""" jobspy.scrapers.linkedin ~~~~~~~~~~~~~~~~~~~ This module contains routines to scrape LinkedIn. """ import time import random from typing import Optional from datetime import datetime import requests from requests.exceptions import ProxyError from threading import Lock from bs4.element import Tag from bs4 import BeautifulSoup from urllib.parse import urlparse, urlunparse from .. import Scraper, ScraperInput, Site from ..exceptions import LinkedInException from ..utils import create_session from ...jobs import ( JobPost, Location, JobResponse, JobType, Country, Compensation ) from ..utils import ( count_urgent_words, extract_emails_from_text, get_enum_from_job_type, currency_parser, modify_and_get_description ) class LinkedInScraper(Scraper): DELAY = 3 def __init__(self, proxy: Optional[str] = None): """ Initializes LinkedInScraper with the LinkedIn job search url """ site = Site(Site.LINKEDIN) self.country = "worldwide" self.url = "https://www.linkedin.com" super().__init__(site, proxy=proxy) def scrape(self, scraper_input: ScraperInput) -> JobResponse: """ Scrapes LinkedIn for jobs with scraper_input criteria :param scraper_input: :return: job_response """ job_list: list[JobPost] = [] seen_urls = set() url_lock = Lock() page = scraper_input.offset // 25 + 25 if scraper_input.offset else 0 def job_type_code(job_type_enum): mapping = { JobType.FULL_TIME: "F", JobType.PART_TIME: "P", JobType.INTERNSHIP: "I", JobType.CONTRACT: "C", JobType.TEMPORARY: "T", } return mapping.get(job_type_enum, "") while len(job_list) < scraper_input.results_wanted and page < 1000: session = create_session(is_tls=False, has_retry=True, delay=5) params = { "keywords": scraper_input.search_term, "location": scraper_input.location, "distance": scraper_input.distance, "f_WT": 2 if scraper_input.is_remote else None, "f_JT": job_type_code(scraper_input.job_type) if scraper_input.job_type else None, "pageNum": 0, "start": page + scraper_input.offset, "f_AL": "true" if scraper_input.easy_apply else None, } params = {k: v for k, v in params.items() if v is not None} try: response = session.get( f"{self.url}/jobs-guest/jobs/api/seeMoreJobPostings/search?", params=params, allow_redirects=True, proxies=self.proxy, headers=self.headers(), timeout=10, ) response.raise_for_status() except requests.HTTPError as e: raise LinkedInException(f"bad response status code: {e.response.status_code}") except ProxyError as e: raise LinkedInException("bad proxy") except Exception as e: raise LinkedInException(str(e)) soup = BeautifulSoup(response.text, "html.parser") job_cards = soup.find_all("div", class_="base-search-card") if len(job_cards) == 0: return JobResponse(jobs=job_list) for job_card in job_cards: job_url = None href_tag = job_card.find("a", class_="base-card__full-link") if href_tag and "href" in href_tag.attrs: href = href_tag.attrs["href"].split("?")[0] job_id = href.split("-")[-1] job_url = f"{self.url}/jobs/view/{job_id}" with url_lock: if job_url in seen_urls: continue seen_urls.add(job_url) # Call process_job directly without threading try: job_post = self.process_job(job_card, job_url, scraper_input.full_description) if job_post: job_list.append(job_post) except Exception as e: raise LinkedInException("Exception occurred while processing jobs") page += 25 time.sleep(random.uniform(LinkedInScraper.DELAY, LinkedInScraper.DELAY + 2)) job_list = job_list[: scraper_input.results_wanted] return JobResponse(jobs=job_list) def process_job(self, job_card: Tag, job_url: str, full_descr: bool) -> Optional[JobPost]: salary_tag = job_card.find('span', class_='job-search-card__salary-info') compensation = None if salary_tag: salary_text = salary_tag.get_text(separator=' ').strip() salary_values = [currency_parser(value) for value in salary_text.split('-')] salary_min = salary_values[0] salary_max = salary_values[1] currency = salary_text[0] if salary_text[0] != '$' else 'USD' compensation = Compensation( min_amount=int(salary_min), max_amount=int(salary_max), currency=currency, ) title_tag = job_card.find("span", class_="sr-only") title = title_tag.get_text(strip=True) if title_tag else "N/A" company_tag = job_card.find("h4", class_="base-search-card__subtitle") company_a_tag = company_tag.find("a") if company_tag else None company_url = ( urlunparse(urlparse(company_a_tag.get("href"))._replace(query="")) if company_a_tag and company_a_tag.has_attr("href") else "" ) company = company_a_tag.get_text(strip=True) if company_a_tag else "N/A" metadata_card = job_card.find("div", class_="base-search-card__metadata") location = self.get_location(metadata_card) datetime_tag = ( metadata_card.find("time", class_="job-search-card__listdate") if metadata_card else None ) date_posted = description = job_type = None if datetime_tag and "datetime" in datetime_tag.attrs: datetime_str = datetime_tag["datetime"] try: date_posted = datetime.strptime(datetime_str, "%Y-%m-%d") except Exception as e: date_posted = None benefits_tag = job_card.find("span", class_="result-benefits__text") benefits = " ".join(benefits_tag.get_text().split()) if benefits_tag else None if full_descr: description, job_type = self.get_job_description(job_url) return JobPost( title=title, company_name=company, company_url=company_url, location=location, date_posted=date_posted, job_url=job_url, compensation=compensation, benefits=benefits, job_type=job_type, description=description, emails=extract_emails_from_text(description) if description else None, num_urgent_words=count_urgent_words(description) if description else None, ) def get_job_description( self, job_page_url: str ) -> tuple[None, None] | tuple[str | None, tuple[str | None, JobType | None]]: """ Retrieves job description by going to the job page url :param job_page_url: :return: description or None """ try: session = create_session(is_tls=False, has_retry=True) response = session.get(job_page_url, timeout=5, proxies=self.proxy) response.raise_for_status() except requests.HTTPError as e: return None, None except Exception as e: return None, None if response.url == "https://www.linkedin.com/signup": return None, None soup = BeautifulSoup(response.text, "html.parser") div_content = soup.find( "div", class_=lambda x: x and "show-more-less-html__markup" in x ) description = None if div_content: description = modify_and_get_description(div_content) def get_job_type( soup_job_type: BeautifulSoup, ) -> list[JobType] | None: """ Gets the job type from job page :param soup_job_type: :return: JobType """ h3_tag = soup_job_type.find( "h3", class_="description__job-criteria-subheader", string=lambda text: "Employment type" in text, ) employment_type = None if h3_tag: employment_type_span = h3_tag.find_next_sibling( "span", class_="description__job-criteria-text description__job-criteria-text--criteria", ) if employment_type_span: employment_type = employment_type_span.get_text(strip=True) employment_type = employment_type.lower() employment_type = employment_type.replace("-", "") return [get_enum_from_job_type(employment_type)] if employment_type else [] return description, get_job_type(soup) def get_location(self, metadata_card: Optional[Tag]) -> Location: """ Extracts the location data from the job metadata card. :param metadata_card :return: location """ location = Location(country=Country.from_string(self.country)) if metadata_card is not None: location_tag = metadata_card.find( "span", class_="job-search-card__location" ) location_string = location_tag.text.strip() if location_tag else "N/A" parts = location_string.split(", ") if len(parts) == 2: city, state = parts location = Location( city=city, state=state, country=Country.from_string(self.country), ) elif len(parts) == 3: city, state, country = parts location = Location( city=city, state=state, country=Country.from_string(country), ) return location @staticmethod def headers() -> dict: return { 'authority': 'www.linkedin.com', 'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7', 'accept-language': 'en-US,en;q=0.9', 'cache-control': 'max-age=0', 'sec-ch-ua': '"Not_A Brand";v="8", "Chromium";v="120", "Google Chrome";v="120"', # 'sec-ch-ua-mobile': '?0', # 'sec-ch-ua-platform': '"macOS"', # 'sec-fetch-dest': 'document', # 'sec-fetch-mode': 'navigate', # 'sec-fetch-site': 'none', # 'sec-fetch-user': '?1', 'upgrade-insecure-requests': '1', 'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36' }