mirror of https://github.com/Bunsly/JobSpy
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@ -62,7 +62,7 @@ zip_recruiter Software Developer TEKsystems Phoenix
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```plaintext
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Required
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├── site_type (List[enum]): linkedin, zip_recruiter, indeed
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├── site_type (List[enum]): linkedin, zip_recruiter, indeed, glassdoor
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└── search_term (str)
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Optional
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├── location (int)
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@ -107,18 +107,19 @@ The following exceptions may be raised when using JobSpy:
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* `LinkedInException`
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* `IndeedException`
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* `ZipRecruiterException`
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* `GlassdoorException`
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## Supported Countries for Job Searching
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### **LinkedIn**
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LinkedIn searches globally & uses only the `location` parameter.
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LinkedIn searches globally & uses only the `location` parameter. You can only fetch 1000 jobs max from the LinkedIn endpoint we're using
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### **ZipRecruiter**
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ZipRecruiter searches for jobs in **US/Canada** & uses only the `location` parameter.
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### **Indeed**
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### **Indeed / Glassdoor**
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Indeed & Glassdoor supports most countries, but the `country_indeed` parameter is required. Additionally, use the `location`
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parameter to narrow down the location, e.g. city & state if necessary.
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@ -145,6 +146,7 @@ You can specify the following countries when searching on Indeed (use the exact
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| Venezuela | Vietnam | | |
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Glassdoor can only fetch 900 jobs from the endpoint we're using on a given search.
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## Frequently Asked Questions
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---
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@ -1,6 +1,6 @@
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[tool.poetry]
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name = "python-jobspy"
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version = "1.1.25"
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version = "1.1.26"
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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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homepage = "https://github.com/Bunsly/JobSpy"
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@ -163,6 +163,7 @@ def scrape_jobs(
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"site",
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"title",
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"company",
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"company_url",
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"location",
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"job_type",
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"date_posted",
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@ -196,6 +196,8 @@ class JobPost(BaseModel):
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location: Optional[Location]
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description: str | None = None
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company_url: str | None = None
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job_type: list[JobType] | None = None
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compensation: Compensation | None = None
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date_posted: date | None = None
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@ -10,10 +10,10 @@ from datetime import datetime
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import requests
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import time
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from requests.exceptions import ProxyError
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from bs4 import BeautifulSoup
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from bs4.element import Tag
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from threading import Lock
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from urllib.parse import urlparse, urlunparse
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from .. import Scraper, ScraperInput, Site
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from ..utils import count_urgent_words, extract_emails_from_text, get_enum_from_job_type
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@ -66,12 +66,10 @@ class LinkedInScraper(Scraper):
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if scraper_input.job_type
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else None,
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"pageNum": 0,
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page: page + scraper_input.offset,
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"start": page + scraper_input.offset,
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"f_AL": "true" if scraper_input.easy_apply else None,
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}
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params = {k: v for k, v in params.items() if v is not None}
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params = {k: v for k, v in params.items() if v is not None}
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retries = 0
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while retries < self.MAX_RETRIES:
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@ -88,7 +86,7 @@ class LinkedInScraper(Scraper):
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break
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except requests.HTTPError as e:
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if hasattr(e, "response") and e.response is not None:
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if e.response.status_code == 429:
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if e.response.status_code in (429, 502):
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time.sleep(self.DELAY)
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retries += 1
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continue
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@ -110,8 +108,6 @@ class LinkedInScraper(Scraper):
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soup = BeautifulSoup(response.text, "html.parser")
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with ThreadPoolExecutor(max_workers=5) as executor:
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futures = []
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for job_card in soup.find_all("div", class_="base-search-card"):
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job_url = None
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href_tag = job_card.find("a", class_="base-card__full-link")
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@ -125,17 +121,14 @@ class LinkedInScraper(Scraper):
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continue
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seen_urls.add(job_url)
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futures.append(executor.submit(self.process_job, job_card, job_url))
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for future in as_completed(futures):
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# Call process_job directly without threading
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try:
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job_post = future.result()
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job_post = self.process_job(job_card, job_url)
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if job_post:
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job_list.append(job_post)
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except Exception as e:
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raise LinkedInException(
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"Exception occurred while processing jobs"
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)
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raise LinkedInException("Exception occurred while processing jobs")
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page += 25
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job_list = job_list[: scraper_input.results_wanted]
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@ -147,6 +140,11 @@ class LinkedInScraper(Scraper):
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company_tag = job_card.find("h4", class_="base-search-card__subtitle")
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company_a_tag = company_tag.find("a") if company_tag else None
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company_url = (
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urlunparse(urlparse(company_a_tag.get("href"))._replace(query=""))
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if company_a_tag and company_a_tag.has_attr("href")
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else ""
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)
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company = company_a_tag.get_text(strip=True) if company_a_tag else "N/A"
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metadata_card = job_card.find("div", class_="base-search-card__metadata")
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@ -168,11 +166,13 @@ class LinkedInScraper(Scraper):
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benefits = " ".join(benefits_tag.get_text().split()) if benefits_tag else None
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description, job_type = self.get_job_description(job_url)
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# description, job_type = None, []
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return JobPost(
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title=title,
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description=description,
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company_name=company,
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company_url=company_url,
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location=location,
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date_posted=date_posted,
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job_url=job_url,
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@ -193,8 +193,15 @@ class LinkedInScraper(Scraper):
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try:
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response = requests.get(job_page_url, timeout=5, proxies=self.proxy)
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response.raise_for_status()
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except requests.HTTPError as e:
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if hasattr(e, "response") and e.response is not None:
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if e.response.status_code in (429, 502):
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time.sleep(self.DELAY)
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return None, None
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except Exception as e:
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return None, None
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if response.url == "https://www.linkedin.com/signup":
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return None, None
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soup = BeautifulSoup(response.text, "html.parser")
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div_content = soup.find(
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@ -230,7 +237,7 @@ class LinkedInScraper(Scraper):
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employment_type = employment_type.lower()
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employment_type = employment_type.replace("-", "")
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return [get_enum_from_job_type(employment_type)]
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return [get_enum_from_job_type(employment_type)] if employment_type else []
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return description, get_job_type(soup)
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