mirror of https://github.com/Bunsly/JobSpy
parent
2ec3b04777
commit
5b3627b244
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@ -67,6 +67,7 @@ Optional
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├── job_type (enum): fulltime, parttime, internship, contract
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├── job_type (enum): fulltime, parttime, internship, contract
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├── proxy (str): in format 'http://user:pass@host:port' or [https, socks]
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├── proxy (str): in format 'http://user:pass@host:port' or [https, socks]
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├── is_remote (bool)
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├── is_remote (bool)
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├── full_description (bool): fetches full description for Indeed / LinkedIn (much slower)
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├── results_wanted (int): number of job results to retrieve for each site specified in 'site_type'
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├── results_wanted (int): number of job results to retrieve for each site specified in 'site_type'
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├── easy_apply (bool): filters for jobs that are hosted on LinkedIn
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├── easy_apply (bool): filters for jobs that are hosted on LinkedIn
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├── country_indeed (enum): filters the country on Indeed (see below for correct spelling)
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├── country_indeed (enum): filters the country on Indeed (see below for correct spelling)
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@ -1,6 +1,6 @@
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[tool.poetry]
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[tool.poetry]
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name = "python-jobspy"
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name = "python-jobspy"
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version = "1.1.34"
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version = "1.1.35"
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description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
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description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
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authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
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authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
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homepage = "https://github.com/Bunsly/JobSpy"
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homepage = "https://github.com/Bunsly/JobSpy"
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@ -40,6 +40,7 @@ def scrape_jobs(
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country_indeed: str = "usa",
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country_indeed: str = "usa",
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hyperlinks: bool = False,
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hyperlinks: bool = False,
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proxy: Optional[str] = None,
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proxy: Optional[str] = None,
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full_description: Optional[bool] = False,
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offset: Optional[int] = 0,
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offset: Optional[int] = 0,
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) -> pd.DataFrame:
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) -> pd.DataFrame:
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"""
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"""
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@ -74,6 +75,7 @@ def scrape_jobs(
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is_remote=is_remote,
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is_remote=is_remote,
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job_type=job_type,
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job_type=job_type,
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easy_apply=easy_apply,
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easy_apply=easy_apply,
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full_description=full_description,
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results_wanted=results_wanted,
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results_wanted=results_wanted,
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offset=offset,
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offset=offset,
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)
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)
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@ -19,6 +19,7 @@ class ScraperInput(BaseModel):
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is_remote: bool = False
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is_remote: bool = False
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job_type: Optional[JobType] = None
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job_type: Optional[JobType] = None
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easy_apply: bool = None # linkedin
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easy_apply: bool = None # linkedin
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full_description: bool = False
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offset: int = 0
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offset: int = 0
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results_wanted: int = 15
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results_wanted: int = 15
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@ -5,8 +5,12 @@ jobspy.scrapers.glassdoor
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This module contains routines to scrape Glassdoor.
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This module contains routines to scrape Glassdoor.
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"""
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"""
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import json
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import json
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from typing import Optional, Any
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import requests
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from bs4 import BeautifulSoup
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from typing import Optional
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from datetime import datetime, timedelta
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from datetime import datetime, timedelta
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from ..utils import count_urgent_words, extract_emails_from_text
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from .. import Scraper, ScraperInput, Site
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from .. import Scraper, ScraperInput, Site
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from ..exceptions import GlassdoorException
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from ..exceptions import GlassdoorException
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@ -66,14 +70,29 @@ class GlassdoorScraper(Scraper):
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jobs_data = res_json["data"]["jobListings"]["jobListings"]
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jobs_data = res_json["data"]["jobListings"]["jobListings"]
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jobs = []
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jobs = []
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for i, job in enumerate(jobs_data):
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with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
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job_url = res_json["data"]["jobListings"]["jobListingSeoLinks"][
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future_to_job_data = {executor.submit(self.process_job, job): job for job in jobs_data}
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"linkItems"
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for future in as_completed(future_to_job_data):
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][i]["url"]
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job_data = future_to_job_data[future]
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try:
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job_post = future.result()
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if job_post:
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jobs.append(job_post)
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except Exception as exc:
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raise GlassdoorException(f'Glassdoor generated an exception: {exc}')
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return jobs, self.get_cursor_for_page(
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res_json["data"]["jobListings"]["paginationCursors"], page_num + 1
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)
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def process_job(self, job_data):
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"""Processes a single job and fetches its description."""
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job_id = job_data["jobview"]["job"]["listingId"]
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job_url = f'{self.url}/job-listing/?jl={job_id}'
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if job_url in self.seen_urls:
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if job_url in self.seen_urls:
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continue
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return None
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self.seen_urls.add(job_url)
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self.seen_urls.add(job_url)
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job = job["jobview"]
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job = job_data["jobview"]
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title = job["job"]["jobTitleText"]
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title = job["job"]["jobTitleText"]
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company_name = job["header"]["employerNameFromSearch"]
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company_name = job["header"]["employerNameFromSearch"]
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location_name = job["header"].get("locationName", "")
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location_name = job["header"].get("locationName", "")
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@ -89,20 +108,24 @@ class GlassdoorScraper(Scraper):
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compensation = self.parse_compensation(job["header"])
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compensation = self.parse_compensation(job["header"])
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job = JobPost(
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try:
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description = self.fetch_job_description(job_id)
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except Exception as e :
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description = None
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job_post = JobPost(
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title=title,
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title=title,
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company_name=company_name,
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company_name=company_name,
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date_posted=date_posted,
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date_posted=date_posted,
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job_url=job_url,
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job_url=job_url,
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location=location,
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location=location,
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compensation=compensation,
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compensation=compensation,
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is_remote=is_remote
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is_remote=is_remote,
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)
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description=description,
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jobs.append(job)
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emails=extract_emails_from_text(description) if description else None,
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num_urgent_words=count_urgent_words(description) if description else None,
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return jobs, self.get_cursor_for_page(
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res_json["data"]["jobListings"]["paginationCursors"], page_num + 1
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)
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)
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return job_post
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def scrape(self, scraper_input: ScraperInput) -> JobResponse:
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def scrape(self, scraper_input: ScraperInput) -> JobResponse:
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"""
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"""
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@ -110,6 +133,7 @@ class GlassdoorScraper(Scraper):
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:param scraper_input: Information about job search criteria.
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:param scraper_input: Information about job search criteria.
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:return: JobResponse containing a list of jobs.
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:return: JobResponse containing a list of jobs.
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"""
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"""
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scraper_input.results_wanted = min(900, scraper_input.results_wanted)
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self.country = scraper_input.country
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self.country = scraper_input.country
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self.url = self.country.get_url()
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self.url = self.country.get_url()
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@ -143,6 +167,43 @@ class GlassdoorScraper(Scraper):
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return JobResponse(jobs=all_jobs)
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return JobResponse(jobs=all_jobs)
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def fetch_job_description(self, job_id):
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"""Fetches the job description for a single job ID."""
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url = f"{self.url}/graph"
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body = [
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{
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"operationName": "JobDetailQuery",
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"variables": {
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"jl": job_id,
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"queryString": "q",
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"pageTypeEnum": "SERP"
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},
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"query": """
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query JobDetailQuery($jl: Long!, $queryString: String, $pageTypeEnum: PageTypeEnum) {
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jobview: jobView(
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listingId: $jl
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contextHolder: {queryString: $queryString, pageTypeEnum: $pageTypeEnum}
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) {
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job {
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description
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__typename
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}
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__typename
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}
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}
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"""
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}
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]
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response = requests.post(url, json=body, headers=GlassdoorScraper.headers())
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if response.status_code != 200:
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return None
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data = response.json()[0]
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desc = data['data']['jobview']['job']['description']
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soup = BeautifulSoup(desc, 'html.parser')
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description = soup.get_text(separator='\n')
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return description
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@staticmethod
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@staticmethod
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def parse_compensation(data: dict) -> Optional[Compensation]:
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def parse_compensation(data: dict) -> Optional[Compensation]:
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pay_period = data.get("payPeriod")
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pay_period = data.get("payPeriod")
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@ -78,7 +78,7 @@ class IndeedScraper(Scraper):
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if sc_values:
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if sc_values:
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params["sc"] = "0kf:" + "".join(sc_values) + ";"
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params["sc"] = "0kf:" + "".join(sc_values) + ";"
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try:
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try:
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session = create_session(self.proxy, is_tls=True)
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session = create_session(self.proxy)
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response = session.get(
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response = session.get(
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f"{self.url}/jobs",
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f"{self.url}/jobs",
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headers=self.get_headers(),
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headers=self.get_headers(),
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date_posted = datetime.fromtimestamp(timestamp_seconds)
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date_posted = datetime.fromtimestamp(timestamp_seconds)
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date_posted = date_posted.strftime("%Y-%m-%d")
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date_posted = date_posted.strftime("%Y-%m-%d")
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description = self.get_description(job_url)
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description = self.get_description(job_url) if scraper_input.full_description else None
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with io.StringIO(job["snippet"]) as f:
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with io.StringIO(job["snippet"]) as f:
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soup_io = BeautifulSoup(f, "html.parser")
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soup_io = BeautifulSoup(f, "html.parser")
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li_elements = soup_io.find_all("li")
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li_elements = soup_io.find_all("li")
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return None
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return None
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soup = BeautifulSoup(job_description, "html.parser")
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soup = BeautifulSoup(job_description, "html.parser")
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text_content = " ".join(soup.get_text(separator=" ").split()).strip()
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text_content = "\n".join(soup.stripped_strings)
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return text_content
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return text_content
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@ -111,7 +111,7 @@ class LinkedInScraper(Scraper):
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# Call process_job directly without threading
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# Call process_job directly without threading
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try:
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try:
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job_post = self.process_job(job_card, job_url)
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job_post = self.process_job(job_card, job_url, scraper_input.full_description)
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if job_post:
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if job_post:
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job_list.append(job_post)
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job_list.append(job_post)
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except Exception as e:
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except Exception as e:
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@ -123,7 +123,7 @@ class LinkedInScraper(Scraper):
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job_list = job_list[: scraper_input.results_wanted]
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job_list = job_list[: scraper_input.results_wanted]
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return JobResponse(jobs=job_list)
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return JobResponse(jobs=job_list)
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def process_job(self, job_card: Tag, job_url: str) -> Optional[JobPost]:
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def process_job(self, job_card: Tag, job_url: str, full_descr: bool) -> Optional[JobPost]:
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salary_tag = job_card.find('span', class_='job-search-card__salary-info')
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salary_tag = job_card.find('span', class_='job-search-card__salary-info')
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compensation = None
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compensation = None
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if metadata_card
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if metadata_card
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else None
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else None
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)
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)
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date_posted = None
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date_posted = description = job_type = None
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if datetime_tag and "datetime" in datetime_tag.attrs:
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if datetime_tag and "datetime" in datetime_tag.attrs:
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datetime_str = datetime_tag["datetime"]
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datetime_str = datetime_tag["datetime"]
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try:
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try:
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@ -169,9 +169,8 @@ class LinkedInScraper(Scraper):
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date_posted = None
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date_posted = None
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benefits_tag = job_card.find("span", class_="result-benefits__text")
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benefits_tag = job_card.find("span", class_="result-benefits__text")
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benefits = " ".join(benefits_tag.get_text().split()) if benefits_tag else None
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benefits = " ".join(benefits_tag.get_text().split()) if benefits_tag else None
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if full_descr:
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# removed to speed up scraping
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description, job_type = self.get_job_description(job_url)
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# description, job_type = self.get_job_description(job_url)
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return JobPost(
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return JobPost(
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title=title,
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title=title,
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job_url=job_url,
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job_url=job_url,
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compensation=compensation,
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compensation=compensation,
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benefits=benefits,
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benefits=benefits,
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# job_type=job_type,
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job_type=job_type,
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# description=description,
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description=description,
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# emails=extract_emails_from_text(description) if description else None,
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emails=extract_emails_from_text(description) if description else None,
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# num_urgent_words=count_urgent_words(description) if description else None,
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num_urgent_words=count_urgent_words(description) if description else None,
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)
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)
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def get_job_description(
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def get_job_description(
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description = None
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description = None
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if div_content:
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if div_content:
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description = " ".join(div_content.get_text().split()).strip()
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description = "\n".join(line.strip() for line in div_content.get_text(separator="\n").splitlines() if line.strip())
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def get_job_type(
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def get_job_type(
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soup_job_type: BeautifulSoup,
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soup_job_type: BeautifulSoup,
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@ -109,7 +109,7 @@ class ZipRecruiterScraper(Scraper):
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description = BeautifulSoup(
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description = BeautifulSoup(
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job.get("job_description", "").strip(), "html.parser"
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job.get("job_description", "").strip(), "html.parser"
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).get_text()
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).get_text(separator="\n")
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company = job["hiring_company"].get("name") if "hiring_company" in job else None
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company = job["hiring_company"].get("name") if "hiring_company" in job else None
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country_value = "usa" if job.get("job_country") == "US" else "canada"
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country_value = "usa" if job.get("job_country") == "US" else "canada"
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Reference in New Issue