}: {error_msg}")
|
||
job_id = full_url.split("/")[-2] if "/jobs/view/" in full_url else "unknown" if 'full_url' in locals() else "unknown"
|
||
job_url = full_url if 'full_url' in locals() else "unknown"
|
||
await self._add_job_to_redis_cache(job_url, job_id, f"exception: {error_msg}")
|
||
if 'job_page' in locals() and job_page:
|
||
await job_page.close()
|
||
continue
|
||
|
||
finally:
|
||
print(" ↩️ Returning to LinkedIn search results...")
|
||
await page.goto(search_url, timeout=120000)
|
||
await asyncio.sleep(4 * self.human_speed)
|
||
|
||
await browser.close()
|
||
|
||
if scraped_count > 0:
|
||
self.engine.report_outcome("success")
|
||
print(f"✅ Completed! Processed {scraped_count} jobs for '{search_keywords}' based on request '{self.user_request}'.")
|
||
else:
|
||
self.engine.report_outcome("captcha")
|
||
print("⚠️ No jobs processed successfully.")
|