enh: proxies (#157 )

* enh: proxies * enh: proxies
docs: readme
2026-03-05 03:54:31 -08:00 · 2024-05-25 14:04:09 -05:00 · 2024-05-25 11:46:23 -05:00 · 2024-05-20 11:46:36 -05:00 · 2024-05-20 11:45:52 -05:00 · 2024-04-30 12:11:48 -05:00
21 changed files with 3364 additions and 2200 deletions
--- a/.gitignore
+++ b/.gitignore
@@ -1,10 +1,10 @@
 /.idea
 **/.DS_Store
 /venv/
-/ven/
+/.idea
 **/__pycache__/
 **/.pytest_cache/
 /.ipynb_checkpoints/
 **/output/
 **/.DS_Store
 *.pyc
 .env
 dist
 /.ipynb_checkpoints/
--- a/.pre-commit-config.yaml
+++ b/.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]
--- a/JobSpy_Demo.ipynb
+++ b/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
 }
--- a/README.md
+++ b/README.md
@@ -2,23 +2,26 @@
 **JobSpy** is a simple, yet comprehensive, job scraping library.
-*Looking to build a data-focused software product?* **[Book a call](https://calendly.com/zachary-products/15min)** *to work with us.*  
+**Not technical?** Try out the web scraping tool on our site at [usejobspy.com](https://usejobspy.com).
-\
+
-Check out another project we wrote: ***[HomeHarvest](https://github.com/ZacharyHampton/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**, **Glassdoor**, & **ZipRecruiter** simultaneously
 - Scrapes job postings from **LinkedIn**, **Indeed** & **ZipRecruiter** simultaneously
 - Aggregates the job postings in a Pandas DataFrame
- Proxy support (HTTP/S, SOCKS)
+- Proxies support
-[Video Guide for JobSpy](https://www.youtube.com/watch?v=RuP1HrAZnxs&pp=ygUgam9icyBzY3JhcGVyIGJvdCBsaW5rZWRpbiBpbmRlZWQ%3D) - Updated for release v1.1.3
+[Video Guide for JobSpy](https://www.youtube.com/watch?v=RuP1HrAZnxs&pp=ygUgam9icyBzY3JhcGVyIGJvdCBsaW5rZWRpbiBpbmRlZWQ%3D) -
 Updated for release v1.1.3
 ![jobspy](https://github.com/cullenwatson/JobSpy/assets/78247585/ec7ef355-05f6-4fd3-8161-a817e31c5c57)
 ### Installation
 ```
-pip install --upgrade python-jobspy
+pip install -U python-jobspy
 ```
 _Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_
@@ -26,42 +29,30 @@ pip install --upgrade python-jobspy
 ### Usage
 ```python
 import csv
 from jobspy import scrape_jobs
 import pandas as pd
-jobs: pd.DataFrame = 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,
+    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
-    country_indeed='USA' # only needed for indeed
+    # linkedin_fetch_description=True # get full description and direct job url for linkedin (slower)
    # proxies=["Efb5EA8OIk0BQb:wifi;us;@proxy.soax.com:9000", "localhost"],
    # use if you want to use a proxy (3 types)
    # proxy="socks5://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
    # proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
    # proxy="https://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
 )
-
+print(f"Found {len(jobs)} jobs")
-# formatting for pandas
+print(jobs.head())
-pd.set_option('display.max_columns', None)
+jobs.to_csv("jobs.csv", quoting=csv.QUOTE_NONNUMERIC, escapechar="\\", index=False) # to_xlsx
 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 display in Jupyter Notebook (1. pip install jupyter 2. jupyter notebook)
 display(jobs)
 #2 output to console
 #print(jobs)
 #3 output to .csv
 #jobs.to_csv('jobs.csv', index=False)
 ```
 ### 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...
@@ -69,52 +60,113 @@ linkedin       Full-Stack Software Engineer      Rain              New York
 zip_recruiter Software Engineer - New Grad       ZipRecruiter      Santa Monica  CA     fulltime  yearly    130000      150000      https://www.ziprecruiter.com/jobs/ziprecruiter...  We offer a hybrid work environment. Most US-ba...
 zip_recruiter Software Developer                 TEKsystems        Phoenix       AZ     fulltime  hourly    65          75          https://www.ziprecruiter.com/jobs/teksystems-0...  Top Skills' Details• 6 years of Java developme...
 ```
 ### Parameters for `scrape_jobs()`
 ```plaintext
 Required
 ├── site_type (List[enum]): linkedin, zip_recruiter, indeed
 └── search_term (str)
 Optional
-├── location (int)
+├── site_name (list|str): 
-├── distance (int): in miles
+|    linkedin, zip_recruiter, indeed, glassdoor 
-├── job_type (enum): fulltime, parttime, internship, contract
+|    (default is all four)
-├── proxy (str): in format 'http://user:pass@host:port' or [https, socks]
+│
 ├── search_term (str)
 │
 ├── location (str)
 │
 ├── distance (int): 
 |    in miles, default 50
 │
 ├── job_type (str): 
 |    fulltime, parttime, internship, contract
 │
 ├── proxies (): 
 |    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
+├── results_wanted (int): 
-├── country_indeed (enum): filters the country on Indeed (see below for correct spelling)
+|    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)
 │   ├── city (str)
 │   ├── state (str)
 ├── description (str)
-├── job_type (enum): fulltime, parttime, internship, contract
+├── job_type (str): fulltime, parttime, internship, contract
 ├── compensation (object)
-│   ├── interval (enum): yearly, monthly, weekly, daily, hourly
+│   ├── interval (str): yearly, monthly, weekly, daily, hourly
 │   ├── min_amount (int)
 │   ├── max_amount (int)
 │   └── currency (enum)
 └── date_posted (date)
 └── emails (str)
 └── is_remote (bool)
 Indeed specific
 ├── company_country (str)
 └── company_addresses (str)
 └── company_industry (str)
 └── company_employees_label (str)
 └── company_revenue_label (str)
 └── company_description (str)
 └── ceo_name (str)
 └── ceo_photo_url (str)
 └── logo_photo_url (str)
 └── banner_photo_url (str)
 ```
 ### Exceptions
 The following exceptions may be raised when using JobSpy:
 * `LinkedInException`
 * `IndeedException`
 * `ZipRecruiterException`
 ## Supported Countries for Job Searching
 ### **LinkedIn**
 LinkedIn searches globally & uses only the `location` parameter. 
@@ -123,53 +175,52 @@ LinkedIn searches globally & uses only the `location` parameter.
 ZipRecruiter searches for jobs in **US/Canada** & uses only the `location` parameter.
 ### **Indeed / Glassdoor**
-### **Indeed**
+Indeed & Glassdoor supports most countries, but the `country_indeed` parameter is required. Additionally, use the `location`
-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.
+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 |
+| Argentina            | Australia*   | Austria*   | Bahrain        |
-| Belgium | Brazil | Canada | Chile |
+| Belgium*             | Brazil*      | Canada*    | Chile          |
 | China                | Colombia     | Costa Rica | Czech Republic |
 | Denmark              | Ecuador      | Egypt      | Finland        |
-| France | Germany | Greece | Hong Kong |
+| France*              | Germany*     | Greece     | Hong Kong*     |
-| Hungary | India | Indonesia | Ireland |
+| Hungary              | India*       | Indonesia  | Ireland*       |
-| Israel | Italy | Japan | Kuwait |
+| Israel               | Italy*       | Japan      | Kuwait         |
-| Luxembourg | Malaysia | Mexico | Morocco |
+| Luxembourg           | Malaysia     | Mexico*    | Morocco        |
-| Netherlands | New Zealand | Nigeria | Norway |
+| Netherlands*         | New Zealand* | Nigeria    | Norway         |
 | Oman                 | Pakistan     | Panama     | Peru           |
 | Philippines          | Poland       | Portugal   | Qatar          |
-| Romania | Saudi Arabia | Singapore | South Africa |
+| Romania              | Saudi Arabia | Singapore* | South Africa   |
-| South Korea | Spain | Sweden | Switzerland |
+| South Korea          | Spain*       | Sweden     | Switzerland*   |
 | Taiwan               | Thailand     | Turkey     | Ukraine        |
-| United Arab Emirates | UK | USA | Uruguay |
+| United Arab Emirates | UK*          | USA*       | Uruguay        |
-| Venezuela | Vietnam |  |  |
+| 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
 ---
 **Q: Encountering issues with your queries?**  
-**A:** Try reducing the number of `results_wanted` and/or broadening the filters. If problems persist, [submit an issue](https://github.com/cullenwatson/JobSpy/issues).
+**A:** Try reducing the number of `results_wanted` and/or broadening the filters. If problems
 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. Currently, **LinkedIn** is particularly aggressive with blocking. We recommend:
+**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.
+- Wait some time between scrapes (site-dependent).
- Trying a VPN or proxy to change your IP address.
+- 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
--- a/poetry.lock
+++ b/poetry.lock
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,9 +1,9 @@
 [tool.poetry]
 name = "python-jobspy"
-version = "1.1.5"
+version = "1.1.54"
-description = "Job scraper for LinkedIn, Indeed & ZipRecruiter"
+description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
-authors = ["Zachary Hampton <zachary@zacharysproducts.com>", "Cullen Watson <cullen@cullen.ai>"]
+authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
-homepage = "https://github.com/cullenwatson/JobSpy"
+homepage = "https://github.com/Bunsly/JobSpy"
 readme = "README.md"
 packages = [
@@ -13,16 +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
--- a/src/jobspy/init.py
+++ b/src/jobspy/init.py
@@ -1,69 +1,84 @@
 from __future__ import annotations
 import pandas as pd
-import concurrent.futures
+from typing import Tuple
-from concurrent.futures import ThreadPoolExecutor
+from concurrent.futures import ThreadPoolExecutor, as_completed
 from typing import List, Tuple, NamedTuple, Dict, Optional
 import traceback
 from .jobs import JobType, Location
 from .scrapers.utils import logger, set_logger_level
 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,
 )
 def scrape_jobs(
    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 = None,
    easy_apply: bool | None = None,
    results_wanted: int = 15,
    country_indeed: str = "usa",
    hyperlinks: bool = False,
    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: 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:
 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,
    is_remote: bool = False,
    job_type: str = None,
    easy_apply: bool = False,  # linkedin
    results_wanted: int = 15,
    country_indeed: str = "usa",
    hyperlinks: bool = False,
    proxy: Optional[str] = None,
 ) -> pd.DataFrame:
    """
    Simultaneously scrapes job data from multiple job sites.
    :return: results_wanted: pandas dataframe containing job data
    """
    def get_enum_from_value(value_str):
        for job_type in JobType:
            if value_str in job_type.value:
                return job_type
        raise Exception(f"Invalid job type: {value_str}")
    job_type = get_enum_from_value(job_type) if job_type else None
-
+    def get_site_type():
-    if type(site_name) == str:
+        site_types = list(Site)
-        site_type = [_map_str_to_site(site_name)]
+        if isinstance(site_name, str):
-    else:  #: if type(site_name) == list
+            site_types = [map_str_to_site(site_name)]
-        site_type = [
+        elif isinstance(site_name, Site):
-            _map_str_to_site(site) if type(site) == str else site_name
+            site_types = [site_name]
        elif isinstance(site_name, list):
            site_types = [
                map_str_to_site(site) if isinstance(site, str) else site
                for site in site_name
            ]
        return site_types
    country_enum = Country.from_string(country_indeed)
    scraper_input = ScraperInput(
-        site_type=site_type,
+        site_type=get_site_type(),
        country=country_enum,
        search_term=search_term,
        location=location,
@@ -71,61 +86,59 @@ 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)
+        scraper = scraper_class(proxies=proxies)
        try:
        scraped_data: JobResponse = scraper.scrape(scraper_input)
-        except (LinkedInException, IndeedException, ZipRecruiterException) as lie:
+        cap_name = site.value.capitalize()
-            raise lie
+        site_name = "ZipRecruiter" if cap_name == "Zip_recruiter" else cap_name
-        except Exception as e:
+        logger.info(f"{site_name} finished scraping")
            # unhandled exceptions
            if site == Site.LINKEDIN:
                raise LinkedInException()
            if site == Site.INDEED:
                raise IndeedException()
            if site == Site.ZIP_RECRUITER:
                raise ZipRecruiterException()
            else:
                raise e
        return site.value, scraped_data
    site_to_jobs_dict = {}
    def worker(site):
-        site_value, scraped_data = scrape_site(site)
+        site_val, scraped_info = scrape_site(site)
-        return site_value, scraped_data
+        return site_val, scraped_info
    with ThreadPoolExecutor() as executor:
        future_to_site = {
            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
-    jobs_dfs: List[pd.DataFrame] = []
+    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 = job_data["job_url"]
-                "job_url_hyper"
+            job_data["job_url_hyper"] = f'<a href="{job_url}">{job_url}</a>'
            ] = f'<a href="{job_data["job_url"]}">{job_data["job_url"]}</a>'
            job_data["site"] = site
            job_data["company"] = job_data["company_name"]
-            if job_data["job_type"]:
+            job_data["job_type"] = (
-                # Take the first value from the job type tuple
+                ", ".join(job_type.value[0] for job_type in job_data["job_type"])
-                job_data["job_type"] = job_data["job_type"].value[0]
+                if job_data["job_type"]
-            else:
+                else None
-                job_data["job_type"] = None
+            )
-
+            job_data["emails"] = (
-            job_data["location"] = Location(**job_data["location"]).display_location()
+                ", ".join(job_data["emails"]) if job_data["emails"] else None
            )
            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):
@@ -147,23 +160,52 @@ def scrape_jobs(
            jobs_dfs.append(job_df)
    if jobs_dfs:
-        jobs_df = pd.concat(jobs_dfs, ignore_index=True)
+        # Step 1: Filter out all-NA columns from each DataFrame before concatenation
-        desired_order: List[str] = [
+        filtered_dfs = [df.dropna(axis=1, how="all") for df in jobs_dfs]
        # 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",
            "date_posted",
            "job_type",
            "date_posted",
            "interval",
            "min_amount",
            "max_amount",
            "currency",
-            "job_url_hyper" if hyperlinks else "job_url",
+            "is_remote",
            "emails",
            "description",
            "company_url",
            "company_url_direct",
            "company_addresses",
            "company_industry",
            "company_num_employees",
            "company_revenue",
            "company_description",
            "logo_photo_url",
            "banner_photo_url",
            "ceo_name",
            "ceo_photo_url",
        ]
        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()
--- a/src/jobspy/jobs/init.py
+++ b/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
 from pydantic import BaseModel, validator
 class JobType(Enum):
@@ -37,10 +38,16 @@ class JobType(Enum):
        "повназайнятість",
        "toànthờigian",
    )
-    PART_TIME = ("parttime", "teilzeit")
+    PART_TIME = ("parttime", "teilzeit", "částečnýúvazek", "deltid")
    CONTRACT = ("contract", "contractor")
    TEMPORARY = ("temporary",)
-    INTERNSHIP = ("internship", "prácticas", "ojt(onthejobtraining)", "praktikum")
+    INTERNSHIP = (
        "internship",
        "prácticas",
        "ojt(onthejobtraining)",
        "praktikum",
        "praktik",
    )
    PER_DIEM = ("perdiem",)
    NIGHTS = ("nights",)
@@ -50,40 +57,46 @@ class JobType(Enum):
 class Country(Enum):
-    ARGENTINA = ("argentina", "ar")
+    """
-    AUSTRALIA = ("australia", "au")
+    Gets the subdomain for Indeed and Glassdoor.
-    AUSTRIA = ("austria", "at")
+    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")
+    BELGIUM = ("belgium", "be", "fr:be")
-    BRAZIL = ("brazil", "br")
+    BRAZIL = ("brazil", "br", "com.br")
-    CANADA = ("canada", "ca")
+    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")
+    FRANCE = ("france", "fr", "fr")
-    GERMANY = ("germany", "de")
+    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")
+    NETHERLANDS = ("netherlands", "nl", "nl")
-    NEWZEALAND = ("new zealand", "nz")
+    NEWZEALAND = ("new zealand", "nz", "co.nz")
    NIGERIA = ("nigeria", "ng")
    NORWAY = ("norway", "no")
    OMAN = ("oman", "om")
@@ -96,54 +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")
+    UK = ("uk,united kingdom", "uk:gb", "co.uk")
-    USA = ("usa", "www")
+    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):
+    @property
-        obj = object.__new__(cls)
+    def indeed_domain_value(self):
-        obj._value_ = country
+        subdomain, _, api_country_code = self.value[1].partition(":")
-        obj.domain = domain
+        if subdomain and api_country_code:
-        return obj
+            return subdomain, api_country_code.upper()
        return self.value[1], self.value[1].upper()
    @property
-    def domain_value(self):
+    def glassdoor_domain_value(self):
-        return self.domain
+        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
@@ -153,11 +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 isinstance(self.country, str):
-            if self.country.value in ("usa", "uk"):
+            location_parts.append(self.country)
-                location_parts.append(self.country.value.upper())
+        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)
@@ -168,24 +201,58 @@ 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: CompensationInterval
+    interval: Optional[CompensationInterval] = None
-    min_amount: int = None
+    min_amount: float | None = None
-    max_amount: int = 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: Optional[str] = None
+    description: str | None = None
-    job_type: Optional[JobType] = None
+    company_url: str | None = None
-    compensation: Optional[Compensation] = None
+    company_url_direct: str | None = None
-    date_posted: Optional[date] = None
+
    job_type: list[JobType] | None = None
    compensation: Compensation | None = None
    date_posted: date | None = None
    emails: list[str] | None = None
    is_remote: bool | None = None
    # indeed specific
    company_addresses: str | None = None
    company_industry: str | None = None
    company_num_employees: str | None = None
    company_revenue: str | None = None
    company_description: str | None = None
    ceo_name: str | None = None
    ceo_photo_url: str | None = None
    logo_photo_url: str | None = None
    banner_photo_url: str | None = None
 class JobResponse(BaseModel):
--- a/src/jobspy/scrapers/init.py
+++ b/src/jobspy/scrapers/init.py
@@ -1,31 +1,47 @@
-from ..jobs import Enum, BaseModel, JobType, JobResponse, Country
+from __future__ import annotations
-from typing import List, Optional, Any
+
 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]
+    site_type: list[Site]
-    search_term: str
+    search_term: str | None = None
-    location: str = None
+    location: str | None = None
-    country: Optional[Country] = Country.USA
+    country: Country | None = Country.USA
-    distance: Optional[int] = None
+    distance: int | None = None
    is_remote: bool = False
-    job_type: Optional[JobType] = None
+    job_type: JobType | None = None
-    easy_apply: bool = None  # linkedin
+    easy_apply: bool | None = None
    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:
+class Scraper(ABC):
-    def __init__(self, site: Site, proxy: Optional[List[str]] = None):
+    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: ...
--- a/src/jobspy/scrapers/exceptions.py
+++ b/src/jobspy/scrapers/exceptions.py
@@ -7,12 +7,20 @@ This module contains the set of Scrapers' exceptions.
 class LinkedInException(Exception):
-    """Failed to scrape LinkedIn"""
+    def __init__(self, message=None):
        super().__init__(message or "An error occurred with LinkedIn")
 class IndeedException(Exception):
-    """Failed to scrape Indeed"""
+    def __init__(self, message=None):
        super().__init__(message or "An error occurred with Indeed")
 class ZipRecruiterException(Exception):
-    """Failed to scrape ZipRecruiter"""
+    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")
--- a/src/jobspy/scrapers/glassdoor/init.py
+++ b/src/jobspy/scrapers/glassdoor/init.py
@@ -0,0 +1,534 @@
 """
 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=[])
        all_jobs: 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
                )
                all_jobs.extend(jobs)
                if not jobs or len(all_jobs) >= scraper_input.results_wanted:
                    all_jobs = all_jobs[: scraper_input.results_wanted]
                    break
            except Exception as e:
                logger.error(f"Glassdoor: {str(e)}")
                break
        return JobResponse(jobs=all_jobs)
    def _fetch_jobs_page(
        self,
        scraper_input: ScraperInput,
        location_id: int,
        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"
        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,
        )
    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
            }
    """
--- a/src/jobspy/scrapers/indeed/init.py
+++ b/src/jobspy/scrapers/indeed/init.py
@@ -4,21 +4,22 @@ jobspy.scrapers.indeed
 This module contains routines to scrape Indeed.
 """
 import re
 import math
 import io
 import json
 import traceback
 from datetime import datetime
 from typing import Optional
-import tls_client
+from __future__ import annotations
-import urllib.parse
+
-from bs4 import BeautifulSoup
+import math
-from bs4.element import Tag
+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 (
    extract_emails_from_text,
    get_enum_from_job_type,
    markdown_converter,
    logger,
    create_session,
 )
 from ...jobs import (
    JobPost,
    Compensation,
@@ -26,148 +27,26 @@ from ...jobs import (
    Location,
    JobResponse,
    JobType,
    DescriptionFormat,
 )
 from .. import Scraper, ScraperInput, Site, Country
 class IndeedScraper(Scraper):
-    def __init__(self, proxy: Optional[str] = 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
        """
-        site = Site(Site.INDEED)
+        super().__init__(Site.INDEED, proxies=proxies)
        super().__init__(site, proxy=proxy)
-        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()
-
+        self.headers = None
-    def scrape_page(
+        self.api_country_code = None
-        self, scraper_input: ScraperInput, page: int, session: tls_client.Session
+        self.base_url = None
-    ) -> tuple[list[JobPost], int]:
+        self.api_url = "https://apis.indeed.com/graphql"
        """
        Scrapes a page of Indeed for jobs with scraper_input criteria
        :param scraper_input:
        :param page:
        :param session:
        :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"
        job_list: list[JobPost] = []
        params = {
            "q": scraper_input.search_term,
            "l": scraper_input.location,
            "filter": 0,
            "start": 0 + 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(
                self.url + "/jobs",
                params=params,
                allow_redirects=True,
                proxy=self.proxy,
                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) -> Optional[JobPost]:
            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("max")),
                        max_amount=int(extracted_salary.get("min")),
                        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, session)
            with io.StringIO(job["snippet"]) as f:
                soup = BeautifulSoup(f, "html.parser")
                li_elements = soup.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,
            )
            return job_post
        with ThreadPoolExecutor(max_workers=1) as executor:
            job_results: list[Future] = [
                executor.submit(process_job, job)
                for job in jobs["metaData"]["mosaicProviderJobCardsModel"]["results"]
            ]
        job_list = [result.result() for result in job_results if result.result()]
        return job_list, total_num_jobs
    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
        """
@@ -175,145 +54,381 @@ class IndeedScraper(Scraper):
        :param scraper_input:
        :return: job_response
        """
-        session = tls_client.Session(
+        self.scraper_input = scraper_input
-            client_identifier="chrome112", random_tls_extension_order=True
+        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
-        pages_to_process = (
+        cursor = None
-            math.ceil(scraper_input.results_wanted / self.jobs_per_page) - 1
+        offset_pages = math.ceil(self.scraper_input.offset / 100)
-        )
+        for _ in range(offset_pages):
-
+            logger.info(f"Indeed skipping search page: {page}")
-        #: get first page to initialize session
+            __, cursor = self._scrape_page(cursor)
-        job_list, total_results = self.scrape_page(scraper_input, 0, session)
+            if not __:
-
+                logger.info(f"Indeed found no jobs on page: {page}")
-        with ThreadPoolExecutor(max_workers=1) as executor:
+                break
            futures: list[Future] = [
                executor.submit(self.scrape_page, scraper_input, page, session)
                for page in range(1, pages_to_process + 1)
            ]
            for future in futures:
                jobs, _ = future.result()
        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])
-        if len(job_list) > scraper_input.results_wanted:
+    def _scrape_page(self, cursor: str | None) -> Tuple[list[JobPost], str | None]:
            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, session: tls_client.Session) -> str:
        """
-        Retrieves job description by going to the job page url
+        Scrapes a page of Indeed for jobs with scraper_input criteria
-        :param job_page_url:
+        :param cursor:
-        :param session:
+        :return: jobs found on page, next page cursor
        :return: description
        """
-        parsed_url = urllib.parse.urlparse(job_page_url)
+        jobs = []
-        params = urllib.parse.parse_qs(parsed_url.query)
+        new_cursor = None
-        jk_value = params.get("jk", [None])[0]
+        filters = self._build_filters()
-        formatted_url = f"{self.url}/viewjob?jk={jk_value}&spa=1"
+        search_term = (
-
+            self.scraper_input.search_term.replace('"', '\\"')
-        try:
+            if self.scraper_input.search_term
-            response = session.get(
+            else ""
                formatted_url, allow_redirects=True, timeout_seconds=5, proxy=self.proxy
        )
-        except Exception as e:
+        query = self.job_search_query.format(
-            return None
+            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)"
            )
            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):
+        with ThreadPoolExecutor(max_workers=self.num_workers) as executor:
-            return None
+            job_results: list[Future] = [
                executor.submit(self._process_job, job["job"]) for job in jobs
            ]
        job_list = [result.result() for result in job_results if result.result()]
        return job_list, new_cursor
-        raw_description = response.json()["body"]["jobInfoWrapperModel"][
+    def _build_filters(self):
-            "jobInfoModel"
+        """
-        ]["sanitizedJobDescription"]
+        Builds the filters dict for job type/is_remote. If hours_old is provided, composite filter for job_type/is_remote is not possible.
-        with io.StringIO(raw_description) as f:
+        IndeedApply: filters: { keyword: { field: "indeedApplyScope", keys: ["DESKTOP"] } }
-            soup = BeautifulSoup(f, "html.parser")
+        """
-            text_content = " ".join(soup.get_text().split()).strip()
+        filters_str = ""
-            return text_content
+        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)  # Prepare your keys string
                filters_str = f"""
                filters: {{
                  composite: {{
                    filters: [{{
                      keyword: {{
                        field: "attributes",
                        keys: ["{keys_str}"]
                      }}
                    }}]
                  }}
                }}
                """
        return filters_str
    def _process_job(self, job: dict) -> JobPost | None:
        """
        Parses the job dict into JobPost model
        :param job: dict to parse
        :return: JobPost if it's a new job
        """
        job_url = f'{self.base_url}/viewjob?jk={job["key"]}'
        if job_url in self.seen_urls:
            return
        self.seen_urls.add(job_url)
        description = job["description"]["html"]
        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()
                if employer_details.get("industry")
                else None
            ),
            company_num_employees=employer_details.get("employeesLocalizedLabel"),
            company_revenue=employer_details.get("revenueLocalizedLabel"),
            company_description=employer_details.get("briefDescription"),
            ceo_name=employer_details.get("ceoName"),
            ceo_photo_url=employer_details.get("ceoPhotoUrl"),
            logo_photo_url=(
                employer["images"].get("squareLogoUrl")
                if employer and employer.get("images")
                else None
            ),
            banner_photo_url=(
                employer["images"].get("headerImageUrl")
                if employer and employer.get("images")
                else None
            ),
        )
    @staticmethod
-    def get_job_type(job: dict) -> Optional[JobType]:
+    def _get_job_type(attributes: list) -> list[JobType]:
        """
-        Parses the job to get JobTypeIndeed
+        Parses the attributes to get list of job types
        :param attributes:
        :return: list of JobType
        """
        job_types: list[JobType] = []
        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 _get_compensation(job: dict) -> Compensation | None:
        """
        Parses the job to get compensation
        :param job:
-        :return:
+        :param job:
        :return: compensation object
        """
-        for taxonomy in job["taxonomyAttributes"]:
+        comp = job["compensation"]["baseSalary"]
-            if taxonomy["label"] == "job-types":
+        if not comp:
                if len(taxonomy["attributes"]) > 0:
                    label = taxonomy["attributes"][0].get("label")
                    if label:
                        job_type_str = label.replace("-", "").replace(" ", "").lower()
                        return IndeedScraper.get_enum_from_value(job_type_str)
            return None
-
+        interval = IndeedScraper._get_compensation_interval(comp["unitOfWork"])
-    @staticmethod
+        if not interval:
    def get_enum_from_value(value_str):
        for job_type in JobType:
            if value_str in job_type.value:
                return job_type
            return None
-
+        min_range = comp["range"].get("min")
-    @staticmethod
+        max_range = comp["range"].get("max")
-    def parse_jobs(soup: BeautifulSoup) -> dict:
+        return Compensation(
-        """
+            interval=interval,
-        Parses the jobs from the soup object
+            min_amount=round(min_range, 2) if min_range is not None else None,
-        :param soup:
+            max_amount=round(max_range, 2) if max_range is not None else None,
-        :return: jobs
+            currency=job["compensation"]["currencyCode"],
        """
        def find_mosaic_script() -> Optional[Tag]:
            """
            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:
+    def _is_job_remote(job: dict, description: str) -> bool:
        """
-        Parses the total jobs for that search from soup object
+        Searches the description, location, and attributes to check if job is remote
        :param soup:
        :return: total_num_jobs
        """
-        script = soup.find("script", string=lambda t: t and "window._initialData" in t)
+        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
        )
-        pattern = re.compile(r"window._initialData\s*=\s*({.*})\s*;", re.DOTALL)
+    @staticmethod
-        match = pattern.search(script.string)
+    def _get_compensation_interval(interval: str) -> CompensationInterval:
-        total_num_jobs = 0
+        interval_mapping = {
-        if match:
+            "DAY": "DAILY",
-            json_str = match.group(1)
+            "YEAR": "YEARLY",
-            data = json.loads(json_str)
+            "HOUR": "HOURLY",
-            total_num_jobs = int(data["searchTitleBarModel"]["totalNumResults"])
+            "WEEK": "WEEKLY",
-        return total_num_jobs
+            "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}
            includeSponsoredResults: NONE
            limit: 100
            sort: DATE
            {cursor}
            {filters}
          ) {{
            pageInfo {{
              nextCursor
            }}
            results {{
              trackingKey
              job {{
                key
                title
                datePublished
                dateOnIndeed
                description {{
                  html
                }}
                location {{
                  countryName
                  countryCode
                  admin1Code
                  city
                  postalCode
                  streetAddress
                  formatted {{
                    short
                    long
                  }}
                }}
                compensation {{
                  baseSalary {{
                    unitOfWork
                    range {{
                      ... on Range {{
                        min
                        max
                      }}
                    }}
                  }}
                  currencyCode
                }}
                attributes {{
                  key
                  label
                }}
                employer {{
                  relativeCompanyPageUrl
                  name
                  dossier {{
                      employerDetails {{
                        addresses
                        industry
                        employeesLocalizedLabel
                        revenueLocalizedLabel
                        briefDescription
                        ceoName
                        ceoPhotoUrl
                      }}
                      images {{
                            headerImageUrl
                            squareLogoUrl
                      }}
                      links {{
                        corporateWebsite
                    }}
                  }}
                }}
                recruit {{
                  viewJobUrl
                  detailedSalary
                  workSchedule
                }}
              }}
            }}
          }}
        }}
        """
--- a/src/jobspy/scrapers/linkedin/init.py
+++ b/src/jobspy/scrapers/linkedin/init.py
@@ -4,35 +4,63 @@ jobspy.scrapers.linkedin
 This module contains routines to scrape LinkedIn.
 """
 from typing import Optional, Tuple
 from datetime import datetime
 import traceback
-import requests
+from __future__ import annotations
-from requests.exceptions import Timeout, ProxyError
+
-from bs4 import BeautifulSoup
+import time
 import random
 import regex as re
 from typing import Optional
 from datetime import datetime
 from threading import Lock
 from bs4.element import Tag
 from bs4 import BeautifulSoup
 from urllib.parse import urlparse, urlunparse, unquote
 from .. import Scraper, ScraperInput, Site
 from ..exceptions import LinkedInException
 from ..utils import create_session
 from ...jobs import (
    JobPost,
    Location,
    JobResponse,
    JobType,
    Country,
    Compensation,
-    CompensationInterval,
+    DescriptionFormat,
 )
 from ..utils import (
    logger,
    extract_emails_from_text,
    get_enum_from_job_type,
    currency_parser,
    markdown_converter,
 )
 class LinkedInScraper(Scraper):
-    def __init__(self, proxy: Optional[str] = None):
+    base_url = "https://www.linkedin.com"
    delay = 3
    band_delay = 4
    jobs_per_page = 25
    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.url = "https://www.linkedin.com"
+        self.session = create_session(
-        super().__init__(site, proxy=proxy)
+            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.job_url_direct_regex = re.compile(r'(?<=\?url=)[^"]+')
    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
        """
@@ -40,194 +68,221 @@ class LinkedInScraper(Scraper):
        :param scraper_input:
        :return: job_response
        """
-        self.country = "worldwide"
+        self.scraper_input = scraper_input
        job_list: list[JobPost] = []
        seen_urls = set()
-        page, processed_jobs, job_count = 0, 0, 0
+        url_lock = Lock()
-
+        page = scraper_input.offset // 25 + 25 if scraper_input.offset else 0
-        def job_type_code(job_type):
+        seconds_old = (
-            mapping = {
+            scraper_input.hours_old * 3600 if scraper_input.hours_old else None
-                JobType.FULL_TIME: "F",
+        )
-                JobType.PART_TIME: "P",
+        continue_search = (
-                JobType.INTERNSHIP: "I",
+            lambda: len(job_list) < scraper_input.results_wanted and page < 1000
-                JobType.CONTRACT: "C",
+        )
-                JobType.TEMPORARY: "T",
+        while continue_search():
-            }
+            logger.info(f"LinkedIn search page: {page // 25 + 1}")
            return mapping.get(job_type, "")
        with requests.Session() as session:
            while len(job_list) < scraper_input.results_wanted:
            params = {
                "keywords": scraper_input.search_term,
                "location": scraper_input.location,
                "distance": scraper_input.distance,
                "f_WT": 2 if scraper_input.is_remote else None,
-                    "f_JT": job_type_code(scraper_input.job_type)
+                "f_JT": (
                    self.job_type_code(scraper_input.job_type)
                    if scraper_input.job_type
-                    else None,
+                    else None
-                    "pageNum": page,
+                ),
                "pageNum": 0,
                "start": page + scraper_input.offset,
                "f_AL": "true" if scraper_input.easy_apply else None,
                "f_C": (
                    ",".join(map(str, scraper_input.linkedin_company_ids))
                    if scraper_input.linkedin_company_ids
                    else None
                ),
            }
            if seconds_old is not None:
                params["f_TPR"] = f"r{seconds_old}"
            params = {k: v for k, v in params.items() if v is not None}
            try:
-                    response = session.get(
+                response = self.session.get(
-                        f"{self.url}/jobs/search",
+                    f"{self.base_url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
                    params=params,
                        allow_redirects=True,
                        proxies=self.proxy,
                    timeout=10,
                )
-                    response.raise_for_status()
+                if response.status_code not in range(200, 400):
-                except requests.HTTPError as e:
+                    if response.status_code == 429:
-                    raise LinkedInException(
+                        err = (
-                        f"bad response status code: {response.status_code}"
+                            f"429 Response - Blocked by LinkedIn for too many requests"
                        )
-                except ProxyError as e:
+                    else:
-                    raise LinkedInException("bad proxy")
+                        err = f"LinkedIn response status code {response.status_code}"
-                except (ProxyError, Exception) as e:
+                        err += f" - {response.text}"
-                    raise LinkedInException(str(e))
+                    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)
-                if page == 0:
+            for job_card in job_cards:
-                    job_count_text = soup.find(
+                job_url = None
-                        "span", class_="results-context-header__job-count"
+                href_tag = job_card.find("a", class_="base-card__full-link")
-                    ).text
+                if href_tag and "href" in href_tag.attrs:
-                    job_count = int("".join(filter(str.isdigit, job_count_text)))
+                    href = href_tag.attrs["href"].split("?")[0]
                    job_id = href.split("-")[-1]
                    job_url = f"{self.base_url}/jobs/view/{job_id}"
-                for job_card in soup.find_all(
+                with url_lock:
                    "div",
                    class_="base-card relative w-full hover:no-underline focus:no-underline base-card--link base-search-card base-search-card--link job-search-card",
                ):
                    processed_jobs += 1
                    data_entity_urn = job_card.get("data-entity-urn", "")
                    job_id = (
                        data_entity_urn.split(":")[-1] if data_entity_urn else "N/A"
                    )
                    job_url = f"{self.url}/jobs/view/{job_id}"
                    if job_url in seen_urls:
                        continue
                    seen_urls.add(job_url)
                    job_info = job_card.find("div", class_="base-search-card__info")
                    if job_info is None:
                        continue
                    title_tag = job_info.find("h3", class_="base-search-card__title")
                    title = title_tag.text.strip() if title_tag else "N/A"
                    company_tag = job_info.find("a", class_="hidden-nested-link")
                    company = company_tag.text.strip() if company_tag else "N/A"
                    metadata_card = job_info.find(
                        "div", class_="base-search-card__metadata"
                    )
                    location: Location = self.get_location(metadata_card)
                    datetime_tag = metadata_card.find(
                        "time", class_="job-search-card__listdate"
                    )
                    description, job_type = self.get_description(job_url)
                    if datetime_tag:
                        datetime_str = datetime_tag["datetime"]
                try:
-                            date_posted = datetime.strptime(datetime_str, "%Y-%m-%d")
+                    fetch_desc = scraper_input.linkedin_fetch_description
-                        except Exception as e:
+                    job_post = self._process_job(job_card, job_url, fetch_desc)
-                            date_posted = None
+                    if job_post:
                    else:
                        date_posted = None
                    job_post = JobPost(
                        title=title,
                        description=description,
                        company_name=company,
                        location=location,
                        date_posted=date_posted,
                        job_url=job_url,
                        job_type=job_type,
                        compensation=Compensation(
                            interval=CompensationInterval.YEARLY, currency=None
                        ),
                    )
                        job_list.append(job_post)
-                    if processed_jobs >= job_count:
+                    if not continue_search():
                        break
                    if len(job_list) >= scraper_input.results_wanted:
                        break
                if processed_jobs >= job_count:
                    break
                if len(job_list) >= scraper_input.results_wanted:
                        break
                except Exception as e:
                    raise LinkedInException(str(e))
-                page += 1
+            if continue_search():
                time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
                page += self.jobs_per_page
        job_list = job_list[: scraper_input.results_wanted]
        return JobResponse(jobs=job_list)
-    def get_description(self, job_page_url: str) -> Optional[str]:
+    def _process_job(
        self, job_card: Tag, job_url: str, full_descr: bool
    ) -> Optional[JobPost]:
        salary_tag = job_card.find("span", class_="job-search-card__salary-info")
        compensation = None
        if salary_tag:
            salary_text = salary_tag.get_text(separator=" ").strip()
            salary_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)
        datetime_tag = (
            metadata_card.find("time", class_="job-search-card__listdate")
            if metadata_card
            else None
        )
        date_posted = None
        if datetime_tag and "datetime" in datetime_tag.attrs:
            datetime_str = datetime_tag["datetime"]
            try:
                date_posted = datetime.strptime(datetime_str, "%Y-%m-%d")
            except:
                date_posted = None
        job_details = {}
        if full_descr:
            job_details = self._get_job_details(job_url)
        return JobPost(
            id=self._get_id(job_url),
            title=title,
            company_name=company,
            company_url=company_url,
            location=location,
            date_posted=date_posted,
            job_url=job_url,
            compensation=compensation,
            job_type=job_details.get("job_type"),
            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"),
        )
    def _get_id(self, url: str):
        """
-        Retrieves job description by going to the job page url
+        Extracts the job id from the job url
        :param url:
        :return: str
        """
        if not url:
            return None
        return url.split("/")[-1]
    def _get_job_details(self, job_page_url: str) -> dict:
        """
        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(job_page_url, timeout=5)
            response.raise_for_status()
-        except Exception as e:
+        except:
-            return None, None
+            return {}
        if response.url == "https://www.linkedin.com/signup":
            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 is not None:
-        text_content = None
+            def remove_attributes(tag):
-        if div_content:
+                for attr in list(tag.attrs):
-            text_content = " ".join(div_content.get_text().split()).strip()
+                    del tag[attr]
                return tag
-        def get_job_type(
+            div_content = remove_attributes(div_content)
-            soup: BeautifulSoup,
+            description = div_content.prettify(formatter="html")
-        ) -> Tuple[Optional[str], Optional[JobType]]:
+            if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
-            """
+                description = markdown_converter(description)
-            Gets the job type from job page
+        return {
-            :param soup:
+            "description": description,
-            :return: JobType
+            "job_type": self._parse_job_type(soup),
-            """
+            "job_url_direct": self._parse_job_url_direct(soup),
-            h3_tag = soup.find(
+            "logo_photo_url": soup.find("img", {"class": "artdeco-entity-image"}).get(
-                "h3",
+                "data-delayed-url"
-                class_="description__job-criteria-subheader",
+            ),
-                string=lambda text: "Employment type" in text,
+        }
            )
-            employment_type = None
+    def _get_location(self, metadata_card: Optional[Tag]) -> Location:
            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 LinkedInScraper.get_enum_from_value(employment_type)
        return text_content, get_job_type(soup)
    @staticmethod
    def get_enum_from_value(value_str):
        for job_type in JobType:
            if value_str in job_type.value:
                return job_type
        return None
    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"
@@ -239,7 +294,71 @@ 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 []
    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",
    }
--- a/src/jobspy/scrapers/utils.py
+++ b/src/jobspy/scrapers/utils.py
@@ -0,0 +1,180 @@
 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)
 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)
        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:
    if not text:
        return None
    email_regex = re.compile(r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}")
    return email_regex.findall(text)
 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.
    """
    res = None
    for job_type in JobType:
        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)
--- a/src/jobspy/scrapers/ziprecruiter/init.py
+++ b/src/jobspy/scrapers/ziprecruiter/init.py
@@ -4,461 +4,210 @@ jobspy.scrapers.ziprecruiter
 This module contains routines to scrape ZipRecruiter.
 """
 import math
 import json
 import re
 import traceback
 from datetime import datetime
 from typing import Optional, Tuple
 from urllib.parse import urlparse, parse_qs
-import tls_client
+from __future__ import annotations
-import requests
+
-from bs4 import BeautifulSoup
+import math
-from bs4.element import Tag
+import time
-from concurrent.futures import ThreadPoolExecutor, Future
+from datetime import datetime
 from typing import Optional, Tuple, Any
 from concurrent.futures import ThreadPoolExecutor
 from .. import Scraper, ScraperInput, Site
-from ..exceptions import ZipRecruiterException
+from ..utils import (
    logger,
    extract_emails_from_text,
    create_session,
    markdown_converter,
 )
 from ...jobs import (
    JobPost,
    Compensation,
    CompensationInterval,
    Location,
    JobResponse,
    JobType,
    Country,
    DescriptionFormat,
 )
 class ZipRecruiterScraper(Scraper):
-    def __init__(self, proxy: Optional[str] = None):
+    base_url = "https://www.ziprecruiter.com"
-        """
+    api_url = "https://api.ziprecruiter.com"
        Initializes LinkedInScraper with the ZipRecruiter job search url
        """
        site = Site(Site.ZIP_RECRUITER)
        self.url = "https://www.ziprecruiter.com"
        super().__init__(site, proxy=proxy)
    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()
        self.session = tls_client.Session(
            client_identifier="chrome112", random_tls_extension_order=True
        )
    def find_jobs_in_page(
        self, scraper_input: ScraperInput, page: int
    ) -> tuple[list[JobPost], int | None]:
        """
        Scrapes a page of ZipRecruiter for jobs with scraper_input criteria
        :param scraper_input:
        :param page:
        :param session:
        :return: jobs found on page, total number of jobs found for search
        """
        job_list: list[JobPost] = []
        try:
            response = self.session.get(
                self.url + "/jobs-search",
                headers=ZipRecruiterScraper.headers(),
                params=ZipRecruiterScraper.add_params(scraper_input, page),
                allow_redirects=True,
                proxy=self.proxy,
                timeout_seconds=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))
        else:
            soup = BeautifulSoup(response.text, "html.parser")
            js_tag = soup.find("script", {"id": "js_variables"})
        if js_tag:
            page_json = json.loads(js_tag.string)
            jobs_list = page_json.get("jobList")
            if jobs_list:
                page_variant = "javascript"
                # print('type javascript', len(jobs_list))
            else:
                page_variant = "html_2"
                jobs_list = soup.find_all("div", {"class": "job_content"})
                # print('type 2 html', len(jobs_list))
        else:
            page_variant = "html_1"
            jobs_list = soup.find_all("li", {"class": "job-listing"})
            # print('type 1 html', len(jobs_list))
            # with open("zip_method_8.html", "w") as f:
            #     f.write(soup.prettify())
        with ThreadPoolExecutor(max_workers=10) as executor:
            if page_variant == "javascript":
                job_results = [
                    executor.submit(self.process_job_javascript, job)
                    for job in jobs_list
                ]
            elif page_variant == "html_1":
                job_results = [
                    executor.submit(self.process_job_html_1, job) for job in jobs_list
                ]
            elif page_variant == "html_2":
                job_results = [
                    executor.submit(self.process_job_html_2, job) for job in jobs_list
                ]
        job_list = [result.result() for result in job_results if result.result()]
        return job_list
    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
        """
-        Scrapes ZipRecruiter for jobs with scraper_input criteria
+        Scrapes ZipRecruiter for jobs with scraper_input criteria.
        :param scraper_input: Information about job search criteria.
        :return: JobResponse containing a list of jobs.
        """
        self.scraper_input = scraper_input
        job_list: list[JobPost] = []
        continue_token = None
        max_pages = math.ceil(scraper_input.results_wanted / self.jobs_per_page)
        for page in range(1, max_pages + 1):
            if len(job_list) >= scraper_input.results_wanted:
                break
            if page > 1:
                time.sleep(self.delay)
            logger.info(f"ZipRecruiter search page: {page}")
            jobs_on_page, continue_token = self._find_jobs_in_page(
                scraper_input, continue_token
            )
            if jobs_on_page:
                job_list.extend(jobs_on_page)
            else:
                break
            if not continue_token:
                break
        return JobResponse(jobs=job_list[: scraper_input.results_wanted])
    def _find_jobs_in_page(
        self, scraper_input: ScraperInput, continue_token: str | None = None
    ) -> Tuple[list[JobPost], Optional[str]]:
        """
        Scrapes a page of ZipRecruiter for jobs with scraper_input criteria
        :param scraper_input:
-        :return: job_response
+        :param continue_token:
        :return: jobs found on page
        """
-        #: get first page to initialize session
+        jobs_list = []
-        job_list: list[JobPost] = self.find_jobs_in_page(scraper_input, 1)
+        params = self._add_params(scraper_input)
-        pages_to_process = max(
+        if continue_token:
-            3, math.ceil(scraper_input.results_wanted / self.jobs_per_page)
+            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, ""
-        with ThreadPoolExecutor(max_workers=10) as executor:
+        res_data = res.json()
-            futures: list[Future] = [
+        jobs_list = res_data.get("jobs", [])
-                executor.submit(self.find_jobs_in_page, scraper_input, page)
+        next_continue_token = res_data.get("continue", None)
-                for page in range(2, pages_to_process + 1)
+        with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
-            ]
+            job_results = [executor.submit(self._process_job, job) for job in jobs_list]
-            for future in futures:
+        job_list = list(filter(None, (result.result() for result in job_results)))
-                jobs = future.result()
+        return job_list, next_continue_token
-                job_list += jobs
+    def _process_job(self, job: dict) -> JobPost | None:
        job_list = job_list[: scraper_input.results_wanted]
        return JobResponse(jobs=job_list)
    def process_job_html_1(self, job: Tag) -> Optional[JobPost]:
        """
-        Parses a job from the job content tag
+        Processes an individual job dict from the response
        :param job: BeautifulSoup Tag for one job post
        :return JobPost
        """
-        job_url = job.find("a", {"class": "job_link"})["href"]
+        title = job.get("name")
        job_url = f"{self.base_url}/jobs//j?lvk={job['listing_key']}"
        if job_url in self.seen_urls:
-            return None
+            return
        self.seen_urls.add(job_url)
-        title = job.find("h2", {"class": "title"}).text
+        description = job.get("job_description", "").strip()
-        company = job.find("a", {"class": "company_name"}).text.strip()
+        description = (
-
+            markdown_converter(description)
-        description, updated_job_url = self.get_description(job_url)
+            if self.scraper_input.description_format == DescriptionFormat.MARKDOWN
-        job_url = updated_job_url if updated_job_url else job_url
+            else description
        if description is None:
            description = job.find("p", {"class": "job_snippet"}).text.strip()
        job_type_element = job.find("li", {"class": "perk_item perk_type"})
        job_type = None
        if job_type_element:
            job_type_text = (
                job_type_element.text.strip().lower().replace("_", "").replace(" ", "")
        )
-            job_type = ZipRecruiterScraper.get_job_type_enum(job_type_text)
+        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)
        date_posted = ZipRecruiterScraper.get_date_posted(job)
        job_post = JobPost(
            title=title,
            description=description,
            company_name=company,
            location=ZipRecruiterScraper.get_location(job),
            job_type=job_type,
            compensation=ZipRecruiterScraper.get_compensation(job),
            date_posted=date_posted,
            job_url=job_url,
        )
        return job_post
    def process_job_html_2(self, job: Tag) -> Optional[JobPost]:
        """
        Parses a job from the job content tag for a second variat of HTML that ZR uses
        :param job: BeautifulSoup Tag for one job post
        :return JobPost
        """
        job_url = job.find("a", class_="job_link")["href"]
        title = job.find("h2", class_="title").text
        company = job.find("a", class_="company_name").text.strip()
        description, updated_job_url = self.get_description(job_url)
        job_url = updated_job_url if updated_job_url else job_url
        if description is None:
            description = job.find("p", class_="job_snippet").get_text().strip()
        job_type_text = job.find("li", class_="perk_item perk_type")
        job_type = None
        if job_type_text:
            job_type_text = (
                job_type_text.get_text()
                .strip()
                .lower()
                .replace("-", "")
                .replace(" ", "")
            )
            job_type = ZipRecruiterScraper.get_job_type_enum(job_type_text)
        date_posted = ZipRecruiterScraper.get_date_posted(job)
        job_post = JobPost(
            title=title,
            description=description,
            company_name=company,
            location=ZipRecruiterScraper.get_location(job),
            job_type=job_type,
            compensation=ZipRecruiterScraper.get_compensation(job),
            date_posted=date_posted,
            job_url=job_url,
        )
        return job_post
    def process_job_javascript(self, job: dict) -> JobPost:
        title = job.get("Title")
        job_url = job.get("JobURL")
        description, updated_job_url = self.get_description(job_url)
        job_url = updated_job_url if updated_job_url else job_url
        if description is None:
            description = BeautifulSoup(
                job.get("Snippet", "").strip(), "html.parser"
            ).get_text()
        company = job.get("OrgName")
        location = Location(
-            city=job.get("City"), state=job.get("State"), country=Country.US_CANADA
+            city=job.get("job_city"), state=job.get("job_state"), country=country_enum
        )
-        job_type = ZipRecruiterScraper.get_job_type_enum(
+        job_type = self._get_job_type_enum(
-            job.get("EmploymentType", "").replace("-", "").lower()
+            job.get("employment_type", "").replace("_", "").lower()
        )
-
+        date_posted = datetime.fromisoformat(job["posted_time"].rstrip("Z")).date()
-        formatted_salary = job.get("FormattedSalaryShort", "")
+        comp_interval = job.get("compensation_interval")
-        salary_parts = formatted_salary.split(" ")
+        comp_interval = "yearly" if comp_interval == "annual" else comp_interval
-
+        comp_min = int(job["compensation_min"]) if "compensation_min" in job else None
-        min_salary_str = salary_parts[0][1:].replace(",", "")
+        comp_max = int(job["compensation_max"]) if "compensation_max" in job else None
-        if "." in min_salary_str:
+        comp_currency = job.get("compensation_currency")
            min_amount = int(float(min_salary_str) * 1000)
        else:
            min_amount = int(min_salary_str.replace("K", "000"))
        if len(salary_parts) >= 3 and salary_parts[2].startswith("$"):
            max_salary_str = salary_parts[2][1:].replace(",", "")
            if "." in max_salary_str:
                max_amount = int(float(max_salary_str) * 1000)
            else:
                max_amount = int(max_salary_str.replace("K", "000"))
        else:
            max_amount = 0
        compensation = Compensation(
            interval=CompensationInterval.YEARLY,
            min_amount=min_amount,
            max_amount=max_amount,
            currency="USD/CAD",
        )
        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()
        job_url = job.get("JobURL")
        return JobPost(
            id=str(job["listing_key"]),
            title=title,
            description=description,
            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,
            emails=extract_emails_from_text(description) if description else None,
        )
-        return job_post
+
    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) -> Optional[JobType]:
+    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:
-                a = True
+                return [job_type]
                return job_type
        return None
    def get_description(self, job_page_url: str) -> Tuple[Optional[str], Optional[str]]:
        """
        Retrieves job description by going to the job page url
        :param job_page_url:
        :param session:
        :return: description or None, response url
        """
        try:
            response = requests.get(
                job_page_url,
                headers=ZipRecruiterScraper.headers(),
                allow_redirects=True,
                timeout=5,
                proxies=self.proxy,
            )
            if response.status_code not in range(200, 400):
                return None, None
        except Exception as e:
            return None, None
        html_string = response.content
        soup_job = BeautifulSoup(html_string, "html.parser")
        job_description_div = soup_job.find("div", {"class": "job_description"})
        if job_description_div:
            return job_description_div.text.strip(), response.url
        return None, response.url
    @staticmethod
-    def add_params(scraper_input, page) -> Optional[str]:
+    def _add_params(scraper_input) -> dict[str, str | Any]:
        params = {
            "search": scraper_input.search_term,
            "location": scraper_input.location,
            "page": page,
            "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 = scraper_input.job_type
-                job_type_value = "full_time"
+            params["employment_type"] = job_type_map.get(job_type, job_type.value[0])
-            elif scraper_input.job_type.value == "parttime":
+        if scraper_input.easy_apply:
-                job_type_value = "part_time"
+            params["zipapply"] = 1
            else:
                job_type_value = scraper_input.job_type.value
        if job_type_value:
            params[
                "refine_by_employment"
            ] = f"employment_type:employment_type:{job_type_value}"
        if scraper_input.is_remote:
-            params["refine_by_location_type"] = "only_remote"
+            params["remote"] = 1
        if scraper_input.distance:
            params["radius"] = scraper_input.distance
        return {k: v for k, v in params.items() if v is not None}
-        return params
+    headers = {
-
+        "Host": "api.ziprecruiter.com",
-    @staticmethod
+        "accept": "*/*",
-    def get_interval(interval_str: str):
+        "x-zr-zva-override": "100000000;vid:ZT1huzm_EQlDTVEc",
-        """
+        "x-pushnotificationid": "0ff4983d38d7fc5b3370297f2bcffcf4b3321c418f5c22dd152a0264707602a0",
-         Maps the interval alias to its appropriate CompensationInterval.
+        "x-deviceid": "D77B3A92-E589-46A4-8A39-6EF6F1D86006",
-        :param interval_str
+        "user-agent": "Job Search/87.0 (iPhone; CPU iOS 16_6_1 like Mac OS X)",
-        :return: CompensationInterval
+        "authorization": "Basic YTBlZjMyZDYtN2I0Yy00MWVkLWEyODMtYTI1NDAzMzI0YTcyOg==",
-        """
+        "accept-language": "en-US,en;q=0.9",
        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: BeautifulSoup) -> 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: BeautifulSoup) -> 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: BeautifulSoup) -> 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 {
            "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.97 Safari/537.36"
    }
--- a/src/tests/test_all.py
+++ b/src/tests/test_all.py
@@ -1,10 +1,14 @@
 from ..jobspy import scrape_jobs
 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,
    )
-    assert result is not None and result.errors.empty is True
+
    assert (
        isinstance(result, pd.DataFrame) and not result.empty
    ), "Result should be a non-empty DataFrame"
--- a/src/tests/test_glassdoor.py
+++ b/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"
--- a/src/tests/test_indeed.py
+++ b/src/tests/test_indeed.py
@@ -1,9 +1,11 @@
 from ..jobspy import scrape_jobs
 import pandas as pd
 def test_indeed():
    result = scrape_jobs(
-        site_name="indeed",
+        site_name="indeed", search_term="software engineer", country_indeed="usa"
        search_term="software engineer",
    )
-    assert result is not None and result.errors.empty is True
+    assert (
        isinstance(result, pd.DataFrame) and not result.empty
    ), "Result should be a non-empty DataFrame"
--- a/src/tests/test_linkedin.py
+++ b/src/tests/test_linkedin.py
@@ -1,4 +1,5 @@
 from ..jobspy import scrape_jobs
 import pandas as pd
 def test_linkedin():
@@ -6,4 +7,6 @@ def test_linkedin():
        site_name="linkedin",
        search_term="software engineer",
    )
-    assert result is not None and result.errors.empty is True
+    assert (
        isinstance(result, pd.DataFrame) and not result.empty
    ), "Result should be a non-empty DataFrame"
--- a/src/tests/test_ziprecruiter.py
+++ b/src/tests/test_ziprecruiter.py
@@ -1,4 +1,5 @@
 from ..jobspy import scrape_jobs
 import pandas as pd
 def test_ziprecruiter():
@@ -7,4 +8,6 @@ def test_ziprecruiter():
        search_term="software engineer",
    )
-    assert result is not None and result.errors.empty is True
+    assert (
        isinstance(result, pd.DataFrame) and not result.empty
    ), "Result should be a non-empty DataFrame"
Author	SHA1	Message	Date
Cullen Watson	5cb7ffe5fd	enh: proxies (#157 ) * enh: proxies * enh: proxies	2024-05-25 14:04:09 -05:00
Cullen Watson	cd29f79796	docs: readme	2024-05-25 11:46:23 -05:00
Cullen Watson	65d2e5e707	Update pyproject.toml	2024-05-20 11:46:36 -05:00
fasih hussain	08d63a87a2	chore: id added for JobPost schema (#152 )	2024-05-20 11:45:52 -05:00
Cullen	1ffdb1756f	fix: dup line	2024-04-30 12:11:48 -05:00
Cullen Watson	1185693422	delete empty file	2024-04-30 12:06:20 -05:00
Lluís Salord Quetglas	dcd7144318	FIX: Allow Indeed search term with complex syntax (#139 )	2024-04-30 12:05:43 -05:00
Cullen Watson	bf73c061bd	enh: linkedin company logo (#141 )	2024-04-30 12:03:10 -05:00
Lluís Salord Quetglas	8dd08ed9fd	FEAT: Allow LinkedIn scraper to get external job apply url (#140 )	2024-04-30 11:36:01 -05:00
Cullen Watson	5d3df732e6	docs: readme	2024-03-12 20:46:25 -05:00
Kellen Mace	86f858e06d	Update scrape_jobs() parameters info in readme (#130 )	2024-03-12 20:45:13 -05:00
Cullen	1089d1f0a5	docs: readme	2024-03-11 21:30:57 -05:00
Cullen	3e93454738	fix(indeed): readd param	2024-03-11 21:23:20 -05:00
Cullen Watson	0d150d519f	docs: readme	2024-03-11 14:52:20 -05:00
Cullen Watson	cc3497f929	docs: readme	2024-03-11 14:45:17 -05:00
Cullen Watson	5986f75346	docs: readme	2024-03-11 14:41:12 -05:00
VitaminB16	4b7bdb9313	feat: Adjust log verbosity via verbose arg (#128 )	2024-03-11 14:38:44 -05:00
Cullen Watson	80213f28d2	chore: version	2024-03-11 09:43:12 -05:00
Cullen Watson	ada38532c3	fix: indeed empty location term	2024-03-11 09:42:43 -05:00
Cullen Watson	3b0017964c	fix: indeed empty search term	2024-03-11 09:21:11 -05:00
VitaminB16	94d8f555fd	format: Apply Black formatter to the codebase (#127 )	2024-03-10 23:36:27 -05:00
Cullen Watson	e8b4b376b8	docs: readme	2024-03-09 13:40:34 -06:00
Cullen Watson	54ac1bad16	docs: readme	2024-03-09 01:49:05 -06:00
Cullen Watson	0a669e9ba8	enh: indeed more fields (#126 )	2024-03-09 01:40:01 -06:00
gigaSec	a4f6851c32	Fix GlassDoor Country Vietnam(#122 )	2024-03-04 17:35:57 -06:00
troy-conte	db01bc6bbb	log search updates, fix glassdoor (#120 )	2024-03-04 16:39:38 -06:00
Cullen Watson	f8a4eccc6b	Remove pandas warning (#118 )	2024-02-29 21:30:56 -06:00
Cullen Watson	ba3a16b228	Description format (#107 )	2024-02-14 16:04:23 -06:00
Cullen Watson	aeb1a50d2c	fix job type search (#106 )	2024-02-12 11:02:48 -06:00
VitaminB16	91b137ef86	feat: Ability to query by time posted for linkedin, indeed, glassdoor, ziprecruiter (#103 )	2024-02-09 14:02:03 -06:00
Cullen Watson	2563c5ca08	enh: Indeed company url (#104 )	2024-02-09 12:05:10 -06:00
Cullen Watson	32282305c8	docs: readme	2024-02-08 18:13:19 -06:00
Cullen Watson	ccbea51f3c	docs: readme	2024-02-04 09:25:10 -06:00
Cullen Watson	6ec7c24f7f	enh(linkedin): search by company ids (#99 )	2024-02-04 09:21:45 -06:00
Cullen Watson	02caf1b38d	fix(zr): date posted (#98 )	2024-02-03 07:20:53 -06:00
Cullen Watson	8e2ab277da	fix(ziprecruiter): pagination (#97 ) * fix(ziprecruiter): pagination * chore: version	2024-02-02 20:48:28 -06:00
Cullen Watson	ce3bd84ee5	fix: indeed parse description bug (#96 ) * fix(indeed): full descr * chore: version	2024-02-02 18:21:55 -06:00
Cullen Watson	1ccf2290fe	docs: readme	2024-02-02 17:59:24 -06:00
Cullen Watson	ec2eefc58a	docs: readme	2024-02-02 17:58:15 -06:00
Cullen Watson	13c7694474	Easy apply (#95 ) * enh(glassdoor): easy apply filter * enh(ziprecruiter): easy apply * enh(indeed): use mobile headers * chore: version	2024-02-02 17:47:15 -06:00
Cullen Watson	bbe46fe3f4	enh(glassdoor): easy apply filter (#92 )	2024-02-01 19:42:24 -06:00
Cullen Watson	b97c73ffd6	fix: clean description (#88 )	2024-01-28 21:50:41 -06:00
Cullen Watson	5b3627b244	enh: full description param (#85 )	2024-01-22 20:22:32 -06:00
Cullen Watson	2ec3b04777	fix(ziprecruiter): init cookies (#82 )	2024-01-12 12:28:35 -06:00
Harish Vadaparty	89a5264391	add long scrape example (#81 )	2024-01-12 12:24:00 -06:00
Cullen Watson	a7ad616567	fix: linkedin no results (#80 )	2024-01-10 14:01:10 -06:00
cullenwatson	53bc33a43a	chore: version	2024-01-09 19:33:56 -06:00
Cullen Watson	22870438c7	linkedin fix delays (#79 )	2024-01-09 19:32:51 -06:00
Cullen Watson	aeb93b99f5	Update pyproject.toml	2024-01-03 12:04:50 -06:00
Cullen Watson	a5916edcdd	fix(glassdoor): add retry adapter (#77 )	2024-01-03 12:04:32 -06:00
Augusto Gunsch	33d442bf1e	Add czech to Indeed (#72 )	2023-12-02 02:42:54 -06:00
Zachary Hampton	6587e464fa	Update README.md	2023-11-30 11:49:31 -07:00
Vincent Yan	eed7fca300	Get full indeed description (#70 )	2023-11-27 15:00:36 -06:00
Faraz Khan	dfb8c18c51	include location with 3 parts (#69 )	2023-11-10 16:59:42 -06:00
Faraz Khan	81f70ff8a5	added salary data for linkedin (#68 )	2023-11-09 14:57:15 -06:00
Cullen Watson	cc9e7866b7	fix linkedin bug & add linkedin company url (#67 )	2023-11-08 15:51:07 -06:00
Zachary Hampton	a2c8fe046e	Update README.md	2023-11-06 22:13:19 -07:00
Cullen Watson	2b7fea40a5	[fix] glassdoor duplicates	2023-10-30 20:29:55 -05:00
Cullen Watson	d37f86e1b9	[fix] glassdoor location	2023-10-30 20:19:56 -05:00
Cullen Watson	0302ab14f5	glassdoor keywords	2023-10-30 20:07:31 -05:00
Cullen Watson	3f2b582445	add glassdoor (#66 )	2023-10-30 19:57:36 -05:00
Cullen Watson	93223b6a38	bug fix	2023-10-30 13:57:23 -05:00
Cullen Watson	e3fc222eb5	readd proxy support for zip (#64 )	2023-10-29 08:54:56 -05:00
Cullen	b303b3f841	chore: version	2023-10-28 16:58:32 -05:00
Cullen	1a0c75f323	chore: version	2023-10-28 16:54:04 -05:00
Cullen	e2f6885d61	chore: format	2023-10-28 16:52:05 -05:00
Cullen	8d65d1b652	[chore] version	2023-10-28 16:43:44 -05:00
Cullen	216d3fd39f	ziprecruiter: 5s delay	2023-10-28 16:41:32 -05:00
Cullen Watson	d3bfdc0a6e	ziprecruiter api (#63 )	2023-10-28 16:17:28 -05:00
Cullen Watson	ba5ed803ca	use ziprecuriter api (#62 )	2023-10-28 15:51:29 -05:00
Cullen Watson	ff1eb0f7b0	[docs] update readme	2023-10-18 14:32:21 -05:00
Cullen Watson	f2cc74b7f2	Fix Indeed exceptions on parsing description	2023-10-18 14:25:53 -05:00
Cullen Watson	5e71866630	[docs] link change	2023-10-18 11:18:03 -05:00
Zachary Hampton	4e67c6e5a3	Update README.md	2023-10-17 20:22:56 -07:00
Cullen Watson	caf655525a	docs: update readme	2023-10-10 11:54:14 -05:00
Cullen Watson	90fa4a4c4f	feat: utils.py	2023-10-10 11:29:29 -05:00
Cullen Watson	e5353e604d	Multiple job types for Indeed, urgent keywords column (#56 ) * enh(indeed): mult job types * feat(jobs): urgent kws * fix(indeed): use new session obj per request * fix: emails as comma separated in output * fix: put num urgent words in output * chore: readme	2023-10-10 11:23:04 -05:00
Cullen Watson	628f4dee9c	[fix] indeed - min & max values swapped (#54 )	2023-10-03 09:22:18 -05:00
Cullen Watson	2e59ab03e3	Merge branch 'main' of https://github.com/cullenwatson/JobSpy	2023-09-28 18:53:59 -05:00
Cullen Watson	008ca61e12	[fix] readd hyperlink param	2023-09-28 18:53:21 -05:00
Cullen Watson	8fc4c3bf90	[docs] readme	2023-09-28 18:35:40 -05:00
Cullen Watson	bff39a2625	[fix] util func	2023-09-28 18:33:14 -05:00
Cullen Watson	c676050dc0	[fix] util func	2023-09-28 18:33:02 -05:00
Cullen Watson	37976f7ec2	[chore] version number	2023-09-28 18:26:55 -05:00
Cullen Watson	9fb2fdd80f	[fix] add utils.py	2023-09-28 18:25:56 -05:00
Cullen Watson	af07c1ecbd	add offset param & email extraction (#51 ) * add offset param * [enh]: extract emails	2023-09-28 18:11:28 -05:00
Cullen Watson	286b9e1256	chore: version number	2023-09-21 20:28:57 -05:00
Cullen Watson	162dd40b0f	docs: add usejobspy.com	2023-09-21 20:27:04 -05:00