enh: indeed more fields (#126)

* fix(ziprecruiter): pagination

* chore: version

README.md

@@ -11,7 +11,7 @@ work with us.*
 
 - Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, & **ZipRecruiter** simultaneously
 - Aggregates the job postings in a Pandas DataFrame
-- Proxy support (HTTP/S, SOCKS)
+- Proxy support
 
 [Video Guide for JobSpy](https://www.youtube.com/watch?v=RuP1HrAZnxs&pp=ygUgam9icyBzY3JhcGVyIGJvdCBsaW5rZWRpbiBpbmRlZWQ%3D) -
 Updated for release v1.1.3
@@ -21,7 +21,7 @@ Updated for release v1.1.3
 ### Installation
 
 ```
-pip install python-jobspy
+pip install -U python-jobspy
 ```
 
 _Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_
@@ -29,18 +29,20 @@ _Python version >= [3.10](https://www.python.org/downloads/release/python-3100/)
 ### Usage
 
 ```python
+import csv
 from jobspy import scrape_jobs
 
 jobs = scrape_jobs(
     site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"],
     search_term="software engineer",
     location="Dallas, TX",
-    results_wanted=10,
+    results_wanted=20,
+    hours_old=72, # (only linkedin is hour specific, others round up to days old)
     country_indeed='USA'  # only needed for indeed / glassdoor
 )
 print(f"Found {len(jobs)} jobs")
 print(jobs.head())
-jobs.to_csv("jobs.csv", index=False) # to_xlsx
+jobs.to_csv("jobs.csv", quoting=csv.QUOTE_NONNUMERIC, escapechar="\\", index=False) # to_xlsx
 ```
 
 ### Output
@@ -62,16 +64,19 @@ Required
 ├── site_type (List[enum]): linkedin, zip_recruiter, indeed, glassdoor
 └── search_term (str)
 Optional
-├── location (int)
+├── location (str)
-├── distance (int): in miles
+├── distance (int): in miles, default 50
 ├── job_type (enum): fulltime, parttime, internship, contract
-├── proxy (str): in format 'http://user:pass@host:port' or [https, socks]
+├── proxy (str): in format 'http://user:pass@host:port'
 ├── is_remote (bool)
-├── full_description (bool): fetches full description for Indeed / LinkedIn (much slower)
+├── linkedin_fetch_description (bool): fetches full description for LinkedIn (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, Glassdoor
+├── easy_apply (bool): filters for jobs that are hosted on the job board site
+├── linkedin_company_ids (list[int): searches for linkedin jobs with specific company ids
+├── description_format (enum): markdown, html (format type of the job descriptions)
 ├── 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)
+├── hours_old (int): filters jobs by the number of hours since the job was posted (ZipRecruiter and Glassdoor round up to next day. If you use this on Indeed, it will not filter by job_type or is_remote)
 ```
 
 ### JobPost Schema
@@ -80,6 +85,7 @@ Optional
 JobPost
 ├── title (str)
 ├── company (str)
+├── company_url (str)
 ├── job_url (str)
 ├── location (object)
 │   ├── country (str)
@@ -94,24 +100,26 @@ JobPost
 │   └── currency (enum)
 └── date_posted (date)
 └── emails (str)
-└── num_urgent_words (int)
 └── is_remote (bool)
+
+Indeed specific
+├── company_country (str)
+└── company_addresses (str)
+└── company_industry (str)
+└── company_employees_label (str)
+└── company_revenue_label (str)
+└── company_description (str)
+└── ceo_name (str)
+└── ceo_photo_url (str)
+└── logo_photo_url (str)
+└── banner_photo_url (str)
 ```
 
-### Exceptions
-
-The following exceptions may be raised when using JobSpy:
-
-* `LinkedInException`
-* `IndeedException`
-* `ZipRecruiterException`
-* `GlassdoorException`
-
 ## Supported Countries for Job Searching
 
 ### **LinkedIn**
 
-LinkedIn searches globally & uses only the `location` parameter. You can only fetch 1000 jobs max from the LinkedIn endpoint we're using
+LinkedIn searches globally & uses only the `location` parameter. You can only fetch 1000 jobs max from the LinkedIn endpoint we are using
 
 ### **ZipRecruiter**
 
@@ -141,10 +149,14 @@ You can specify the following countries when searching on Indeed (use the exact
 | South Korea          | Spain*       | Sweden     | Switzerland*   |
 | Taiwan               | Thailand     | Turkey     | Ukraine        |
 | United Arab Emirates | UK*          | USA*       | Uruguay        |
-| Venezuela            | Vietnam      |            |                |
+| Venezuela            | Vietnam*     |            |                |
 
 
-Glassdoor can only fetch 900 jobs from the endpoint we're using on a given search.
+## Notes
+* Indeed is the best scraper currently with no rate limiting.  
+* Glassdoor can only fetch 900 jobs from the endpoint we're using on a given search.  
+* LinkedIn is the most restrictive and usually rate limits on around the 10th page  
+* ZipRecruiter is okay but has a 5 second delay in between each page to avoid rate limiting.
 ## Frequently Asked Questions
 
 ---
@@ -158,16 +170,7 @@ persist, [submit an issue](https://github.com/Bunsly/JobSpy/issues).
 **Q: Received a response code 429?**  
 **A:** This indicates that you have been blocked by the job board site for sending too many requests. All of the job board sites are aggressive with blocking. We recommend:
 
-- Waiting a few seconds between requests.
+- Waiting some time between scrapes (site-dependent).
 - Trying a VPN or proxy to change your IP address.
 
----
+---
-
-**Q: Experiencing a "Segmentation fault: 11" on macOS Catalina?**  
-**A:** This is due to `tls_client` dependency not supporting your architecture. Solutions and workarounds include:
-
-- Upgrade to a newer version of MacOS
-- Reach out to the maintainers of [tls_client](https://github.com/bogdanfinn/tls-client) for fixes
-
-
-  

poetry.lock

@@ -1026,6 +1026,21 @@ files = [
     {file = "jupyterlab_widgets-3.0.8.tar.gz", hash = "sha256:d428ab97b8d87cc7c54cbf37644d6e0f0e662f23876e05fa460a73ec3257252a"},
 ]
 
+[[package]]
+name = "markdownify"
+version = "0.11.6"
+description = "Convert HTML to markdown."
+optional = false
+python-versions = "*"
+files = [
+    {file = "markdownify-0.11.6-py3-none-any.whl", hash = "sha256:ba35fe289d5e9073bcd7d2cad629278fe25f1a93741fcdc0bfb4f009076d8324"},
+    {file = "markdownify-0.11.6.tar.gz", hash = "sha256:009b240e0c9f4c8eaf1d085625dcd4011e12f0f8cec55dedf9ea6f7655e49bfe"},
+]
+
+[package.dependencies]
+beautifulsoup4 = ">=4.9,<5"
+six = ">=1.15,<2"
+
 [[package]]
 name = "markupsafe"
 version = "2.1.3"
@@ -2260,13 +2275,13 @@ test = ["flake8", "isort", "pytest"]
 
 [[package]]
 name = "tls-client"
-version = "1.0"
+version = "1.0.1"
 description = "Advanced Python HTTP Client."
 optional = false
 python-versions = "*"
 files = [
-    {file = "tls_client-1.0-py3-none-any.whl", hash = "sha256:f1183f5e18cb31914bd62d11b350a33ea0293ea80fb91d69a3072821dece3e66"},
+    {file = "tls_client-1.0.1-py3-none-any.whl", hash = "sha256:2f8915c0642c2226c9e33120072a2af082812f6310d32f4ea4da322db7d3bb1c"},
-    {file = "tls_client-1.0.tar.gz", hash = "sha256:7f6de48ad4a0ef69b72682c76ce604155971e07b4bfb2148a36276194ae3e7a0"},
+    {file = "tls_client-1.0.1.tar.gz", hash = "sha256:dad797f3412bb713606e0765d489f547ffb580c5ffdb74aed47a183ce8505ff5"},
 ]
 
 [[package]]
@@ -2435,4 +2450,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "404a77d78066cbb2ef71015562baf44aa11d12aac29a191c1ccc7758bfda598a"
+content-hash = "ba7f7cc9b6833a4a6271981f90610395639dd8b9b3db1370cbd1149d70cc9632"

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "python-jobspy"
-version = "1.1.37"
+version = "1.1.48"
 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"
@@ -13,11 +13,12 @@ packages = [
 [tool.poetry.dependencies]
 python = "^3.10"
 requests = "^2.31.0"
-tls-client = "*"
 beautifulsoup4 = "^4.12.2"
 pandas = "^2.1.0"
 NUMPY = "1.24.2"
 pydantic = "^2.3.0"
+tls-client = "^1.0.1"
+markdownify = "^0.11.6"
 
 
 [tool.poetry.group.dev.dependencies]

src/jobspy/__init__.py

@@ -1,9 +1,9 @@
 import pandas as pd
-import concurrent.futures
+from typing import Tuple
-from concurrent.futures import ThreadPoolExecutor
+from concurrent.futures import ThreadPoolExecutor, as_completed
-from typing import Tuple, Optional
 
 from .jobs import JobType, Location
+from .scrapers.utils import logger
 from .scrapers.indeed import IndeedScraper
 from .scrapers.ziprecruiter import ZipRecruiterScraper
 from .scrapers.glassdoor import GlassdoorScraper
@@ -16,37 +16,39 @@ from .scrapers.exceptions import (
     GlassdoorException,
 )
 
-SCRAPER_MAPPING = {
-    Site.LINKEDIN: LinkedInScraper,
-    Site.INDEED: IndeedScraper,
-    Site.ZIP_RECRUITER: ZipRecruiterScraper,
-    Site.GLASSDOOR: GlassdoorScraper,
-}
-
-
-def _map_str_to_site(site_name: str) -> Site:
-    return Site[site_name.upper()]
-
 
 def scrape_jobs(
-    site_name: str | list[str] | Site | list[Site],
+    site_name: str | list[str] | Site | list[Site] | None = None,
-    search_term: str,
+    search_term: str | None = None,
-    location: str = "",
+    location: str | None = None,
-    distance: int = None,
+    distance: int | None = 50,
     is_remote: bool = False,
-    job_type: str = None,
+    job_type: str | None = None,
-    easy_apply: bool = False,  # linkedin
+    easy_apply: bool | None = None,
     results_wanted: int = 15,
     country_indeed: str = "usa",
     hyperlinks: bool = False,
-    proxy: Optional[str] = None,
+    proxy: str | None = None,
-    full_description: Optional[bool] = False,
+    description_format: str = "markdown",
-    offset: Optional[int] = 0,
+    linkedin_fetch_description: bool | None = False,
+    linkedin_company_ids: list[int] | None = None,
+    offset: int | None = 0,
+    hours_old: int = None,
+    **kwargs,
 ) -> pd.DataFrame:
     """
     Simultaneously scrapes job data from multiple job sites.
     :return: results_wanted: pandas dataframe containing job data
     """
+    SCRAPER_MAPPING = {
+        Site.LINKEDIN: LinkedInScraper,
+        Site.INDEED: IndeedScraper,
+        Site.ZIP_RECRUITER: ZipRecruiterScraper,
+        Site.GLASSDOOR: GlassdoorScraper,
+    }
+
+    def map_str_to_site(site_name: str) -> Site:
+        return Site[site_name.upper()]
 
     def get_enum_from_value(value_str):
         for job_type in JobType:
@@ -56,18 +58,22 @@ def scrape_jobs(
 
     job_type = get_enum_from_value(job_type) if job_type else None
 
-    if type(site_name) == str:
+    def get_site_type():
-        site_type = [_map_str_to_site(site_name)]
+        site_types = list(Site)
-    else:  #: if type(site_name) == list
+        if isinstance(site_name, str):
-        site_type = [
+            site_types = [map_str_to_site(site_name)]
-            _map_str_to_site(site) if type(site) == str else site_name
+        elif isinstance(site_name, Site):
-            for site in site_name
+            site_types = [site_name]
-        ]
+        elif isinstance(site_name, list):
-
+            site_types = [
+                map_str_to_site(site) if isinstance(site, str) else site
+                for site in site_name
+            ]
+        return site_types
     country_enum = Country.from_string(country_indeed)
 
     scraper_input = ScraperInput(
-        site_type=site_type,
+        site_type=get_site_type(),
         country=country_enum,
         search_term=search_term,
         location=location,
@@ -75,30 +81,20 @@ def scrape_jobs(
         is_remote=is_remote,
         job_type=job_type,
         easy_apply=easy_apply,
-        full_description=full_description,
+        description_format=description_format,
+        linkedin_fetch_description=linkedin_fetch_description,
         results_wanted=results_wanted,
+        linkedin_company_ids=linkedin_company_ids,
         offset=offset,
+        hours_old=hours_old
     )
 
     def scrape_site(site: Site) -> Tuple[str, JobResponse]:
         scraper_class = SCRAPER_MAPPING[site]
         scraper = scraper_class(proxy=proxy)
-
+        scraped_data: JobResponse = scraper.scrape(scraper_input)
-        try:
+        site_name = 'ZipRecruiter' if site.value.capitalize() == 'Zip_recruiter' else site.value.capitalize()
-            scraped_data: JobResponse = scraper.scrape(scraper_input)
+        logger.info(f"{site_name} finished scraping")
-        except (LinkedInException, IndeedException, ZipRecruiterException) as lie:
-            raise lie
-        except Exception as e:
-            if site == Site.LINKEDIN:
-                raise LinkedInException(str(e))
-            if site == Site.INDEED:
-                raise IndeedException(str(e))
-            if site == Site.ZIP_RECRUITER:
-                raise ZipRecruiterException(str(e))
-            if site == Site.GLASSDOOR:
-                raise GlassdoorException(str(e))
-            else:
-                raise e
         return site.value, scraped_data
 
     site_to_jobs_dict = {}
@@ -112,7 +108,7 @@ def scrape_jobs(
             executor.submit(worker, site): site for site in scraper_input.site_type
         }
 
-        for future in concurrent.futures.as_completed(future_to_site):
+        for future in as_completed(future_to_site):
             site_value, scraped_data = future.result()
             site_to_jobs_dict[site_value] = scraped_data
 
@@ -159,13 +155,19 @@ def scrape_jobs(
             jobs_dfs.append(job_df)
 
     if jobs_dfs:
-        jobs_df = pd.concat(jobs_dfs, ignore_index=True)
+        # Step 1: Filter out all-NA columns from each DataFrame before concatenation
-        desired_order: list[str] = [
+        filtered_dfs = [df.dropna(axis=1, how='all') for df in jobs_dfs]
-            "job_url_hyper" if hyperlinks else "job_url",
+        
+        # Step 2: Concatenate the filtered DataFrames
+        jobs_df = pd.concat(filtered_dfs, ignore_index=True)
+        
+        # Desired column order
+        desired_order = [
             "site",
+            "job_url_hyper" if hyperlinks else "job_url",
+            "job_url_direct",
             "title",
             "company",
-            "company_url",
             "location",
             "job_type",
             "date_posted",
@@ -174,13 +176,31 @@ def scrape_jobs(
             "max_amount",
             "currency",
             "is_remote",
-            "num_urgent_words",
-            "benefits",
             "emails",
             "description",
-        ]
-        jobs_formatted_df = jobs_df[desired_order]
-    else:
-        jobs_formatted_df = pd.DataFrame()
 
-    return jobs_formatted_df
+            "company_url",
+            "company_url_direct",
+            "company_addresses",
+            "company_industry",
+            "company_num_employees",
+            "company_revenue",
+            "company_description",
+            "logo_photo_url",
+            "banner_photo_url",
+            "ceo_name",
+            "ceo_photo_url",
+        ]
+        
+        # Step 3: Ensure all desired columns are present, adding missing ones as empty
+        for column in desired_order:
+            if column not in jobs_df.columns:
+                jobs_df[column] = None  # Add missing columns as empty
+        
+        # Reorder the DataFrame according to the desired order
+        jobs_df = jobs_df[desired_order]
+        
+        # Step 4: Sort the DataFrame as required
+        return jobs_df.sort_values(by=['site', 'date_posted'], ascending=[True, False])
+    else:
+        return pd.DataFrame()

src/jobspy/jobs/__init__.py

@@ -57,7 +57,7 @@ class JobType(Enum):
 class Country(Enum):
     """
     Gets the subdomain for Indeed and Glassdoor.
-    The second item in the tuple is the subdomain for Indeed
+    The second item in the tuple is the subdomain (and API country code if there's a ':' separator) for Indeed
     The third item in the tuple is the subdomain (and tld if there's a ':' separator) for Glassdoor
     """
 
@@ -118,11 +118,11 @@ class Country(Enum):
     TURKEY = ("turkey", "tr")
     UKRAINE = ("ukraine", "ua")
     UNITEDARABEMIRATES = ("united arab emirates", "ae")
-    UK = ("uk,united kingdom", "uk", "co.uk")
+    UK = ("uk,united kingdom", "uk:gb", "co.uk")
-    USA = ("usa,us,united states", "www", "com")
+    USA = ("usa,us,united states", "www:us", "com")
     URUGUAY = ("uruguay", "uy")
     VENEZUELA = ("venezuela", "ve")
-    VIETNAM = ("vietnam", "vn")
+    VIETNAM = ("vietnam", "vn", "com")
 
     # internal for ziprecruiter
     US_CANADA = ("usa/ca", "www")
@@ -132,7 +132,10 @@ class Country(Enum):
 
     @property
     def indeed_domain_value(self):
-        return self.value[1]
+        subdomain, _, api_country_code = self.value[1].partition(":")
+        if subdomain and api_country_code:
+            return subdomain, api_country_code.upper()
+        return self.value[1], self.value[1].upper()
 
     @property
     def glassdoor_domain_value(self):
@@ -145,7 +148,7 @@ class Country(Enum):
         else:
             raise Exception(f"Glassdoor is not available for {self.name}")
 
-    def get_url(self):
+    def get_glassdoor_url(self):
         return f"https://{self.glassdoor_domain_value}/"
 
     @classmethod
@@ -163,7 +166,7 @@ class Country(Enum):
 
 
 class Location(BaseModel):
-    country: Country | None = None
+    country: Country | str | None = None
     city: Optional[str] = None
     state: Optional[str] = None
 
@@ -173,7 +176,9 @@ class Location(BaseModel):
             location_parts.append(self.city)
         if self.state:
             location_parts.append(self.state)
-        if self.country and self.country not in (Country.US_CANADA, Country.WORLDWIDE):
+        if isinstance(self.country, str):
+            location_parts.append(self.country)
+        elif self.country and self.country not in (Country.US_CANADA, Country.WORLDWIDE):
             country_name = self.country.value[0]
             if "," in country_name:
                 country_name = country_name.split(",")[0]
@@ -193,33 +198,55 @@ class CompensationInterval(Enum):
 
     @classmethod
     def get_interval(cls, pay_period):
-        return cls[pay_period].value if pay_period in cls.__members__ else None
+        interval_mapping = {
+            "YEAR": cls.YEARLY,
+            "HOUR": cls.HOURLY,
+        }
+        if pay_period in interval_mapping:
+            return interval_mapping[pay_period].value
+        else:
+            return cls[pay_period].value if pay_period in cls.__members__ else None
 
 
 class Compensation(BaseModel):
     interval: Optional[CompensationInterval] = None
-    min_amount: int | None = None
+    min_amount: float | None = None
-    max_amount: int | None = None
+    max_amount: float | None = None
     currency: Optional[str] = "USD"
 
 
+class DescriptionFormat(Enum):
+    MARKDOWN = "markdown"
+    HTML = "html"
+
+
 class JobPost(BaseModel):
     title: str
-    company_name: str
+    company_name: str | None
     job_url: str
+    job_url_direct: str | None = None
     location: Optional[Location]
 
     description: str | None = None
     company_url: str | None = None
+    company_url_direct: str | None = None
 
     job_type: list[JobType] | None = None
     compensation: Compensation | None = None
     date_posted: date | None = None
-    benefits: str | None = None
     emails: list[str] | None = None
-    num_urgent_words: int | None = None
     is_remote: bool | None = None
-    # company_industry: str | None = None
+
+    # indeed specific
+    company_addresses: str | None = None
+    company_industry: str | None = None
+    company_num_employees: str | None = None
+    company_revenue: str | None = None
+    company_description: str | None = None
+    ceo_name: str | None = None
+    ceo_photo_url: str | None = None
+    logo_photo_url: str | None = None
+    banner_photo_url: str | None = None
 
 
 class JobResponse(BaseModel):

src/jobspy/scrapers/__init__.py

@@ -1,5 +1,11 @@
-from ..jobs import Enum, BaseModel, JobType, JobResponse, Country
+from ..jobs import (
-from typing import List, Optional, Any
+    Enum,
+    BaseModel,
+    JobType,
+    JobResponse,
+    Country,
+    DescriptionFormat
+)
 
 
 class Site(Enum):
@@ -10,25 +16,27 @@ class Site(Enum):
 
 
 class ScraperInput(BaseModel):
-    site_type: List[Site]
+    site_type: list[Site]
-    search_term: str
+    search_term: str | None = None
 
-    location: str = None
+    location: str | None = None
-    country: Optional[Country] = Country.USA
+    country: Country | None = Country.USA
-    distance: Optional[int] = None
+    distance: int | None = None
     is_remote: bool = False
-    job_type: Optional[JobType] = None
+    job_type: JobType | None = None
-    easy_apply: bool = None  # linkedin
+    easy_apply: bool | None = None
-    full_description: bool = False
     offset: int = 0
+    linkedin_fetch_description: bool = False
+    linkedin_company_ids: list[int] | None = None
+    description_format: DescriptionFormat | None = DescriptionFormat.MARKDOWN
 
     results_wanted: int = 15
+    hours_old: int | None = None
 
 
 class Scraper:
-    def __init__(self, site: Site, proxy: Optional[List[str]] = None):
+    def __init__(self, site: Site, proxy: list[str] | None = None):
         self.site = site
         self.proxy = (lambda p: {"http": p, "https": p} if p else None)(proxy)
 
-    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
+    def scrape(self, scraper_input: ScraperInput) -> JobResponse: ...
-        ...

src/jobspy/scrapers/glassdoor/__init__.py

@@ -5,16 +5,21 @@ jobspy.scrapers.glassdoor
 This module contains routines to scrape Glassdoor.
 """
 import json
+import re
+
 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 ..utils import extract_emails_from_text
 
 from .. import Scraper, ScraperInput, Site
 from ..exceptions import GlassdoorException
-from ..utils import create_session, modify_and_get_description
+from ..utils import (
+    create_session,
+    markdown_converter,
+    logger
+)
 from ...jobs import (
     JobPost,
     Compensation,
@@ -22,6 +27,7 @@ from ...jobs import (
     Location,
     JobResponse,
     JobType,
+    DescriptionFormat
 )
 
 
@@ -33,12 +39,59 @@ class GlassdoorScraper(Scraper):
         site = Site(Site.GLASSDOOR)
         super().__init__(site, proxy=proxy)
 
-        self.url = None
+        self.base_url = None
         self.country = None
+        self.session = None
+        self.scraper_input = None
         self.jobs_per_page = 30
+        self.max_pages = 30
         self.seen_urls = set()
 
-    def fetch_jobs_page(
+    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.
+        """
+        self.scraper_input = scraper_input
+        self.scraper_input.results_wanted = min(900, scraper_input.results_wanted)
+        self.base_url = self.scraper_input.country.get_glassdoor_url()
+
+        self.session = create_session(self.proxy, is_tls=True, has_retry=True)
+        token = self._get_csrf_token()
+        self.headers['gd-csrf-token'] = token if token else self.fallback_token
+
+        location_id, location_type = self._get_location(
+            scraper_input.location, scraper_input.is_remote
+        )
+        if location_type is None:
+            logger.error('Glassdoor: location not parsed')
+            return JobResponse(jobs=[])
+        all_jobs: list[JobPost] = []
+        cursor = None
+
+        for page in range(
+            1 + (scraper_input.offset // self.jobs_per_page),
+            min(
+                (scraper_input.results_wanted // self.jobs_per_page) + 2,
+                self.max_pages + 1,
+            ),
+        ):
+            logger.info(f'Glassdoor search page: {page}')
+            try:
+                jobs, cursor = self._fetch_jobs_page(
+                    scraper_input, location_id, location_type, page, cursor
+                )
+                all_jobs.extend(jobs)
+                if not jobs or len(all_jobs) >= scraper_input.results_wanted:
+                    all_jobs = all_jobs[: scraper_input.results_wanted]
+                    break
+            except Exception as e:
+                logger.error(f'Glassdoor: {str(e)}')
+                break
+        return JobResponse(jobs=all_jobs)
+
+    def _fetch_jobs_page(
         self,
         scraper_input: ScraperInput,
         location_id: int,
@@ -49,31 +102,29 @@ class GlassdoorScraper(Scraper):
         """
         Scrapes a page of Glassdoor for jobs with scraper_input criteria
         """
+        jobs = []
+        self.scraper_input = scraper_input
         try:
-            payload = self.add_payload(
+            payload = self._add_payload(
-                scraper_input, location_id, location_type, page_num, cursor
+                location_id, location_type, page_num, cursor
             )
-            session = create_session(self.proxy, is_tls=False, has_retry=True)
+            response = self.session.post(
-            response = session.post(
+                f"{self.base_url}/graph", headers=self.headers, timeout_seconds=15, data=payload
-                f"{self.url}/graph", headers=self.headers(), timeout=10, data=payload
             )
             if response.status_code != 200:
-                raise GlassdoorException(
+                raise GlassdoorException(f"bad response status code: {response.status_code}")
-                    f"bad response status code: {response.status_code}"
-                )
             res_json = response.json()[0]
             if "errors" in res_json:
                 raise ValueError("Error encountered in API response")
-        except Exception as e:
+        except (requests.exceptions.ReadTimeout, GlassdoorException, ValueError, Exception) as e:
-            raise GlassdoorException(str(e))
+            logger.error(f'Glassdoor: {str(e)}')
+            return jobs, None
 
         jobs_data = res_json["data"]["jobListings"]["jobListings"]
 
-        jobs = []
         with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
-            future_to_job_data = {executor.submit(self.process_job, job): job for job in jobs_data}
+            future_to_job_data = {executor.submit(self._process_job, job): job for job in jobs_data}
             for future in as_completed(future_to_job_data):
-                job_data = future_to_job_data[future]
                 try:
                     job_post = future.result()
                     if job_post:
@@ -85,10 +136,24 @@ class GlassdoorScraper(Scraper):
             res_json["data"]["jobListings"]["paginationCursors"], page_num + 1
         )
 
-    def process_job(self, job_data):
+    def _get_csrf_token(self):
-        """Processes a single job and fetches its description."""
+        """
+        Fetches csrf token needed for API by visiting a generic page
+        """
+        res = self.session.get(f'{self.base_url}/Job/computer-science-jobs.htm', headers=self.headers)
+        pattern = r'"token":\s*"([^"]+)"'
+        matches = re.findall(pattern, res.text)
+        token = None
+        if matches:
+            token = matches[0]
+        return token
+
+    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}'
+        job_url = f'{self.base_url}job-listing/j?jl={job_id}'
         if job_url in self.seen_urls:
             return None
         self.seen_urls.add(job_url)
@@ -100,7 +165,7 @@ class GlassdoorScraper(Scraper):
         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
+        date_posted = (datetime.now() - timedelta(days=age_in_days)).date() if age_in_days is not None else None
 
         if location_type == "S":
             is_remote = True
@@ -108,15 +173,13 @@ class GlassdoorScraper(Scraper):
             location = self.parse_location(location_name)
 
         compensation = self.parse_compensation(job["header"])
-
         try:
-            description = self.fetch_job_description(job_id)
+            description = self._fetch_job_description(job_id)
-        except Exception as e :
+        except:
             description = None
-
+        return JobPost(
-        job_post = JobPost(
             title=title,
-            company_url=f"{self.url}Overview/W-EI_IE{company_id}.htm" if company_id else None,
+            company_url=f"{self.base_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,
@@ -125,53 +188,13 @@ class GlassdoorScraper(Scraper):
             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:
+    def _fetch_job_description(self, job_id):
         """
-        Scrapes Glassdoor for jobs with scraper_input criteria.
+        Fetches the job description for a single job ID.
-        :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)
+        url = f"{self.base_url}/graph"
-        self.country = scraper_input.country
-        self.url = self.country.get_url()
-
-        location_id, location_type = self.get_location(
-            scraper_input.location, scraper_input.is_remote
-        )
-        all_jobs: list[JobPost] = []
-        cursor = None
-        max_pages = 30
-
-        try:
-            for page in range(
-                1 + (scraper_input.offset // self.jobs_per_page),
-                min(
-                    (scraper_input.results_wanted // self.jobs_per_page) + 2,
-                    max_pages + 1,
-                ),
-            ):
-                try:
-                    jobs, cursor = self.fetch_jobs_page(
-                        scraper_input, location_id, location_type, page, cursor
-                    )
-                    all_jobs.extend(jobs)
-                    if len(all_jobs) >= scraper_input.results_wanted:
-                        all_jobs = all_jobs[: scraper_input.results_wanted]
-                        break
-                except Exception as e:
-                    raise GlassdoorException(str(e))
-        except Exception as e:
-            raise GlassdoorException(str(e))
-
-        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",
@@ -196,20 +219,80 @@ class GlassdoorScraper(Scraper):
                 """
             }
         ]
-        response = requests.post(url, json=body, headers=GlassdoorScraper.headers())
+        res = requests.post(url, json=body, headers=self.headers)
-        if response.status_code != 200:
+        if res.status_code != 200:
             return None
-        data = response.json()[0]
+        data = res.json()[0]
         desc = data['data']['jobview']['job']['description']
-        soup = BeautifulSoup(desc, 'html.parser')
+        return markdown_converter(desc) if self.scraper_input.description_format == DescriptionFormat.MARKDOWN else desc
-        return modify_and_get_description(soup)
+
+    def _get_location(self, location: str, is_remote: bool) -> (int, str):
+        if not location or is_remote:
+            return "11047", "STATE"  # remote options
+        url = f"{self.base_url}/findPopularLocationAjax.htm?maxLocationsToReturn=10&term={location}"
+        session = create_session(self.proxy, has_retry=True)
+        res = self.session.get(url, headers=self.headers)
+        if res.status_code != 200:
+            if res.status_code == 429:
+                logger.error(f'429 Response - Blocked by Glassdoor for too many requests')
+                return None, None
+            else:
+                logger.error(f'Glassdoor response status code {res.status_code}')
+                return None, None
+        items = res.json()
+
+        if not items:
+            raise ValueError(f"Location '{location}' not found on Glassdoor")
+        location_type = items[0]["locationType"]
+        if location_type == "C":
+            location_type = "CITY"
+        elif location_type == "S":
+            location_type = "STATE"
+        elif location_type == 'N':
+            location_type = "COUNTRY"
+        return int(items[0]["locationId"]), location_type
+
+    def _add_payload(
+        self,
+        location_id: int,
+        location_type: str,
+        page_num: int,
+        cursor: str | None = None,
+    ) -> str:
+        fromage = max(self.scraper_input.hours_old // 24, 1) if self.scraper_input.hours_old else None
+        filter_params = []
+        if self.scraper_input.easy_apply:
+            filter_params.append({"filterKey": "applicationType", "values": "1"})
+        if fromage:
+            filter_params.append({"filterKey": "fromAge", "values": str(fromage)})
+        payload = {
+            "operationName": "JobSearchResultsQuery",
+            "variables": {
+                "excludeJobListingIds": [],
+                "filterParams": filter_params,
+                "keyword": self.scraper_input.search_term,
+                "numJobsToShow": 30,
+                "locationType": location_type,
+                "locationId": int(location_id),
+                "parameterUrlInput": f"IL.0,12_I{location_type}{location_id}",
+                "pageNumber": page_num,
+                "pageCursor": cursor,
+                "fromage": fromage,
+                "sort": "date"
+            },
+            "query": self.query_template
+        }
+        if self.scraper_input.job_type:
+            payload["variables"]["filterParams"].append(
+                {"filterKey": "jobType", "values": self.scraper_input.job_type.value[0]}
+            )
+        return json.dumps([payload])
 
     @staticmethod
     def parse_compensation(data: dict) -> Optional[Compensation]:
         pay_period = data.get("payPeriod")
         adjusted_pay = data.get("payPeriodAdjustedPay")
         currency = data.get("payCurrency", "USD")
-
         if not pay_period or not adjusted_pay:
             return None
 
@@ -220,7 +303,6 @@ class GlassdoorScraper(Scraper):
             interval = CompensationInterval.get_interval(pay_period)
         min_amount = int(adjusted_pay.get("p10") // 1)
         max_amount = int(adjusted_pay.get("p90") // 1)
-
         return Compensation(
             interval=interval,
             min_amount=min_amount,
@@ -228,65 +310,6 @@ class GlassdoorScraper(Scraper):
             currency=currency,
         )
 
-    def get_location(self, location: str, is_remote: bool) -> (int, str):
-        if not location or is_remote:
-            return "11047", "STATE"  # remote options
-        url = f"{self.url}/findPopularLocationAjax.htm?maxLocationsToReturn=10&term={location}"
-        session = create_session(self.proxy, has_retry=True)
-        response = session.get(url)
-        if response.status_code != 200:
-            raise GlassdoorException(
-                f"bad response status code: {response.status_code}"
-            )
-        items = response.json()
-        if not items:
-            raise ValueError(f"Location '{location}' not found on Glassdoor")
-        location_type = items[0]["locationType"]
-        if location_type == "C":
-            location_type = "CITY"
-        elif location_type == "S":
-            location_type = "STATE"
-        return int(items[0]["locationId"]), location_type
-
-    @staticmethod
-    def add_payload(
-        scraper_input,
-        location_id: int,
-        location_type: str,
-        page_num: int,
-        cursor: str | None = None,
-    ) -> str:
-        payload = {
-            "operationName": "JobSearchResultsQuery",
-            "variables": {
-                "excludeJobListingIds": [],
-                "filterParams": [{"filterKey": "applicationType", "values": "1"}] if scraper_input.easy_apply else [],
-                "keyword": scraper_input.search_term,
-                "numJobsToShow": 30,
-                "locationType": location_type,
-                "locationId": int(location_id),
-                "parameterUrlInput": f"IL.0,12_I{location_type}{location_id}",
-                "pageNumber": page_num,
-                "pageCursor": cursor,
-            },
-            "query": "query JobSearchResultsQuery($excludeJobListingIds: [Long!], $keyword: String, $locationId: Int, $locationType: LocationTypeEnum, $numJobsToShow: Int!, $pageCursor: String, $pageNumber: Int, $filterParams: [FilterParams], $originalPageUrl: String, $seoFriendlyUrlInput: String, $parameterUrlInput: String, $seoUrl: Boolean) {\n  jobListings(\n    contextHolder: {searchParams: {excludeJobListingIds: $excludeJobListingIds, keyword: $keyword, locationId: $locationId, locationType: $locationType, numPerPage: $numJobsToShow, pageCursor: $pageCursor, pageNumber: $pageNumber, filterParams: $filterParams, originalPageUrl: $originalPageUrl, seoFriendlyUrlInput: $seoFriendlyUrlInput, parameterUrlInput: $parameterUrlInput, seoUrl: $seoUrl, searchType: SR}}\n  ) {\n    companyFilterOptions {\n      id\n      shortName\n      __typename\n    }\n    filterOptions\n    indeedCtk\n    jobListings {\n      ...JobView\n      __typename\n    }\n    jobListingSeoLinks {\n      linkItems {\n        position\n        url\n        __typename\n      }\n      __typename\n    }\n    jobSearchTrackingKey\n    jobsPageSeoData {\n      pageMetaDescription\n      pageTitle\n      __typename\n    }\n    paginationCursors {\n      cursor\n      pageNumber\n      __typename\n    }\n    indexablePageForSeo\n    searchResultsMetadata {\n      searchCriteria {\n        implicitLocation {\n          id\n          localizedDisplayName\n          type\n          __typename\n        }\n        keyword\n        location {\n          id\n          shortName\n          localizedShortName\n          localizedDisplayName\n          type\n          __typename\n        }\n        __typename\n      }\n      footerVO {\n        countryMenu {\n          childNavigationLinks {\n            id\n            link\n            textKey\n            __typename\n          }\n          __typename\n        }\n        __typename\n      }\n      helpCenterDomain\n      helpCenterLocale\n      jobAlert {\n        jobAlertExists\n        __typename\n      }\n      jobSerpFaq {\n        questions {\n          answer\n          question\n          __typename\n        }\n        __typename\n      }\n      jobSerpJobOutlook {\n        occupation\n        paragraph\n        __typename\n      }\n      showMachineReadableJobs\n      __typename\n    }\n    serpSeoLinksVO {\n      relatedJobTitlesResults\n      searchedJobTitle\n      searchedKeyword\n      searchedLocationIdAsString\n      searchedLocationSeoName\n      searchedLocationType\n      topCityIdsToNameResults {\n        key\n        value\n        __typename\n      }\n      topEmployerIdsToNameResults {\n        key\n        value\n        __typename\n      }\n      topEmployerNameResults\n      topOccupationResults\n      __typename\n    }\n    totalJobsCount\n    __typename\n  }\n}\n\nfragment JobView on JobListingSearchResult {\n  jobview {\n    header {\n      adOrderId\n      advertiserType\n      adOrderSponsorshipLevel\n      ageInDays\n      divisionEmployerName\n      easyApply\n      employer {\n        id\n        name\n        shortName\n        __typename\n      }\n      employerNameFromSearch\n      goc\n      gocConfidence\n      gocId\n      jobCountryId\n      jobLink\n      jobResultTrackingKey\n      jobTitleText\n      locationName\n      locationType\n      locId\n      needsCommission\n      payCurrency\n      payPeriod\n      payPeriodAdjustedPay {\n        p10\n        p50\n        p90\n        __typename\n      }\n      rating\n      salarySource\n      savedJobId\n      sponsored\n      __typename\n    }\n    job {\n      descriptionFragments\n      importConfigId\n      jobTitleId\n      jobTitleText\n      listingId\n      __typename\n    }\n    jobListingAdminDetails {\n      cpcVal\n      importConfigId\n      jobListingId\n      jobSourceId\n      userEligibleForAdminJobDetails\n      __typename\n    }\n    overview {\n      shortName\n      squareLogoUrl\n      __typename\n    }\n    __typename\n  }\n  __typename\n}\n",
-        }
-
-        job_type_filters = {
-            JobType.FULL_TIME: "fulltime",
-            JobType.PART_TIME: "parttime",
-            JobType.CONTRACT: "contract",
-            JobType.INTERNSHIP: "internship",
-            JobType.TEMPORARY: "temporary",
-        }
-
-        if scraper_input.job_type in job_type_filters:
-            filter_value = job_type_filters[scraper_input.job_type]
-            payload["variables"]["filterParams"].append(
-                {"filterKey": "jobType", "values": filter_value}
-            )
-        return json.dumps([payload])
-
     @staticmethod
     def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
         for job_type in JobType:
@@ -306,28 +329,187 @@ class GlassdoorScraper(Scraper):
             if cursor_data["pageNumber"] == page_num:
                 return cursor_data["cursor"]
 
-    @staticmethod
+    fallback_token = "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok"
-    def headers() -> dict:
+    headers = {
-        """
+        "authority": "www.glassdoor.com",
-        Returns headers needed for requests
+        "accept": "*/*",
-        :return: dict - Dictionary containing headers
+        "accept-language": "en-US,en;q=0.9",
-        """
+        "apollographql-client-name": "job-search-next",
-        return {
+        "apollographql-client-version": "4.65.5",
-            "authority": "www.glassdoor.com",
+        "content-type": "application/json",
-            "accept": "*/*",
+        "origin": "https://www.glassdoor.com",
-            "accept-language": "en-US,en;q=0.9",
+        "referer": "https://www.glassdoor.com/",
-            "apollographql-client-name": "job-search-next",
+        "sec-ch-ua": '"Chromium";v="118", "Google Chrome";v="118", "Not=A?Brand";v="99"',
-            "apollographql-client-version": "4.65.5",
+        "sec-ch-ua-mobile": "?0",
-            "content-type": "application/json",
+        "sec-ch-ua-platform": '"macOS"',
-            "cookie": 'gdId=91e2dfc4-c8b5-4fa7-83d0-11512b80262c; G_ENABLED_IDPS=google; trs=https%3A%2F%2Fwww.redhat.com%2F:referral:referral:2023-07-05+09%3A50%3A14.862:undefined:undefined; g_state={"i_p":1688587331651,"i_l":1}; _cfuvid=.7llazxhYFZWi6EISSPdVjtqF0NMVwzxr_E.cB1jgLs-1697828392979-0-604800000; GSESSIONID=undefined; JSESSIONID=F03DD1B5EE02DB6D842FE42B142F88F3; cass=1; jobsClicked=true; indeedCtk=1hd77b301k79i801; asst=1697829114.2; G_AUTHUSER_H=0; uc=8013A8318C98C517FE6DD0024636DFDEF978FC33266D93A2FAFEF364EACA608949D8B8FA2DC243D62DE271D733EB189D809ABE5B08D7B1AE865D217BD4EEBB97C282F5DA5FEFE79C937E3F6110B2A3A0ADBBA3B4B6DF5A996FEE00516100A65FCB11DA26817BE8D1C1BF6CFE36B5B68A3FDC2CFEC83AB797F7841FBB157C202332FC7E077B56BD39B167BDF3D9866E3B; AWSALB=zxc/Yk1nbWXXT6HjNyn3H4h4950ckVsFV/zOrq5LSoChYLE1qV+hDI8Axi3fUa9rlskndcO0M+Fw+ZnJ+AQ2afBFpyOd1acouLMYgkbEpqpQaWhY6/Gv4QH1zBcJ; AWSALBCORS=zxc/Yk1nbWXXT6HjNyn3H4h4950ckVsFV/zOrq5LSoChYLE1qV+hDI8Axi3fUa9rlskndcO0M+Fw+ZnJ+AQ2afBFpyOd1acouLMYgkbEpqpQaWhY6/Gv4QH1zBcJ; gdsid=1697828393025:1697830776351:668396EDB9E6A832022D34414128093D; at=HkH8Hnqi9uaMC7eu0okqyIwqp07ht9hBvE1_St7E_hRqPvkO9pUeJ1Jcpds4F3g6LL5ADaCNlxrPn0o6DumGMfog8qI1-zxaV_jpiFs3pugntw6WpVyYWdfioIZ1IDKupyteeLQEM1AO4zhGjY_rPZynpsiZBPO_B1au94sKv64rv23yvP56OiWKKfI-8_9hhLACEwWvM-Az7X-4aE2QdFt93VJbXbbGVf07bdDZfimsIkTtgJCLSRhU1V0kEM1Efyu66vo3m77gFFaMW7lxyYnb36I5PdDtEXBm3aL-zR7-qa5ywd94ISEivgqQOA4FPItNhqIlX4XrfD1lxVz6rfPaoTIDi4DI6UMCUjwyPsuv8mn0rYqDfRnmJpZ97fJ5AnhrknAd_6ZWN5v1OrxJczHzcXd8LO820QPoqxzzG13bmSTXLwGSxMUCtSrVsq05hicimQ3jpRt0c1dA4OkTNqF7_770B9JfcHcM8cr8-C4IL56dnOjr9KBGfN1Q2IvZM2cOBRbV7okiNOzKVZ3qJ24AE34WA2F3U6Whiu6H8nIuGG5hSNkVygY6CtglNZfFF9p8pJAZm79PngrrBv-CXFBZmhYLFo46lmFetDkiJ6mirtez4tKpzTIYjIp4_JAkiZFwbLJ2QGH4mK8kyyW0lZiX1DTuQec50N_5wvRo0Gt7nlKxzLsApMnaNhuQeH5ygh_pa381ORo9mQGi0EYF9zk00pa2--z4PtjfQ8KFq36GgpxKy5-o4qgqygZj8F01L8r-FiX2G4C7PREMIpAyHX2A4-_JxA1IS2j12EyqKTLqE9VcP06qm2Z-YuIW3ctmpMxy5G9_KiEiGv17weizhSFnl6SbpAEY-2VSmQ5V6jm3hoMp2jemkuGCRkZeFstLDEPxlzFN7WM; __cf_bm=zGaVjIJw4irf40_7UVw54B6Ohm271RUX4Tc8KVScrbs-1697830777-0-AYv2GnKTnnCU+cY9xHbJunO0DwlLDO6SIBnC/s/qldpKsGK0rRAjD6y8lbyATT/KlS7g29OZaN4fbd0lrJg0KmWbIybZIzfWVLHSYePVuOhu; asst=1697829114.2; at=dFhXf64wsf2TlnWy41xLs7skJkuxgKToEGcjGtDfUvW4oEAJ4tTIR5dKQ8wbwT75aIaGgdCfvcb-da7vwrCGWscCncmfLFQpJ9l-LLwoRfk-pMsxHhd77wvf-W7I0HSm7-Q5lQJqI9WyNGRxOa-RpzBTf4L8_Et4-3FzjPaAoYY5pY1FhuwXbN5asGOAMW-p8cjpbfn3PumlIYuckguWnjrcY2F31YJ_1noeoHM9tCGpymANbqGXRkG6aXY7yCfVXtdgZU1K5SMeaSPZIuF_iLUxjc_corzpNiH6qq7BIAmh-e5Aa-g7cwpZcln1fmwTVw4uTMZf1eLIMTa9WzgqZNkvG-sGaq_XxKA_Wai6xTTkOHfRgm4632Ba2963wdJvkGmUUa3tb_L4_wTgk3eFnHp5JhghLfT2Pe3KidP-yX__vx8JOsqe3fndCkKXgVz7xQKe1Dur-sMNlGwi4LXfguTT2YUI8C5Miq3pj2IHc7dC97eyyAiAM4HvyGWfaXWZcei6oIGrOwMvYgy0AcwFry6SIP2SxLT5TrxinRRuem1r1IcOTJsMJyUPp1QsZ7bOyq9G_0060B4CPyovw5523hEuqLTM-R5e5yavY6C_1DHUyE15C3mrh7kdvmlGZeflnHqkFTEKwwOftm-Mv-CKD5Db9ABFGNxKB2FH7nDH67hfOvm4tGNMzceBPKYJ3wciTt9jK3wy39_7cOYVywfrZ-oLhw_XtsbGSSeGn3HytrfgSADAh2sT0Gg6eCC9Xy1vh-Za337SVLUDXZ73W2xJxxUHBkFzZs8L_Xndo5DsbpWhVs9IYUGyraJdqB3SLgDbAppIBCJl4fx6_DG8-xOQPBvuFMlTROe1JVdHOzXI1GElwFDTuH1pjkg4I2G0NhAbE06Y-1illQE; gdsid=1697828393025:1697831731408:99C30D94108AC3030D61C736DDCDF11C',
+        "sec-fetch-dest": "empty",
-            "gd-csrf-token": "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok",
+        "sec-fetch-mode": "cors",
-            "origin": "https://www.glassdoor.com",
+        "sec-fetch-site": "same-origin",
-            "referer": "https://www.glassdoor.com/",
+        "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/118.0.0.0 Safari/537.36",
-            "sec-ch-ua": '"Chromium";v="118", "Google Chrome";v="118", "Not=A?Brand";v="99"',
+    }
-            "sec-ch-ua-mobile": "?0",
+    query_template = """
-            "sec-ch-ua-platform": '"macOS"',
+            query JobSearchResultsQuery(
-            "sec-fetch-dest": "empty",
+                $excludeJobListingIds: [Long!], 
-            "sec-fetch-mode": "cors",
+                $keyword: String, 
-            "sec-fetch-site": "same-origin",
+                $locationId: Int, 
-            "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/118.0.0.0 Safari/537.36",
+                $locationType: LocationTypeEnum, 
-        }
+                $numJobsToShow: Int!, 
+                $pageCursor: String, 
+                $pageNumber: Int, 
+                $filterParams: [FilterParams], 
+                $originalPageUrl: String, 
+                $seoFriendlyUrlInput: String, 
+                $parameterUrlInput: String, 
+                $seoUrl: Boolean
+            ) {
+                jobListings(
+                    contextHolder: {
+                        searchParams: {
+                            excludeJobListingIds: $excludeJobListingIds, 
+                            keyword: $keyword, 
+                            locationId: $locationId, 
+                            locationType: $locationType, 
+                            numPerPage: $numJobsToShow, 
+                            pageCursor: $pageCursor, 
+                            pageNumber: $pageNumber, 
+                            filterParams: $filterParams, 
+                            originalPageUrl: $originalPageUrl, 
+                            seoFriendlyUrlInput: $seoFriendlyUrlInput, 
+                            parameterUrlInput: $parameterUrlInput, 
+                            seoUrl: $seoUrl, 
+                            searchType: SR
+                        }
+                    }
+                ) {
+                    companyFilterOptions {
+                        id
+                        shortName
+                        __typename
+                    }
+                    filterOptions
+                    indeedCtk
+                    jobListings {
+                        ...JobView
+                        __typename
+                    }
+                    jobListingSeoLinks {
+                        linkItems {
+                            position
+                            url
+                            __typename
+                        }
+                        __typename
+                    }
+                    jobSearchTrackingKey
+                    jobsPageSeoData {
+                        pageMetaDescription
+                        pageTitle
+                        __typename
+                    }
+                    paginationCursors {
+                        cursor
+                        pageNumber
+                        __typename
+                    }
+                    indexablePageForSeo
+                    searchResultsMetadata {
+                        searchCriteria {
+                            implicitLocation {
+                                id
+                                localizedDisplayName
+                                type
+                                __typename
+                            }
+                            keyword
+                            location {
+                                id
+                                shortName
+                                localizedShortName
+                                localizedDisplayName
+                                type
+                                __typename
+                            }
+                            __typename
+                        }
+                        helpCenterDomain
+                        helpCenterLocale
+                        jobSerpJobOutlook {
+                            occupation
+                            paragraph
+                            __typename
+                        }
+                        showMachineReadableJobs
+                        __typename
+                    }
+                    totalJobsCount
+                    __typename
+                }
+            }
+
+            fragment JobView on JobListingSearchResult {
+                jobview {
+                    header {
+                        adOrderId
+                        advertiserType
+                        adOrderSponsorshipLevel
+                        ageInDays
+                        divisionEmployerName
+                        easyApply
+                        employer {
+                            id
+                            name
+                            shortName
+                            __typename
+                        }
+                        employerNameFromSearch
+                        goc
+                        gocConfidence
+                        gocId
+                        jobCountryId
+                        jobLink
+                        jobResultTrackingKey
+                        jobTitleText
+                        locationName
+                        locationType
+                        locId
+                        needsCommission
+                        payCurrency
+                        payPeriod
+                        payPeriodAdjustedPay {
+                            p10
+                            p50
+                            p90
+                            __typename
+                        }
+                        rating
+                        salarySource
+                        savedJobId
+                        sponsored
+                        __typename
+                    }
+                    job {
+                        description
+                        importConfigId
+                        jobTitleId
+                        jobTitleText
+                        listingId
+                        __typename
+                    }
+                    jobListingAdminDetails {
+                        cpcVal
+                        importConfigId
+                        jobListingId
+                        jobSourceId
+                        userEligibleForAdminJobDetails
+                        __typename
+                    }
+                    overview {
+                        shortName
+                        squareLogoUrl
+                        __typename
+                    }
+                    __typename
+                }
+                __typename
+            }
+    """

src/jobspy/scrapers/indeed/__init__.py

@@ -4,24 +4,18 @@ jobspy.scrapers.indeed
 
 This module contains routines to scrape Indeed.
 """
-import re
 import math
-import io
+from concurrent.futures import ThreadPoolExecutor, Future
-import json
 from datetime import datetime
 
-import urllib.parse
+import requests
-from bs4 import BeautifulSoup
-from bs4.element import Tag
-from concurrent.futures import ThreadPoolExecutor, Future
 
-from ..exceptions import IndeedException
+from .. import Scraper, ScraperInput, Site
 from ..utils import (
-    count_urgent_words,
     extract_emails_from_text,
-    create_session,
     get_enum_from_job_type,
-    modify_and_get_description
+    markdown_converter,
+    logger
 )
 from ...jobs import (
     JobPost,
@@ -30,327 +24,351 @@ from ...jobs import (
     Location,
     JobResponse,
     JobType,
+    DescriptionFormat
 )
-from .. import Scraper, ScraperInput, Site
 
 
 class IndeedScraper(Scraper):
     def __init__(self, proxy: str | None = None):
         """
-        Initializes IndeedScraper with the Indeed job search url
+        Initializes IndeedScraper with the Indeed API url
         """
-        self.url = None
+        self.scraper_input = None
-        self.country = None
+        self.jobs_per_page = 100
+        self.num_workers = 10
+        self.seen_urls = set()
+        self.headers = None
+        self.api_country_code = None
+        self.base_url = None
+        self.api_url = "https://apis.indeed.com/graphql"
         site = Site(Site.INDEED)
         super().__init__(site, proxy=proxy)
 
-        self.jobs_per_page = 15
-        self.seen_urls = set()
-
-    def scrape_page(
-        self, scraper_input: ScraperInput, page: int
-    ) -> tuple[list[JobPost], int]:
-        """
-        Scrapes a page of Indeed for jobs with scraper_input criteria
-        :param scraper_input:
-        :param page:
-        :return: jobs found on page, total number of jobs found for search
-        """
-        self.country = scraper_input.country
-        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)
-            response = session.get(
-                f"{self.url}/jobs",
-                headers=self.get_headers(),
-                params=params,
-                allow_redirects=True,
-                timeout_seconds=10,
-            )
-            if response.status_code not in range(200, 400):
-                raise IndeedException(
-                    f"bad response with status code: {response.status_code}"
-                )
-        except Exception as e:
-            if "Proxy responded with" in str(e):
-                raise IndeedException("bad proxy")
-            raise IndeedException(str(e))
-
-        soup = BeautifulSoup(response.content, "html.parser")
-        if "did not match any jobs" in response.text:
-            raise IndeedException("Parsing exception: Search did not match any jobs")
-
-        jobs = IndeedScraper.parse_jobs(
-            soup
-        )  #: can raise exception, handled by main scrape function
-        total_num_jobs = IndeedScraper.total_jobs(soup)
-
-        if (
-            not jobs.get("metaData", {})
-            .get("mosaicProviderJobCardsModel", {})
-            .get("results")
-        ):
-            raise IndeedException("No jobs found.")
-
-        def process_job(job) -> JobPost | None:
-            job_url = f'{self.url}/jobs/viewjob?jk={job["jobkey"]}'
-            job_url_client = f'{self.url}/viewjob?jk={job["jobkey"]}'
-            if job_url in self.seen_urls:
-                return None
-
-            extracted_salary = job.get("extractedSalary")
-            compensation = None
-            if extracted_salary:
-                salary_snippet = job.get("salarySnippet")
-                currency = salary_snippet.get("currency") if salary_snippet else None
-                interval = (extracted_salary.get("type"),)
-                if isinstance(interval, tuple):
-                    interval = interval[0]
-
-                interval = interval.upper()
-                if interval in CompensationInterval.__members__:
-                    compensation = Compensation(
-                        interval=CompensationInterval[interval],
-                        min_amount=int(extracted_salary.get("min")),
-                        max_amount=int(extracted_salary.get("max")),
-                        currency=currency,
-                    )
-
-            job_type = IndeedScraper.get_job_type(job)
-            timestamp_seconds = job["pubDate"] / 1000
-            date_posted = datetime.fromtimestamp(timestamp_seconds)
-            date_posted = date_posted.strftime("%Y-%m-%d")
-
-            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")
-                if description is None and li_elements:
-                    description = " ".join(li.text for li in li_elements)
-
-            job_post = JobPost(
-                title=job["normTitle"],
-                description=description,
-                company_name=job["company"],
-                company_url=self.url + job["companyOverviewLink"] if "companyOverviewLink" in job else None,
-                location=Location(
-                    city=job.get("jobLocationCity"),
-                    state=job.get("jobLocationState"),
-                    country=self.country,
-                ),
-                job_type=job_type,
-                compensation=compensation,
-                date_posted=date_posted,
-                job_url=job_url_client,
-                emails=extract_emails_from_text(description) if description else None,
-                num_urgent_words=count_urgent_words(description)
-                if description
-                else None,
-                is_remote=self.is_remote_job(job),
-            )
-            return job_post
-
-        jobs = jobs["metaData"]["mosaicProviderJobCardsModel"]["results"]
-        with ThreadPoolExecutor(max_workers=1) as executor:
-            job_results: list[Future] = [
-                executor.submit(process_job, job) for job in jobs
-            ]
-
-        job_list = [result.result() for result in job_results if result.result()]
-
-        return job_list, total_num_jobs
-
     def scrape(self, scraper_input: ScraperInput) -> JobResponse:
         """
         Scrapes Indeed for jobs with scraper_input criteria
         :param scraper_input:
         :return: job_response
         """
-        pages_to_process = (
+        self.scraper_input = scraper_input
-            math.ceil(scraper_input.results_wanted / self.jobs_per_page) - 1
+        domain, self.api_country_code = self.scraper_input.country.indeed_domain_value
-        )
+        self.base_url = f"https://{domain}.indeed.com"
+        self.headers = self.api_headers.copy()
+        self.headers['indeed-co'] = self.scraper_input.country.indeed_domain_value
+        job_list = []
+        page = 1
 
-        #: get first page to initialize session
+        cursor = None
-        job_list, total_results = self.scrape_page(scraper_input, 0)
+        offset_pages = math.ceil(self.scraper_input.offset / 100)
+        for _ in range(offset_pages):
+            logger.info(f'Indeed skipping search page: {page}')
+            __, cursor = self._scrape_page(cursor)
+            if not __:
+                logger.info(f'Indeed found no jobs on page: {page}')
+                break
 
-        with ThreadPoolExecutor(max_workers=1) as executor:
+        while len(self.seen_urls) < scraper_input.results_wanted:
-            futures: list[Future] = [
+            logger.info(f'Indeed search page: {page}')
-                executor.submit(self.scrape_page, scraper_input, page)
+            jobs, cursor = self._scrape_page(cursor)
-                for page in range(1, pages_to_process + 1)
+            if not jobs:
-            ]
+                logger.info(f'Indeed found no jobs on page: {page}')
+                break
+            job_list += jobs
+            page += 1
+        return JobResponse(jobs=job_list[:scraper_input.results_wanted])
 
-            for future in futures:
+    def _scrape_page(self, cursor: str | None) -> (list[JobPost], str | None):
-                jobs, _ = future.result()
-
-                job_list += jobs
-
-        if len(job_list) > scraper_input.results_wanted:
-            job_list = job_list[: scraper_input.results_wanted]
-
-        job_response = JobResponse(
-            jobs=job_list,
-            total_results=total_results,
-        )
-        return job_response
-
-    def get_description(self, job_page_url: str) -> str | None:
         """
-        Retrieves job description by going to the job page url
+        Scrapes a page of Indeed for jobs with scraper_input criteria
-        :param job_page_url:
+        :param cursor:
-        :return: description
+        :return: jobs found on page, next page cursor
         """
-        parsed_url = urllib.parse.urlparse(job_page_url)
+        jobs = []
-        params = urllib.parse.parse_qs(parsed_url.query)
+        new_cursor = None
-        jk_value = params.get("jk", [None])[0]
+        filters = self._build_filters()
-        formatted_url = f"{self.url}/viewjob?jk={jk_value}&spa=1"
+        query = self.job_search_query.format(
-        session = create_session(self.proxy)
+            what=self.scraper_input.search_term,
+            location=self.scraper_input.location if self.scraper_input.location else self.scraper_input.country.value[0].split(',')[-1],
+            radius=self.scraper_input.distance,
+            dateOnIndeed=self.scraper_input.hours_old,
+            cursor=f'cursor: "{cursor}"' if cursor else '',
+            filters=filters
+        )
+        payload = {
+            'query': query,
+        }
+        api_headers = self.api_headers.copy()
+        api_headers['indeed-co'] = self.api_country_code
+        response = requests.post(self.api_url, headers=api_headers, json=payload, proxies=self.proxy, timeout=10)
+        if response.status_code != 200:
+            logger.info(f'Indeed responded with status code: {response.status_code} (submit GitHub issue if this appears to be a beg)')
+            return jobs, new_cursor
+        data = response.json()
+        jobs = data['data']['jobSearch']['results']
+        new_cursor = data['data']['jobSearch']['pageInfo']['nextCursor']
 
-        try:
+        with ThreadPoolExecutor(max_workers=self.num_workers) as executor:
-            response = session.get(
+            job_results: list[Future] = [
-                formatted_url,
+                executor.submit(self._process_job, job['job']) for job in jobs
-                headers=self.get_headers(),
+           ]
-                allow_redirects=True,
+        job_list = [result.result() for result in job_results if result.result()]
-                timeout_seconds=5,
+        return job_list, new_cursor
-            )
-        except Exception as e:
-            return None
 
-        if response.status_code not in range(200, 400):
+    def _build_filters(self):
-            return None
+        """
+        Builds the filters dict for job type/is_remote. If hours_old is provided, composite filter for job_type/is_remote is not possible.
+        IndeedApply: filters: { keyword: { field: "indeedApplyScope", keys: ["DESKTOP"] } }
+        """
+        filters_str = ""
+        if self.scraper_input.hours_old:
+            filters_str = """
+            filters: {{
+                date: {{
+                  field: "dateOnIndeed",
+                  start: "{start}h"
+                }}
+            }}
+            """.format(start=self.scraper_input.hours_old)
+        elif self.scraper_input.job_type or self.scraper_input.is_remote:
+            job_type_key_mapping = {
+                JobType.FULL_TIME: "CF3CP",
+                JobType.PART_TIME: "75GKK",
+                JobType.CONTRACT: "NJXCK",
+                JobType.INTERNSHIP: "VDTG7",
+            }
 
-        try:
+            keys = []
-            data = json.loads(response.text)
+            if self.scraper_input.job_type:
-            job_description = data["body"]["jobInfoWrapperModel"]["jobInfoModel"][
+                key = job_type_key_mapping[self.scraper_input.job_type]
-                "sanitizedJobDescription"
+                keys.append(key)
-            ]
-        except (KeyError, TypeError, IndexError):
-            return None
 
-        soup = BeautifulSoup(job_description, "html.parser")
+            if self.scraper_input.is_remote:
-        return modify_and_get_description(soup)
+                keys.append("DSQF7")
+
+            if keys:
+                keys_str = '", "'.join(keys)  # Prepare your keys string
+                filters_str = f"""
+                filters: {{
+                  composite: {{
+                    filters: [{{
+                      keyword: {{
+                        field: "attributes",
+                        keys: ["{keys_str}"]
+                      }}
+                    }}]
+                  }}
+                }}
+                """
+        return filters_str
+
+    def _process_job(self, job: dict) -> JobPost | None:
+        """
+        Parses the job dict into JobPost model
+        :param job: dict to parse
+        :return: JobPost if it's a new job
+        """
+        job_url = f'{self.base_url}/viewjob?jk={job["key"]}'
+        if job_url in self.seen_urls:
+            return
+        self.seen_urls.add(job_url)
+        description = job['description']['html']
+        description = markdown_converter(description) if self.scraper_input.description_format == DescriptionFormat.MARKDOWN else description
+
+        job_type = self._get_job_type(job['attributes'])
+        timestamp_seconds = job["datePublished"] / 1000
+        date_posted = datetime.fromtimestamp(timestamp_seconds).strftime("%Y-%m-%d")
+        employer = job['employer'].get('dossier') if job['employer'] else None
+        employer_details = employer.get('employerDetails', {}) if employer else {}
+        return JobPost(
+            title=job["title"],
+            description=description,
+            company_name=job['employer'].get("name") if job.get('employer') else None,
+            company_url=f"{self.base_url}{job['employer']['relativeCompanyPageUrl']}" if job[
+                'employer'] else None,
+            company_url_direct=employer['links']['corporateWebsite'] if employer else None,
+
+            location=Location(
+                city=job.get("location", {}).get("city"),
+                state=job.get("location", {}).get("admin1Code"),
+                country=job.get("location", {}).get("countryCode"),
+            ),
+            job_type=job_type,
+            compensation=self._get_compensation(job),
+            date_posted=date_posted,
+            job_url=job_url,
+            job_url_direct=job['recruit'].get('viewJobUrl') if job.get('recruit') else None,
+            emails=extract_emails_from_text(description) if description else None,
+            is_remote=self._is_job_remote(job, description),
+
+            company_addresses=employer_details['addresses'][0] if employer_details.get('addresses') else None,
+            company_industry=employer_details['industry'].replace('Iv1', '').replace('_', ' ').title() if employer_details.get('industry') else None,
+            company_num_employees=employer_details.get('employeesLocalizedLabel'),
+            company_revenue=employer_details.get('revenueLocalizedLabel'),
+            company_description=employer_details.get('briefDescription'),
+            ceo_name=employer_details.get('ceoName'),
+            ceo_photo_url=employer_details.get('ceoPhotoUrl'),
+
+            logo_photo_url=employer['images'].get('squareLogoUrl') if employer and employer.get('images') else None,
+            banner_photo_url=employer['images'].get('headerImageUrl') if employer and employer.get('images') else None,
+        )
 
     @staticmethod
-    def get_job_type(job: dict) -> list[JobType] | None:
+    def _get_job_type(attributes: list) -> list[JobType]:
         """
-        Parses the job to get list of job types
+        Parses the attributes to get list of job types
-        :param job:
+        :param attributes:
-        :return:
+        :return: list of JobType
         """
         job_types: list[JobType] = []
-        for taxonomy in job["taxonomyAttributes"]:
+        for attribute in attributes:
-            if taxonomy["label"] == "job-types":
+            job_type_str = attribute['label'].replace("-", "").replace(" ", "").lower()
-                for i in range(len(taxonomy["attributes"])):
+            job_type = get_enum_from_job_type(job_type_str)
-                    label = taxonomy["attributes"][i].get("label")
+            if job_type:
-                    if label:
+                job_types.append(job_type)
-                        job_type_str = label.replace("-", "").replace(" ", "").lower()
-                        job_type = get_enum_from_job_type(job_type_str)
-                        if job_type:
-                            job_types.append(job_type)
         return job_types
 
     @staticmethod
-    def parse_jobs(soup: BeautifulSoup) -> dict:
+    def _get_compensation(job: dict) -> Compensation | None:
-        """
-        Parses the jobs from the soup object
-        :param soup:
-        :return: jobs
-        """
-
-        def find_mosaic_script() -> Tag | None:
-            """
-            Finds jobcards script tag
-            :return: script_tag
-            """
-            script_tags = soup.find_all("script")
-
-            for tag in script_tags:
-                if (
-                    tag.string
-                    and "mosaic.providerData" in tag.string
-                    and "mosaic-provider-jobcards" in tag.string
-                ):
-                    return tag
-            return None
-
-        script_tag = find_mosaic_script()
-
-        if script_tag:
-            script_str = script_tag.string
-            pattern = r'window.mosaic.providerData\["mosaic-provider-jobcards"\]\s*=\s*({.*?});'
-            p = re.compile(pattern, re.DOTALL)
-            m = p.search(script_str)
-            if m:
-                jobs = json.loads(m.group(1).strip())
-                return jobs
-            else:
-                raise IndeedException("Could not find mosaic provider job cards data")
-        else:
-            raise IndeedException(
-                "Could not find any results for the search"
-            )
-
-    @staticmethod
-    def total_jobs(soup: BeautifulSoup) -> int:
-        """
-        Parses the total jobs for that search from soup object
-        :param soup:
-        :return: total_num_jobs
-        """
-        script = soup.find("script", string=lambda t: t and "window._initialData" in t)
-
-        pattern = re.compile(r"window._initialData\s*=\s*({.*})\s*;", re.DOTALL)
-        match = pattern.search(script.string)
-        total_num_jobs = 0
-        if match:
-            json_str = match.group(1)
-            data = json.loads(json_str)
-            total_num_jobs = int(data["searchTitleBarModel"]["totalNumResults"])
-        return total_num_jobs
-
-    @staticmethod
-    def get_headers():
-        return {
-            "authority": "www.indeed.com",
-            "accept": "*/*",
-            "accept-language": "en-US,en;q=0.9",
-            "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-ch-ua": '"Google Chrome";v="119", "Chromium";v="119", "Not?A_Brand";v="24"',
-            "sec-ch-ua-mobile": "?0",
-            "sec-ch-ua-platform": '"Windows"',
-            "sec-fetch-dest": "empty",
-            "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
-    def is_remote_job(job: dict) -> bool:
         """
+        Parses the job to get compensation
         :param job:
-        :return: bool
+        :param job:
+        :return: compensation object
+        """
+        comp = job['compensation']['baseSalary']
+        if comp:
+            interval = IndeedScraper._get_compensation_interval(comp['unitOfWork'])
+            if interval:
+                return Compensation(
+                    interval=interval,
+                    min_amount=round(comp['range'].get('min'), 2) if comp['range'].get('min') is not None else None,
+                    max_amount=round(comp['range'].get('max'), 2) if comp['range'].get('max') is not None else None,
+                    currency=job['compensation']['currencyCode']
+                )
+
+    @staticmethod
+    def _is_job_remote(job: dict, description: str) -> bool:
+        """
+        Searches the description, location, and attributes to check if job is remote
+        """
+        remote_keywords = ['remote', 'work from home', 'wfh']
+        is_remote_in_attributes = any(
+            any(keyword in attr['label'].lower() for keyword in remote_keywords)
+            for attr in job['attributes']
+        )
+        is_remote_in_description = any(keyword in description.lower() for keyword in remote_keywords)
+        is_remote_in_location = any(
+            keyword in job['location']['formatted']['long'].lower()
+            for keyword in remote_keywords
+        )
+        return is_remote_in_attributes or is_remote_in_description or is_remote_in_location
+
+    @staticmethod
+    def _get_compensation_interval(interval: str) -> CompensationInterval:
+        interval_mapping = {
+            "DAY": "DAILY",
+            "YEAR": "YEARLY",
+            "HOUR": "HOURLY",
+            "WEEK": "WEEKLY",
+            "MONTH": "MONTHLY"
+        }
+        mapped_interval = interval_mapping.get(interval.upper(), None)
+        if mapped_interval and mapped_interval in CompensationInterval.__members__:
+            return CompensationInterval[mapped_interval]
+        else:
+            raise ValueError(f"Unsupported interval: {interval}")
+
+    api_headers = {
+        'Host': 'apis.indeed.com',
+        'content-type': 'application/json',
+        'indeed-api-key': '161092c2017b5bbab13edb12461a62d5a833871e7cad6d9d475304573de67ac8',
+        'accept': 'application/json',
+        'indeed-locale': 'en-US',
+        'accept-language': 'en-US,en;q=0.9',
+        '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 193.1',
+        'indeed-app-info': 'appv=193.1; appid=com.indeed.jobsearch; osv=16.6.1; os=ios; dtype=phone',
+    }
+    job_search_query = """
+        query GetJobData {{
+          jobSearch(
+            what: "{what}"
+            location: {{ where: "{location}", radius: {radius}, radiusUnit: MILES }}
+            includeSponsoredResults: NONE
+            limit: 100
+            sort: DATE
+            {cursor}
+            {filters}
+          ) {{
+            pageInfo {{
+              nextCursor
+            }}
+            results {{
+              trackingKey
+              job {{
+                key
+                title
+                datePublished
+                dateOnIndeed
+                description {{
+                  html
+                }}
+                location {{
+                  countryName
+                  countryCode
+                  admin1Code
+                  city
+                  postalCode
+                  streetAddress
+                  formatted {{
+                    short
+                    long
+                  }}
+                }}
+                compensation {{
+                  baseSalary {{
+                    unitOfWork
+                    range {{
+                      ... on Range {{
+                        min
+                        max
+                      }}
+                    }}
+                  }}
+                  currencyCode
+                }}
+                attributes {{
+                  key
+                  label
+                }}
+                employer {{
+                  relativeCompanyPageUrl
+                  name
+                  dossier {{
+                      employerDetails {{
+                        addresses
+                        industry
+                        employeesLocalizedLabel
+                        revenueLocalizedLabel
+                        briefDescription
+                        ceoName
+                        ceoPhotoUrl
+                      }}
+                      images {{
+                            headerImageUrl
+                            squareLogoUrl
+                      }}
+                      links {{
+                        corporateWebsite
+                    }}
+                  }}
+                }}
+                recruit {{
+                  viewJobUrl
+                  detailedSalary
+                  workSchedule
+                }}
+              }}
+            }}
+          }}
+        }}
         """
-        for taxonomy in job.get("taxonomyAttributes", []):
-            if taxonomy["label"] == "remote" and len(taxonomy["attributes"]) > 0:
-                return True
-        return False

src/jobspy/scrapers/linkedin/__init__.py

@@ -9,8 +9,6 @@ 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
@@ -25,28 +23,31 @@ from ...jobs import (
     JobResponse,
     JobType,
     Country,
-    Compensation
+    Compensation,
+    DescriptionFormat
 )
 from ..utils import (
-    count_urgent_words,
+    logger,
     extract_emails_from_text,
     get_enum_from_job_type,
     currency_parser,
-    modify_and_get_description
+    markdown_converter
 )
 
 
 class LinkedInScraper(Scraper):
-    DELAY = 3
+    base_url = "https://www.linkedin.com"
+    delay = 3
+    band_delay = 4
+    jobs_per_page = 25
 
     def __init__(self, proxy: Optional[str] = None):
         """
         Initializes LinkedInScraper with the LinkedIn job search url
         """
-        site = Site(Site.LINKEDIN)
+        super().__init__(Site(Site.LINKEDIN), proxy=proxy)
+        self.scraper_input = None
         self.country = "worldwide"
-        self.url = "https://www.linkedin.com"
-        super().__init__(site, proxy=proxy)
 
     def scrape(self, scraper_input: ScraperInput) -> JobResponse:
         """
@@ -54,55 +55,58 @@ class LinkedInScraper(Scraper):
         :param scraper_input:
         :return: job_response
         """
+        self.scraper_input = scraper_input
         job_list: list[JobPost] = []
         seen_urls = set()
         url_lock = Lock()
         page = scraper_input.offset // 25 + 25 if scraper_input.offset else 0
-
+        seconds_old = (
-        def job_type_code(job_type_enum):
+            scraper_input.hours_old * 3600
-            mapping = {
+            if scraper_input.hours_old
-                JobType.FULL_TIME: "F",
+            else None
-                JobType.PART_TIME: "P",
+        )
-                JobType.INTERNSHIP: "I",
+        continue_search = lambda: len(job_list) < scraper_input.results_wanted and page < 1000
-                JobType.CONTRACT: "C",
+        while continue_search():
-                JobType.TEMPORARY: "T",
+            logger.info(f'LinkedIn search page: {page // 25 + 1}')
-            }
-
-            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)
+                "f_JT": self.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,
+                "f_C": ','.join(map(str, scraper_input.linkedin_company_ids)) if scraper_input.linkedin_company_ids else None,
             }
+            if seconds_old is not None:
+                params["f_TPR"] = f"r{seconds_old}"
 
             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?",
+                    f"{self.base_url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
                     params=params,
                     allow_redirects=True,
                     proxies=self.proxy,
-                    headers=self.headers(),
+                    headers=self.headers,
                     timeout=10,
                 )
-                response.raise_for_status()
+                if response.status_code not in range(200, 400):
-
+                    if response.status_code == 429:
-            except requests.HTTPError as e:
+                        logger.error(f'429 Response - Blocked by LinkedIn for too many requests')
-                raise LinkedInException(f"bad response status code: {e.response.status_code}")
+                    else:
-            except ProxyError as e:
+                        logger.error(f'LinkedIn response status code {response.status_code}')
-                raise LinkedInException("bad proxy")
+                    return JobResponse(jobs=job_list)
             except Exception as e:
-                raise LinkedInException(str(e))
+                if "Proxy responded with" in str(e):
+                    logger.error(f'LinkedIn: Bad proxy')
+                else:
+                    logger.error(f'LinkedIn: {str(e)}')
+                return JobResponse(jobs=job_list)
 
             soup = BeautifulSoup(response.text, "html.parser")
             job_cards = soup.find_all("div", class_="base-search-card")
@@ -115,37 +119,38 @@ class LinkedInScraper(Scraper):
                 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}"
+                    job_url = f"{self.base_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)
+                    job_post = self._process_job(job_card, job_url, scraper_input.linkedin_fetch_description)
                     if job_post:
                         job_list.append(job_post)
+                    if not continue_search():
+                       break
                 except Exception as e:
-                    raise LinkedInException("Exception occurred while processing jobs")
+                    raise LinkedInException(str(e))
 
-            page += 25
+            if continue_search():
-            time.sleep(random.uniform(LinkedInScraper.DELAY, LinkedInScraper.DELAY + 2))
+                time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
+                page += self.jobs_per_page
 
         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]:
+    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_text = salary_tag.get_text(separator=" ").strip()
-            salary_values = [currency_parser(value) for value in salary_text.split('-')]
+            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] != '$' else 'USD'
+            currency = salary_text[0] if salary_text[0] != "$" else "USD"
 
             compensation = Compensation(
                 min_amount=int(salary_min),
@@ -166,7 +171,7 @@ class LinkedInScraper(Scraper):
         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)
+        location = self._get_location(metadata_card)
 
         datetime_tag = (
             metadata_card.find("time", class_="job-search-card__listdate")
@@ -178,12 +183,11 @@ class LinkedInScraper(Scraper):
             datetime_str = datetime_tag["datetime"]
             try:
                 date_posted = datetime.strptime(datetime_str, "%Y-%m-%d")
-            except Exception as e:
+            except:
                 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)
+            description, job_type = self._get_job_description(job_url)
 
         return JobPost(
             title=title,
@@ -193,14 +197,12 @@ class LinkedInScraper(Scraper):
             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(
+    def _get_job_description(
         self, job_page_url: str
     ) -> tuple[None, None] | tuple[str | None, tuple[str | None, JobType | None]]:
         """
@@ -210,11 +212,9 @@ class LinkedInScraper(Scraper):
         """
         try:
             session = create_session(is_tls=False, has_retry=True)
-            response = session.get(job_page_url, timeout=5, proxies=self.proxy)
+            response = session.get(job_page_url, headers=self.headers, timeout=5, proxies=self.proxy)
             response.raise_for_status()
-        except requests.HTTPError as e:
+        except:
-            return None, None
-        except Exception as e:
             return None, None
         if response.url == "https://www.linkedin.com/signup":
             return None, None
@@ -223,41 +223,19 @@ class LinkedInScraper(Scraper):
         div_content = soup.find(
             "div", class_=lambda x: x and "show-more-less-html__markup" in x
         )
-
         description = None
-        if div_content:
+        if div_content is not None:
-            description = modify_and_get_description(div_content)
+            def remove_attributes(tag):
+                for attr in list(tag.attrs):
+                    del tag[attr]
+                return tag
+            div_content = remove_attributes(div_content)
+            description = div_content.prettify(formatter="html")
+            if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
+                description = markdown_converter(description)
+        return description, self._parse_job_type(soup)
 
-        def get_job_type(
+    def _get_location(self, metadata_card: Optional[Tag]) -> Location:
-            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
@@ -282,25 +260,50 @@ class LinkedInScraper(Scraper):
                 location = Location(
                     city=city,
                     state=state,
-                    country=Country.from_string(country),
+                    country=Country.from_string(country)
                 )
-
         return location
 
     @staticmethod
-    def headers() -> dict:
+    def _parse_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 []
+
+    @staticmethod
+    def job_type_code(job_type_enum: JobType) -> str:
         return {
-            'authority': 'www.linkedin.com',
+            JobType.FULL_TIME: "F",
-            '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',
+            JobType.PART_TIME: "P",
-            'accept-language': 'en-US,en;q=0.9',
+            JobType.INTERNSHIP: "I",
-            'cache-control': 'max-age=0',
+            JobType.CONTRACT: "C",
-            'sec-ch-ua': '"Not_A Brand";v="8", "Chromium";v="120", "Google Chrome";v="120"',
+            JobType.TEMPORARY: "T",
-            # 'sec-ch-ua-mobile': '?0',
+        }.get(job_type_enum, "")
-            # 'sec-ch-ua-platform': '"macOS"',
+
-            # 'sec-fetch-dest': 'document',
+    headers = {
-            # 'sec-fetch-mode': 'navigate',
+        "authority": "www.linkedin.com",
-            # 'sec-fetch-site': 'none',
+        "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",
-            # 'sec-fetch-user': '?1',
+        "accept-language": "en-US,en;q=0.9",
-            'upgrade-insecure-requests': '1',
+        "cache-control": "max-age=0",
-            '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'
+        "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",
+    }

src/jobspy/scrapers/utils.py

@@ -1,34 +1,29 @@
+import logging
 import re
-import numpy as np
 
-import tls_client
+import numpy as np
 import requests
+import tls_client
+from markdownify import markdownify as md
 from requests.adapters import HTTPAdapter, Retry
 
 from ..jobs import JobType
 
-
+logger = logging.getLogger("JobSpy")
-def modify_and_get_description(soup):
+logger.propagate = False
-    for li in soup.find_all('li'):
+if not logger.handlers:
-        li.string = "- " + li.get_text()
+    logger.setLevel(logging.INFO)
-
+    console_handler = logging.StreamHandler()
-    description = soup.get_text(separator='\n').strip()
+    formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
-    description = re.sub(r'\n+', '\n', description)
+    console_handler.setFormatter(formatter)
-    return description
+    logger.addHandler(console_handler)
 
 
-def count_urgent_words(description: str) -> int:
+def markdown_converter(description_html: str):
-    """
+    if description_html is None:
-    Count the number of urgent words or phrases in a job description.
+        return None
-    """
+    markdown = md(description_html)
-    urgent_patterns = re.compile(
+    return markdown.strip()
-        r"\burgen(t|cy)|\bimmediate(ly)?\b|start asap|\bhiring (now|immediate(ly)?)\b",
-        re.IGNORECASE,
-    )
-    matches = re.findall(urgent_patterns, description)
-    count = len(matches)
-
-    return count
 
 
 def extract_emails_from_text(text: str) -> list[str] | None:
@@ -41,14 +36,10 @@ def extract_emails_from_text(text: str) -> list[str] | None:
 def create_session(proxy: dict | None = None, is_tls: bool = True, has_retry: bool = False, delay: int = 1) -> requests.Session:
     """
     Creates a requests session with optional tls, proxy, and retry settings.
-
     :return: A session object
     """
     if is_tls:
-        session = tls_client.Session(
+        session = tls_client.Session(random_tls_extension_order=True)
-            client_identifier="chrome112",
-            random_tls_extension_order=True,
-        )
         session.proxies = proxy
     else:
         session = requests.Session()
@@ -65,7 +56,6 @@ def create_session(proxy: dict | None = None, is_tls: bool = True, has_retry: bo
 
             session.mount('http://', adapter)
             session.mount('https://', adapter)
-
     return session
 
 
@@ -79,6 +69,7 @@ def get_enum_from_job_type(job_type_str: str) -> JobType | None:
             res = job_type
     return res
 
+
 def currency_parser(cur_str):
     # Remove any non-numerical characters
     # except for ',' '.' or '-' (e.g. EUR)
@@ -94,3 +85,5 @@ def currency_parser(cur_str):
         num = float(cur_str)
 
     return np.round(num, 2)
+
+

src/jobspy/scrapers/ziprecruiter/__init__.py

@@ -6,34 +6,75 @@ This module contains routines to scrape ZipRecruiter.
 """
 import math
 import time
-import re
+from datetime import datetime
-from datetime import datetime, date
 from typing import Optional, Tuple, Any
 
-from bs4 import BeautifulSoup
 from concurrent.futures import ThreadPoolExecutor
 
 from .. import Scraper, ScraperInput, Site
-from ..exceptions import ZipRecruiterException
+from ..utils import (
-from ...jobs import JobPost, Compensation, Location, JobResponse, JobType, Country
+    logger,
-from ..utils import count_urgent_words, extract_emails_from_text, create_session, modify_and_get_description
+    extract_emails_from_text,
+    create_session,
+    markdown_converter
+)
+from ...jobs import (
+    JobPost,
+    Compensation,
+    Location,
+    JobResponse,
+    JobType,
+    Country,
+    DescriptionFormat
+)
 
 
 class ZipRecruiterScraper(Scraper):
+    base_url = "https://www.ziprecruiter.com"
+    api_url = "https://api.ziprecruiter.com"
+
     def __init__(self, proxy: Optional[str] = None):
         """
         Initializes ZipRecruiterScraper with the ZipRecruiter job search url
         """
-        site = Site(Site.ZIP_RECRUITER)
+        self.scraper_input = None
-        self.url = "https://www.ziprecruiter.com"
         self.session = create_session(proxy)
-        self.get_cookies()
+        self._get_cookies()
-        super().__init__(site, proxy=proxy)
+        super().__init__(Site.ZIP_RECRUITER, proxy=proxy)
 
+        self.delay = 5
         self.jobs_per_page = 20
         self.seen_urls = set()
 
-    def find_jobs_in_page(
+    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
+        """
+        Scrapes ZipRecruiter for jobs with scraper_input criteria.
+        :param scraper_input: Information about job search criteria.
+        :return: JobResponse containing a list of jobs.
+        """
+        self.scraper_input = scraper_input
+        job_list: list[JobPost] = []
+        continue_token = None
+
+        max_pages = math.ceil(scraper_input.results_wanted / self.jobs_per_page)
+        for page in range(1, max_pages + 1):
+            if len(job_list) >= scraper_input.results_wanted:
+                break
+            if page > 1:
+                time.sleep(self.delay)
+            logger.info(f'ZipRecruiter search page: {page}')
+            jobs_on_page, continue_token = self._find_jobs_in_page(
+                scraper_input, continue_token
+            )
+            if jobs_on_page:
+                job_list.extend(jobs_on_page)
+            else:
+                break
+            if not continue_token:
+                break
+        return JobResponse(jobs=job_list[: scraper_input.results_wanted])
+
+    def _find_jobs_in_page(
         self, scraper_input: ScraperInput, continue_token: str | None = None
     ) -> Tuple[list[JobPost], Optional[str]]:
         """
@@ -42,96 +83,62 @@ class ZipRecruiterScraper(Scraper):
         :param continue_token:
         :return: jobs found on page
         """
-        params = self.add_params(scraper_input)
+        jobs_list = []
+        params = self._add_params(scraper_input)
         if continue_token:
-            params["continue"] = continue_token
+            params["continue_from"] = continue_token
         try:
-            response = self.session.get(
+            res= self.session.get(
-                f"https://api.ziprecruiter.com/jobs-app/jobs",
+                f"{self.api_url}/jobs-app/jobs",
-                headers=self.headers(),
+                headers=self.headers,
-                params=self.add_params(scraper_input),
+                params=params
             )
-            if response.status_code != 200:
+            if res.status_code not in range(200, 400):
-                raise ZipRecruiterException(
+                if res.status_code == 429:
-                    f"bad response status code: {response.status_code}"
+                    logger.error(f'429 Response - Blocked by ZipRecruiter for too many requests')
-                )
+                else:
+                    logger.error(f'ZipRecruiter response status code {res.status_code}')
+                return jobs_list, ""
         except Exception as e:
-            if "Proxy responded with non 200 code" in str(e):
+            if "Proxy responded with" in str(e):
-                raise ZipRecruiterException("bad proxy")
+                logger.error(f'Indeed: Bad proxy')
-            raise ZipRecruiterException(str(e))
+            else:
+                logger.error(f'Indeed: {str(e)}')
+            return jobs_list, ""
 
-        time.sleep(5)
-        response_data = response.json()
-        jobs_list = response_data.get("jobs", [])
-        next_continue_token = response_data.get("continue", None)
 
+        res_data = res.json()
+        jobs_list = res_data.get("jobs", [])
+        next_continue_token = res_data.get("continue", None)
         with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
-            job_results = [executor.submit(self.process_job, job) for job in jobs_list]
+            job_results = [executor.submit(self._process_job, job) for job in jobs_list]
 
-        job_list = [result.result() for result in job_results if result.result()]
+        job_list = list(filter(None, (result.result() for result in job_results)))
         return job_list, next_continue_token
 
-    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
+    def _process_job(self, job: dict) -> JobPost | None:
         """
-        Scrapes ZipRecruiter for jobs with scraper_input criteria.
+        Processes an individual job dict from the response
-        :param scraper_input: Information about job search criteria.
-        :return: JobResponse containing a list of jobs.
         """
-        job_list: list[JobPost] = []
-        continue_token = None
-
-        max_pages = math.ceil(scraper_input.results_wanted / self.jobs_per_page)
-
-        for page in range(1, max_pages + 1):
-            if len(job_list) >= scraper_input.results_wanted:
-                break
-
-            jobs_on_page, continue_token = self.find_jobs_in_page(
-                scraper_input, continue_token
-            )
-            if jobs_on_page:
-                job_list.extend(jobs_on_page)
-
-            if not continue_token:
-                break
-
-        if len(job_list) > scraper_input.results_wanted:
-            job_list = job_list[: scraper_input.results_wanted]
-
-        return JobResponse(jobs=job_list)
-
-    @staticmethod
-    def process_job(job: dict) -> JobPost:
-        """Processes an individual job dict from the response"""
         title = job.get("name")
-        job_url = job.get("job_url")
+        job_url = f"{self.base_url}/jobs//j?lvk={job['listing_key']}"
+        if job_url in self.seen_urls:
+            return
+        self.seen_urls.add(job_url)
 
-        job_description_html = job.get("job_description", "").strip()
+        description = job.get("job_description", "").strip()
-        description_soup = BeautifulSoup(job_description_html, "html.parser")
+        description = markdown_converter(description) if self.scraper_input.description_format == DescriptionFormat.MARKDOWN else description
-        description = modify_and_get_description(description_soup)
+        company = job.get("hiring_company", {}).get("name")
-
-        company = job["hiring_company"].get("name") if "hiring_company" in job else None
         country_value = "usa" if job.get("job_country") == "US" else "canada"
         country_enum = Country.from_string(country_value)
 
         location = Location(
             city=job.get("job_city"), state=job.get("job_state"), country=country_enum
         )
-        job_type = ZipRecruiterScraper.get_job_type_enum(
+        job_type = self._get_job_type_enum(
             job.get("employment_type", "").replace("_", "").lower()
         )
-
+        date_posted = datetime.fromisoformat(job['posted_time'].rstrip("Z")).date()
-        save_job_url = job.get("SaveJobURL", "")
-        posted_time_match = re.search(
-            r"posted_time=(\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}Z)", save_job_url
-        )
-        if posted_time_match:
-            date_time_str = posted_time_match.group(1)
-            date_posted_obj = datetime.strptime(date_time_str, "%Y-%m-%dT%H:%M:%SZ")
-            date_posted = date_posted_obj.date()
-        else:
-            date_posted = date.today()
-
         return JobPost(
             title=title,
             company_name=company,
@@ -153,63 +160,49 @@ class ZipRecruiterScraper(Scraper):
             job_url=job_url,
             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_cookies(self):
+    def _get_cookies(self):
-        url="https://api.ziprecruiter.com/jobs-app/event"
         data="event_type=session&logged_in=false&number_of_retry=1&property=model%3AiPhone&property=os%3AiOS&property=locale%3Aen_us&property=app_build_number%3A4734&property=app_version%3A91.0&property=manufacturer%3AApple&property=timestamp%3A2024-01-12T12%3A04%3A42-06%3A00&property=screen_height%3A852&property=os_version%3A16.6.1&property=source%3Ainstall&property=screen_width%3A393&property=device_model%3AiPhone%2014%20Pro&property=brand%3AApple"
-        self.session.post(url, data=data, headers=ZipRecruiterScraper.headers())
+        self.session.post(f"{self.api_url}/jobs-app/event", data=data, headers=self.headers)
 
     @staticmethod
-    def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
+    def _get_job_type_enum(job_type_str: str) -> list[JobType] | None:
         for job_type in JobType:
             if job_type_str in job_type.value:
                 return [job_type]
         return None
 
     @staticmethod
-    def add_params(scraper_input) -> dict[str, str | Any]:
+    def _add_params(scraper_input) -> dict[str, str | Any]:
         params = {
             "search": scraper_input.search_term,
             "location": scraper_input.location,
-            "form": "jobs-landing",
         }
-        job_type_value = None
+        if scraper_input.hours_old:
+            fromage = max(scraper_input.hours_old // 24, 1) if scraper_input.hours_old else None
+            params['days'] = fromage
+        job_type_map = {
+            JobType.FULL_TIME: 'full_time',
+            JobType.PART_TIME: 'part_time'
+        }
         if scraper_input.job_type:
-            if scraper_input.job_type.value == "fulltime":
+            params['employment_type'] = job_type_map[scraper_input.job_type] if scraper_input.job_type in job_type_map else scraper_input.job_type.value[0]
-                job_type_value = "full_time"
+        if scraper_input.easy_apply:
-            elif scraper_input.job_type.value == "parttime":
+            params['zipapply'] = 1
-                job_type_value = "part_time"
-            else:
-                job_type_value = scraper_input.job_type.value
-
-        if job_type_value:
-            params[
-                "refine_by_employment"
-            ] = f"employment_type:employment_type:{job_type_value}"
-
         if scraper_input.is_remote:
-            params["refine_by_location_type"] = "only_remote"
+            params["remote"] = 1
-
         if scraper_input.distance:
             params["radius"] = scraper_input.distance
+        return {k: v for k, v in params.items() if v is not None}
 
-        return params
+    headers = {
-
+        "Host": "api.ziprecruiter.com",
-    @staticmethod
+        "accept": "*/*",
-    def headers() -> dict:
+        "x-zr-zva-override": "100000000;vid:ZT1huzm_EQlDTVEc",
-        """
+        "x-pushnotificationid": "0ff4983d38d7fc5b3370297f2bcffcf4b3321c418f5c22dd152a0264707602a0",
-        Returns headers needed for requests
+        "x-deviceid": "D77B3A92-E589-46A4-8A39-6EF6F1D86006",
-        :return: dict - Dictionary containing headers
+        "user-agent": "Job Search/87.0 (iPhone; CPU iOS 16_6_1 like Mac OS X)",
-        """
+        "authorization": "Basic YTBlZjMyZDYtN2I0Yy00MWVkLWEyODMtYTI1NDAzMzI0YTcyOg==",
-        return {
+        "accept-language": "en-US,en;q=0.9",
-            "Host": "api.ziprecruiter.com",
+    }
-            "accept": "*/*",
-            "x-zr-zva-override": "100000000;vid:ZT1huzm_EQlDTVEc",
-            "x-pushnotificationid": "0ff4983d38d7fc5b3370297f2bcffcf4b3321c418f5c22dd152a0264707602a0",
-            "x-deviceid": "D77B3A92-E589-46A4-8A39-6EF6F1D86006",
-            "user-agent": "Job Search/87.0 (iPhone; CPU iOS 16_6_1 like Mac OS X)",
-            "authorization": "Basic YTBlZjMyZDYtN2I0Yy00MWVkLWEyODMtYTI1NDAzMzI0YTcyOg==",
-            "accept-language": "en-US,en;q=0.9",
-        }