minor fix

Correct initial page offset calculation
Separate page variable from request counter
Fix job offset starting value
Increment offset by number of jobs returned instead of expected value

.pre-commit-config.yaml

@@ -0,0 +1,7 @@
+repos:
+- repo: https://github.com/psf/black
+  rev: 24.2.0
+  hooks:
+  - id: black
+    language_version: python
+    args: [--line-length=88, --quiet]

README.md

@@ -4,27 +4,21 @@
 
 **Not technical?** Try out the web scraping tool on our site at [usejobspy.com](https://usejobspy.com).
 
-*Looking to build a data-focused software product?* **[Book a call](https://calendly.com/bunsly/15min)** *to
-work with us.*  
-\
-Check out another project we wrote: ***[HomeHarvest](https://github.com/Bunsly/HomeHarvest)** – a Python package
-for real estate scraping*
+*Looking to build a data-focused software product?* **[Book a call](https://bunsly.com/)** *to
+work with us.*
 
 ## Features
 
-- Scrapes job postings from **LinkedIn**, **Indeed** & **ZipRecruiter** simultaneously
+- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, & **ZipRecruiter** simultaneously
 - Aggregates the job postings in a Pandas DataFrame
-- Proxy support (HTTP/S, SOCKS)
-
-[Video Guide for JobSpy](https://www.youtube.com/watch?v=RuP1HrAZnxs&pp=ygUgam9icyBzY3JhcGVyIGJvdCBsaW5rZWRpbiBpbmRlZWQ%3D) -
-Updated for release v1.1.3
+- Proxies support
 
 ![jobspy](https://github.com/cullenwatson/JobSpy/assets/78247585/ec7ef355-05f6-4fd3-8161-a817e31c5c57)
 
 ### Installation
 
 ```
-pip install python-jobspy
+pip install -U python-jobspy
 ```
 
 _Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_
@@ -32,24 +26,30 @@ _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"],
+    site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"],
     search_term="software engineer",
     location="Dallas, TX",
-    results_wanted=10,
-    country_indeed='USA'  # only needed for indeed
+    results_wanted=20,
+    hours_old=72, # (only Linkedin/Indeed is hour specific, others round up to days old)
+    country_indeed='USA',  # only needed for indeed / glassdoor
+    
+    # linkedin_fetch_description=True # get full description , direct job url , company industry and job level (seniority level) for linkedin (slower)
+    # proxies=["208.195.175.46:65095", "208.195.175.45:65095", "localhost"],
+    
 )
 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_excel
 ```
 
 ### Output
 
 ```
-SITE           TITLE                             COMPANY_NAME      CITY          STATE  JOB_TYPE  INTERVAL  MIN_AMOUNT  MAX_AMOUNT  JOB_URL                                            DESCRIPTION
+SITE           TITLE                             COMPANY           CITY          STATE  JOB_TYPE  INTERVAL  MIN_AMOUNT  MAX_AMOUNT  JOB_URL                                            DESCRIPTION
 indeed         Software Engineer                 AMERICAN SYSTEMS  Arlington     VA     None      yearly    200000      150000      https://www.indeed.com/viewjob?jk=5e409e577046...  THIS POSITION COMES WITH A 10K SIGNING BONUS!...
 indeed         Senior Software Engineer          TherapyNotes.com  Philadelphia  PA     fulltime  yearly    135000      110000      https://www.indeed.com/viewjob?jk=da39574a40cb...  About Us TherapyNotes is the national leader i...
 linkedin       Software Engineer - Early Career  Lockheed Martin   Sunnyvale     CA     fulltime  yearly    None        None        https://www.linkedin.com/jobs/view/3693012711      Description:By bringing together people that u...
@@ -61,27 +61,78 @@ zip_recruiter Software Developer                 TEKsystems        Phoenix
 ### Parameters for `scrape_jobs()`
 
 ```plaintext
-Required
-├── site_type (List[enum]): linkedin, zip_recruiter, indeed
-└── search_term (str)
 Optional
-├── location (int)
-├── distance (int): in miles
-├── job_type (enum): fulltime, parttime, internship, contract
-├── proxy (str): in format 'http://user:pass@host:port' or [https, socks]
+├── site_name (list|str): 
+|    linkedin, zip_recruiter, indeed, glassdoor 
+|    (default is all four)
+│
+├── search_term (str)
+│
+├── location (str)
+│
+├── distance (int): 
+|    in miles, default 50
+│
+├── job_type (str): 
+|    fulltime, parttime, internship, contract
+│
+├── proxies (list): 
+|    in format ['user:pass@host:port', 'localhost']
+|    each job board will round robin through the proxies
+│
 ├── is_remote (bool)
-├── 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
-├── 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)
+│
+├── results_wanted (int): 
+|    number of job results to retrieve for each site specified in 'site_name'
+│
+├── easy_apply (bool): 
+|    filters for jobs that are hosted on the job board site
+│
+├── description_format (str): 
+|    markdown, html (Format type of the job descriptions. Default is markdown.)
+│
+├── offset (int): 
+|    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.)
+│
+├── verbose (int) {0, 1, 2}: 
+|    Controls the verbosity of the runtime printouts 
+|    (0 prints only errors, 1 is errors+warnings, 2 is all logs. Default is 2.)
+
+├── linkedin_fetch_description (bool): 
+|    fetches full description and direct job url for LinkedIn (Increases requests by O(n))
+│
+├── linkedin_company_ids (list[int]): 
+|    searches for linkedin jobs with specific company ids
+|
+├── country_indeed (str): 
+|    filters the country on Indeed & Glassdoor (see below for correct spelling)
 ```
 
+```
+├── Indeed limitations:
+|    Only one from this list can be used in a search:
+|    - hours_old
+|    - job_type & is_remote
+|    - easy_apply
+│
+└── LinkedIn limitations:
+|    Only one from this list can be used in a search:
+|    - hours_old
+|    - easy_apply
+```
+
+
 ### JobPost Schema
 
 ```plaintext
 JobPost
 ├── title (str)
 ├── company (str)
+├── company_url (str)
 ├── job_url (str)
 ├── location (object)
 │   ├── country (str)
@@ -89,60 +140,75 @@ JobPost
 │   ├── state (str)
 ├── description (str)
 ├── job_type (str): fulltime, parttime, internship, contract
+├── job_function (str)
 ├── compensation (object)
 │   ├── interval (str): yearly, monthly, weekly, daily, hourly
 │   ├── min_amount (int)
 │   ├── max_amount (int)
 │   └── currency (enum)
-└── date_posted (date)
-└── emails (str)
-└── num_urgent_words (int)
+├── date_posted (date)
+├── emails (str)
 └── is_remote (bool)
+
+Linkedin specific
+└── job_level (str)
+
+Linkedin & Indeed specific
+└── company_industry (str)
+
+Indeed specific
+├── company_country (str)
+└── company_addresses (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`
-
 ## Supported Countries for Job Searching
 
 ### **LinkedIn**
 
-LinkedIn searches globally & uses only the `location` parameter.
+LinkedIn searches globally & uses only the `location` parameter. 
 
 ### **ZipRecruiter**
 
 ZipRecruiter searches for jobs in **US/Canada** & uses only the `location` parameter.
 
-### **Indeed**
+### **Indeed / Glassdoor**
 
-Indeed supports most countries, but the `country_indeed` parameter is required. Additionally, use the `location`
-parameter to narrow down the location, e.g. city & state if necessary.
+Indeed & Glassdoor supports most countries, but the `country_indeed` parameter is required. Additionally, use the `location`
+parameter to narrow down the location, e.g. city & state if necessary. 
 
-You can specify the following countries when searching on Indeed (use the exact name):
+You can specify the following countries when searching on Indeed (use the exact name, * indicates support for Glassdoor):
 
 |                      |              |            |                |
 |----------------------|--------------|------------|----------------|
-| Argentina            | Australia    | Austria    | Bahrain        |
-| Belgium              | Brazil       | Canada     | Chile          |
+| Argentina            | Australia*   | Austria*   | Bahrain        |
+| Belgium*             | Brazil*      | Canada*    | Chile          |
 | China                | Colombia     | Costa Rica | Czech Republic |
 | Denmark              | Ecuador      | Egypt      | Finland        |
-| France               | Germany      | Greece     | Hong Kong      |
-| Hungary              | India        | Indonesia  | Ireland        |
-| Israel               | Italy        | Japan      | Kuwait         |
-| Luxembourg           | Malaysia     | Mexico     | Morocco        |
-| Netherlands          | New Zealand  | Nigeria    | Norway         |
+| France*              | Germany*     | Greece     | Hong Kong*     |
+| Hungary              | India*       | Indonesia  | Ireland*       |
+| Israel               | Italy*       | Japan      | Kuwait         |
+| Luxembourg           | Malaysia     | Mexico*    | Morocco        |
+| Netherlands*         | New Zealand* | Nigeria    | Norway         |
 | Oman                 | Pakistan     | Panama     | Peru           |
 | Philippines          | Poland       | Portugal   | Qatar          |
-| Romania              | Saudi Arabia | Singapore  | South Africa   |
-| South Korea          | Spain        | Sweden     | Switzerland    |
+| Romania              | Saudi Arabia | Singapore* | South Africa   |
+| South Korea          | Spain*       | Sweden     | Switzerland*   |
 | Taiwan               | Thailand     | Turkey     | Ukraine        |
-| United Arab Emirates | UK           | USA        | Uruguay        |
-| Venezuela            | Vietnam      |            |                |
+| United Arab Emirates | UK*          | USA*       | Uruguay        |
+| Venezuela            | Vietnam*     |            |                |
+
+
+## Notes
+* Indeed is the best scraper currently with no rate limiting.  
+* All the job board endpoints are capped at around 1000 jobs on a given search.  
+* LinkedIn is the most restrictive and usually rate limits around the 10th page with one ip. Proxies are a must basically.
 
 ## Frequently Asked Questions
 
@@ -157,16 +223,7 @@ 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.
-- Trying a VPN or proxy to change your IP address.
+- Wait some time between scrapes (site-dependent).
+- Try using the proxies param 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
-
-
-  

examples/JobSpy_Demo.ipynb

@@ -1,167 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "00a94b47-f47b-420f-ba7e-714ef219c006",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from jobspy import scrape_jobs\n",
-    "import pandas as pd\n",
-    "from IPython.display import display, HTML"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9f773e6c-d9fc-42cc-b0ef-63b739e78435",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "pd.set_option('display.max_columns', None)\n",
-    "pd.set_option('display.max_rows', None)\n",
-    "pd.set_option('display.width', None)\n",
-    "pd.set_option('display.max_colwidth', 50)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1253c1f8-9437-492e-9dd3-e7fe51099420",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# example 1 (no hyperlinks, USA)\n",
-    "jobs = scrape_jobs(\n",
-    "    site_name=[\"linkedin\"],\n",
-    "    location='san francisco',\n",
-    "    search_term=\"engineer\",\n",
-    "    results_wanted=5,\n",
-    "\n",
-    "    # use if you want to use a proxy\n",
-    "    # proxy=\"socks5://jobspy:5a4vpWtj4EeJ2hoYzk@us.smartproxy.com:10001\",\n",
-    "    proxy=\"http://jobspy:5a4vpWtj4EeJ2hoYzk@us.smartproxy.com:10001\",\n",
-    "    #proxy=\"https://jobspy:5a4vpWtj4EeJ2hoYzk@us.smartproxy.com:10001\",\n",
-    ")\n",
-    "display(jobs)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6a581b2d-f7da-4fac-868d-9efe143ee20a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# example 2 - remote USA & hyperlinks\n",
-    "jobs = scrape_jobs(\n",
-    "    site_name=[\"linkedin\", \"zip_recruiter\", \"indeed\"],\n",
-    "    # location='san francisco',\n",
-    "    search_term=\"software engineer\",\n",
-    "    country_indeed=\"USA\",\n",
-    "    hyperlinks=True,\n",
-    "    is_remote=True,\n",
-    "    results_wanted=5, \n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "fe8289bc-5b64-4202-9a64-7c117c83fd9a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# use if hyperlinks=True\n",
-    "html = jobs.to_html(escape=False)\n",
-    "# change max-width: 200px to show more or less of the content\n",
-    "truncate_width = f'<style>.dataframe td {{ max-width: 200px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }}</style>{html}'\n",
-    "display(HTML(truncate_width))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "951c2fe1-52ff-407d-8bb1-068049b36777",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# example 3 - with hyperlinks, international - linkedin (no zip_recruiter)\n",
-    "jobs = scrape_jobs(\n",
-    "    site_name=[\"linkedin\"],\n",
-    "    location='berlin',\n",
-    "    search_term=\"engineer\",\n",
-    "    hyperlinks=True,\n",
-    "    results_wanted=5,\n",
-    "    easy_apply=True\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1e37a521-caef-441c-8fc2-2eb5b2e7da62",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# use if hyperlinks=True\n",
-    "html = jobs.to_html(escape=False)\n",
-    "# change max-width: 200px to show more or less of the content\n",
-    "truncate_width = f'<style>.dataframe td {{ max-width: 200px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }}</style>{html}'\n",
-    "display(HTML(truncate_width))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "0650e608-0b58-4bf5-ae86-68348035b16a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# example 4 - international indeed (no zip_recruiter)\n",
-    "jobs = scrape_jobs(\n",
-    "    site_name=[\"indeed\"],\n",
-    "    search_term=\"engineer\",\n",
-    "    country_indeed = \"China\",\n",
-    "    hyperlinks=True\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "40913ac8-3f8a-4d7e-ac47-afb88316432b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# use if hyperlinks=True\n",
-    "html = jobs.to_html(escape=False)\n",
-    "# change max-width: 200px to show more or less of the content\n",
-    "truncate_width = f'<style>.dataframe td {{ max-width: 200px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }}</style>{html}'\n",
-    "display(HTML(truncate_width))"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.11.5"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}

examples/JobSpy_Demo.py

@@ -1,31 +0,0 @@
-from jobspy import scrape_jobs
-import pandas as pd
-
-jobs: pd.DataFrame = scrape_jobs(
-    site_name=["indeed", "linkedin", "zip_recruiter"],
-    search_term="software engineer",
-    location="Dallas, TX",
-    results_wanted=50,  # be wary the higher it is, the more likey you'll get blocked (rotating proxy should work tho)
-    country_indeed="USA",
-    offset=25  # start jobs from an offset (use if search failed and want to continue)
-    # proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
-)
-
-# formatting for pandas
-pd.set_option("display.max_columns", None)
-pd.set_option("display.max_rows", None)
-pd.set_option("display.width", None)
-pd.set_option("display.max_colwidth", 50)  # set to 0 to see full job url / desc
-
-# 1: output to console
-print(jobs)
-
-# 2: output to .csv
-jobs.to_csv("./jobs.csv", index=False)
-print("outputted to jobs.csv")
-
-# 3: output to .xlsx
-# jobs.to_xlsx('jobs.xlsx', index=False)
-
-# 4: display in Jupyter Notebook (1. pip install jupyter 2. jupyter notebook)
-# display(jobs)

pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "python-jobspy"
-version = "1.1.15"
-description = "Job scraper for LinkedIn, Indeed & ZipRecruiter"
+version = "1.1.58"
+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"
 readme = "README.md"
@@ -13,17 +13,24 @@ packages = [
 [tool.poetry.dependencies]
 python = "^3.10"
 requests = "^2.31.0"
-tls-client = "^0.2.1"
 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"
+regex = "^2024.4.28"
 
 
 [tool.poetry.group.dev.dependencies]
 pytest = "^7.4.1"
 jupyter = "^1.0.0"
+black = "*"
+pre-commit = "*"
 
 [build-system]
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"
+
+[tool.black]
+line-length = 88

src/jobspy/__init__.py

@@ -1,48 +1,58 @@
+from __future__ import annotations
+
 import pandas as pd
-import concurrent.futures
-from concurrent.futures import ThreadPoolExecutor
-from typing import Tuple, Optional
+from typing import Tuple
+from concurrent.futures import ThreadPoolExecutor, as_completed
 
 from .jobs import JobType, Location
+from .scrapers.utils import logger, set_logger_level, extract_salary
 from .scrapers.indeed import IndeedScraper
 from .scrapers.ziprecruiter import ZipRecruiterScraper
+from .scrapers.glassdoor import GlassdoorScraper
 from .scrapers.linkedin import LinkedInScraper
 from .scrapers import ScraperInput, Site, JobResponse, Country
 from .scrapers.exceptions import (
     LinkedInException,
     IndeedException,
     ZipRecruiterException,
+    GlassdoorException,
 )
 
-SCRAPER_MAPPING = {
-    Site.LINKEDIN: LinkedInScraper,
-    Site.INDEED: IndeedScraper,
-    Site.ZIP_RECRUITER: ZipRecruiterScraper,
-}
-
-
-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],
-    search_term: str,
-    location: str = "",
-    distance: int = None,
+    site_name: str | list[str] | Site | list[Site] | None = None,
+    search_term: str | None = None,
+    location: str | None = None,
+    distance: int | None = 50,
     is_remote: bool = False,
-    job_type: str = None,
-    easy_apply: bool = False,  # linkedin
+    job_type: str | None = None,
+    easy_apply: bool | None = None,
     results_wanted: int = 15,
     country_indeed: str = "usa",
     hyperlinks: bool = False,
-    proxy: Optional[str] = None,
-    offset: Optional[int] = 0,
+    proxies: list[str] | str | None = None,
+    description_format: str = "markdown",
+    linkedin_fetch_description: bool | None = False,
+    linkedin_company_ids: list[int] | None = None,
+    offset: int | None = 0,
+    hours_old: int = None,
+    verbose: int = 2,
+    **kwargs,
 ) -> pd.DataFrame:
     """
     Simultaneously scrapes job data from multiple job sites.
-    :return: results_wanted: pandas dataframe containing job data
+    :return: pandas dataframe containing job data
     """
+    SCRAPER_MAPPING = {
+        Site.LINKEDIN: LinkedInScraper,
+        Site.INDEED: IndeedScraper,
+        Site.ZIP_RECRUITER: ZipRecruiterScraper,
+        Site.GLASSDOOR: GlassdoorScraper,
+    }
+    set_logger_level(verbose)
+
+    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:
@@ -52,18 +62,23 @@ def scrape_jobs(
 
     job_type = get_enum_from_value(job_type) if job_type else None
 
-    if type(site_name) == str:
-        site_type = [_map_str_to_site(site_name)]
-    else:  #: if type(site_name) == list
-        site_type = [
-            _map_str_to_site(site) if type(site) == str else site_name
-            for site in site_name
-        ]
+    def get_site_type():
+        site_types = list(Site)
+        if isinstance(site_name, str):
+            site_types = [map_str_to_site(site_name)]
+        elif isinstance(site_name, Site):
+            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,
@@ -71,27 +86,21 @@ def scrape_jobs(
         is_remote=is_remote,
         job_type=job_type,
         easy_apply=easy_apply,
+        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)
-
-        try:
-            scraped_data: JobResponse = scraper.scrape(scraper_input)
-        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))
-            else:
-                raise e
+        scraper = scraper_class(proxies=proxies)
+        scraped_data: JobResponse = scraper.scrape(scraper_input)
+        cap_name = site.value.capitalize()
+        site_name = "ZipRecruiter" if cap_name == "Zip_recruiter" else cap_name
+        logger.info(f"{site_name} finished scraping")
         return site.value, scraped_data
 
     site_to_jobs_dict = {}
@@ -105,18 +114,32 @@ 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
 
+    def convert_to_annual(job_data: dict):
+        if job_data["interval"] == "hourly":
+            job_data["min_amount"] *= 2080
+            job_data["max_amount"] *= 2080
+        if job_data["interval"] == "monthly":
+            job_data["min_amount"] *= 12
+            job_data["max_amount"] *= 12
+        if job_data["interval"] == "weekly":
+            job_data["min_amount"] *= 52
+            job_data["max_amount"] *= 52
+        if job_data["interval"] == "daily":
+            job_data["min_amount"] *= 260
+            job_data["max_amount"] *= 260
+        job_data["interval"] = "yearly"
+
     jobs_dfs: list[pd.DataFrame] = []
 
     for site, job_response in site_to_jobs_dict.items():
         for job in job_response.jobs:
             job_data = job.dict()
-            job_data[
-                "job_url_hyper"
-            ] = f'<a href="{job_data["job_url"]}">{job_data["job_url"]}</a>'
+            job_url = job_data["job_url"]
+            job_data["job_url_hyper"] = f'<a href="{job_url}">{job_url}</a>'
             job_data["site"] = site
             job_data["company"] = job_data["company_name"]
             job_data["job_type"] = (
@@ -127,7 +150,10 @@ def scrape_jobs(
             job_data["emails"] = (
                 ", ".join(job_data["emails"]) if job_data["emails"] else None
             )
-            job_data["location"] = Location(**job_data["location"]).display_location()
+            if job_data["location"]:
+                job_data["location"] = Location(
+                    **job_data["location"]
+                ).display_location()
 
             compensation_obj = job_data.get("compensation")
             if compensation_obj and isinstance(compensation_obj, dict):
@@ -139,20 +165,39 @@ def scrape_jobs(
                 job_data["min_amount"] = compensation_obj.get("min_amount")
                 job_data["max_amount"] = compensation_obj.get("max_amount")
                 job_data["currency"] = compensation_obj.get("currency", "USD")
+                if (
+                    job_data["interval"]
+                    and job_data["interval"] != "yearly"
+                    and job_data["min_amount"]
+                    and job_data["max_amount"]
+                ):
+                    convert_to_annual(job_data)
+
             else:
-                job_data["interval"] = None
-                job_data["min_amount"] = None
-                job_data["max_amount"] = None
-                job_data["currency"] = None
+                if country_enum == Country.USA:
+                    (
+                        job_data["interval"],
+                        job_data["min_amount"],
+                        job_data["max_amount"],
+                        job_data["currency"],
+                    ) = extract_salary(job_data["description"])
 
             job_df = pd.DataFrame([job_data])
             jobs_dfs.append(job_df)
 
     if jobs_dfs:
-        jobs_df = pd.concat(jobs_dfs, ignore_index=True)
-        desired_order: list[str] = [
-            "job_url_hyper" if hyperlinks else "job_url",
+        # Step 1: Filter out all-NA columns from each DataFrame before concatenation
+        filtered_dfs = [df.dropna(axis=1, how="all") for df in jobs_dfs]
+
+        # Step 2: Concatenate the filtered DataFrames
+        jobs_df = pd.concat(filtered_dfs, ignore_index=True)
+
+        # Desired column order
+        desired_order = [
+            "id",
             "site",
+            "job_url_hyper" if hyperlinks else "job_url",
+            "job_url_direct",
             "title",
             "company",
             "location",
@@ -163,13 +208,33 @@ def scrape_jobs(
             "max_amount",
             "currency",
             "is_remote",
-            "num_urgent_words",
-            "benefits",
+            "job_level",
+            "job_function",
+            "company_industry",
+            "listing_type",
             "emails",
             "description",
+            "company_url",
+            "company_url_direct",
+            "company_addresses",
+            "company_num_employees",
+            "company_revenue",
+            "company_description",
+            "logo_photo_url",
+            "banner_photo_url",
+            "ceo_name",
+            "ceo_photo_url",
         ]
-        jobs_formatted_df = jobs_df[desired_order]
-    else:
-        jobs_formatted_df = pd.DataFrame()
 
-    return jobs_formatted_df
+        # 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

@@ -1,8 +1,9 @@
-from typing import Union, Optional
+from __future__ import annotations
+
+from typing import Optional
 from datetime import date
 from enum import Enum
-
-from pydantic import BaseModel, validator
+from pydantic import BaseModel
 
 
 class JobType(Enum):
@@ -56,40 +57,46 @@ class JobType(Enum):
 
 
 class Country(Enum):
-    ARGENTINA = ("argentina", "ar")
-    AUSTRALIA = ("australia", "au")
-    AUSTRIA = ("austria", "at")
+    """
+    Gets the subdomain for Indeed and Glassdoor.
+    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
+    """
+
+    ARGENTINA = ("argentina", "ar", "com.ar")
+    AUSTRALIA = ("australia", "au", "com.au")
+    AUSTRIA = ("austria", "at", "at")
     BAHRAIN = ("bahrain", "bh")
-    BELGIUM = ("belgium", "be")
-    BRAZIL = ("brazil", "br")
-    CANADA = ("canada", "ca")
+    BELGIUM = ("belgium", "be", "fr:be")
+    BRAZIL = ("brazil", "br", "com.br")
+    CANADA = ("canada", "ca", "ca")
     CHILE = ("chile", "cl")
     CHINA = ("china", "cn")
     COLOMBIA = ("colombia", "co")
     COSTARICA = ("costa rica", "cr")
-    CZECHREPUBLIC = ("czech republic", "cz")
+    CZECHREPUBLIC = ("czech republic,czechia", "cz")
     DENMARK = ("denmark", "dk")
     ECUADOR = ("ecuador", "ec")
     EGYPT = ("egypt", "eg")
     FINLAND = ("finland", "fi")
-    FRANCE = ("france", "fr")
-    GERMANY = ("germany", "de")
+    FRANCE = ("france", "fr", "fr")
+    GERMANY = ("germany", "de", "de")
     GREECE = ("greece", "gr")
-    HONGKONG = ("hong kong", "hk")
+    HONGKONG = ("hong kong", "hk", "com.hk")
     HUNGARY = ("hungary", "hu")
-    INDIA = ("india", "in")
+    INDIA = ("india", "in", "co.in")
     INDONESIA = ("indonesia", "id")
-    IRELAND = ("ireland", "ie")
+    IRELAND = ("ireland", "ie", "ie")
     ISRAEL = ("israel", "il")
-    ITALY = ("italy", "it")
+    ITALY = ("italy", "it", "it")
     JAPAN = ("japan", "jp")
     KUWAIT = ("kuwait", "kw")
     LUXEMBOURG = ("luxembourg", "lu")
     MALAYSIA = ("malaysia", "malaysia")
-    MEXICO = ("mexico", "mx")
+    MEXICO = ("mexico", "mx", "com.mx")
     MOROCCO = ("morocco", "ma")
-    NETHERLANDS = ("netherlands", "nl")
-    NEWZEALAND = ("new zealand", "nz")
+    NETHERLANDS = ("netherlands", "nl", "nl")
+    NEWZEALAND = ("new zealand", "nz", "co.nz")
     NIGERIA = ("nigeria", "ng")
     NORWAY = ("norway", "no")
     OMAN = ("oman", "om")
@@ -102,54 +109,66 @@ class Country(Enum):
     QATAR = ("qatar", "qa")
     ROMANIA = ("romania", "ro")
     SAUDIARABIA = ("saudi arabia", "sa")
-    SINGAPORE = ("singapore", "sg")
+    SINGAPORE = ("singapore", "sg", "sg")
     SOUTHAFRICA = ("south africa", "za")
     SOUTHKOREA = ("south korea", "kr")
-    SPAIN = ("spain", "es")
+    SPAIN = ("spain", "es", "es")
     SWEDEN = ("sweden", "se")
-    SWITZERLAND = ("switzerland", "ch")
+    SWITZERLAND = ("switzerland", "ch", "de:ch")
     TAIWAN = ("taiwan", "tw")
     THAILAND = ("thailand", "th")
     TURKEY = ("turkey", "tr")
     UKRAINE = ("ukraine", "ua")
     UNITEDARABEMIRATES = ("united arab emirates", "ae")
-    UK = ("uk", "uk")
-    USA = ("usa", "www")
+    UK = ("uk,united kingdom", "uk:gb", "co.uk")
+    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")
 
-    # internal for linkeind
+    # internal for linkedin
     WORLDWIDE = ("worldwide", "www")
 
-    def __new__(cls, country, domain):
-        obj = object.__new__(cls)
-        obj._value_ = country
-        obj.domain = domain
-        return obj
+    @property
+    def indeed_domain_value(self):
+        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 domain_value(self):
-        return self.domain
+    def glassdoor_domain_value(self):
+        if len(self.value) == 3:
+            subdomain, _, domain = self.value[2].partition(":")
+            if subdomain and domain:
+                return f"{subdomain}.glassdoor.{domain}"
+            else:
+                return f"www.glassdoor.{self.value[2]}"
+        else:
+            raise Exception(f"Glassdoor is not available for {self.name}")
+
+    def get_glassdoor_url(self):
+        return f"https://{self.glassdoor_domain_value}/"
 
     @classmethod
     def from_string(cls, country_str: str):
         """Convert a string to the corresponding Country enum."""
         country_str = country_str.strip().lower()
         for country in cls:
-            if country.value == country_str:
+            country_names = country.value[0].split(",")
+            if country_str in country_names:
                 return country
         valid_countries = [country.value for country in cls]
         raise ValueError(
-            f"Invalid country string: '{country_str}'. Valid countries (only include this param for Indeed) are: {', '.join(valid_countries)}"
+            f"Invalid country string: '{country_str}'. Valid countries are: {', '.join([country[0] for country in valid_countries])}"
         )
 
 
 class Location(BaseModel):
-    country: Country = None
+    country: Country | str | None = None
     city: Optional[str] = None
     state: Optional[str] = None
 
@@ -159,11 +178,19 @@ 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 self.country.value in ("usa", "uk"):
-                location_parts.append(self.country.value.upper())
+        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]
+            if country_name in ("usa", "uk"):
+                location_parts.append(country_name.upper())
             else:
-                location_parts.append(self.country.value.title())
+                location_parts.append(country_name.title())
         return ", ".join(location_parts)
 
 
@@ -174,29 +201,67 @@ class CompensationInterval(Enum):
     DAILY = "daily"
     HOURLY = "hourly"
 
+    @classmethod
+    def get_interval(cls, pay_period):
+        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
-    max_amount: int = None
+    min_amount: float | None = None
+    max_amount: float | None = None
     currency: Optional[str] = "USD"
 
 
+class DescriptionFormat(Enum):
+    MARKDOWN = "markdown"
+    HTML = "html"
+
+
 class JobPost(BaseModel):
+    id: str | None = None
     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
+    listing_type: str | None = None
+
+    # linkedin specific
+    job_level: str | None = None
+
+    # linkedin and indeed specific
+    company_industry: str | None = None
+
+    # indeed specific
+    company_addresses: 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
+
+    # linkedin only atm
+    job_function: str | None = None
 
 
 class JobResponse(BaseModel):

src/jobspy/scrapers/__init__.py

@@ -1,32 +1,47 @@
-from ..jobs import Enum, BaseModel, JobType, JobResponse, Country
-from typing import List, Optional, Any
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+
+from ..jobs import (
+    Enum,
+    BaseModel,
+    JobType,
+    JobResponse,
+    Country,
+    DescriptionFormat,
+)
 
 
 class Site(Enum):
     LINKEDIN = "linkedin"
     INDEED = "indeed"
     ZIP_RECRUITER = "zip_recruiter"
+    GLASSDOOR = "glassdoor"
 
 
 class ScraperInput(BaseModel):
-    site_type: List[Site]
-    search_term: str
+    site_type: list[Site]
+    search_term: str | None = None
 
-    location: str = None
-    country: Optional[Country] = Country.USA
-    distance: Optional[int] = None
+    location: str | None = None
+    country: Country | None = Country.USA
+    distance: int | None = None
     is_remote: bool = False
-    job_type: Optional[JobType] = None
-    easy_apply: bool = None  # linkedin
+    job_type: JobType | None = None
+    easy_apply: bool | None = None
     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):
+class Scraper(ABC):
+    def __init__(self, site: Site, proxies: list[str] | None = None):
+        self.proxies = proxies
         self.site = site
-        self.proxy = (lambda p: {"http": p, "https": p} if p else None)(proxy)
 
-    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
-        ...
+    @abstractmethod
+    def scrape(self, scraper_input: ScraperInput) -> JobResponse: ...

src/jobspy/scrapers/exceptions.py

@@ -19,3 +19,8 @@ class IndeedException(Exception):
 class ZipRecruiterException(Exception):
     def __init__(self, message=None):
         super().__init__(message or "An error occurred with ZipRecruiter")
+
+
+class GlassdoorException(Exception):
+    def __init__(self, message=None):
+        super().__init__(message or "An error occurred with Glassdoor")

src/jobspy/scrapers/glassdoor/__init__.py

@@ -0,0 +1,545 @@
+"""
+jobspy.scrapers.glassdoor
+~~~~~~~~~~~~~~~~~~~
+
+This module contains routines to scrape Glassdoor.
+"""
+
+from __future__ import annotations
+
+import re
+import json
+import requests
+from typing import Optional, Tuple
+from datetime import datetime, timedelta
+from concurrent.futures import ThreadPoolExecutor, as_completed
+
+from .. import Scraper, ScraperInput, Site
+from ..utils import extract_emails_from_text
+from ..exceptions import GlassdoorException
+from ..utils import (
+    create_session,
+    markdown_converter,
+    logger,
+)
+from ...jobs import (
+    JobPost,
+    Compensation,
+    CompensationInterval,
+    Location,
+    JobResponse,
+    JobType,
+    DescriptionFormat,
+)
+
+
+class GlassdoorScraper(Scraper):
+    def __init__(self, proxies: list[str] | str | None = None):
+        """
+        Initializes GlassdoorScraper with the Glassdoor job search url
+        """
+        site = Site(Site.GLASSDOOR)
+        super().__init__(site, proxies=proxies)
+
+        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 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(proxies=self.proxies, 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=[])
+        job_list: list[JobPost] = []
+        cursor = None
+
+        range_start = 1 + (scraper_input.offset // self.jobs_per_page)
+        tot_pages = (scraper_input.results_wanted // self.jobs_per_page) + 2
+        range_end = min(tot_pages, self.max_pages + 1)
+        for page in range(range_start, range_end):
+            logger.info(f"Glassdoor search page: {page}")
+            try:
+                jobs, cursor = self._fetch_jobs_page(
+                    scraper_input, location_id, location_type, page, cursor
+                )
+                job_list.extend(jobs)
+                if not jobs or len(job_list) >= scraper_input.results_wanted:
+                    job_list = job_list[: scraper_input.results_wanted]
+                    break
+            except Exception as e:
+                logger.error(f"Glassdoor: {str(e)}")
+                break
+        return JobResponse(jobs=job_list)
+
+    def _fetch_jobs_page(
+        self,
+        scraper_input: ScraperInput,
+        location_id: int,
+        location_type: str,
+        page_num: int,
+        cursor: str | None,
+    ) -> Tuple[list[JobPost], str | None]:
+        """
+        Scrapes a page of Glassdoor for jobs with scraper_input criteria
+        """
+        jobs = []
+        self.scraper_input = scraper_input
+        try:
+            payload = self._add_payload(location_id, location_type, page_num, cursor)
+            response = self.session.post(
+                f"{self.base_url}/graph",
+                headers=self.headers,
+                timeout_seconds=15,
+                data=payload,
+            )
+            if response.status_code != 200:
+                exc_msg = f"bad response status code: {response.status_code}"
+                raise GlassdoorException(exc_msg)
+            res_json = response.json()[0]
+            if "errors" in res_json:
+                raise ValueError("Error encountered in API response")
+        except (
+            requests.exceptions.ReadTimeout,
+            GlassdoorException,
+            ValueError,
+            Exception,
+        ) as e:
+            logger.error(f"Glassdoor: {str(e)}")
+            return jobs, None
+
+        jobs_data = res_json["data"]["jobListings"]["jobListings"]
+
+        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
+            }
+            for future in as_completed(future_to_job_data):
+                try:
+                    job_post = future.result()
+                    if job_post:
+                        jobs.append(job_post)
+                except Exception as exc:
+                    raise GlassdoorException(f"Glassdoor generated an exception: {exc}")
+
+        return jobs, self.get_cursor_for_page(
+            res_json["data"]["jobListings"]["paginationCursors"], page_num + 1
+        )
+
+    def _get_csrf_token(self):
+        """
+        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.base_url}job-listing/j?jl={job_id}"
+        if job_url in self.seen_urls:
+            return None
+        self.seen_urls.add(job_url)
+        job = job_data["jobview"]
+        title = job["job"]["jobTitleText"]
+        company_name = job["header"]["employerNameFromSearch"]
+        company_id = job_data["jobview"]["header"]["employer"]["id"]
+        location_name = job["header"].get("locationName", "")
+        location_type = job["header"].get("locationType", "")
+        age_in_days = job["header"].get("ageInDays")
+        is_remote, location = False, None
+        date_diff = (datetime.now() - timedelta(days=age_in_days)).date()
+        date_posted = date_diff if age_in_days is not None else None
+
+        if location_type == "S":
+            is_remote = True
+        else:
+            location = self.parse_location(location_name)
+
+        compensation = self.parse_compensation(job["header"])
+        try:
+            description = self._fetch_job_description(job_id)
+        except:
+            description = None
+        company_url = f"{self.base_url}Overview/W-EI_IE{company_id}.htm"
+        company_logo = (
+            job_data["jobview"].get("overview", {}).get("squareLogoUrl", None)
+        )
+        listing_type = (
+            job_data["jobview"]
+            .get("header", {})
+            .get("adOrderSponsorshipLevel", "")
+            .lower()
+        )
+        return JobPost(
+            id=str(job_id),
+            title=title,
+            company_url=company_url if company_id else None,
+            company_name=company_name,
+            date_posted=date_posted,
+            job_url=job_url,
+            location=location,
+            compensation=compensation,
+            is_remote=is_remote,
+            description=description,
+            emails=extract_emails_from_text(description) if description else None,
+            logo_photo_url=company_logo,
+            listing_type=listing_type,
+        )
+
+    def _fetch_job_description(self, job_id):
+        """
+        Fetches the job description for a single job ID.
+        """
+        url = f"{self.base_url}/graph"
+        body = [
+            {
+                "operationName": "JobDetailQuery",
+                "variables": {
+                    "jl": job_id,
+                    "queryString": "q",
+                    "pageTypeEnum": "SERP",
+                },
+                "query": """
+                query JobDetailQuery($jl: Long!, $queryString: String, $pageTypeEnum: PageTypeEnum) {
+                    jobview: jobView(
+                        listingId: $jl
+                        contextHolder: {queryString: $queryString, pageTypeEnum: $pageTypeEnum}
+                    ) {
+                        job {
+                            description
+                            __typename
+                        }
+                        __typename
+                    }
+                }
+                """,
+            }
+        ]
+        res = requests.post(url, json=body, headers=self.headers)
+        if res.status_code != 200:
+            return None
+        data = res.json()[0]
+        desc = data["data"]["jobview"]["job"]["description"]
+        if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
+            desc = markdown_converter(desc)
+        return desc
+
+    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}"
+        res = self.session.get(url, headers=self.headers)
+        if res.status_code != 200:
+            if res.status_code == 429:
+                err = f"429 Response - Blocked by Glassdoor for too many requests"
+                logger.error(err)
+                return None, None
+            else:
+                err = f"Glassdoor response status code {res.status_code}"
+                err += f" - {res.text}"
+                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 = None
+        if self.scraper_input.hours_old:
+            fromage = max(self.scraper_input.hours_old // 24, 1)
+        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
+
+        interval = None
+        if pay_period == "ANNUAL":
+            interval = CompensationInterval.YEARLY
+        elif pay_period:
+            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,
+            max_amount=max_amount,
+            currency=currency,
+        )
+
+    @staticmethod
+    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]
+
+    @staticmethod
+    def parse_location(location_name: str) -> Location | None:
+        if not location_name or location_name == "Remote":
+            return
+        city, _, state = location_name.partition(", ")
+        return Location(city=city, state=state)
+
+    @staticmethod
+    def get_cursor_for_page(pagination_cursors, page_num):
+        for cursor_data in pagination_cursors:
+            if cursor_data["pageNumber"] == page_num:
+                return cursor_data["cursor"]
+
+    fallback_token = "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok"
+    headers = {
+        "authority": "www.glassdoor.com",
+        "accept": "*/*",
+        "accept-language": "en-US,en;q=0.9",
+        "apollographql-client-name": "job-search-next",
+        "apollographql-client-version": "4.65.5",
+        "content-type": "application/json",
+        "origin": "https://www.glassdoor.com",
+        "referer": "https://www.glassdoor.com/",
+        "sec-ch-ua": '"Chromium";v="118", "Google Chrome";v="118", "Not=A?Brand";v="99"',
+        "sec-ch-ua-mobile": "?0",
+        "sec-ch-ua-platform": '"macOS"',
+        "sec-fetch-dest": "empty",
+        "sec-fetch-mode": "cors",
+        "sec-fetch-site": "same-origin",
+        "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",
+    }
+    query_template = """
+            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
+            ) {
+                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

@@ -4,23 +4,21 @@ jobspy.scrapers.indeed
 
 This module contains routines to scrape Indeed.
 """
-import re
-import math
-import io
-import json
-from datetime import datetime
 
-import urllib.parse
-from bs4 import BeautifulSoup
-from bs4.element import Tag
+from __future__ import annotations
+
+import math
+from typing import Tuple
+from datetime import datetime
 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,
+    markdown_converter,
+    logger,
+    create_session,
 )
 from ...jobs import (
     JobPost,
@@ -29,153 +27,26 @@ from ...jobs import (
     Location,
     JobResponse,
     JobType,
+    DescriptionFormat,
 )
-from .. import Scraper, ScraperInput, Site
 
 
 class IndeedScraper(Scraper):
-    def __init__(self, proxy: str | None = None):
+    def __init__(self, proxies: list[str] | str | None = None):
         """
-        Initializes IndeedScraper with the Indeed job search url
+        Initializes IndeedScraper with the Indeed API url
         """
-        self.url = None
-        self.country = None
-        site = Site(Site.INDEED)
-        super().__init__(site, proxy=proxy)
+        super().__init__(Site.INDEED, proxies=proxies)
 
-        self.jobs_per_page = 15
+        self.session = create_session(proxies=self.proxies, is_tls=False)
+        self.scraper_input = None
+        self.jobs_per_page = 100
+        self.num_workers = 10
         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.domain_value
-        self.url = f"https://{domain}.indeed.com"
-        session = create_session(self.proxy)
-
-        params = {
-            "q": scraper_input.search_term,
-            "l": scraper_input.location,
-            "filter": 0,
-            "start": scraper_input.offset + page * 10,
-        }
-        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:
-            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)
-            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"],
-                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
+        self.headers = None
+        self.api_country_code = None
+        self.base_url = None
+        self.api_url = "https://apis.indeed.com/graphql"
 
     def scrape(self, scraper_input: ScraperInput) -> JobResponse:
         """
@@ -183,191 +54,384 @@ class IndeedScraper(Scraper):
         :param scraper_input:
         :return: job_response
         """
-        pages_to_process = (
-            math.ceil(scraper_input.results_wanted / self.jobs_per_page) - 1
-        )
+        self.scraper_input = scraper_input
+        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
-        job_list, total_results = self.scrape_page(scraper_input, 0)
+        cursor = None
+        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:
-            futures: list[Future] = [
-                executor.submit(self.scrape_page, scraper_input, page)
-                for page in range(1, pages_to_process + 1)
-            ]
+        while len(self.seen_urls) < scraper_input.results_wanted:
+            logger.info(f"Indeed search page: {page}")
+            jobs, cursor = self._scrape_page(cursor)
+            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:
-                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:
+    def _scrape_page(self, cursor: str | None) -> Tuple[list[JobPost], str | None]:
         """
-        Retrieves job description by going to the job page url
-        :param job_page_url:
-        :return: description
+        Scrapes a page of Indeed for jobs with scraper_input criteria
+        :param cursor:
+        :return: jobs found on page, next page cursor
         """
-        parsed_url = urllib.parse.urlparse(job_page_url)
-        params = urllib.parse.parse_qs(parsed_url.query)
-        jk_value = params.get("jk", [None])[0]
-        formatted_url = f"{self.url}/viewjob?jk={jk_value}&spa=1"
-        session = create_session(self.proxy)
-
-        try:
-            response = session.get(
-                formatted_url,
-                headers=self.get_headers(),
-                allow_redirects=True,
-                timeout_seconds=5,
+        jobs = []
+        new_cursor = None
+        filters = self._build_filters()
+        search_term = (
+            self.scraper_input.search_term.replace('"', '\\"')
+            if self.scraper_input.search_term
+            else ""
+        )
+        query = self.job_search_query.format(
+            what=(f'what: "{search_term}"' if search_term else ""),
+            location=(
+                f'location: {{where: "{self.scraper_input.location}", radius: {self.scraper_input.distance}, radiusUnit: MILES}}'
+                if self.scraper_input.location
+                else ""
+            ),
+            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 = self.session.post(
+            self.api_url,
+            headers=api_headers,
+            json=payload,
+            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 bug)"
             )
-        except Exception as e:
-            return None
+            return jobs, new_cursor
+        data = response.json()
+        jobs = data["data"]["jobSearch"]["results"]
+        new_cursor = data["data"]["jobSearch"]["pageInfo"]["nextCursor"]
 
-        if response.status_code not in range(200, 400):
-            return None
-
-        soup = BeautifulSoup(response.text, "html.parser")
-        script_tag = soup.find(
-            "script", text=lambda x: x and "window._initialData" in x
-        )
-
-        if not script_tag:
-            return None
-
-        script_code = script_tag.string
-        match = re.search(r"window\._initialData\s*=\s*({.*?})\s*;", script_code, re.S)
-
-        if not match:
-            return None
-
-        json_string = match.group(1)
-        data = json.loads(json_string)
-        try:
-            job_description = data["jobInfoWrapperModel"]["jobInfoModel"][
-                "sanitizedJobDescription"
+        with ThreadPoolExecutor(max_workers=self.num_workers) as executor:
+            job_results: list[Future] = [
+                executor.submit(self._process_job, job["job"]) for job in jobs
             ]
-        except (KeyError, TypeError, IndexError):
-            return None
+        job_list = [result.result() for result in job_results if result.result()]
+        return job_list, new_cursor
 
-        soup = BeautifulSoup(
-            job_description, "html.parser"
+    def _build_filters(self):
+        """
+        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.easy_apply:
+            filters_str = """
+            filters: {
+                keyword: {
+                  field: "indeedApplyScope",
+                  keys: ["DESKTOP"]
+                }
+            }
+            """
+        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",
+            }
+
+            keys = []
+            if self.scraper_input.job_type:
+                key = job_type_key_mapping[self.scraper_input.job_type]
+                keys.append(key)
+
+            if self.scraper_input.is_remote:
+                keys.append("DSQF7")
+
+            if keys:
+                keys_str = '", "'.join(keys)
+                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"]
+        if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
+            description = markdown_converter(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 {}
+        rel_url = job["employer"]["relativeCompanyPageUrl"] if job["employer"] else None
+        return JobPost(
+            id=str(job["key"]),
+            title=job["title"],
+            description=description,
+            company_name=job["employer"].get("name") if job.get("employer") else None,
+            company_url=(f"{self.base_url}{rel_url}" 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()
+                .strip()
+                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
+            ),
         )
-        text_content = " ".join(
-            soup.get_text(separator=" ").split()
-        ).strip()
-
-        return text_content
 
     @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
-        :param job:
-        :return:
+        Parses the attributes to get list of job types
+        :param attributes:
+        :return: list of JobType
         """
         job_types: list[JobType] = []
-        for taxonomy in job["taxonomyAttributes"]:
-            if taxonomy["label"] == "job-types":
-                for i in range(len(taxonomy["attributes"])):
-                    label = taxonomy["attributes"][i].get("label")
-                    if label:
-                        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)
+        for attribute in attributes:
+            job_type_str = attribute["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:
-        """
-        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 a script tag containing mosaic provider data"
-            )
-
-    @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:
+    def _get_compensation(job: dict) -> Compensation | None:
         """
+        Parses the job to get compensation
         :param job:
-        :return: bool
+        :param job:
+        :return: compensation object
+        """
+        comp = job["compensation"]["baseSalary"]
+        if not comp:
+            return None
+        interval = IndeedScraper._get_compensation_interval(comp["unitOfWork"])
+        if not interval:
+            return None
+        min_range = comp["range"].get("min")
+        max_range = comp["range"].get("max")
+        return Compensation(
+            interval=interval,
+            min_amount=int(min_range) if min_range is not None else None,
+            max_amount=int(max_range) if max_range 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}
+            {location}
+            limit: 100
+            sort: DATE
+            {cursor}
+            {filters}
+          ) {{
+            pageInfo {{
+              nextCursor
+            }}
+            results {{
+              trackingKey
+              job {{
+                source {{
+                  name
+                }}
+                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

@@ -4,40 +4,62 @@ jobspy.scrapers.linkedin
 
 This module contains routines to scrape LinkedIn.
 """
+
+from __future__ import annotations
+
+import time
+import random
+import regex as re
 from typing import Optional
 from datetime import datetime
 
-import requests
-import time
-from requests.exceptions import ProxyError
-from concurrent.futures import ThreadPoolExecutor, as_completed
-from bs4 import BeautifulSoup
 from bs4.element import Tag
-from threading import Lock
+from bs4 import BeautifulSoup
+from urllib.parse import urlparse, urlunparse, unquote
 
 from .. import Scraper, ScraperInput, Site
-from ..utils import count_urgent_words, extract_emails_from_text, get_enum_from_job_type
 from ..exceptions import LinkedInException
+from ..utils import create_session, remove_attributes
 from ...jobs import (
     JobPost,
     Location,
     JobResponse,
     JobType,
+    Country,
+    Compensation,
+    DescriptionFormat,
+)
+from ..utils import (
+    logger,
+    extract_emails_from_text,
+    get_enum_from_job_type,
+    currency_parser,
+    markdown_converter,
 )
 
 
 class LinkedInScraper(Scraper):
-    MAX_RETRIES = 3
-    DELAY = 10
+    base_url = "https://www.linkedin.com"
+    delay = 3
+    band_delay = 4
+    jobs_per_page = 25
 
-    def __init__(self, proxy: Optional[str] = None):
+    def __init__(self, proxies: list[str] | str | None = None):
         """
         Initializes LinkedInScraper with the LinkedIn job search url
         """
-        site = Site(Site.LINKEDIN)
+        super().__init__(Site.LINKEDIN, proxies=proxies)
+        self.session = create_session(
+            proxies=self.proxies,
+            is_tls=False,
+            has_retry=True,
+            delay=5,
+            clear_cookies=True,
+        )
+        self.session.headers.update(self.headers)
+        self.scraper_input = None
         self.country = "worldwide"
-        self.url = "https://www.linkedin.com"
-        super().__init__(site, proxy=proxy)
+        self.job_url_direct_regex = re.compile(r'(?<=\?url=)[^"]+')
 
     def scrape(self, scraper_input: ScraperInput) -> JobResponse:
         """
@@ -45,117 +67,131 @@ 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
-
-        def job_type_code(job_type_enum):
-            mapping = {
-                JobType.FULL_TIME: "F",
-                JobType.PART_TIME: "P",
-                JobType.INTERNSHIP: "I",
-                JobType.CONTRACT: "C",
-                JobType.TEMPORARY: "T",
-            }
-
-            return mapping.get(job_type_enum, "")
-
-        while len(job_list) < scraper_input.results_wanted and page < 1000:
+        seen_ids = set()
+        page = scraper_input.offset // 10 * 10 if scraper_input.offset else 0
+        request_count = 0
+        seconds_old = (
+            scraper_input.hours_old * 3600 if scraper_input.hours_old else None
+        )
+        continue_search = (
+            lambda: len(job_list) < scraper_input.results_wanted and page < 1000
+        )
+        while continue_search():
+            request_count += 1
+            logger.info(f"LinkedIn search page: {request_count}")
             params = {
                 "keywords": scraper_input.search_term,
                 "location": scraper_input.location,
                 "distance": scraper_input.distance,
                 "f_WT": 2 if scraper_input.is_remote else None,
-                "f_JT": job_type_code(scraper_input.job_type)
-                if scraper_input.job_type
-                else None,
+                "f_JT": (
+                    self.job_type_code(scraper_input.job_type)
+                    if scraper_input.job_type
+                    else None
+                ),
                 "pageNum": 0,
-                page: page + scraper_input.offset,
+                "start": page,
                 "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}
-
-            params = {k: v for k, v in params.items() if v is not None}
-            retries = 0
-            while retries < self.MAX_RETRIES:
-                try:
-                    response = requests.get(
-                        f"{self.url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
-                        params=params,
-                        allow_redirects=True,
-                        proxies=self.proxy,
-                        timeout=10,
-                    )
-                    response.raise_for_status()
-
-                    break
-                except requests.HTTPError as e:
-                    if hasattr(e, "response") and e.response is not None:
-                        if e.response.status_code == 429:
-                            time.sleep(self.DELAY)
-                            retries += 1
-                            continue
-                        else:
-                            raise LinkedInException(
-                                f"bad response status code: {e.response.status_code}"
-                            )
-                    else:
-                        raise
-                except ProxyError as e:
-                    raise LinkedInException("bad proxy")
-                except Exception as e:
-                    raise LinkedInException(str(e))
-            else:
-                # Raise an exception if the maximum number of retries is reached
-                raise LinkedInException(
-                    "Max retries reached, failed to get a valid response"
+            try:
+                response = self.session.get(
+                    f"{self.base_url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
+                    params=params,
+                    timeout=10,
                 )
+                if response.status_code not in range(200, 400):
+                    if response.status_code == 429:
+                        err = (
+                            f"429 Response - Blocked by LinkedIn for too many requests"
+                        )
+                    else:
+                        err = f"LinkedIn response status code {response.status_code}"
+                        err += f" - {response.text}"
+                    logger.error(err)
+                    return JobResponse(jobs=job_list)
+            except Exception as 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")
+            if len(job_cards) == 0:
+                return JobResponse(jobs=job_list)
 
-            with ThreadPoolExecutor(max_workers=5) as executor:
-                futures = []
-                for job_card in soup.find_all("div", class_="base-search-card"):
-                    job_url = None
-                    href_tag = job_card.find("a", class_="base-card__full-link")
-                    if href_tag and "href" in href_tag.attrs:
-                        href = href_tag.attrs["href"].split("?")[0]
-                        job_id = href.split("-")[-1]
-                        job_url = f"{self.url}/jobs/view/{job_id}"
+            for job_card in job_cards:
+                href_tag = job_card.find("a", class_="base-card__full-link")
+                if href_tag and "href" in href_tag.attrs:
+                    href = href_tag.attrs["href"].split("?")[0]
+                    job_id = href.split("-")[-1]
 
-                    with url_lock:
-                        if job_url in seen_urls:
-                            continue
-                        seen_urls.add(job_url)
+                    if job_id in seen_ids:
+                        continue
+                    seen_ids.add(job_id)
 
-                    futures.append(executor.submit(self.process_job, job_card, job_url))
-
-                for future in as_completed(futures):
                     try:
-                        job_post = future.result()
+                        fetch_desc = scraper_input.linkedin_fetch_description
+                        job_post = self._process_job(job_card, job_id, fetch_desc)
                         if job_post:
                             job_list.append(job_post)
+                        if not continue_search():
+                            break
                     except Exception as e:
-                        raise LinkedInException(
-                            "Exception occurred while processing jobs"
-                        )
-            page += 25
+                        raise LinkedInException(str(e))
+
+            if continue_search():
+                time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
+                page += len(job_list)
 
         job_list = job_list[: scraper_input.results_wanted]
         return JobResponse(jobs=job_list)
 
-    def process_job(self, job_card: Tag, job_url: str) -> Optional[JobPost]:
+    def _process_job(
+        self, job_card: Tag, job_id: str, full_descr: bool
+    ) -> Optional[JobPost]:
+        salary_tag = job_card.find("span", class_="job-search-card__salary-info")
+
+        compensation = None
+        if salary_tag:
+            salary_text = salary_tag.get_text(separator=" ").strip()
+            salary_values = [currency_parser(value) for value in salary_text.split("-")]
+            salary_min = salary_values[0]
+            salary_max = salary_values[1]
+            currency = salary_text[0] if salary_text[0] != "$" else "USD"
+
+            compensation = Compensation(
+                min_amount=int(salary_min),
+                max_amount=int(salary_max),
+                currency=currency,
+            )
+
         title_tag = job_card.find("span", class_="sr-only")
         title = title_tag.get_text(strip=True) if title_tag else "N/A"
 
         company_tag = job_card.find("h4", class_="base-search-card__subtitle")
         company_a_tag = company_tag.find("a") if company_tag else None
+        company_url = (
+            urlunparse(urlparse(company_a_tag.get("href"))._replace(query=""))
+            if company_a_tag and company_a_tag.has_attr("href")
+            else ""
+        )
         company = company_a_tag.get_text(strip=True) if company_a_tag else "N/A"
 
         metadata_card = job_card.find("div", class_="base-search-card__metadata")
-        location = self.get_location(metadata_card)
+        location = self._get_location(metadata_card)
 
         datetime_tag = (
             metadata_card.find("time", class_="job-search-card__listdate")
@@ -167,86 +203,88 @@ 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
-
-        description, job_type = self.get_job_description(job_url)
+        job_details = {}
+        if full_descr:
+            job_details = self._get_job_details(job_id)
 
         return JobPost(
+            id=job_id,
             title=title,
-            description=description,
             company_name=company,
+            company_url=company_url,
             location=location,
             date_posted=date_posted,
-            job_url=job_url,
-            # job_type=[JobType.FULL_TIME],
-            job_type=job_type,
-            benefits=benefits,
-            emails=extract_emails_from_text(description) if description else None,
-            num_urgent_words=count_urgent_words(description) if description else None,
+            job_url=f"{self.base_url}/jobs/view/{job_id}",
+            compensation=compensation,
+            job_type=job_details.get("job_type"),
+            job_level=job_details.get("job_level", "").lower(),
+            company_industry=job_details.get("company_industry"),
+            description=job_details.get("description"),
+            job_url_direct=job_details.get("job_url_direct"),
+            emails=extract_emails_from_text(job_details.get("description")),
+            logo_photo_url=job_details.get("logo_photo_url"),
+            job_function=job_details.get("job_function"),
         )
 
-    def get_job_description(
-        self, job_page_url: str
-    ) -> tuple[None, None] | tuple[str | None, tuple[str | None, JobType | None]]:
+    def _get_job_details(self, job_id: str) -> dict:
         """
-        Retrieves job description by going to the job page url
+        Retrieves job description and other job details by going to the job page url
         :param job_page_url:
-        :return: description or None
+        :return: dict
         """
         try:
-            response = requests.get(job_page_url, timeout=5, proxies=self.proxy)
+            response = self.session.get(
+                f"{self.base_url}/jobs-guest/jobs/api/jobPosting/{job_id}", timeout=5
+            )
             response.raise_for_status()
-        except Exception as e:
-            return None, None
+        except:
+            return {}
+        if "linkedin.com/signup" in response.url:
+            return {}
 
         soup = BeautifulSoup(response.text, "html.parser")
         div_content = soup.find(
             "div", class_=lambda x: x and "show-more-less-html__markup" in x
         )
-
         description = None
-        if div_content:
-            description = " ".join(div_content.get_text().split()).strip()
+        if div_content is not None:
+            div_content = remove_attributes(div_content)
+            description = div_content.prettify(formatter="html")
+            if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
+                description = markdown_converter(description)
 
-        def get_job_type(
-            soup_job_type: BeautifulSoup,
-        ) -> list[JobType] | None:
-            """
-            Gets the job type from job page
-            :param soup_job_type:
-            :return: JobType
-            """
-            h3_tag = soup_job_type.find(
-                "h3",
-                class_="description__job-criteria-subheader",
-                string=lambda text: "Employment type" in text,
+        h3_tag = soup.find(
+            "h3", text=lambda text: text and "Job function" in text.strip()
+        )
+
+        job_function = None
+        if h3_tag:
+            job_function_span = h3_tag.find_next(
+                "span", class_="description__job-criteria-text"
             )
+            if job_function_span:
+                job_function = job_function_span.text.strip()
+        return {
+            "description": description,
+            "job_level": self._parse_job_level(soup),
+            "company_industry": self._parse_company_industry(soup),
+            "job_type": self._parse_job_type(soup),
+            "job_url_direct": self._parse_job_url_direct(soup),
+            "logo_photo_url": soup.find("img", {"class": "artdeco-entity-image"}).get(
+                "data-delayed-url"
+            ),
+            "job_function": job_function,
+        }
 
-            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)]
-
-        return description, get_job_type(soup)
-
-    def get_location(self, metadata_card: Optional[Tag]) -> Location:
+    def _get_location(self, metadata_card: Optional[Tag]) -> Location:
         """
         Extracts the location data from the job metadata card.
         :param metadata_card
         :return: location
         """
-        location = Location(country=self.country)
+        location = Location(country=Country.from_string(self.country))
         if metadata_card is not None:
             location_tag = metadata_card.find(
                 "span", class_="job-search-card__location"
@@ -258,7 +296,117 @@ class LinkedInScraper(Scraper):
                 location = Location(
                     city=city,
                     state=state,
-                    country=self.country,
+                    country=Country.from_string(self.country),
                 )
-
+            elif len(parts) == 3:
+                city, state, country = parts
+                country = Country.from_string(country)
+                location = Location(city=city, state=state, country=country)
         return location
+
+    @staticmethod
+    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 _parse_job_level(soup_job_level: BeautifulSoup) -> str | None:
+        """
+        Gets the job level from job page
+        :param soup_job_level:
+        :return: str
+        """
+        h3_tag = soup_job_level.find(
+            "h3",
+            class_="description__job-criteria-subheader",
+            string=lambda text: "Seniority level" in text,
+        )
+        job_level = None
+        if h3_tag:
+            job_level_span = h3_tag.find_next_sibling(
+                "span",
+                class_="description__job-criteria-text description__job-criteria-text--criteria",
+            )
+            if job_level_span:
+                job_level = job_level_span.get_text(strip=True)
+
+        return job_level
+
+    @staticmethod
+    def _parse_company_industry(soup_industry: BeautifulSoup) -> str | None:
+        """
+        Gets the company industry from job page
+        :param soup_industry:
+        :return: str
+        """
+        h3_tag = soup_industry.find(
+            "h3",
+            class_="description__job-criteria-subheader",
+            string=lambda text: "Industries" in text,
+        )
+        industry = None
+        if h3_tag:
+            industry_span = h3_tag.find_next_sibling(
+                "span",
+                class_="description__job-criteria-text description__job-criteria-text--criteria",
+            )
+            if industry_span:
+                industry = industry_span.get_text(strip=True)
+
+        return industry
+
+    def _parse_job_url_direct(self, soup: BeautifulSoup) -> str | None:
+        """
+        Gets the job url direct from job page
+        :param soup:
+        :return: str
+        """
+        job_url_direct = None
+        job_url_direct_content = soup.find("code", id="applyUrl")
+        if job_url_direct_content:
+            job_url_direct_match = self.job_url_direct_regex.search(
+                job_url_direct_content.decode_contents().strip()
+            )
+            if job_url_direct_match:
+                job_url_direct = unquote(job_url_direct_match.group())
+
+        return job_url_direct
+
+    @staticmethod
+    def job_type_code(job_type_enum: JobType) -> str:
+        return {
+            JobType.FULL_TIME: "F",
+            JobType.PART_TIME: "P",
+            JobType.INTERNSHIP: "I",
+            JobType.CONTRACT: "C",
+            JobType.TEMPORARY: "T",
+        }.get(job_type_enum, "")
+
+    headers = {
+        "authority": "www.linkedin.com",
+        "accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7",
+        "accept-language": "en-US,en;q=0.9",
+        "cache-control": "max-age=0",
+        "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

@@ -1,20 +1,149 @@
+from __future__ import annotations
+
 import re
+import logging
+from itertools import cycle
+
+import requests
 import tls_client
+import numpy as np
+from markdownify import markdownify as md
+from requests.adapters import HTTPAdapter, Retry
+
 from ..jobs import JobType
 
+logger = logging.getLogger("JobSpy")
+logger.propagate = False
+if not logger.handlers:
+    logger.setLevel(logging.INFO)
+    console_handler = logging.StreamHandler()
+    format = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
+    formatter = logging.Formatter(format)
+    console_handler.setFormatter(formatter)
+    logger.addHandler(console_handler)
 
-def count_urgent_words(description: str) -> int:
-    """
-    Count the number of urgent words or phrases in a job description.
-    """
-    urgent_patterns = re.compile(
-        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
+class RotatingProxySession:
+    def __init__(self, proxies=None):
+        if isinstance(proxies, str):
+            self.proxy_cycle = cycle([self.format_proxy(proxies)])
+        elif isinstance(proxies, list):
+            self.proxy_cycle = (
+                cycle([self.format_proxy(proxy) for proxy in proxies])
+                if proxies
+                else None
+            )
+        else:
+            self.proxy_cycle = None
+
+    @staticmethod
+    def format_proxy(proxy):
+        """Utility method to format a proxy string into a dictionary."""
+        if proxy.startswith("http://") or proxy.startswith("https://"):
+            return {"http": proxy, "https": proxy}
+        return {"http": f"http://{proxy}", "https": f"http://{proxy}"}
+
+
+class RequestsRotating(RotatingProxySession, requests.Session):
+
+    def __init__(self, proxies=None, has_retry=False, delay=1, clear_cookies=False):
+        RotatingProxySession.__init__(self, proxies=proxies)
+        requests.Session.__init__(self)
+        self.clear_cookies = clear_cookies
+        self.allow_redirects = True
+        self.setup_session(has_retry, delay)
+
+    def setup_session(self, has_retry, delay):
+        if has_retry:
+            retries = Retry(
+                total=3,
+                connect=3,
+                status=3,
+                status_forcelist=[500, 502, 503, 504, 429],
+                backoff_factor=delay,
+            )
+            adapter = HTTPAdapter(max_retries=retries)
+            self.mount("http://", adapter)
+            self.mount("https://", adapter)
+
+    def request(self, method, url, **kwargs):
+        if self.clear_cookies:
+            self.cookies.clear()
+
+        if self.proxy_cycle:
+            next_proxy = next(self.proxy_cycle)
+            if next_proxy["http"] != "http://localhost":
+                self.proxies = next_proxy
+            else:
+                self.proxies = {}
+        return requests.Session.request(self, method, url, **kwargs)
+
+
+class TLSRotating(RotatingProxySession, tls_client.Session):
+
+    def __init__(self, proxies=None):
+        RotatingProxySession.__init__(self, proxies=proxies)
+        tls_client.Session.__init__(self, random_tls_extension_order=True)
+
+    def execute_request(self, *args, **kwargs):
+        if self.proxy_cycle:
+            next_proxy = next(self.proxy_cycle)
+            if next_proxy["http"] != "http://localhost":
+                self.proxies = next_proxy
+            else:
+                self.proxies = {}
+        response = tls_client.Session.execute_request(self, *args, **kwargs)
+        response.ok = response.status_code in range(200, 400)
+        return response
+
+
+def create_session(
+    *,
+    proxies: dict | str | None = None,
+    is_tls: bool = True,
+    has_retry: bool = False,
+    delay: int = 1,
+    clear_cookies: bool = False,
+) -> requests.Session:
+    """
+    Creates a requests session with optional tls, proxy, and retry settings.
+    :return: A session object
+    """
+    if is_tls:
+        session = TLSRotating(proxies=proxies)
+    else:
+        session = RequestsRotating(
+            proxies=proxies,
+            has_retry=has_retry,
+            delay=delay,
+            clear_cookies=clear_cookies,
+        )
+
+    return session
+
+
+def set_logger_level(verbose: int = 2):
+    """
+    Adjusts the logger's level. This function allows the logging level to be changed at runtime.
+
+    Parameters:
+    - verbose: int {0, 1, 2} (default=2, all logs)
+    """
+    if verbose is None:
+        return
+    level_name = {2: "INFO", 1: "WARNING", 0: "ERROR"}.get(verbose, "INFO")
+    level = getattr(logging, level_name.upper(), None)
+    if level is not None:
+        logger.setLevel(level)
+    else:
+        raise ValueError(f"Invalid log level: {level_name}")
+
+
+def markdown_converter(description_html: str):
+    if description_html is None:
+        return None
+    markdown = md(description_html)
+    return markdown.strip()
 
 
 def extract_emails_from_text(text: str) -> list[str] | None:
@@ -24,27 +153,6 @@ def extract_emails_from_text(text: str) -> list[str] | None:
     return email_regex.findall(text)
 
 
-def create_session(proxy: str | None = None):
-    """
-    Creates a tls client session
-
-    :return: A session object with or without proxies.
-    """
-    session = tls_client.Session(
-        client_identifier="chrome112",
-        random_tls_extension_order=True,
-    )
-    session.proxies = proxy
-    # TODO multiple proxies
-    # if self.proxies:
-    #     session.proxies = {
-    #         "http": random.choice(self.proxies),
-    #         "https": random.choice(self.proxies),
-    #     }
-
-    return session
-
-
 def get_enum_from_job_type(job_type_str: str) -> JobType | None:
     """
     Given a string, returns the corresponding JobType enum member if a match is found.
@@ -54,3 +162,78 @@ def get_enum_from_job_type(job_type_str: str) -> JobType | None:
         if job_type_str in job_type.value:
             res = job_type
     return res
+
+
+def currency_parser(cur_str):
+    # Remove any non-numerical characters
+    # except for ',' '.' or '-' (e.g. EUR)
+    cur_str = re.sub("[^-0-9.,]", "", cur_str)
+    # Remove any 000s separators (either , or .)
+    cur_str = re.sub("[.,]", "", cur_str[:-3]) + cur_str[-3:]
+
+    if "." in list(cur_str[-3:]):
+        num = float(cur_str)
+    elif "," in list(cur_str[-3:]):
+        num = float(cur_str.replace(",", "."))
+    else:
+        num = float(cur_str)
+
+    return np.round(num, 2)
+
+
+def remove_attributes(tag):
+    for attr in list(tag.attrs):
+        del tag[attr]
+    return tag
+
+
+def extract_salary(
+    salary_str,
+    lower_limit=1000,
+    upper_limit=700000,
+    hourly_threshold=350,
+    monthly_threshold=30000,
+):
+    if not salary_str:
+        return None, None, None, None
+
+    min_max_pattern = r"\$(\d+(?:,\d+)?(?:\.\d+)?)([kK]?)\s*[-—–]\s*(?:\$)?(\d+(?:,\d+)?(?:\.\d+)?)([kK]?)"
+
+    def to_int(s):
+        return int(float(s.replace(",", "")))
+
+    def convert_hourly_to_annual(hourly_wage):
+        return hourly_wage * 2080
+
+    def convert_monthly_to_annual(monthly_wage):
+        return monthly_wage * 12
+
+    match = re.search(min_max_pattern, salary_str)
+
+    if match:
+        min_salary = to_int(match.group(1))
+        max_salary = to_int(match.group(3))
+        # Handle 'k' suffix for min and max salaries independently
+        if "k" in match.group(2).lower() or "k" in match.group(4).lower():
+            min_salary *= 1000
+            max_salary *= 1000
+
+        # Convert to annual if less than the hourly threshold
+        if min_salary < hourly_threshold:
+            min_salary = convert_hourly_to_annual(min_salary)
+            if max_salary < hourly_threshold:
+                max_salary = convert_hourly_to_annual(max_salary)
+
+        elif min_salary < monthly_threshold:
+            min_salary = convert_monthly_to_annual(min_salary)
+            if max_salary < monthly_threshold:
+                max_salary = convert_monthly_to_annual(max_salary)
+
+        # Ensure salary range is within specified limits
+        if (
+            lower_limit <= min_salary <= upper_limit
+            and lower_limit <= max_salary <= upper_limit
+            and min_salary < max_salary
+        ):
+            return "yearly", min_salary, max_salary, "USD"
+    return None, None, None, None

src/jobspy/scrapers/ziprecruiter/__init__.py

@@ -4,303 +4,251 @@ jobspy.scrapers.ziprecruiter
 
 This module contains routines to scrape ZipRecruiter.
 """
-import math
-import json
-import re
-from datetime import datetime, date
-from typing import Optional, Tuple, Any
-from urllib.parse import urlparse, parse_qs, urlunparse
 
-import requests
+from __future__ import annotations
+
+import json
+import math
+import re
+import time
+from datetime import datetime
+from typing import Optional, Tuple, Any
+
+from concurrent.futures import ThreadPoolExecutor
+
 from bs4 import BeautifulSoup
-from bs4.element import Tag
-from concurrent.futures import ThreadPoolExecutor, Future
 
 from .. import Scraper, ScraperInput, Site
-from ..exceptions import ZipRecruiterException
-from ..utils import count_urgent_words, extract_emails_from_text, create_session
+from ..utils import (
+    logger,
+    extract_emails_from_text,
+    create_session,
+    markdown_converter,
+    remove_attributes,
+)
 from ...jobs import (
     JobPost,
     Compensation,
-    CompensationInterval,
     Location,
     JobResponse,
     JobType,
     Country,
+    DescriptionFormat,
 )
 
 
 class ZipRecruiterScraper(Scraper):
-    def __init__(self, proxy: Optional[str] = None):
-        """
-        Initializes LinkedInScraper with the ZipRecruiter job search url
-        """
-        site = Site(Site.ZIP_RECRUITER)
-        self.url = "https://www.ziprecruiter.com"
-        super().__init__(site, proxy=proxy)
+    base_url = "https://www.ziprecruiter.com"
+    api_url = "https://api.ziprecruiter.com"
 
+    def __init__(self, proxies: list[str] | str | None = None):
+        """
+        Initializes ZipRecruiterScraper with the ZipRecruiter job search url
+        """
+        super().__init__(Site.ZIP_RECRUITER, proxies=proxies)
+
+        self.scraper_input = None
+        self.session = create_session(proxies=proxies)
+        self._get_cookies()
+
+        self.delay = 5
         self.jobs_per_page = 20
         self.seen_urls = set()
 
-    def find_jobs_in_page(self, scraper_input: ScraperInput, continue_token: Optional[str] = None) -> Tuple[list[JobPost], Optional[str]]:
-        """
-        Scrapes a page of ZipRecruiter for jobs with scraper_input criteria
-        :param scraper_input:
-        :return: jobs found on page
-        """
-        params = self.add_params(scraper_input)
-        if continue_token:
-            params['continue'] = continue_token
-        try:
-            response = requests.get(
-                f"https://api.ziprecruiter.com/jobs-app/jobs",
-                headers=self.headers(),
-                params=self.add_params(scraper_input),
-                allow_redirects=True,
-                timeout=10,
-            )
-            if response.status_code != 200:
-                raise ZipRecruiterException(
-                    f"bad response status code: {response.status_code}"
-                )
-        except Exception as e:
-            if "Proxy responded with non 200 code" in str(e):
-                raise ZipRecruiterException("bad proxy")
-            raise ZipRecruiterException(str(e))
-
-        response_data = response.json()
-        jobs_list = response_data.get("jobs", [])
-        next_continue_token = response_data.get('continue', None)
-
-        with ThreadPoolExecutor(max_workers=10) as executor:
-            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()]
-        return job_list, next_continue_token
-
     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
-
-            jobs_on_page, continue_token = self.find_jobs_in_page(scraper_input, continue_token)
+            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])
 
-        if len(job_list) > scraper_input.results_wanted:
-            job_list = 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]]:
+        """
+        Scrapes a page of ZipRecruiter for jobs with scraper_input criteria
+        :param scraper_input:
+        :param continue_token:
+        :return: jobs found on page
+        """
+        jobs_list = []
+        params = self._add_params(scraper_input)
+        if continue_token:
+            params["continue_from"] = continue_token
+        try:
+            res = self.session.get(
+                f"{self.api_url}/jobs-app/jobs", headers=self.headers, params=params
+            )
+            if res.status_code not in range(200, 400):
+                if res.status_code == 429:
+                    err = "429 Response - Blocked by ZipRecruiter for too many requests"
+                else:
+                    err = f"ZipRecruiter response status code {res.status_code}"
+                    err += f" with response: {res.text}"  # ZipRecruiter likely not available in EU
+                logger.error(err)
+                return jobs_list, ""
+        except Exception as e:
+            if "Proxy responded with" in str(e):
+                logger.error(f"Indeed: Bad proxy")
+            else:
+                logger.error(f"Indeed: {str(e)}")
+            return jobs_list, ""
 
-        return JobResponse(jobs=job_list)
+        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]
 
-    def process_job(self, job: dict) -> JobPost:
-        """the most common type of jobs page on ZR"""
+        job_list = list(filter(None, (result.result() for result in job_results)))
+        return job_list, next_continue_token
+
+    def _process_job(self, job: dict) -> JobPost | None:
+        """
+        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_url = updated_job_url if updated_job_url else job_url
-        description = BeautifulSoup(
-            job.get("job_description", "").strip(), "html.parser"
-        ).get_text()
-
-        company = job.get("source")
-        location = Location(
-            city=job.get("job_city"), state=job.get("job_state"), country='usa' if job.get("job_country") == 'US' else 'canada'
+        description = job.get("job_description", "").strip()
+        listing_type = job.get("buyer_type", "")
+        description = (
+            markdown_converter(description)
+            if self.scraper_input.description_format == DescriptionFormat.MARKDOWN
+            else description
         )
-        job_type = ZipRecruiterScraper.get_job_type_enum(
+        company = job.get("hiring_company", {}).get("name")
+        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 = self._get_job_type_enum(
             job.get("employment_type", "").replace("_", "").lower()
         )
-
-        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()
+        date_posted = datetime.fromisoformat(job["posted_time"].rstrip("Z")).date()
+        comp_interval = job.get("compensation_interval")
+        comp_interval = "yearly" if comp_interval == "annual" else comp_interval
+        comp_min = int(job["compensation_min"]) if "compensation_min" in job else None
+        comp_max = int(job["compensation_max"]) if "compensation_max" in job else None
+        comp_currency = job.get("compensation_currency")
+        description_full, job_url_direct = self._get_descr(job_url)
 
         return JobPost(
+            id=str(job["listing_key"]),
             title=title,
             company_name=company,
             location=location,
             job_type=job_type,
-            # compensation=compensation,
+            compensation=Compensation(
+                interval=comp_interval,
+                min_amount=comp_min,
+                max_amount=comp_max,
+                currency=comp_currency,
+            ),
             date_posted=date_posted,
             job_url=job_url,
-            description=description,
+            description=description_full if description_full else description,
             emails=extract_emails_from_text(description) if description else None,
-            num_urgent_words=count_urgent_words(description) if description else None,
+            job_url_direct=job_url_direct,
+            listing_type=listing_type,
         )
 
+    def _get_descr(self, job_url):
+        res = self.session.get(job_url, headers=self.headers, allow_redirects=True)
+        description_full = job_url_direct = None
+        if res.ok:
+            soup = BeautifulSoup(res.text, "html.parser")
+            job_descr_div = soup.find("div", class_="job_description")
+            company_descr_section = soup.find("section", class_="company_description")
+            job_description_clean = (
+                remove_attributes(job_descr_div).prettify(formatter="html")
+                if job_descr_div
+                else ""
+            )
+            company_description_clean = (
+                remove_attributes(company_descr_section).prettify(formatter="html")
+                if company_descr_section
+                else ""
+            )
+            description_full = job_description_clean + company_description_clean
+            script_tag = soup.find("script", type="application/json")
+            if script_tag:
+                job_json = json.loads(script_tag.string)
+                job_url_val = job_json["model"]["saveJobURL"]
+                m = re.search(r"job_url=(.+)", job_url_val)
+                if m:
+                    job_url_direct = m.group(1)
+
+            if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
+                description_full = markdown_converter(description_full)
+
+        return description_full, job_url_direct
+
+    def _get_cookies(self):
+        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"
+        url = f"{self.api_url}/jobs-app/event"
+        self.session.post(url, 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:
+            params["days"] = max(scraper_input.hours_old // 24, 1)
+        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":
-                job_type_value = "full_time"
-            elif scraper_input.job_type.value == "parttime":
-                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}"
-
+            job_type = scraper_input.job_type
+            params["employment_type"] = job_type_map.get(job_type, job_type.value[0])
+        if scraper_input.easy_apply:
+            params["zipapply"] = 1
         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
-
-    @staticmethod
-    def get_interval(interval_str: str):
-        """
-         Maps the interval alias to its appropriate CompensationInterval.
-        :param interval_str
-        :return: CompensationInterval
-        """
-        interval_alias = {"annually": CompensationInterval.YEARLY}
-        interval_str = interval_str.lower()
-
-        if interval_str in interval_alias:
-            return interval_alias[interval_str]
-
-        return CompensationInterval(interval_str)
-
-    @staticmethod
-    def get_date_posted(job: Tag) -> Optional[datetime.date]:
-        """
-        Extracts the date a job was posted
-        :param job
-        :return: date the job was posted or None
-        """
-        button = job.find(
-            "button", {"class": "action_input save_job zrs_btn_secondary_200"}
-        )
-        if not button:
-            return None
-
-        url_time = button.get("data-href", "")
-        url_components = urlparse(url_time)
-        params = parse_qs(url_components.query)
-        posted_time_str = params.get("posted_time", [None])[0]
-
-        if posted_time_str:
-            posted_date = datetime.strptime(
-                posted_time_str, "%Y-%m-%dT%H:%M:%SZ"
-            ).date()
-            return posted_date
-
-        return None
-
-    @staticmethod
-    def get_compensation(job: Tag) -> Optional[Compensation]:
-        """
-        Parses the compensation tag from the job BeautifulSoup object
-        :param job
-        :return: Compensation object or None
-        """
-        pay_element = job.find("li", {"class": "perk_item perk_pay"})
-        if pay_element is None:
-            return None
-        pay = pay_element.find("div", {"class": "value"}).find("span").text.strip()
-
-        def create_compensation_object(pay_string: str) -> Compensation:
-            """
-            Creates a Compensation object from a pay_string
-            :param pay_string
-            :return: compensation
-            """
-            interval = ZipRecruiterScraper.get_interval(pay_string.split()[-1])
-
-            amounts = []
-            for amount in pay_string.split("to"):
-                amount = amount.replace(",", "").strip("$ ").split(" ")[0]
-                if "K" in amount:
-                    amount = amount.replace("K", "")
-                    amount = int(float(amount)) * 1000
-                else:
-                    amount = int(float(amount))
-                amounts.append(amount)
-
-            compensation = Compensation(
-                interval=interval,
-                min_amount=min(amounts),
-                max_amount=max(amounts),
-                currency="USD/CAD",
-            )
-
-            return compensation
-
-        return create_compensation_object(pay)
-
-    @staticmethod
-    def get_location(job: Tag) -> Location:
-        """
-        Extracts the job location from BeatifulSoup object
-        :param job:
-        :return: location
-        """
-        location_link = job.find("a", {"class": "company_location"})
-        if location_link is not None:
-            location_string = location_link.text.strip()
-            parts = location_string.split(", ")
-            if len(parts) == 2:
-                city, state = parts
-            else:
-                city, state = None, None
-        else:
-            city, state = None, None
-        return Location(city=city, state=state, country=Country.US_CANADA)
-
-    @staticmethod
-    def headers() -> dict:
-        """
-        Returns headers needed for requests
-        :return: dict - Dictionary containing headers
-        """
-        return {
-            'Host': 'api.ziprecruiter.com',
-            'Cookie': 'ziprecruiter_browser=018188e0-045b-4ad7-aa50-627a6c3d43aa; ziprecruiter_session=5259b2219bf95b6d2299a1417424bc2edc9f4b38; SplitSV=2016-10-19%3AU2FsdGVkX19f9%2Bx70knxc%2FeR3xXR8lWoTcYfq5QjmLU%3D%0A; __cf_bm=qXim3DtLPbOL83GIp.ddQEOFVFTc1OBGPckiHYxcz3o-1698521532-0-AfUOCkgCZyVbiW1ziUwyefCfzNrJJTTKPYnif1FZGQkT60dMowmSU/Y/lP+WiygkFPW/KbYJmyc+MQSkkad5YygYaARflaRj51abnD+SyF9V; zglobalid=68d49bd5-0326-428e-aba8-8a04b64bc67c.af2d99ff7c03.653d61bb; ziprecruiter_browser=018188e0-045b-4ad7-aa50-627a6c3d43aa; ziprecruiter_session=5259b2219bf95b6d2299a1417424bc2edc9f4b38',
-            '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'
-        }
+    headers = {
+        "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",
+    }

src/tests/test_all.py

@@ -4,7 +4,7 @@ import pandas as pd
 
 def test_all():
     result = scrape_jobs(
-        site_name=["linkedin", "indeed", "zip_recruiter"],
+        site_name=["linkedin", "indeed", "zip_recruiter", "glassdoor"],
         search_term="software engineer",
         results_wanted=5,
     )

src/tests/test_glassdoor.py

@@ -0,0 +1,11 @@
+from ..jobspy import scrape_jobs
+import pandas as pd
+
+
+def test_indeed():
+    result = scrape_jobs(
+        site_name="glassdoor", search_term="software engineer", country_indeed="USA"
+    )
+    assert (
+        isinstance(result, pd.DataFrame) and not result.empty
+    ), "Result should be a non-empty DataFrame"

src/tests/test_indeed.py

@@ -4,8 +4,7 @@ import pandas as pd
 
 def test_indeed():
     result = scrape_jobs(
-        site_name="indeed",
-        search_term="software engineer",
+        site_name="indeed", search_term="software engineer", country_indeed="usa"
     )
     assert (
         isinstance(result, pd.DataFrame) and not result.empty