Easy apply (#95)

* enh(glassdoor): easy apply filter

* enh(ziprecruiter): easy apply

* enh(indeed): use mobile headers

* chore: version

README.md

@@ -67,8 +67,9 @@ Optional
 ├── job_type (enum): fulltime, parttime, internship, contract
 ├── proxy (str): in format 'http://user:pass@host:port' or [https, socks]
 ├── is_remote (bool)
+├── full_description (bool): fetches full description for Indeed / LinkedIn (much slower)
 ├── results_wanted (int): number of job results to retrieve for each site specified in 'site_type'
-├── easy_apply (bool): filters for jobs that are hosted on LinkedIn
+├── easy_apply (bool): filters for jobs that are hosted on the job board site
 ├── country_indeed (enum): filters the country on Indeed (see below for correct spelling)
 ├── offset (num): starts the search from an offset (e.g. 25 will start the search from the 25th result)
 ```

poetry.lock

@@ -1053,16 +1053,6 @@ files = [
     {file = "MarkupSafe-2.1.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:5bbe06f8eeafd38e5d0a4894ffec89378b6c6a625ff57e3028921f8ff59318ac"},
     {file = "MarkupSafe-2.1.3-cp311-cp311-win32.whl", hash = "sha256:dd15ff04ffd7e05ffcb7fe79f1b98041b8ea30ae9234aed2a9168b5797c3effb"},
     {file = "MarkupSafe-2.1.3-cp311-cp311-win_amd64.whl", hash = "sha256:134da1eca9ec0ae528110ccc9e48041e0828d79f24121a1a146161103c76e686"},
-    {file = "MarkupSafe-2.1.3-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:f698de3fd0c4e6972b92290a45bd9b1536bffe8c6759c62471efaa8acb4c37bc"},
-    {file = "MarkupSafe-2.1.3-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:aa57bd9cf8ae831a362185ee444e15a93ecb2e344c8e52e4d721ea3ab6ef1823"},
-    {file = "MarkupSafe-2.1.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ffcc3f7c66b5f5b7931a5aa68fc9cecc51e685ef90282f4a82f0f5e9b704ad11"},
-    {file = "MarkupSafe-2.1.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:47d4f1c5f80fc62fdd7777d0d40a2e9dda0a05883ab11374334f6c4de38adffd"},
-    {file = "MarkupSafe-2.1.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:1f67c7038d560d92149c060157d623c542173016c4babc0c1913cca0564b9939"},
-    {file = "MarkupSafe-2.1.3-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:9aad3c1755095ce347e26488214ef77e0485a3c34a50c5a5e2471dff60b9dd9c"},
-    {file = "MarkupSafe-2.1.3-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:14ff806850827afd6b07a5f32bd917fb7f45b046ba40c57abdb636674a8b559c"},
-    {file = "MarkupSafe-2.1.3-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:8f9293864fe09b8149f0cc42ce56e3f0e54de883a9de90cd427f191c346eb2e1"},
-    {file = "MarkupSafe-2.1.3-cp312-cp312-win32.whl", hash = "sha256:715d3562f79d540f251b99ebd6d8baa547118974341db04f5ad06d5ea3eb8007"},
-    {file = "MarkupSafe-2.1.3-cp312-cp312-win_amd64.whl", hash = "sha256:1b8dd8c3fd14349433c79fa8abeb573a55fc0fdd769133baac1f5e07abf54aeb"},
     {file = "MarkupSafe-2.1.3-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:8e254ae696c88d98da6555f5ace2279cf7cd5b3f52be2b5cf97feafe883b58d2"},
     {file = "MarkupSafe-2.1.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cb0932dc158471523c9637e807d9bfb93e06a95cbf010f1a38b98623b929ef2b"},
     {file = "MarkupSafe-2.1.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9402b03f1a1b4dc4c19845e5c749e3ab82d5078d16a2a4c2cd2df62d57bb0707"},
@@ -2270,13 +2260,13 @@ test = ["flake8", "isort", "pytest"]
 
 [[package]]
 name = "tls-client"
-version = "0.2.1"
+version = "1.0"
 description = "Advanced Python HTTP Client."
 optional = false
 python-versions = "*"
 files = [
-    {file = "tls_client-0.2.1-py3-none-any.whl", hash = "sha256:124a710952b979d5e20b4e2b7879b7958d6e48a259d0f5b83101055eb173f0bd"},
+    {file = "tls_client-1.0-py3-none-any.whl", hash = "sha256:f1183f5e18cb31914bd62d11b350a33ea0293ea80fb91d69a3072821dece3e66"},
-    {file = "tls_client-0.2.1.tar.gz", hash = "sha256:473fb4c671d9d4ca6b818548ab6e955640dd589767bfce520830c5618c2f2e2b"},
+    {file = "tls_client-1.0.tar.gz", hash = "sha256:7f6de48ad4a0ef69b72682c76ce604155971e07b4bfb2148a36276194ae3e7a0"},
 ]
 
 [[package]]
@@ -2445,4 +2435,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "f966f3979873eec2c3b13460067f5aa414c69aa8ab5cd3239c1cfa564fcb5deb"
+content-hash = "404a77d78066cbb2ef71015562baf44aa11d12aac29a191c1ccc7758bfda598a"

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "python-jobspy"
-version = "1.1.34"
+version = "1.1.38"
 description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
 authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
 homepage = "https://github.com/Bunsly/JobSpy"
@@ -13,7 +13,7 @@ packages = [
 [tool.poetry.dependencies]
 python = "^3.10"
 requests = "^2.31.0"
-tls-client = "^0.2.1"
+tls-client = "*"
 beautifulsoup4 = "^4.12.2"
 pandas = "^2.1.0"
 NUMPY = "1.24.2"

src/jobspy/__init__.py

@@ -40,6 +40,7 @@ def scrape_jobs(
     country_indeed: str = "usa",
     hyperlinks: bool = False,
     proxy: Optional[str] = None,
+    full_description: Optional[bool] = False,
     offset: Optional[int] = 0,
 ) -> pd.DataFrame:
     """
@@ -74,6 +75,7 @@ def scrape_jobs(
         is_remote=is_remote,
         job_type=job_type,
         easy_apply=easy_apply,
+        full_description=full_description,
         results_wanted=results_wanted,
         offset=offset,
     )

src/jobspy/jobs/__init__.py

@@ -1,7 +1,7 @@
-from typing import Union, Optional
+from typing import Optional
 from datetime import date
 from enum import Enum
-from pydantic import BaseModel, validator
+from pydantic import BaseModel
 
 
 class JobType(Enum):

src/jobspy/scrapers/__init__.py

@@ -19,6 +19,7 @@ class ScraperInput(BaseModel):
     is_remote: bool = False
     job_type: Optional[JobType] = None
     easy_apply: bool = None  # linkedin
+    full_description: bool = False
     offset: int = 0
 
     results_wanted: int = 15

src/jobspy/scrapers/glassdoor/__init__.py

@@ -5,12 +5,16 @@ jobspy.scrapers.glassdoor
 This module contains routines to scrape Glassdoor.
 """
 import json
-from typing import Optional, Any
+import requests
+from bs4 import BeautifulSoup
+from typing import Optional
 from datetime import datetime, timedelta
+from concurrent.futures import ThreadPoolExecutor, as_completed
+from ..utils import count_urgent_words, extract_emails_from_text
 
 from .. import Scraper, ScraperInput, Site
 from ..exceptions import GlassdoorException
-from ..utils import create_session
+from ..utils import create_session, modify_and_get_description
 from ...jobs import (
     JobPost,
     Compensation,
@@ -66,50 +70,72 @@ class GlassdoorScraper(Scraper):
         jobs_data = res_json["data"]["jobListings"]["jobListings"]
 
         jobs = []
-        for i, job in enumerate(jobs_data):
+        with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
-            job_url = res_json["data"]["jobListings"]["jobListingSeoLinks"][
+            future_to_job_data = {executor.submit(self.process_job, job): job for job in jobs_data}
-                "linkItems"
+            for future in as_completed(future_to_job_data):
-            ][i]["url"]
+                job_data = future_to_job_data[future]
-            if job_url in self.seen_urls:
+                try:
-                continue
+                    job_post = future.result()
-            self.seen_urls.add(job_url)
+                    if job_post:
-            job = job["jobview"]
+                        jobs.append(job_post)
-            title = job["job"]["jobTitleText"]
+                except Exception as exc:
-            company_name = job["header"]["employerNameFromSearch"]
+                    raise GlassdoorException(f'Glassdoor generated an exception: {exc}')
-            location_name = job["header"].get("locationName", "")
-            location_type = job["header"].get("locationType", "")
-            age_in_days = job["header"].get("ageInDays")
-            is_remote, location = False, None
-            date_posted = (datetime.now() - timedelta(days=age_in_days)).date() if age_in_days else None
-
-            if location_type == "S":
-                is_remote = True
-            else:
-                location = self.parse_location(location_name)
-
-            compensation = self.parse_compensation(job["header"])
-
-            job = JobPost(
-                title=title,
-                company_name=company_name,
-                date_posted=date_posted,
-                job_url=job_url,
-                location=location,
-                compensation=compensation,
-                is_remote=is_remote
-            )
-            jobs.append(job)
 
         return jobs, self.get_cursor_for_page(
             res_json["data"]["jobListings"]["paginationCursors"], page_num + 1
         )
 
+    def process_job(self, job_data):
+        """Processes a single job and fetches its description."""
+        job_id = job_data["jobview"]["job"]["listingId"]
+        job_url = f'{self.url}job-listing/j?jl={job_id}'
+        if job_url in self.seen_urls:
+            return None
+        self.seen_urls.add(job_url)
+        job = job_data["jobview"]
+        title = job["job"]["jobTitleText"]
+        company_name = job["header"]["employerNameFromSearch"]
+        company_id = job_data['jobview']['header']['employer']['id']
+        location_name = job["header"].get("locationName", "")
+        location_type = job["header"].get("locationType", "")
+        age_in_days = job["header"].get("ageInDays")
+        is_remote, location = False, None
+        date_posted = (datetime.now() - timedelta(days=age_in_days)).date() if age_in_days else None
+
+        if location_type == "S":
+            is_remote = True
+        else:
+            location = self.parse_location(location_name)
+
+        compensation = self.parse_compensation(job["header"])
+
+        try:
+            description = self.fetch_job_description(job_id)
+        except Exception as e :
+            description = None
+
+        job_post = JobPost(
+            title=title,
+            company_url=f"{self.url}Overview/W-EI_IE{company_id}.htm" if company_id else None,
+            company_name=company_name,
+            date_posted=date_posted,
+            job_url=job_url,
+            location=location,
+            compensation=compensation,
+            is_remote=is_remote,
+            description=description,
+            emails=extract_emails_from_text(description) if description else None,
+            num_urgent_words=count_urgent_words(description) if description else None,
+        )
+        return job_post
+
     def scrape(self, scraper_input: ScraperInput) -> JobResponse:
         """
         Scrapes Glassdoor for jobs with scraper_input criteria.
         :param scraper_input: Information about job search criteria.
         :return: JobResponse containing a list of jobs.
         """
+        scraper_input.results_wanted = min(900, scraper_input.results_wanted)
         self.country = scraper_input.country
         self.url = self.country.get_url()
 
@@ -143,6 +169,41 @@ class GlassdoorScraper(Scraper):
 
         return JobResponse(jobs=all_jobs)
 
+    def fetch_job_description(self, job_id):
+        """Fetches the job description for a single job ID."""
+        url = f"{self.url}/graph"
+        body = [
+            {
+                "operationName": "JobDetailQuery",
+                "variables": {
+                    "jl": job_id,
+                    "queryString": "q",
+                    "pageTypeEnum": "SERP"
+                },
+                "query": """
+                query JobDetailQuery($jl: Long!, $queryString: String, $pageTypeEnum: PageTypeEnum) {
+                    jobview: jobView(
+                        listingId: $jl
+                        contextHolder: {queryString: $queryString, pageTypeEnum: $pageTypeEnum}
+                    ) {
+                        job {
+                            description
+                            __typename
+                        }
+                        __typename
+                    }
+                }
+                """
+            }
+        ]
+        response = requests.post(url, json=body, headers=GlassdoorScraper.headers())
+        if response.status_code != 200:
+            return None
+        data = response.json()[0]
+        desc = data['data']['jobview']['job']['description']
+        soup = BeautifulSoup(desc, 'html.parser')
+        return modify_and_get_description(soup)
+
     @staticmethod
     def parse_compensation(data: dict) -> Optional[Compensation]:
         pay_period = data.get("payPeriod")
@@ -199,7 +260,7 @@ class GlassdoorScraper(Scraper):
             "operationName": "JobSearchResultsQuery",
             "variables": {
                 "excludeJobListingIds": [],
-                "filterParams": [],
+                "filterParams": [{"filterKey": "applicationType", "values": "1"}] if scraper_input.easy_apply else [],
                 "keyword": scraper_input.search_term,
                 "numJobsToShow": 30,
                 "locationType": location_type,
@@ -231,12 +292,11 @@ class GlassdoorScraper(Scraper):
         for job_type in JobType:
             if job_type_str in job_type.value:
                 return [job_type]
-        return None
 
     @staticmethod
-    def parse_location(location_name: str) -> Location:
+    def parse_location(location_name: str) -> Location | None:
         if not location_name or location_name == "Remote":
-            return None
+            return
         city, _, state = location_name.partition(", ")
         return Location(city=city, state=state)
 
@@ -245,7 +305,6 @@ class GlassdoorScraper(Scraper):
         for cursor_data in pagination_cursors:
             if cursor_data["pageNumber"] == page_num:
                 return cursor_data["cursor"]
-        return None
 
     @staticmethod
     def headers() -> dict:

src/jobspy/scrapers/indeed/__init__.py

@@ -8,6 +8,7 @@ import re
 import math
 import io
 import json
+from typing import Any
 from datetime import datetime
 
 import urllib.parse
@@ -21,6 +22,7 @@ from ..utils import (
     extract_emails_from_text,
     create_session,
     get_enum_from_job_type,
+    modify_and_get_description
 )
 from ...jobs import (
     JobPost,
@@ -43,7 +45,7 @@ class IndeedScraper(Scraper):
         site = Site(Site.INDEED)
         super().__init__(site, proxy=proxy)
 
-        self.jobs_per_page = 15
+        self.jobs_per_page = 25
         self.seen_urls = set()
 
     def scrape_page(
@@ -59,30 +61,12 @@ class IndeedScraper(Scraper):
         domain = self.country.indeed_domain_value
         self.url = f"https://{domain}.indeed.com"
 
-        params = {
-            "q": scraper_input.search_term,
-            "l": scraper_input.location,
-            "filter": 0,
-            "start": scraper_input.offset + page * 10,
-            "sort": "date"
-        }
-        if scraper_input.distance:
-            params["radius"] = scraper_input.distance
-
-        sc_values = []
-        if scraper_input.is_remote:
-            sc_values.append("attr(DSQF7)")
-        if scraper_input.job_type:
-            sc_values.append("jt({})".format(scraper_input.job_type.value))
-
-        if sc_values:
-            params["sc"] = "0kf:" + "".join(sc_values) + ";"
         try:
-            session = create_session(self.proxy, is_tls=True)
+            session = create_session(self.proxy)
             response = session.get(
-                f"{self.url}/jobs",
+                f"{self.url}/m/jobs",
                 headers=self.get_headers(),
-                params=params,
+                params=self.add_params(scraper_input, page),
                 allow_redirects=True,
                 timeout_seconds=10,
             )
@@ -111,8 +95,8 @@ class IndeedScraper(Scraper):
         ):
             raise IndeedException("No jobs found.")
 
-        def process_job(job) -> JobPost | None:
+        def process_job(job: dict) -> JobPost | None:
-            job_url = f'{self.url}/jobs/viewjob?jk={job["jobkey"]}'
+            job_url = f'{self.url}/m/jobs/viewjob?jk={job["jobkey"]}'
             job_url_client = f'{self.url}/viewjob?jk={job["jobkey"]}'
             if job_url in self.seen_urls:
                 return None
@@ -140,7 +124,8 @@ class IndeedScraper(Scraper):
             date_posted = datetime.fromtimestamp(timestamp_seconds)
             date_posted = date_posted.strftime("%Y-%m-%d")
 
-            description = self.get_description(job_url)
+            description = self.get_description(job_url) if scraper_input.full_description else None
+
             with io.StringIO(job["snippet"]) as f:
                 soup_io = BeautifulSoup(f, "html.parser")
                 li_elements = soup_io.find_all("li")
@@ -192,7 +177,7 @@ class IndeedScraper(Scraper):
         #: get first page to initialize session
         job_list, total_results = self.scrape_page(scraper_input, 0)
 
-        with ThreadPoolExecutor(max_workers=1) as executor:
+        with ThreadPoolExecutor(max_workers=10) as executor:
             futures: list[Future] = [
                 executor.submit(self.scrape_page, scraper_input, page)
                 for page in range(1, pages_to_process + 1)
@@ -246,9 +231,7 @@ class IndeedScraper(Scraper):
             return None
 
         soup = BeautifulSoup(job_description, "html.parser")
-        text_content = " ".join(soup.get_text(separator=" ").split()).strip()
+        return modify_and_get_description(soup)
-
-        return text_content
 
     @staticmethod
     def get_job_type(job: dict) -> list[JobType] | None:
@@ -331,17 +314,14 @@ class IndeedScraper(Scraper):
     @staticmethod
     def get_headers():
         return {
-            "authority": "www.indeed.com",
+          'Host': 'www.indeed.com',
-            "accept": "*/*",
+          'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
-            "accept-language": "en-US,en;q=0.9",
+          'sec-fetch-site': 'same-origin',
-            "referer": "https://www.indeed.com/viewjob?jk=fe6182337d72c7b1&tk=1hcbfcmd0k62t802&from=serp&vjs=3&advn=8132938064490989&adid=408692607&ad=-6NYlbfkN0A3Osc99MJFDKjquSk4WOGT28ALb_ad4QMtrHreCb9ICg6MiSVy9oDAp3evvOrI7Q-O9qOtQTg1EPbthP9xWtBN2cOuVeHQijxHjHpJC65TjDtftH3AXeINjBvAyDrE8DrRaAXl8LD3Fs1e_xuDHQIssdZ2Mlzcav8m5jHrA0fA64ZaqJV77myldaNlM7-qyQpy4AsJQfvg9iR2MY7qeC5_FnjIgjKIy_lNi9OPMOjGRWXA94CuvC7zC6WeiJmBQCHISl8IOBxf7EdJZlYdtzgae3593TFxbkd6LUwbijAfjax39aAuuCXy3s9C4YgcEP3TwEFGQoTpYu9Pmle-Ae1tHGPgsjxwXkgMm7Cz5mBBdJioglRCj9pssn-1u1blHZM4uL1nK9p1Y6HoFgPUU9xvKQTHjKGdH8d4y4ETyCMoNF4hAIyUaysCKdJKitC8PXoYaWhDqFtSMR4Jys8UPqUV&xkcb=SoDD-_M3JLQfWnQTDh0LbzkdCdPP&xpse=SoBa6_I3JLW9FlWZlB0PbzkdCdPP&sjdu=i6xVERweJM_pVUvgf-MzuaunBTY7G71J5eEX6t4DrDs5EMPQdODrX7Nn-WIPMezoqr5wA_l7Of-3CtoiUawcHw",
+          'sec-fetch-dest': 'document',
-            "sec-ch-ua": '"Google Chrome";v="119", "Chromium";v="119", "Not?A_Brand";v="24"',
+          'accept-language': 'en-US,en;q=0.9',
-            "sec-ch-ua-mobile": "?0",
+          'sec-fetch-mode': 'navigate',
-            "sec-ch-ua-platform": '"Windows"',
+          'user-agent': 'Mozilla/5.0 (iPhone; CPU iPhone OS 16_6_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/15E148 Indeed App 192.0',
-            "sec-fetch-dest": "empty",
+          'referer': 'https://www.indeed.com/m/jobs?q=software%20intern&l=Dallas%2C%20TX&from=serpso&rq=1&rsIdx=3',
-            "sec-fetch-mode": "cors",
-            "sec-fetch-site": "same-origin",
-            "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36",
         }
 
     @staticmethod
@@ -354,3 +334,29 @@ class IndeedScraper(Scraper):
             if taxonomy["label"] == "remote" and len(taxonomy["attributes"]) > 0:
                 return True
         return False
+
+    @staticmethod
+    def add_params(scraper_input: ScraperInput, page: int) -> dict[str, str | Any]:
+        params = {
+            "q": scraper_input.search_term,
+            "l": scraper_input.location,
+            "filter": 0,
+            "start": scraper_input.offset + page * 10,
+            "sort": "date"
+        }
+        if scraper_input.distance:
+            params["radius"] = scraper_input.distance
+
+        sc_values = []
+        if scraper_input.is_remote:
+            sc_values.append("attr(DSQF7)")
+        if scraper_input.job_type:
+            sc_values.append("jt({})".format(scraper_input.job_type.value))
+
+        if sc_values:
+            params["sc"] = "0kf:" + "".join(sc_values) + ";"
+
+        if scraper_input.easy_apply:
+            params['iafilter'] = 1
+
+        return params

src/jobspy/scrapers/linkedin/__init__.py

@@ -4,23 +4,36 @@ jobspy.scrapers.linkedin
 
 This module contains routines to scrape LinkedIn.
 """
+import time
 import random
 from typing import Optional
 from datetime import datetime
 
 import requests
-import time
 from requests.exceptions import ProxyError
-from bs4 import BeautifulSoup
-from bs4.element import Tag
 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 ...jobs import (
-from ..utils import count_urgent_words, extract_emails_from_text, get_enum_from_job_type, currency_parser
+    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):
@@ -111,7 +124,7 @@ class LinkedInScraper(Scraper):
 
                 # Call process_job directly without threading
                 try:
-                    job_post = self.process_job(job_card, job_url)
+                    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:
@@ -123,7 +136,7 @@ class LinkedInScraper(Scraper):
         job_list = job_list[: scraper_input.results_wanted]
         return JobResponse(jobs=job_list)
 
-    def process_job(self, job_card: Tag, job_url: str) -> Optional[JobPost]:
+    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
@@ -160,7 +173,7 @@ class LinkedInScraper(Scraper):
             if metadata_card
             else None
         )
-        date_posted = None
+        date_posted = description = job_type = None
         if datetime_tag and "datetime" in datetime_tag.attrs:
             datetime_str = datetime_tag["datetime"]
             try:
@@ -169,9 +182,8 @@ class LinkedInScraper(Scraper):
                 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:
-        # removed to speed up scraping
+            description, job_type = self.get_job_description(job_url)
-        # description, job_type = self.get_job_description(job_url)
 
         return JobPost(
             title=title,
@@ -182,10 +194,10 @@ class LinkedInScraper(Scraper):
             job_url=job_url,
             compensation=compensation,
             benefits=benefits,
-            # job_type=job_type,
+            job_type=job_type,
-            # description=description,
+            description=description,
-            # emails=extract_emails_from_text(description) if description else None,
+            emails=extract_emails_from_text(description) if description else None,
-            # num_urgent_words=count_urgent_words(description) if description else None,
+            num_urgent_words=count_urgent_words(description) if description else None,
         )
 
     def get_job_description(
@@ -214,7 +226,7 @@ class LinkedInScraper(Scraper):
 
         description = None
         if div_content:
-            description = " ".join(div_content.get_text().split()).strip()
+            description = modify_and_get_description(div_content)
 
         def get_job_type(
             soup_job_type: BeautifulSoup,

src/jobspy/scrapers/utils.py

@@ -8,6 +8,15 @@ from requests.adapters import HTTPAdapter, Retry
 from ..jobs import JobType
 
 
+def modify_and_get_description(soup):
+    for li in soup.find_all('li'):
+        li.string = "- " + li.get_text()
+
+    description = soup.get_text(separator='\n').strip()
+    description = re.sub(r'\n+', '\n', description)
+    return description
+
+
 def count_urgent_words(description: str) -> int:
     """
     Count the number of urgent words or phrases in a job description.

src/jobspy/scrapers/ziprecruiter/__init__.py

@@ -10,14 +10,13 @@ import re
 from datetime import datetime, date
 from typing import Optional, Tuple, Any
 
-import requests
 from bs4 import BeautifulSoup
 from concurrent.futures import ThreadPoolExecutor
 
 from .. import Scraper, ScraperInput, Site
 from ..exceptions import ZipRecruiterException
-from ..utils import count_urgent_words, extract_emails_from_text, create_session
 from ...jobs import JobPost, Compensation, Location, JobResponse, JobType, Country
+from ..utils import count_urgent_words, extract_emails_from_text, create_session, modify_and_get_description
 
 
 class ZipRecruiterScraper(Scraper):
@@ -107,9 +106,9 @@ class ZipRecruiterScraper(Scraper):
         title = job.get("name")
         job_url = job.get("job_url")
 
-        description = BeautifulSoup(
+        job_description_html = job.get("job_description", "").strip()
-            job.get("job_description", "").strip(), "html.parser"
+        description_soup = BeautifulSoup(job_description_html, "html.parser")
-        ).get_text()
+        description = modify_and_get_description(description_soup)
 
         company = job["hiring_company"].get("name") if "hiring_company" in job else None
         country_value = "usa" if job.get("job_country") == "US" else "canada"
@@ -184,6 +183,8 @@ class ZipRecruiterScraper(Scraper):
                 job_type_value = "part_time"
             else:
                 job_type_value = scraper_input.job_type.value
+        if scraper_input.easy_apply:
+            params['zipapply'] = 1
 
         if job_type_value:
             params[