chore:readme

Bdjobs Fixed (#280 )
fix: glassdoor ua
2026-03-04 19:44:30 -08:00 · 2025-07-28 17:15:09 +02:00 · 2025-07-28 10:05:10 -05:00 · 2025-07-28 16:55:51 +02:00 · 2025-07-28 09:55:05 -05:00 · 2025-04-10 15:53:28 -05:00
44 changed files with 4769 additions and 2974 deletions
--- a/.github/workflows/publish-to-pypi.yml
+++ b/.github/workflows/publish-to-pypi.yml
@@ -1,9 +1,13 @@
-name: Publish Python 🐍 distributions 📦 to PyPI
-on: push
+name: Publish JobSpy to PyPi
+on:
+  push:
+    branches:
+      - main
+  workflow_dispatch:

 jobs:
  build-n-publish:
-    name: Build and publish Python 🐍 distributions 📦 to PyPI
+    name: Build and publish JobSpy to PyPi
    runs-on: ubuntu-latest

    steps:
@@ -27,7 +31,7 @@ jobs:
          build

      - name: Publish distribution 📦 to PyPI
-        if: startsWith(github.ref, 'refs/tags')
+        if: startsWith(github.ref, 'refs/tags') || github.event_name == 'workflow_dispatch'
        uses: pypa/gh-action-pypi-publish@release/v1
        with:
          password: ${{ secrets.PYPI_API_TOKEN }}
--- a/README.md
+++ b/README.md
@@ -1,20 +1,12 @@
 <img src="https://github.com/cullenwatson/JobSpy/assets/78247585/ae185b7e-e444-4712-8bb9-fa97f53e896b" width="400">

-**JobSpy** is a simple, yet comprehensive, job scraping library.
-
-**Not technical?** Try out the web scraping tool on our site at [usejobspy.com](https://usejobspy.com).
-
-*Looking to build a data-focused software product?* **[Book a call](https://bunsly.com/)** *to
-work with us.*
+**JobSpy** is a job scraping library with the goal of aggregating all the jobs from popular job boards with one tool.

 ## Features

- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, & **ZipRecruiter** simultaneously
- Aggregates the job postings in a Pandas DataFrame
- Proxy support
-
-[Video Guide for JobSpy](https://www.youtube.com/watch?v=RuP1HrAZnxs&pp=ygUgam9icyBzY3JhcGVyIGJvdCBsaW5rZWRpbiBpbmRlZWQ%3D) -
-Updated for release v1.1.3
+- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, **Google**, **ZipRecruiter**, & other job boards concurrently
+- Aggregates the job postings in a dataframe
+- Proxies support to bypass blocking

 ![jobspy](https://github.com/cullenwatson/JobSpy/assets/78247585/ec7ef355-05f6-4fd3-8161-a817e31c5c57)

@@ -33,93 +25,120 @@ import csv
 from jobspy import scrape_jobs

 jobs = scrape_jobs(
-    site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"],
+    site_name=["indeed", "linkedin", "zip_recruiter", "google"], # "glassdoor", "bayt", "naukri", "bdjobs"
    search_term="software engineer",
-    location="Dallas, TX",
+    google_search_term="software engineer jobs near San Francisco, CA since yesterday",
+    location="San Francisco, CA",
    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
+    hours_old=72,
+    country_indeed='USA',
+    
+    # linkedin_fetch_description=True # gets more info such as description, direct job url (slower)
+    # proxies=["208.195.175.46:65095", "208.195.175.45:65095", "localhost"],
 )
 print(f"Found {len(jobs)} jobs")
 print(jobs.head())
-jobs.to_csv("jobs.csv", quoting=csv.QUOTE_NONNUMERIC, escapechar="\\", index=False) # to_xlsx
+jobs.to_csv("jobs.csv", quoting=csv.QUOTE_NONNUMERIC, escapechar="\\", index=False) # to_excel
 ```

 ### Output

 ```
-SITE           TITLE                             COMPANY_NAME      CITY          STATE  JOB_TYPE  INTERVAL  MIN_AMOUNT  MAX_AMOUNT  JOB_URL                                            DESCRIPTION
+SITE           TITLE                             COMPANY           CITY          STATE  JOB_TYPE  INTERVAL  MIN_AMOUNT  MAX_AMOUNT  JOB_URL                                            DESCRIPTION
 indeed         Software Engineer                 AMERICAN SYSTEMS  Arlington     VA     None      yearly    200000      150000      https://www.indeed.com/viewjob?jk=5e409e577046...  THIS POSITION COMES WITH A 10K SIGNING BONUS!...
 indeed         Senior Software Engineer          TherapyNotes.com  Philadelphia  PA     fulltime  yearly    135000      110000      https://www.indeed.com/viewjob?jk=da39574a40cb...  About Us TherapyNotes is the national leader i...
 linkedin       Software Engineer - Early Career  Lockheed Martin   Sunnyvale     CA     fulltime  yearly    None        None        https://www.linkedin.com/jobs/view/3693012711      Description:By bringing together people that u...
 linkedin       Full-Stack Software Engineer      Rain              New York      NY     fulltime  yearly    None        None        https://www.linkedin.com/jobs/view/3696158877      Rain’s mission is to create the fastest and ea...
 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, glassdoor
-└── search_term (str)
 Optional
+├── site_name (list|str): 
+|    linkedin, zip_recruiter, indeed, glassdoor, google, bayt, bdjobs
+|    (default is all)
+│
+├── search_term (str)
+|
+├── google_search_term (str)
+|     search term for google jobs. This is the only param for filtering google jobs.
+│
 ├── location (str)
-├── distance (int): in miles, default 50
-├── job_type (enum): fulltime, parttime, internship, contract
-├── proxy (str): in format 'http://user:pass@host:port'
+│
+├── distance (int): 
+|    in miles, default 50
+│
+├── job_type (str): 
+|    fulltime, parttime, internship, contract
+│
+├── proxies (list): 
+|    in format ['user:pass@host:port', 'localhost']
+|    each job board scraper will round robin through the proxies
+|
 ├── is_remote (bool)
-├── linkedin_fetch_description (bool): fetches full description for LinkedIn (slower)
-├── results_wanted (int): number of job results to retrieve for each site specified in 'site_type'
-├── easy_apply (bool): filters for jobs that are hosted on the job board site (not supported on Indeed)
-├── linkedin_company_ids (list[int): searches for linkedin jobs with specific company ids
-├── description_format (enum): markdown, html (format type of the job descriptions)
-├── country_indeed (enum): filters the country on Indeed (see below for correct spelling)
-├── offset (num): starts the search from an offset (e.g. 25 will start the search from the 25th result)
-├── hours_old (int): filters jobs by the number of hours since the job was posted (ZipRecruiter and Glassdoor round up to next day. If you use this on Indeed, it will not filter by job_type or is_remote)
+│
+├── results_wanted (int): 
+|    number of job results to retrieve for each site specified in 'site_name'
+│
+├── easy_apply (bool): 
+|    filters for jobs that are hosted on the job board site (LinkedIn easy apply filter no longer works)
+|
+├── user_agent (str): 
+|    override the default user agent which may be outdated
+|
+│
+├── 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)
+|
+├── enforce_annual_salary (bool): 
+|    converts wages to annual salary
+|
+├── ca_cert (str)
+|    path to CA Certificate file for proxies
 ```

-### 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 (str): fulltime, parttime, internship, contract
-├── compensation (object)
-│   ├── 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)
+```
+├── 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
 ```

 ## Supported Countries for Job Searching

 ### **LinkedIn**

-LinkedIn searches globally & uses only the `location` parameter. You can only fetch 1000 jobs max from the LinkedIn endpoint we are using
+LinkedIn searches globally & uses only the `location` parameter. 

 ### **ZipRecruiter**

@@ -151,26 +170,92 @@ You can specify the following countries when searching on Indeed (use the exact
 | United Arab Emirates | UK*          | USA*       | Uruguay        |
 | Venezuela            | Vietnam*     |            |                |

+### **Bayt**
+
+Bayt only uses the search_term parameter currently and searches internationally
+
+

 ## Notes
 * Indeed is the best scraper currently with no rate limiting.  
-* Glassdoor/Ziprecruiter can only fetch 900/1000 jobs from the endpoints we are using on a given search.  
-* LinkedIn is the most restrictive and usually rate limits around the 10th page.
+* 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: Why is Indeed giving unrelated roles?**  
+**A:** Indeed searches the description too.

-**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/Bunsly/JobSpy/issues).
+- use - to remove words
+- "" for exact match
+
+Example of a good Indeed query
+
+```py
+search_term='"engineering intern" software summer (java OR python OR c++) 2025 -tax -marketing'
+```
+
+This searches the description/title and must include software, summer, 2025, one of the languages, engineering intern exactly, no tax, no marketing.
+
+---
+
+**Q: No results when using "google"?**  
+**A:** You have to use super specific syntax. Search for google jobs on your browser and then whatever pops up in the google jobs search box after applying some filters is what you need to copy & paste into the google_search_term. 

 ---

 **Q: Received a response code 429?**  
 **A:** This indicates that you have been blocked by the job board site for sending too many requests. All of the job board sites are aggressive with blocking. We recommend:

- Waiting some time between scrapes (site-dependent).
- Trying a VPN or proxy to change your IP address.
+- Wait some time between scrapes (site-dependent).
+- Try using the proxies param to change your IP address.

 ---
+
+### JobPost Schema
+
+```plaintext
+JobPost
+├── title
+├── company
+├── company_url
+├── job_url
+├── location
+│   ├── country
+│   ├── city
+│   ├── state
+├── is_remote
+├── description
+├── job_type: fulltime, parttime, internship, contract
+├── job_function
+│   ├── interval: yearly, monthly, weekly, daily, hourly
+│   ├── min_amount
+│   ├── max_amount
+│   ├── currency
+│   └── salary_source: direct_data, description (parsed from posting)
+├── date_posted
+└── emails
+
+Linkedin specific
+└── job_level
+
+Linkedin & Indeed specific
+└── company_industry
+
+Indeed specific
+├── company_country
+├── company_addresses
+├── company_employees_label
+├── company_revenue_label
+├── company_description
+└── company_logo
+
+Naukri specific
+├── skills
+├── experience_range
+├── company_rating
+├── company_reviews_count
+├── vacancy_count
+└── work_from_home_type
+```
--- a/examples/JobSpy_AllSites.py
+++ b/examples/JobSpy_AllSites.py
@@ -1,30 +0,0 @@
-from jobspy import scrape_jobs
-import pandas as pd
-
-jobs: pd.DataFrame = scrape_jobs(
-    site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"],
-    search_term="software engineer",
-    location="Dallas, TX",
-    results_wanted=25,  # be wary the higher it is, the more likey you'll get blocked (rotating proxy can help tho)
-    country_indeed="USA",
-    # proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
-)
-
-# formatting for pandas
-pd.set_option("display.max_columns", None)
-pd.set_option("display.max_rows", None)
-pd.set_option("display.width", None)
-pd.set_option("display.max_colwidth", 50)  # set to 0 to see full job url / desc
-
-# 1: output to console
-print(jobs)
-
-# 2: output to .csv
-jobs.to_csv("./jobs.csv", index=False)
-print("outputted to jobs.csv")
-
-# 3: output to .xlsx
-# jobs.to_xlsx('jobs.xlsx', index=False)
-
-# 4: display in Jupyter Notebook (1. pip install jupyter 2. jupyter notebook)
-# display(jobs)
--- a/examples/JobSpy_Demo.ipynb
+++ b/examples/JobSpy_Demo.ipynb
@@ -1,167 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "00a94b47-f47b-420f-ba7e-714ef219c006",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from jobspy import scrape_jobs\n",
-    "import pandas as pd\n",
-    "from IPython.display import display, HTML"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9f773e6c-d9fc-42cc-b0ef-63b739e78435",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "pd.set_option('display.max_columns', None)\n",
-    "pd.set_option('display.max_rows', None)\n",
-    "pd.set_option('display.width', None)\n",
-    "pd.set_option('display.max_colwidth', 50)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1253c1f8-9437-492e-9dd3-e7fe51099420",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# example 1 (no hyperlinks, USA)\n",
-    "jobs = scrape_jobs(\n",
-    "    site_name=[\"linkedin\"],\n",
-    "    location='san francisco',\n",
-    "    search_term=\"engineer\",\n",
-    "    results_wanted=5,\n",
-    "\n",
-    "    # use if you want to use a proxy\n",
-    "    # proxy=\"socks5://jobspy:5a4vpWtj4EeJ2hoYzk@us.smartproxy.com:10001\",\n",
-    "    proxy=\"http://jobspy:5a4vpWtj4EeJ2hoYzk@us.smartproxy.com:10001\",\n",
-    "    #proxy=\"https://jobspy:5a4vpWtj4EeJ2hoYzk@us.smartproxy.com:10001\",\n",
-    ")\n",
-    "display(jobs)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6a581b2d-f7da-4fac-868d-9efe143ee20a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# example 2 - remote USA & hyperlinks\n",
-    "jobs = scrape_jobs(\n",
-    "    site_name=[\"linkedin\", \"zip_recruiter\", \"indeed\"],\n",
-    "    # location='san francisco',\n",
-    "    search_term=\"software engineer\",\n",
-    "    country_indeed=\"USA\",\n",
-    "    hyperlinks=True,\n",
-    "    is_remote=True,\n",
-    "    results_wanted=5, \n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "fe8289bc-5b64-4202-9a64-7c117c83fd9a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# use if hyperlinks=True\n",
-    "html = jobs.to_html(escape=False)\n",
-    "# change max-width: 200px to show more or less of the content\n",
-    "truncate_width = f'<style>.dataframe td {{ max-width: 200px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }}</style>{html}'\n",
-    "display(HTML(truncate_width))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "951c2fe1-52ff-407d-8bb1-068049b36777",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# example 3 - with hyperlinks, international - linkedin (no zip_recruiter)\n",
-    "jobs = scrape_jobs(\n",
-    "    site_name=[\"linkedin\"],\n",
-    "    location='berlin',\n",
-    "    search_term=\"engineer\",\n",
-    "    hyperlinks=True,\n",
-    "    results_wanted=5,\n",
-    "    easy_apply=True\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1e37a521-caef-441c-8fc2-2eb5b2e7da62",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# use if hyperlinks=True\n",
-    "html = jobs.to_html(escape=False)\n",
-    "# change max-width: 200px to show more or less of the content\n",
-    "truncate_width = f'<style>.dataframe td {{ max-width: 200px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }}</style>{html}'\n",
-    "display(HTML(truncate_width))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "0650e608-0b58-4bf5-ae86-68348035b16a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# example 4 - international indeed (no zip_recruiter)\n",
-    "jobs = scrape_jobs(\n",
-    "    site_name=[\"indeed\"],\n",
-    "    search_term=\"engineer\",\n",
-    "    country_indeed = \"China\",\n",
-    "    hyperlinks=True\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "40913ac8-3f8a-4d7e-ac47-afb88316432b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# use if hyperlinks=True\n",
-    "html = jobs.to_html(escape=False)\n",
-    "# change max-width: 200px to show more or less of the content\n",
-    "truncate_width = f'<style>.dataframe td {{ max-width: 200px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }}</style>{html}'\n",
-    "display(HTML(truncate_width))"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.11.5"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
--- a/examples/JobSpy_LongScrape.py
+++ b/examples/JobSpy_LongScrape.py
@@ -1,77 +0,0 @@
-from jobspy import scrape_jobs
-import pandas as pd
-import os
-import time
-
-# creates csv a new filename if the jobs.csv already exists.
-csv_filename = "jobs.csv"
-counter = 1
-while os.path.exists(csv_filename):
-    csv_filename = f"jobs_{counter}.csv"
-    counter += 1
-
-# results wanted and offset
-results_wanted = 1000
-offset = 0
-
-all_jobs = []
-
-# max retries
-max_retries = 3
-
-# nuumber of results at each iteration
-results_in_each_iteration = 30
-
-while len(all_jobs) < results_wanted:
-    retry_count = 0
-    while retry_count < max_retries:
-        print("Doing from", offset, "to", offset + results_in_each_iteration, "jobs")
-        try:
-            jobs = scrape_jobs(
-                site_name=["indeed"],
-                search_term="software engineer",
-                # New York, NY
-                # Dallas, TX
-
-                # Los Angeles, CA
-                location="Los Angeles, CA",
-                results_wanted=min(results_in_each_iteration, results_wanted - len(all_jobs)),
-                country_indeed="USA",
-                offset=offset,
-                # proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
-            )
-
-            # Add the scraped jobs to the list
-            all_jobs.extend(jobs.to_dict('records'))
-
-            # Increment the offset for the next page of results
-            offset += results_in_each_iteration
-
-            # Add a delay to avoid rate limiting (you can adjust the delay time as needed)
-            print(f"Scraped {len(all_jobs)} jobs")
-            print("Sleeping secs", 100 * (retry_count + 1))
-            time.sleep(100 * (retry_count + 1))  # Sleep for 2 seconds between requests
-
-            break  # Break out of the retry loop if successful
-        except Exception as e:
-            print(f"Error: {e}")
-            retry_count += 1
-            print("Sleeping secs before retry", 100 * (retry_count + 1))
-            time.sleep(100 * (retry_count + 1))
-            if retry_count >= max_retries:
-                print("Max retries reached. Exiting.")
-                break
-
-# DataFrame from the collected job data
-jobs_df = pd.DataFrame(all_jobs)
-
-# Formatting
-pd.set_option("display.max_columns", None)
-pd.set_option("display.max_rows", None)
-pd.set_option("display.width", None)
-pd.set_option("display.max_colwidth", 50)
-
-print(jobs_df)
-
-jobs_df.to_csv(csv_filename, index=False)
-print(f"Outputted to {csv_filename}")
--- a/src/jobspy/init.py
+++ b/src/jobspy/init.py
@@ -1,27 +1,37 @@
 from __future__ import annotations

-import pandas as pd
-from typing import Tuple
 from concurrent.futures import ThreadPoolExecutor, as_completed
+from typing import Tuple

-from .jobs import JobType, Location
-from .scrapers.utils import logger
-from .scrapers.indeed import IndeedScraper
-from .scrapers.ziprecruiter import ZipRecruiterScraper
-from .scrapers.glassdoor import GlassdoorScraper
-from .scrapers.linkedin import LinkedInScraper
-from .scrapers import ScraperInput, Site, JobResponse, Country
-from .scrapers.exceptions import (
-    LinkedInException,
-    IndeedException,
-    ZipRecruiterException,
-    GlassdoorException,
+import pandas as pd
+
+from jobspy.bayt import BaytScraper
+from jobspy.bdjobs import BDJobs
+from jobspy.glassdoor import Glassdoor
+from jobspy.google import Google
+from jobspy.indeed import Indeed
+from jobspy.linkedin import LinkedIn
+from jobspy.naukri import Naukri
+from jobspy.model import JobType, Location, JobResponse, Country
+from jobspy.model import SalarySource, ScraperInput, Site
+from jobspy.util import (
+    set_logger_level,
+    extract_salary,
+    create_logger,
+    get_enum_from_value,
+    map_str_to_site,
+    convert_to_annual,
+    desired_order,
 )
+from jobspy.ziprecruiter import ZipRecruiter


+# Update the SCRAPER_MAPPING dictionary in the scrape_jobs function
+
 def scrape_jobs(
    site_name: str | list[str] | Site | list[Site] | None = None,
    search_term: str | None = None,
+    google_search_term: str | None = None,
    location: str | None = None,
    distance: int | None = 50,
    is_remote: bool = False,
@@ -29,35 +39,33 @@ def scrape_jobs(
    easy_apply: bool | None = None,
    results_wanted: int = 15,
    country_indeed: str = "usa",
-    hyperlinks: bool = False,
-    proxy: str | None = None,
+    proxies: list[str] | str | None = None,
+    ca_cert: 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,
+    enforce_annual_salary: bool = False,
+    verbose: int = 0,
+    user_agent: str = None,
    **kwargs,
 ) -> pd.DataFrame:
    """
-    Simultaneously scrapes job data from multiple job sites.
-    :return: results_wanted: pandas dataframe containing job data
+    Scrapes job data from job boards concurrently
+    :return: Pandas DataFrame containing job data
    """
    SCRAPER_MAPPING = {
-        Site.LINKEDIN: LinkedInScraper,
-        Site.INDEED: IndeedScraper,
-        Site.ZIP_RECRUITER: ZipRecruiterScraper,
-        Site.GLASSDOOR: GlassdoorScraper,
+        Site.LINKEDIN: LinkedIn,
+        Site.INDEED: Indeed,
+        Site.ZIP_RECRUITER: ZipRecruiter,
+        Site.GLASSDOOR: Glassdoor,
+        Site.GOOGLE: Google,
+        Site.BAYT: BaytScraper,
+        Site.NAUKRI: Naukri,
+        Site.BDJOBS: BDJobs,  # Add BDJobs to the scraper mapping
    }
-
-    def map_str_to_site(site_name: str) -> Site:
-        return Site[site_name.upper()]
-
-    def get_enum_from_value(value_str):
-        for job_type in JobType:
-            if value_str in job_type.value:
-                return job_type
-        raise Exception(f"Invalid job type: {value_str}")
-
+    set_logger_level(verbose)
    job_type = get_enum_from_value(job_type) if job_type else None

    def get_site_type():
@@ -79,6 +87,7 @@ def scrape_jobs(
        site_type=get_site_type(),
        country=country_enum,
        search_term=search_term,
+        google_search_term=google_search_term,
        location=location,
        distance=distance,
        is_remote=is_remote,
@@ -94,11 +103,11 @@ def scrape_jobs(

    def scrape_site(site: Site) -> Tuple[str, JobResponse]:
        scraper_class = SCRAPER_MAPPING[site]
-        scraper = scraper_class(proxy=proxy)
+        scraper = scraper_class(proxies=proxies, ca_cert=ca_cert, user_agent=user_agent)
        scraped_data: JobResponse = scraper.scrape(scraper_input)
        cap_name = site.value.capitalize()
        site_name = "ZipRecruiter" if cap_name == "Zip_recruiter" else cap_name
-        logger.info(f"{site_name} finished scraping")
+        create_logger(site_name).info(f"finished scraping")
        return site.value, scraped_data

    site_to_jobs_dict = {}
@@ -122,7 +131,6 @@ def scrape_jobs(
        for job in job_response.jobs:
            job_data = job.dict()
            job_url = job_data["job_url"]
-            job_data["job_url_hyper"] = f'<a href="{job_url}">{job_url}</a>'
            job_data["site"] = site
            job_data["company"] = job_data["company_name"]
            job_data["job_type"] = (
@@ -138,6 +146,7 @@ def scrape_jobs(
                    **job_data["location"]
                ).display_location()

+            # Handle compensation
            compensation_obj = job_data.get("compensation")
            if compensation_obj and isinstance(compensation_obj, dict):
                job_data["interval"] = (
@@ -148,11 +157,42 @@ def scrape_jobs(
                job_data["min_amount"] = compensation_obj.get("min_amount")
                job_data["max_amount"] = compensation_obj.get("max_amount")
                job_data["currency"] = compensation_obj.get("currency", "USD")
+                job_data["salary_source"] = SalarySource.DIRECT_DATA.value
+                if enforce_annual_salary and (
+                    job_data["interval"]
+                    and job_data["interval"] != "yearly"
+                    and job_data["min_amount"]
+                    and job_data["max_amount"]
+                ):
+                    convert_to_annual(job_data)
            else:
-                job_data["interval"] = None
-                job_data["min_amount"] = None
-                job_data["max_amount"] = None
-                job_data["currency"] = None
+                if country_enum == Country.USA:
+                    (
+                        job_data["interval"],
+                        job_data["min_amount"],
+                        job_data["max_amount"],
+                        job_data["currency"],
+                    ) = extract_salary(
+                        job_data["description"],
+                        enforce_annual_salary=enforce_annual_salary,
+                    )
+                    job_data["salary_source"] = SalarySource.DESCRIPTION.value
+
+            job_data["salary_source"] = (
+                job_data["salary_source"]
+                if "min_amount" in job_data and job_data["min_amount"]
+                else None
+            )
+
+            #naukri-specific fields
+            job_data["skills"] = (
+                ", ".join(job_data["skills"]) if job_data["skills"] else None
+            )
+            job_data["experience_range"] = job_data.get("experience_range")
+            job_data["company_rating"] = job_data.get("company_rating")
+            job_data["company_reviews_count"] = job_data.get("company_reviews_count")
+            job_data["vacancy_count"] = job_data.get("vacancy_count")
+            job_data["work_from_home_type"] = job_data.get("work_from_home_type")

            job_df = pd.DataFrame([job_data])
            jobs_dfs.append(job_df)
@@ -164,36 +204,6 @@ def scrape_jobs(
        # Step 2: Concatenate the filtered DataFrames
        jobs_df = pd.concat(filtered_dfs, ignore_index=True)

-        # Desired column order
-        desired_order = [
-            "site",
-            "job_url_hyper" if hyperlinks else "job_url",
-            "job_url_direct",
-            "title",
-            "company",
-            "location",
-            "job_type",
-            "date_posted",
-            "interval",
-            "min_amount",
-            "max_amount",
-            "currency",
-            "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",
-        ]
-
        # 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:
@@ -203,6 +213,14 @@ def scrape_jobs(
        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])
+        return jobs_df.sort_values(
+            by=["site", "date_posted"], ascending=[True, False]
+        ).reset_index(drop=True)
    else:
        return pd.DataFrame()
+
+
+# Add BDJobs to __all__
+__all__ = [
+    "BDJobs",
+]
--- a/jobspy/bayt/init.py
+++ b/jobspy/bayt/init.py
@@ -0,0 +1,145 @@
+from __future__ import annotations
+
+import random
+import time
+
+from bs4 import BeautifulSoup
+
+from jobspy.model import (
+    Scraper,
+    ScraperInput,
+    Site,
+    JobPost,
+    JobResponse,
+    Location,
+    Country,
+)
+from jobspy.util import create_logger, create_session
+
+log = create_logger("Bayt")
+
+
+class BaytScraper(Scraper):
+    base_url = "https://www.bayt.com"
+    delay = 2
+    band_delay = 3
+
+    def __init__(
+        self, proxies: list[str] | str | None = None, ca_cert: str | None = None, user_agent: str | None = None
+    ):
+        super().__init__(Site.BAYT, proxies=proxies, ca_cert=ca_cert)
+        self.scraper_input = None
+        self.session = None
+        self.country = "worldwide"
+
+    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
+        self.scraper_input = scraper_input
+        self.session = create_session(
+            proxies=self.proxies, ca_cert=self.ca_cert, is_tls=False, has_retry=True
+        )
+        job_list: list[JobPost] = []
+        page = 1
+        results_wanted = (
+            scraper_input.results_wanted if scraper_input.results_wanted else 10
+        )
+
+        while len(job_list) < results_wanted:
+            log.info(f"Fetching Bayt jobs page {page}")
+            job_elements = self._fetch_jobs(self.scraper_input.search_term, page)
+            if not job_elements:
+                break
+
+            if job_elements:
+                log.debug(
+                    "First job element snippet:\n" + job_elements[0].prettify()[:500]
+                )
+
+            initial_count = len(job_list)
+            for job in job_elements:
+                try:
+                    job_post = self._extract_job_info(job)
+                    if job_post:
+                        job_list.append(job_post)
+                        if len(job_list) >= results_wanted:
+                            break
+                    else:
+                        log.debug(
+                            "Extraction returned None. Job snippet:\n"
+                            + job.prettify()[:500]
+                        )
+                except Exception as e:
+                    log.error(f"Bayt: Error extracting job info: {str(e)}")
+                    continue
+
+            if len(job_list) == initial_count:
+                log.info(f"No new jobs found on page {page}. Ending pagination.")
+                break
+
+            page += 1
+            time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
+
+        job_list = job_list[: scraper_input.results_wanted]
+        return JobResponse(jobs=job_list)
+
+    def _fetch_jobs(self, query: str, page: int) -> list | None:
+        """
+        Grabs the job results for the given query and page number.
+        """
+        try:
+            url = f"{self.base_url}/en/international/jobs/{query}-jobs/?page={page}"
+            response = self.session.get(url)
+            response.raise_for_status()
+            soup = BeautifulSoup(response.text, "html.parser")
+            job_listings = soup.find_all("li", attrs={"data-js-job": ""})
+            log.debug(f"Found {len(job_listings)} job listing elements")
+            return job_listings
+        except Exception as e:
+            log.error(f"Bayt: Error fetching jobs - {str(e)}")
+            return None
+
+    def _extract_job_info(self, job: BeautifulSoup) -> JobPost | None:
+        """
+        Extracts the job information from a single job listing.
+        """
+        # Find the h2 element holding the title and link (no class filtering)
+        job_general_information = job.find("h2")
+        if not job_general_information:
+            return
+
+        job_title = job_general_information.get_text(strip=True)
+        job_url = self._extract_job_url(job_general_information)
+        if not job_url:
+            return
+
+        # Extract company name using the original approach:
+        company_tag = job.find("div", class_="t-nowrap p10l")
+        company_name = (
+            company_tag.find("span").get_text(strip=True)
+            if company_tag and company_tag.find("span")
+            else None
+        )
+
+        # Extract location using the original approach:
+        location_tag = job.find("div", class_="t-mute t-small")
+        location = location_tag.get_text(strip=True) if location_tag else None
+
+        job_id = f"bayt-{abs(hash(job_url))}"
+        location_obj = Location(
+            city=location,
+            country=Country.from_string(self.country),
+        )
+        return JobPost(
+            id=job_id,
+            title=job_title,
+            company_name=company_name,
+            location=location_obj,
+            job_url=job_url,
+        )
+
+    def _extract_job_url(self, job_general_information: BeautifulSoup) -> str | None:
+        """
+        Pulls the job URL from the 'a' within the h2 element.
+        """
+        a_tag = job_general_information.find("a")
+        if a_tag and a_tag.has_attr("href"):
+            return self.base_url + a_tag["href"].strip()
--- a/jobspy/bdjobs/init.py
+++ b/jobspy/bdjobs/init.py
@@ -0,0 +1,353 @@
+# __init__.py
+from __future__ import annotations
+
+import random
+import time
+from datetime import datetime
+from typing import Optional, List, Dict, Any
+from urllib.parse import urljoin
+
+from bs4 import BeautifulSoup
+from bs4.element import Tag
+
+from jobspy.exception import BDJobsException
+from jobspy.bdjobs.constant import headers, search_params
+from jobspy.bdjobs.util import (
+    parse_location,
+    parse_date,
+    find_job_listings,
+    is_job_remote,
+)
+from jobspy.model import (
+    JobPost,
+    Location,
+    JobResponse,
+    Country,
+    Scraper,
+    ScraperInput,
+    Site,
+    DescriptionFormat,
+)
+from jobspy.util import (
+    extract_emails_from_text,
+    create_session,
+    create_logger,
+    remove_attributes,
+    markdown_converter,
+)
+
+log = create_logger("BDJobs")
+
+
+class BDJobs(Scraper):
+    base_url = "https://jobs.bdjobs.com"
+    search_url = "https://jobs.bdjobs.com/jobsearch.asp"
+    delay = 2
+    band_delay = 3
+
+    def __init__(
+        self, proxies: list[str] | str | None = None, ca_cert: str | None = None
+    ):
+        """
+        Initializes BDJobsScraper with the BDJobs job search url
+        """
+        super().__init__(Site.BDJOBS, proxies=proxies, ca_cert=ca_cert)
+        self.session = create_session(
+            proxies=self.proxies,
+            ca_cert=ca_cert,
+            is_tls=False,
+            has_retry=True,
+            delay=5,
+            clear_cookies=True,
+        )
+        self.session.headers.update(headers)
+        self.scraper_input = None
+        self.country = "bangladesh"
+
+    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
+        """
+        Scrapes BDJobs for jobs with scraper_input criteria
+        :param scraper_input:
+        :return: job_response
+        """
+        self.scraper_input = scraper_input
+        job_list: list[JobPost] = []
+        seen_ids = set()
+        page = 1
+        request_count = 0
+
+        # Set up search parameters
+        params = search_params.copy()
+        params["txtsearch"] = scraper_input.search_term
+
+        continue_search = lambda: len(job_list) < scraper_input.results_wanted
+
+        while continue_search():
+            request_count += 1
+            log.info(f"search page: {request_count}")
+
+            try:
+                # Add page parameter if needed
+                if page > 1:
+                    params["pg"] = page
+
+                response = self.session.get(
+                    self.search_url,
+                    params=params,
+                    timeout=getattr(scraper_input, "request_timeout", 60),
+                )
+
+                if response.status_code != 200:
+                    log.error(f"BDJobs response status code {response.status_code}")
+                    break
+
+                soup = BeautifulSoup(response.text, "html.parser")
+                job_cards = find_job_listings(soup)
+
+                if not job_cards or len(job_cards) == 0:
+                    log.info("No more job listings found")
+                    break
+
+                log.info(f"Found {len(job_cards)} job cards on page {page}")
+
+                for job_card in job_cards:
+                    try:
+                        job_post = self._process_job(job_card)
+                        if job_post and job_post.id not in seen_ids:
+                            seen_ids.add(job_post.id)
+                            job_list.append(job_post)
+
+                            if not continue_search():
+                                break
+                    except Exception as e:
+                        log.error(f"Error processing job card: {str(e)}")
+
+                page += 1
+                # Add delay between requests
+                time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
+
+            except Exception as e:
+                log.error(f"Error during scraping: {str(e)}")
+                break
+
+        job_list = job_list[: scraper_input.results_wanted]
+        return JobResponse(jobs=job_list)
+
+    def _process_job(self, job_card: Tag) -> Optional[JobPost]:
+        """
+        Processes a job card element into a JobPost object
+        :param job_card: Job card element
+        :return: JobPost object
+        """
+        try:
+            # Extract job ID and URL
+            job_link = job_card.find("a", href=lambda h: h and "jobdetail" in h.lower())
+            if not job_link:
+                return None
+
+            job_url = job_link.get("href")
+            if not job_url.startswith("http"):
+                job_url = urljoin(self.base_url, job_url)
+
+            # Extract job ID from URL
+            job_id = (
+                job_url.split("jobid=")[-1].split("&")[0]
+                if "jobid=" in job_url
+                else f"bdjobs-{hash(job_url)}"
+            )
+
+            # Extract title
+            title = job_link.get_text(strip=True)
+            if not title:
+                title_elem = job_card.find(
+                    ["h2", "h3", "h4", "strong", "div"],
+                    class_=lambda c: c and "job-title-text" in c,
+                )
+                title = title_elem.get_text(strip=True) if title_elem else "N/A"
+
+            # Extract company name - IMPROVED
+            company_elem = job_card.find(
+                ["span", "div"],
+                class_=lambda c: c and "comp-name-text" in (c or "").lower(),
+            )
+            if company_elem:
+                company_name = company_elem.get_text(strip=True)
+            else:
+                # Try alternative selectors
+                company_elem = job_card.find(
+                    ["span", "div"],
+                    class_=lambda c: c
+                    and any(
+                        term in (c or "").lower()
+                        for term in ["company", "org", "comp-name"]
+                    ),
+                )
+                company_name = (
+                    company_elem.get_text(strip=True) if company_elem else "N/A"
+                )
+
+            # Extract location
+            location_elem = job_card.find(
+                ["span", "div"],
+                class_=lambda c: c and "locon-text-d" in (c or "").lower(),
+            )
+            if not location_elem:
+                location_elem = job_card.find(
+                    ["span", "div"],
+                    class_=lambda c: c
+                    and any(
+                        term in (c or "").lower()
+                        for term in ["location", "area", "locon"]
+                    ),
+                )
+            location_text = (
+                location_elem.get_text(strip=True)
+                if location_elem
+                else "Dhaka, Bangladesh"
+            )
+
+            # Create Location object
+            location = parse_location(location_text, self.country)
+
+            # Extract date posted
+            date_elem = job_card.find(
+                ["span", "div"],
+                class_=lambda c: c
+                and any(
+                    term in (c or "").lower()
+                    for term in ["date", "deadline", "published"]
+                ),
+            )
+            date_posted = None
+            if date_elem:
+                date_text = date_elem.get_text(strip=True)
+                date_posted = parse_date(date_text)
+
+            # Check if job is remote
+            is_remote = is_job_remote(title, location=location)
+
+            # Create job post object
+            job_post = JobPost(
+                id=job_id,
+                title=title,
+                company_name=company_name,  # Use company_name instead of company
+                location=location,
+                date_posted=date_posted,
+                job_url=job_url,
+                is_remote=is_remote,
+                site=self.site,
+            )
+
+            # Always fetch description for BDJobs
+            job_details = self._get_job_details(job_url)
+            job_post.description = job_details.get("description", "")
+            job_post.job_type = job_details.get("job_type", "")
+
+            return job_post
+        except Exception as e:
+            log.error(f"Error in _process_job: {str(e)}")
+            return None
+
+    def _get_job_details(self, job_url: str) -> Dict[str, Any]:
+        """
+        Gets detailed job information from the job page
+        :param job_url: Job page URL
+        :return: Dictionary with job details
+        """
+        try:
+            response = self.session.get(job_url, timeout=60)
+            if response.status_code != 200:
+                return {}
+
+            soup = BeautifulSoup(response.text, "html.parser")
+
+            # Find job description - IMPROVED based on correct.py
+            description = ""
+
+            # Try to find the job content div first (as in correct.py)
+            job_content_div = soup.find("div", class_="jobcontent")
+            if job_content_div:
+                # Look for responsibilities section
+                responsibilities_heading = job_content_div.find(
+                    "h4", id="job_resp"
+                ) or job_content_div.find(
+                    ["h4", "h5"], string=lambda s: s and "responsibilities" in s.lower()
+                )
+                if responsibilities_heading:
+                    responsibilities_elements = []
+                    # Find all following elements until the next heading or hr
+                    for sibling in responsibilities_heading.find_next_siblings():
+                        if sibling.name in ["hr", "h4", "h5"]:
+                            break
+                        if sibling.name == "ul":
+                            responsibilities_elements.extend(
+                                li.get_text(separator=" ", strip=True)
+                                for li in sibling.find_all("li")
+                            )
+                        elif sibling.name == "p":
+                            responsibilities_elements.append(
+                                sibling.get_text(separator=" ", strip=True)
+                            )
+
+                description = (
+                    "\n".join(responsibilities_elements)
+                    if responsibilities_elements
+                    else ""
+                )
+
+            # If no description found yet, try the original approach
+            if not description:
+                description_elem = soup.find(
+                    ["div", "section"],
+                    class_=lambda c: c
+                    and any(
+                        term in (c or "").lower()
+                        for term in ["job-description", "details", "requirements"]
+                    ),
+                )
+                if description_elem:
+                    description_elem = remove_attributes(description_elem)
+                    description = description_elem.prettify(formatter="html")
+                    if (
+                        hasattr(self.scraper_input, "description_format")
+                        and self.scraper_input.description_format
+                        == DescriptionFormat.MARKDOWN
+                    ):
+                        description = markdown_converter(description)
+
+            # Extract job type
+            job_type_elem = soup.find(
+                ["span", "div"],
+                string=lambda s: s
+                and any(
+                    term in (s or "").lower()
+                    for term in ["job type", "employment type"]
+                ),
+            )
+            job_type = None
+            if job_type_elem:
+                job_type_text = job_type_elem.find_next(["span", "div"]).get_text(
+                    strip=True
+                )
+                job_type = job_type_text if job_type_text else None
+
+            # Extract company industry
+            industry_elem = soup.find(
+                ["span", "div"], string=lambda s: s and "industry" in (s or "").lower()
+            )
+            company_industry = None
+            if industry_elem:
+                industry_text = industry_elem.find_next(["span", "div"]).get_text(
+                    strip=True
+                )
+                company_industry = industry_text if industry_text else None
+
+            return {
+                "description": description,
+                "job_type": job_type,
+                "company_industry": company_industry,
+            }
+
+        except Exception as e:
+            log.error(f"Error getting job details: {str(e)}")
+            return {}
--- a/jobspy/bdjobs/constant.py
+++ b/jobspy/bdjobs/constant.py
@@ -0,0 +1,32 @@
+#constant.py
+# Headers for BDJobs requests
+headers = {
+    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/122.0.0.0 Safari/537.36",
+    "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8",
+    "Accept-Language": "en-US,en;q=0.5",
+    "Connection": "keep-alive",
+    "Referer": "https://jobs.bdjobs.com/",
+    "Cache-Control": "max-age=0",
+}
+
+# Search parameters that work best for BDJobs
+search_params = {
+    "hidJobSearch": "jobsearch",
+}
+
+# Selectors for job listings
+job_selectors = [
+    "div.job-item",  # Catches both normal and premium job cards, as well as other types
+    "div.sout-jobs-wrapper", # Catches job listings in the main search results page
+    "div.norm-jobs-wrapper", # Catches normal job listings
+    "div.featured-wrap",     # Catches featured job listings
+]
+
+# Date formats used by BDJobs
+date_formats = [
+    "%d %b %Y",
+    "%d-%b-%Y",
+    "%d %B %Y",
+    "%B %d, %Y",
+    "%d/%m/%Y",
+]
--- a/jobspy/bdjobs/util.py
+++ b/jobspy/bdjobs/util.py
@@ -0,0 +1,100 @@
+#util.py
+from bs4 import BeautifulSoup
+from datetime import datetime
+from typing import Optional, List, Dict, Any
+
+from jobspy.model import Location, Country
+
+
+def parse_location(location_text: str, country: str = "bangladesh") -> Location:
+    """
+    Parses location text into a Location object
+    :param location_text: Location text from job listing
+    :param country: Default country
+    :return: Location object
+    """
+    parts = location_text.split(",")
+    if len(parts) >= 2:
+        city = parts[0].strip()
+        state = parts[1].strip()
+        return Location(
+            city=city,
+            state=state,
+            country=Country.from_string(country)
+        )
+    else:
+        return Location(
+            city=location_text.strip(),
+            country=Country.from_string(country)
+        )
+
+
+def parse_date(date_text: str) -> Optional[datetime]:
+    """
+    Parses date text into a datetime object
+    :param date_text: Date text from job listing
+    :return: datetime object or None if parsing fails
+    """
+    from .constant import date_formats
+    
+    try:
+        # Clean up date text
+        if "Deadline:" in date_text:
+            date_text = date_text.replace("Deadline:", "").strip()
+        
+        # Try different date formats
+        for fmt in date_formats:
+            try:
+                return datetime.strptime(date_text, fmt)
+            except ValueError:
+                continue
+        
+        return None
+    except Exception:
+        return None
+
+
+def find_job_listings(soup: BeautifulSoup) -> List[Any]:
+    """
+    Finds job listing elements in the HTML
+    :param soup: BeautifulSoup object
+    :return: List of job card elements
+    """
+    from .constant import job_selectors
+    
+    # Try different selectors
+    for selector in job_selectors:
+        if "." in selector:
+            tag_name, class_name = selector.split(".", 1)
+            elements = soup.find_all(tag_name, class_=class_name)
+            if elements and len(elements) > 0:
+                return elements
+    
+    # If no selectors match, look for job detail links
+    job_links = soup.find_all("a", href=lambda h: h and "jobdetail" in h.lower())
+    if job_links:
+        # Return parent elements of job links
+        return [link.parent for link in job_links]
+    
+    return []
+
+
+def is_job_remote(title: str, description: str = None, location: Location = None) -> bool:
+    """
+    Determines if a job is remote based on title, description, and location
+    :param title: Job title
+    :param description: Job description
+    :param location: Job location
+    :return: True if job is remote, False otherwise
+    """
+    remote_keywords = ["remote", "work from home", "wfh", "home based"]
+    
+    # Combine all text fields
+    full_text = title.lower()
+    if description:
+        full_text += " " + description.lower()
+    if location:
+        full_text += " " + location.display_location().lower()
+    
+    # Check for remote keywords
+    return any(keyword in full_text for keyword in remote_keywords)
--- a/src/jobspy/scrapers/exceptions.py
+++ b/src/jobspy/scrapers/exceptions.py
@@ -1,5 +1,5 @@
 """
-jobspy.scrapers.exceptions
+jobspy.jobboard.exceptions
 ~~~~~~~~~~~~~~~~~~~

 This module contains the set of Scrapers' exceptions.
@@ -24,3 +24,22 @@ class ZipRecruiterException(Exception):
 class GlassdoorException(Exception):
    def __init__(self, message=None):
        super().__init__(message or "An error occurred with Glassdoor")
+
+
+class GoogleJobsException(Exception):
+    def __init__(self, message=None):
+        super().__init__(message or "An error occurred with Google Jobs")
+
+
+class BaytException(Exception):
+    def __init__(self, message=None):
+        super().__init__(message or "An error occurred with Bayt")
+
+class NaukriException(Exception):
+    def __init__(self,message=None):
+        super().__init__(message or "An error occurred with Naukri")
+
+
+class BDJobsException(Exception):
+    def __init__(self, message=None):
+        super().__init__(message or "An error occurred with BDJobs")
--- a/jobspy/glassdoor/init.py
+++ b/jobspy/glassdoor/init.py
@@ -0,0 +1,322 @@
+from __future__ import annotations
+
+import re
+import json
+import requests
+from typing import Tuple
+from datetime import datetime, timedelta
+from concurrent.futures import ThreadPoolExecutor, as_completed
+
+from jobspy.glassdoor.constant import fallback_token, query_template, headers
+from jobspy.glassdoor.util import (
+    get_cursor_for_page,
+    parse_compensation,
+    parse_location,
+)
+from jobspy.util import (
+    extract_emails_from_text,
+    create_logger,
+    create_session,
+    markdown_converter,
+)
+from jobspy.exception import GlassdoorException
+from jobspy.model import (
+    JobPost,
+    JobResponse,
+    DescriptionFormat,
+    Scraper,
+    ScraperInput,
+    Site,
+)
+
+log = create_logger("Glassdoor")
+
+
+class Glassdoor(Scraper):
+    def __init__(
+        self, proxies: list[str] | str | None = None, ca_cert: str | None = None, user_agent: str | None = None
+    ):
+        """
+        Initializes GlassdoorScraper with the Glassdoor job search url
+        """
+        site = Site(Site.GLASSDOOR)
+        super().__init__(site, proxies=proxies, ca_cert=ca_cert, user_agent=user_agent)
+
+        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, ca_cert=self.ca_cert, has_retry=True
+        )
+        token = self._get_csrf_token()
+        headers["gd-csrf-token"] = token if token else fallback_token
+        if self.user_agent:
+            headers["user-agent"] = self.user_agent
+        self.session.headers.update(headers)
+
+        location_id, location_type = self._get_location(
+            scraper_input.location, scraper_input.is_remote
+        )
+        if location_type is None:
+            log.error("Glassdoor: location not parsed")
+            return JobResponse(jobs=[])
+        job_list: list[JobPost] = []
+        cursor = None
+
+        range_start = 1 + (scraper_input.offset // self.jobs_per_page)
+        tot_pages = (scraper_input.results_wanted // self.jobs_per_page) + 2
+        range_end = min(tot_pages, self.max_pages + 1)
+        for page in range(range_start, range_end):
+            log.info(f"search page: {page} / {range_end - 1}")
+            try:
+                jobs, cursor = self._fetch_jobs_page(
+                    scraper_input, location_id, location_type, page, cursor
+                )
+                job_list.extend(jobs)
+                if not jobs or len(job_list) >= scraper_input.results_wanted:
+                    job_list = job_list[: scraper_input.results_wanted]
+                    break
+            except Exception as e:
+                log.error(f"Glassdoor: {str(e)}")
+                break
+        return JobResponse(jobs=job_list)
+
+    def _fetch_jobs_page(
+        self,
+        scraper_input: ScraperInput,
+        location_id: int,
+        location_type: str,
+        page_num: int,
+        cursor: str | None,
+    ) -> Tuple[list[JobPost], str | None]:
+        """
+        Scrapes a page of Glassdoor for jobs with scraper_input criteria
+        """
+        jobs = []
+        self.scraper_input = scraper_input
+        try:
+            payload = self._add_payload(location_id, location_type, page_num, cursor)
+            response = self.session.post(
+                f"{self.base_url}/graph",
+                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:
+            log.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, 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")
+        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 = parse_location(location_name)
+
+        compensation = parse_compensation(job["header"])
+        try:
+            description = self._fetch_job_description(job_id)
+        except:
+            description = None
+        company_url = f"{self.base_url}Overview/W-EI_IE{company_id}.htm"
+        company_logo = (
+            job_data["jobview"].get("overview", {}).get("squareLogoUrl", None)
+        )
+        listing_type = (
+            job_data["jobview"]
+            .get("header", {})
+            .get("adOrderSponsorshipLevel", "")
+            .lower()
+        )
+        return JobPost(
+            id=f"gd-{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,
+            company_logo=company_logo,
+            listing_type=listing_type,
+        )
+
+    def _fetch_job_description(self, job_id):
+        """
+        Fetches the job description for a single job ID.
+        """
+        url = f"{self.base_url}/graph"
+        body = [
+            {
+                "operationName": "JobDetailQuery",
+                "variables": {
+                    "jl": job_id,
+                    "queryString": "q",
+                    "pageTypeEnum": "SERP",
+                },
+                "query": """
+                query JobDetailQuery($jl: Long!, $queryString: String, $pageTypeEnum: PageTypeEnum) {
+                    jobview: jobView(
+                        listingId: $jl
+                        contextHolder: {queryString: $queryString, pageTypeEnum: $pageTypeEnum}
+                    ) {
+                        job {
+                            description
+                            __typename
+                        }
+                        __typename
+                    }
+                }
+                """,
+            }
+        ]
+        res = requests.post(url, json=body, headers=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)
+        if res.status_code != 200:
+            if res.status_code == 429:
+                err = f"429 Response - Blocked by Glassdoor for too many requests"
+                log.error(err)
+                return None, None
+            else:
+                err = f"Glassdoor response status code {res.status_code}"
+                err += f" - {res.text}"
+                log.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": 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])
--- a/jobspy/glassdoor/constant.py
+++ b/jobspy/glassdoor/constant.py
@@ -0,0 +1,184 @@
+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/138.0.0.0 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
+        }
+"""
+fallback_token = "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok"
--- a/jobspy/glassdoor/util.py
+++ b/jobspy/glassdoor/util.py
@@ -0,0 +1,42 @@
+from jobspy.model import Compensation, CompensationInterval, Location, JobType
+
+
+def parse_compensation(data: dict) -> Compensation | None:
+    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,
+    )
+
+
+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]
+
+
+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)
+
+
+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"]
--- a/jobspy/google/init.py
+++ b/jobspy/google/init.py
@@ -0,0 +1,202 @@
+from __future__ import annotations
+
+import math
+import re
+import json
+from typing import Tuple
+from datetime import datetime, timedelta
+
+from jobspy.google.constant import headers_jobs, headers_initial, async_param
+from jobspy.model import (
+    Scraper,
+    ScraperInput,
+    Site,
+    JobPost,
+    JobResponse,
+    Location,
+    JobType,
+)
+from jobspy.util import extract_emails_from_text, extract_job_type, create_session
+from jobspy.google.util import log, find_job_info_initial_page, find_job_info
+
+
+class Google(Scraper):
+    def __init__(
+        self, proxies: list[str] | str | None = None, ca_cert: str | None = None, user_agent: str | None = None
+    ):
+        """
+        Initializes Google Scraper with the Goodle jobs search url
+        """
+        site = Site(Site.GOOGLE)
+        super().__init__(site, proxies=proxies, ca_cert=ca_cert)
+
+        self.country = None
+        self.session = None
+        self.scraper_input = None
+        self.jobs_per_page = 10
+        self.seen_urls = set()
+        self.url = "https://www.google.com/search"
+        self.jobs_url = "https://www.google.com/async/callback:550"
+
+    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
+        """
+        Scrapes Google 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.session = create_session(
+            proxies=self.proxies, ca_cert=self.ca_cert, is_tls=False, has_retry=True
+        )
+        forward_cursor, job_list = self._get_initial_cursor_and_jobs()
+        if forward_cursor is None:
+            log.warning(
+                "initial cursor not found, try changing your query or there was at most 10 results"
+            )
+            return JobResponse(jobs=job_list)
+
+        page = 1
+
+        while (
+            len(self.seen_urls) < scraper_input.results_wanted + scraper_input.offset
+            and forward_cursor
+        ):
+            log.info(
+                f"search page: {page} / {math.ceil(scraper_input.results_wanted / self.jobs_per_page)}"
+            )
+            try:
+                jobs, forward_cursor = self._get_jobs_next_page(forward_cursor)
+            except Exception as e:
+                log.error(f"failed to get jobs on page: {page}, {e}")
+                break
+            if not jobs:
+                log.info(f"found no jobs on page: {page}")
+                break
+            job_list += jobs
+            page += 1
+        return JobResponse(
+            jobs=job_list[
+                scraper_input.offset : scraper_input.offset
+                + scraper_input.results_wanted
+            ]
+        )
+
+    def _get_initial_cursor_and_jobs(self) -> Tuple[str, list[JobPost]]:
+        """Gets initial cursor and jobs to paginate through job listings"""
+        query = f"{self.scraper_input.search_term} jobs"
+
+        def get_time_range(hours_old):
+            if hours_old <= 24:
+                return "since yesterday"
+            elif hours_old <= 72:
+                return "in the last 3 days"
+            elif hours_old <= 168:
+                return "in the last week"
+            else:
+                return "in the last month"
+
+        job_type_mapping = {
+            JobType.FULL_TIME: "Full time",
+            JobType.PART_TIME: "Part time",
+            JobType.INTERNSHIP: "Internship",
+            JobType.CONTRACT: "Contract",
+        }
+
+        if self.scraper_input.job_type in job_type_mapping:
+            query += f" {job_type_mapping[self.scraper_input.job_type]}"
+
+        if self.scraper_input.location:
+            query += f" near {self.scraper_input.location}"
+
+        if self.scraper_input.hours_old:
+            time_filter = get_time_range(self.scraper_input.hours_old)
+            query += f" {time_filter}"
+
+        if self.scraper_input.is_remote:
+            query += " remote"
+
+        if self.scraper_input.google_search_term:
+            query = self.scraper_input.google_search_term
+
+        params = {"q": query, "udm": "8"}
+        response = self.session.get(self.url, headers=headers_initial, params=params)
+
+        pattern_fc = r'<div jsname="Yust4d"[^>]+data-async-fc="([^"]+)"'
+        match_fc = re.search(pattern_fc, response.text)
+        data_async_fc = match_fc.group(1) if match_fc else None
+        jobs_raw = find_job_info_initial_page(response.text)
+        jobs = []
+        for job_raw in jobs_raw:
+            job_post = self._parse_job(job_raw)
+            if job_post:
+                jobs.append(job_post)
+        return data_async_fc, jobs
+
+    def _get_jobs_next_page(self, forward_cursor: str) -> Tuple[list[JobPost], str]:
+        params = {"fc": [forward_cursor], "fcv": ["3"], "async": [async_param]}
+        response = self.session.get(self.jobs_url, headers=headers_jobs, params=params)
+        return self._parse_jobs(response.text)
+
+    def _parse_jobs(self, job_data: str) -> Tuple[list[JobPost], str]:
+        """
+        Parses jobs on a page with next page cursor
+        """
+        start_idx = job_data.find("[[[")
+        end_idx = job_data.rindex("]]]") + 3
+        s = job_data[start_idx:end_idx]
+        parsed = json.loads(s)[0]
+
+        pattern_fc = r'data-async-fc="([^"]+)"'
+        match_fc = re.search(pattern_fc, job_data)
+        data_async_fc = match_fc.group(1) if match_fc else None
+        jobs_on_page = []
+        for array in parsed:
+            _, job_data = array
+            if not job_data.startswith("[[["):
+                continue
+            job_d = json.loads(job_data)
+
+            job_info = find_job_info(job_d)
+            job_post = self._parse_job(job_info)
+            if job_post:
+                jobs_on_page.append(job_post)
+        return jobs_on_page, data_async_fc
+
+    def _parse_job(self, job_info: list):
+        job_url = job_info[3][0][0] if job_info[3] and job_info[3][0] else None
+        if job_url in self.seen_urls:
+            return
+        self.seen_urls.add(job_url)
+
+        title = job_info[0]
+        company_name = job_info[1]
+        location = city = job_info[2]
+        state = country = date_posted = None
+        if location and "," in location:
+            city, state, *country = [*map(lambda x: x.strip(), location.split(","))]
+
+        days_ago_str = job_info[12]
+        if type(days_ago_str) == str:
+            match = re.search(r"\d+", days_ago_str)
+            days_ago = int(match.group()) if match else None
+            date_posted = (datetime.now() - timedelta(days=days_ago)).date()
+
+        description = job_info[19]
+
+        job_post = JobPost(
+            id=f"go-{job_info[28]}",
+            title=title,
+            company_name=company_name,
+            location=Location(
+                city=city, state=state, country=country[0] if country else None
+            ),
+            job_url=job_url,
+            date_posted=date_posted,
+            is_remote="remote" in description.lower() or "wfh" in description.lower(),
+            description=description,
+            emails=extract_emails_from_text(description),
+            job_type=extract_job_type(description),
+        )
+        return job_post
--- a/jobspy/google/constant.py
+++ b/jobspy/google/constant.py
@@ -0,0 +1,52 @@
+headers_initial = {
+    "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",
+    "priority": "u=0, i",
+    "referer": "https://www.google.com/",
+    "sec-ch-prefers-color-scheme": "dark",
+    "sec-ch-ua": '"Chromium";v="130", "Google Chrome";v="130", "Not?A_Brand";v="99"',
+    "sec-ch-ua-arch": '"arm"',
+    "sec-ch-ua-bitness": '"64"',
+    "sec-ch-ua-form-factors": '"Desktop"',
+    "sec-ch-ua-full-version": '"130.0.6723.58"',
+    "sec-ch-ua-full-version-list": '"Chromium";v="130.0.6723.58", "Google Chrome";v="130.0.6723.58", "Not?A_Brand";v="99.0.0.0"',
+    "sec-ch-ua-mobile": "?0",
+    "sec-ch-ua-model": '""',
+    "sec-ch-ua-platform": '"macOS"',
+    "sec-ch-ua-platform-version": '"15.0.1"',
+    "sec-ch-ua-wow64": "?0",
+    "sec-fetch-dest": "document",
+    "sec-fetch-mode": "navigate",
+    "sec-fetch-site": "same-origin",
+    "sec-fetch-user": "?1",
+    "upgrade-insecure-requests": "1",
+    "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36",
+    "x-browser-channel": "stable",
+    "x-browser-copyright": "Copyright 2024 Google LLC. All rights reserved.",
+    "x-browser-year": "2024",
+}
+
+headers_jobs = {
+    "accept": "*/*",
+    "accept-language": "en-US,en;q=0.9",
+    "priority": "u=1, i",
+    "referer": "https://www.google.com/",
+    "sec-ch-prefers-color-scheme": "dark",
+    "sec-ch-ua": '"Chromium";v="130", "Google Chrome";v="130", "Not?A_Brand";v="99"',
+    "sec-ch-ua-arch": '"arm"',
+    "sec-ch-ua-bitness": '"64"',
+    "sec-ch-ua-form-factors": '"Desktop"',
+    "sec-ch-ua-full-version": '"130.0.6723.58"',
+    "sec-ch-ua-full-version-list": '"Chromium";v="130.0.6723.58", "Google Chrome";v="130.0.6723.58", "Not?A_Brand";v="99.0.0.0"',
+    "sec-ch-ua-mobile": "?0",
+    "sec-ch-ua-model": '""',
+    "sec-ch-ua-platform": '"macOS"',
+    "sec-ch-ua-platform-version": '"15.0.1"',
+    "sec-ch-ua-wow64": "?0",
+    "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/130.0.0.0 Safari/537.36",
+}
+
+async_param = "_basejs:/xjs/_/js/k=xjs.s.en_US.JwveA-JiKmg.2018.O/am=AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAIAAAAAAAAACAAAoICAAAAAAAKMAfAAAAIAQAAAAAAAAAAAAACCAAAEJDAAACAAAAAGABAIAAARBAAABAAAAAgAgQAABAASKAfv8JAAABAAAAAAwAQAQACQAAAAAAcAEAQABoCAAAABAAAIABAACAAAAEAAAAFAAAAAAAAAAAAAAAAAAAAAAAAACAQADoBwAAAAAAAAAAAAAQBAAAAATQAAoACOAHAAAAAAAAAQAAAIIAAAA_ZAACAAAAAAAAcB8APB4wHFJ4AAAAAAAAAAAAAAAACECCYA5If0EACAAAAAAAAAAAAAAAAAAAUgRNXG4AMAE/dg=0/br=1/rs=ACT90oGxMeaFMCopIHq5tuQM-6_3M_VMjQ,_basecss:/xjs/_/ss/k=xjs.s.IwsGu62EDtU.L.B1.O/am=QOoQIAQAAAQAREADEBAAAAAAAAAAAAAAAAAAAAAgAQAAIAAAgAQAAAIAIAIAoEwCAADIC8AfsgEAawwAPkAAjgoAGAAAAAAAAEADAAAAAAIgAECHAAAAAAAAAAABAQAggAARQAAAQCEAAAAAIAAAABgAAAAAIAQIACCAAfB-AAFIQABoCEA_CgEAAIABAACEgHAEwwAEFQAM4CgAAAAAAAAAAAAACABCAAAAQEAAABAgAMCPAAA4AoE2BAEAggSAAIoAQAAAAAgAAAAACCAQAAAxEwA_ZAACAAAAAAAAAAkAAAAAAAAgAAAAAAAAAAAAAAAAAAAAAAAAQAEAAAAAAAAAAAAAAAAAAAAAQA/br=1/rs=ACT90oGZc36t3uUQkj0srnIvvbHjO2hgyg,_basecomb:/xjs/_/js/k=xjs.s.en_US.JwveA-JiKmg.2018.O/ck=xjs.s.IwsGu62EDtU.L.B1.O/am=QOoQIAQAAAQAREADEBAAAAAAAAAAAAAAAAAAAAAgAQAAIAAAgAQAAAKAIAoIqEwCAADIK8AfsgEAawwAPkAAjgoAGAAACCAAAEJDAAACAAIgAGCHAIAAARBAAABBAQAggAgRQABAQSOAfv8JIAABABgAAAwAYAQICSCAAfB-cAFIQABoCEA_ChEAAIABAACEgHAEwwAEFQAM4CgAAAAAAAAAAAAACABCAACAQEDoBxAgAMCPAAA4AoE2BAEAggTQAIoASOAHAAgAAAAACSAQAIIxEwA_ZAACAAAAAAAAcB8APB4wHFJ4AAAAAAAAAAAAAAAACECCYA5If0EACAAAAAAAAAAAAAAAAAAAUgRNXG4AMAE/d=1/ed=1/dg=0/br=1/ujg=1/rs=ACT90oFNLTjPzD_OAqhhtXwe2pg1T3WpBg,_fmt:prog,_id:fc_5FwaZ86OKsfdwN4P4La3yA4_2"
--- a/jobspy/google/util.py
+++ b/jobspy/google/util.py
@@ -0,0 +1,41 @@
+import re
+
+from jobspy.util import create_logger
+
+log = create_logger("Google")
+
+
+def find_job_info(jobs_data: list | dict) -> list | None:
+    """Iterates through the JSON data to find the job listings"""
+    if isinstance(jobs_data, dict):
+        for key, value in jobs_data.items():
+            if key == "520084652" and isinstance(value, list):
+                return value
+            else:
+                result = find_job_info(value)
+                if result:
+                    return result
+    elif isinstance(jobs_data, list):
+        for item in jobs_data:
+            result = find_job_info(item)
+            if result:
+                return result
+    return None
+
+
+def find_job_info_initial_page(html_text: str):
+    pattern = f'520084652":(' + r"\[.*?\]\s*])\s*}\s*]\s*]\s*]\s*]\s*]"
+    results = []
+    matches = re.finditer(pattern, html_text)
+
+    import json
+
+    for match in matches:
+        try:
+            parsed_data = json.loads(match.group(1))
+            results.append(parsed_data)
+
+        except json.JSONDecodeError as e:
+            log.error(f"Failed to parse match: {str(e)}")
+            results.append({"raw_match": match.group(0), "error": str(e)})
+    return results
--- a/jobspy/indeed/init.py
+++ b/jobspy/indeed/init.py
@@ -0,0 +1,260 @@
+from __future__ import annotations
+
+import math
+from datetime import datetime
+from typing import Tuple
+
+from jobspy.indeed.constant import job_search_query, api_headers
+from jobspy.indeed.util import is_job_remote, get_compensation, get_job_type
+from jobspy.model import (
+    Scraper,
+    ScraperInput,
+    Site,
+    JobPost,
+    Location,
+    JobResponse,
+    JobType,
+    DescriptionFormat,
+)
+from jobspy.util import (
+    extract_emails_from_text,
+    markdown_converter,
+    create_session,
+    create_logger,
+)
+
+log = create_logger("Indeed")
+
+
+class Indeed(Scraper):
+    def __init__(
+        self, proxies: list[str] | str | None = None, ca_cert: str | None = None, user_agent: str | None = None
+    ):
+        """
+        Initializes IndeedScraper with the Indeed API url
+        """
+        super().__init__(Site.INDEED, proxies=proxies)
+
+        self.session = create_session(
+            proxies=self.proxies, ca_cert=ca_cert, is_tls=False
+        )
+        self.scraper_input = None
+        self.jobs_per_page = 100
+        self.num_workers = 10
+        self.seen_urls = set()
+        self.headers = None
+        self.api_country_code = None
+        self.base_url = None
+        self.api_url = "https://apis.indeed.com/graphql"
+
+    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
+        """
+        Scrapes Indeed for jobs with scraper_input criteria
+        :param scraper_input:
+        :return: job_response
+        """
+        self.scraper_input = scraper_input
+        domain, self.api_country_code = self.scraper_input.country.indeed_domain_value
+        self.base_url = f"https://{domain}.indeed.com"
+        self.headers = api_headers.copy()
+        self.headers["indeed-co"] = self.scraper_input.country.indeed_domain_value
+        job_list = []
+        page = 1
+
+        cursor = None
+
+        while len(self.seen_urls) < scraper_input.results_wanted + scraper_input.offset:
+            log.info(
+                f"search page: {page} / {math.ceil(scraper_input.results_wanted / self.jobs_per_page)}"
+            )
+            jobs, cursor = self._scrape_page(cursor)
+            if not jobs:
+                log.info(f"found no jobs on page: {page}")
+                break
+            job_list += jobs
+            page += 1
+        return JobResponse(
+            jobs=job_list[
+                scraper_input.offset : scraper_input.offset
+                + scraper_input.results_wanted
+            ]
+        )
+
+    def _scrape_page(self, cursor: str | None) -> Tuple[list[JobPost], str | None]:
+        """
+        Scrapes a page of Indeed for jobs with scraper_input criteria
+        :param cursor:
+        :return: jobs found on page, next page cursor
+        """
+        jobs = []
+        new_cursor = None
+        filters = self._build_filters()
+        search_term = (
+            self.scraper_input.search_term.replace('"', '\\"')
+            if self.scraper_input.search_term
+            else ""
+        )
+        query = job_search_query.format(
+            what=(f'what: "{search_term}"' if search_term else ""),
+            location=(
+                f'location: {{where: "{self.scraper_input.location}", radius: {self.scraper_input.distance}, radiusUnit: MILES}}'
+                if self.scraper_input.location
+                else ""
+            ),
+            dateOnIndeed=self.scraper_input.hours_old,
+            cursor=f'cursor: "{cursor}"' if cursor else "",
+            filters=filters,
+        )
+        payload = {
+            "query": query,
+        }
+        api_headers_temp = api_headers.copy()
+        api_headers_temp["indeed-co"] = self.api_country_code
+        response = self.session.post(
+            self.api_url,
+            headers=api_headers_temp,
+            json=payload,
+            timeout=10,
+            verify=False,
+        )
+        if not response.ok:
+            log.info(
+                f"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"]
+
+        job_list = []
+        for job in jobs:
+            processed_job = self._process_job(job["job"])
+            if processed_job:
+                job_list.append(processed_job)
+
+        return job_list, new_cursor
+
+    def _build_filters(self):
+        """
+        Builds the filters dict for job type/is_remote. If hours_old is provided, composite filter for job_type/is_remote is not possible.
+        IndeedApply: filters: { keyword: { field: "indeedApplyScope", keys: ["DESKTOP"] } }
+        """
+        filters_str = ""
+        if self.scraper_input.hours_old:
+            filters_str = """
+            filters: {{
+                date: {{
+                  field: "dateOnIndeed",
+                  start: "{start}h"
+                }}
+            }}
+            """.format(
+                start=self.scraper_input.hours_old
+            )
+        elif self.scraper_input.easy_apply:
+            filters_str = """
+            filters: {
+                keyword: {
+                  field: "indeedApplyScope",
+                  keys: ["DESKTOP"]
+                }
+            }
+            """
+        elif self.scraper_input.job_type or self.scraper_input.is_remote:
+            job_type_key_mapping = {
+                JobType.FULL_TIME: "CF3CP",
+                JobType.PART_TIME: "75GKK",
+                JobType.CONTRACT: "NJXCK",
+                JobType.INTERNSHIP: "VDTG7",
+            }
+
+            keys = []
+            if self.scraper_input.job_type:
+                key = job_type_key_mapping[self.scraper_input.job_type]
+                keys.append(key)
+
+            if self.scraper_input.is_remote:
+                keys.append("DSQF7")
+
+            if keys:
+                keys_str = '", "'.join(keys)
+                filters_str = f"""
+                filters: {{
+                  composite: {{
+                    filters: [{{
+                      keyword: {{
+                        field: "attributes",
+                        keys: ["{keys_str}"]
+                      }}
+                    }}]
+                  }}
+                }}
+                """
+        return filters_str
+
+    def _process_job(self, job: dict) -> JobPost | None:
+        """
+        Parses the job dict into JobPost model
+        :param job: dict to parse
+        :return: JobPost if it's a new job
+        """
+        job_url = f'{self.base_url}/viewjob?jk={job["key"]}'
+        if job_url in self.seen_urls:
+            return
+        self.seen_urls.add(job_url)
+        description = job["description"]["html"]
+        if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
+            description = markdown_converter(description)
+
+        job_type = 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=f'in-{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=get_compensation(job["compensation"]),
+            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=is_job_remote(job, description),
+            company_addresses=(
+                employer_details["addresses"][0]
+                if employer_details.get("addresses")
+                else None
+            ),
+            company_industry=(
+                employer_details["industry"]
+                .replace("Iv1", "")
+                .replace("_", " ")
+                .title()
+                .strip()
+                if employer_details.get("industry")
+                else None
+            ),
+            company_num_employees=employer_details.get("employeesLocalizedLabel"),
+            company_revenue=employer_details.get("revenueLocalizedLabel"),
+            company_description=employer_details.get("briefDescription"),
+            company_logo=(
+                employer["images"].get("squareLogoUrl")
+                if employer and employer.get("images")
+                else None
+            ),
+        )
--- a/jobspy/indeed/constant.py
+++ b/jobspy/indeed/constant.py
@@ -0,0 +1,109 @@
+job_search_query = """
+    query GetJobData {{
+        jobSearch(
+        {what}
+        {location}
+        limit: 100
+        {cursor}
+        sort: RELEVANCE
+        {filters}
+        ) {{
+        pageInfo {{
+            nextCursor
+        }}
+        results {{
+            trackingKey
+            job {{
+            source {{
+                name
+            }}
+            key
+            title
+            datePublished
+            dateOnIndeed
+            description {{
+                html
+            }}
+            location {{
+                countryName
+                countryCode
+                admin1Code
+                city
+                postalCode
+                streetAddress
+                formatted {{
+                short
+                long
+                }}
+            }}
+            compensation {{
+                estimated {{
+                currencyCode
+                baseSalary {{
+                    unitOfWork
+                    range {{
+                    ... on Range {{
+                        min
+                        max
+                    }}
+                    }}
+                }}
+                }}
+                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
+            }}
+            }}
+        }}
+        }}
+    }}
+    """
+
+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",
+}
--- a/jobspy/indeed/util.py
+++ b/jobspy/indeed/util.py
@@ -0,0 +1,83 @@
+from jobspy.model import CompensationInterval, JobType, Compensation
+from jobspy.util import get_enum_from_job_type
+
+
+def get_job_type(attributes: list) -> list[JobType]:
+    """
+    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
+
+
+def get_compensation(compensation: dict) -> Compensation | None:
+    """
+    Parses the job to get compensation
+    :param compensation:
+    :return: compensation object
+    """
+    if not compensation["baseSalary"] and not compensation["estimated"]:
+        return None
+    comp = (
+        compensation["baseSalary"]
+        if compensation["baseSalary"]
+        else compensation["estimated"]["baseSalary"]
+    )
+    if not comp:
+        return None
+    interval = get_compensation_interval(comp["unitOfWork"])
+    if not interval:
+        return None
+    min_range = comp["range"].get("min")
+    max_range = comp["range"].get("max")
+    return Compensation(
+        interval=interval,
+        min_amount=int(min_range) if min_range is not None else None,
+        max_amount=int(max_range) if max_range is not None else None,
+        currency=(
+            compensation["estimated"]["currencyCode"]
+            if compensation["estimated"]
+            else compensation["currencyCode"]
+        ),
+    )
+
+
+def is_job_remote(job: dict, description: str) -> bool:
+    """
+    Searches the description, location, and attributes to check if job is remote
+    """
+    remote_keywords = ["remote", "work from home", "wfh"]
+    is_remote_in_attributes = any(
+        any(keyword in attr["label"].lower() for keyword in remote_keywords)
+        for attr in job["attributes"]
+    )
+    is_remote_in_description = any(
+        keyword in description.lower() for keyword in remote_keywords
+    )
+    is_remote_in_location = any(
+        keyword in job["location"]["formatted"]["long"].lower()
+        for keyword in remote_keywords
+    )
+    return is_remote_in_attributes or is_remote_in_description or is_remote_in_location
+
+
+def get_compensation_interval(interval: str) -> CompensationInterval:
+    interval_mapping = {
+        "DAY": "DAILY",
+        "YEAR": "YEARLY",
+        "HOUR": "HOURLY",
+        "WEEK": "WEEKLY",
+        "MONTH": "MONTHLY",
+    }
+    mapped_interval = interval_mapping.get(interval.upper(), None)
+    if mapped_interval and mapped_interval in CompensationInterval.__members__:
+        return CompensationInterval[mapped_interval]
+    else:
+        raise ValueError(f"Unsupported interval: {interval}")
--- a/src/jobspy/scrapers/linkedin/init.py
+++ b/src/jobspy/scrapers/linkedin/init.py
@@ -1,56 +1,73 @@
-"""
-jobspy.scrapers.linkedin
-~~~~~~~~~~~~~~~~~~~
-
-This module contains routines to scrape LinkedIn.
-"""
-
 from __future__ import annotations

-import time
+import math
 import random
-from typing import Optional
+import time
 from datetime import datetime
+from typing import Optional
+from urllib.parse import urlparse, urlunparse, unquote

-from threading import Lock
-from bs4.element import Tag
+import regex as re
 from bs4 import BeautifulSoup
-from urllib.parse import urlparse, urlunparse
+from bs4.element import Tag

-from .. import Scraper, ScraperInput, Site
-from ..exceptions import LinkedInException
-from ..utils import create_session
-from ...jobs import (
+from jobspy.exception import LinkedInException
+from jobspy.linkedin.constant import headers
+from jobspy.linkedin.util import (
+    is_job_remote,
+    job_type_code,
+    parse_job_type,
+    parse_job_level,
+    parse_company_industry
+)
+from jobspy.model import (
    JobPost,
    Location,
    JobResponse,
-    JobType,
    Country,
    Compensation,
    DescriptionFormat,
+    Scraper,
+    ScraperInput,
+    Site,
 )
-from ..utils import (
-    logger,
+from jobspy.util import (
    extract_emails_from_text,
-    get_enum_from_job_type,
    currency_parser,
    markdown_converter,
+    create_session,
+    remove_attributes,
+    create_logger,
 )

+log = create_logger("LinkedIn")

-class LinkedInScraper(Scraper):
+
+class LinkedIn(Scraper):
    base_url = "https://www.linkedin.com"
    delay = 3
    band_delay = 4
    jobs_per_page = 25

-    def __init__(self, proxy: Optional[str] = None):
+    def __init__(
+        self, proxies: list[str] | str | None = None, ca_cert: str | None = None, user_agent: str | None = None
+    ):
        """
        Initializes LinkedInScraper with the LinkedIn job search url
        """
-        super().__init__(Site(Site.LINKEDIN), proxy=proxy)
+        super().__init__(Site.LINKEDIN, proxies=proxies, ca_cert=ca_cert)
+        self.session = create_session(
+            proxies=self.proxies,
+            ca_cert=ca_cert,
+            is_tls=False,
+            has_retry=True,
+            delay=5,
+            clear_cookies=True,
+        )
+        self.session.headers.update(headers)
        self.scraper_input = None
        self.country = "worldwide"
+        self.job_url_direct_regex = re.compile(r'(?<=\?url=)[^"]+')

    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
        """
@@ -60,30 +77,32 @@ class LinkedInScraper(Scraper):
        """
        self.scraper_input = scraper_input
        job_list: list[JobPost] = []
-        seen_urls = set()
-        url_lock = Lock()
-        page = scraper_input.offset // 25 + 25 if scraper_input.offset else 0
+        seen_ids = set()
+        start = scraper_input.offset // 10 * 10 if scraper_input.offset else 0
+        request_count = 0
        seconds_old = (
            scraper_input.hours_old * 3600 if scraper_input.hours_old else None
        )
        continue_search = (
-            lambda: len(job_list) < scraper_input.results_wanted and page < 1000
+            lambda: len(job_list) < scraper_input.results_wanted and start < 1000
        )
        while continue_search():
-            logger.info(f"LinkedIn search page: {page // 25 + 1}")
-            session = create_session(is_tls=False, has_retry=True, delay=5)
+            request_count += 1
+            log.info(
+                f"search page: {request_count} / {math.ceil(scraper_input.results_wanted / 10)}"
+            )
            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": (
-                    self.job_type_code(scraper_input.job_type)
+                    job_type_code(scraper_input.job_type)
                    if scraper_input.job_type
                    else None
                ),
                "pageNum": 0,
-                "start": page + scraper_input.offset,
+                "start": start,
                "f_AL": "true" if scraper_input.easy_apply else None,
                "f_C": (
                    ",".join(map(str, scraper_input.linkedin_company_ids))
@@ -96,12 +115,9 @@ class LinkedInScraper(Scraper):

            params = {k: v for k, v in params.items() if v is not None}
            try:
-                response = session.get(
+                response = self.session.get(
                    f"{self.base_url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
                    params=params,
-                    allow_redirects=True,
-                    proxies=self.proxy,
-                    headers=self.headers,
                    timeout=10,
                )
                if response.status_code not in range(200, 400):
@@ -112,13 +128,13 @@ class LinkedInScraper(Scraper):
                    else:
                        err = f"LinkedIn response status code {response.status_code}"
                        err += f" - {response.text}"
-                    logger.error(err)
+                    log.error(err)
                    return JobResponse(jobs=job_list)
            except Exception as e:
                if "Proxy responded with" in str(e):
-                    logger.error(f"LinkedIn: Bad proxy")
+                    log.error(f"LinkedIn: Bad proxy")
                else:
-                    logger.error(f"LinkedIn: {str(e)}")
+                    log.error(f"LinkedIn: {str(e)}")
                return JobResponse(jobs=job_list)

            soup = BeautifulSoup(response.text, "html.parser")
@@ -127,40 +143,38 @@ class LinkedInScraper(Scraper):
                return JobResponse(jobs=job_list)

            for job_card in job_cards:
-                job_url = None
                href_tag = job_card.find("a", class_="base-card__full-link")
                if href_tag and "href" in href_tag.attrs:
                    href = href_tag.attrs["href"].split("?")[0]
                    job_id = href.split("-")[-1]
-                    job_url = f"{self.base_url}/jobs/view/{job_id}"

-                with url_lock:
-                    if job_url in seen_urls:
+                    if job_id in seen_ids:
                        continue
-                    seen_urls.add(job_url)
-                try:
-                    fetch_desc = scraper_input.linkedin_fetch_description
-                    job_post = self._process_job(job_card, job_url, fetch_desc)
-                    if job_post:
-                        job_list.append(job_post)
-                    if not continue_search():
-                        break
-                except Exception as e:
-                    raise LinkedInException(str(e))
+                    seen_ids.add(job_id)
+
+                    try:
+                        fetch_desc = scraper_input.linkedin_fetch_description
+                        job_post = self._process_job(job_card, job_id, fetch_desc)
+                        if job_post:
+                            job_list.append(job_post)
+                        if not continue_search():
+                            break
+                    except Exception as e:
+                        raise LinkedInException(str(e))

            if continue_search():
                time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
-                page += self.jobs_per_page
+                start += len(job_list)

        job_list = job_list[: scraper_input.results_wanted]
        return JobResponse(jobs=job_list)

    def _process_job(
-        self, job_card: Tag, job_url: str, full_descr: bool
+        self, job_card: Tag, job_id: str, full_descr: bool
    ) -> Optional[JobPost]:
        salary_tag = job_card.find("span", class_="job-search-card__salary-info")

-        compensation = None
+        compensation = description = None
        if salary_tag:
            salary_text = salary_tag.get_text(separator=" ").strip()
            salary_values = [currency_parser(value) for value in salary_text.split("-")]
@@ -194,48 +208,54 @@ class LinkedInScraper(Scraper):
            if metadata_card
            else None
        )
-        date_posted = description = job_type = 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
-        benefits_tag = job_card.find("span", class_="result-benefits__text")
+        job_details = {}
        if full_descr:
-            description, job_type = self._get_job_description(job_url)
+            job_details = self._get_job_details(job_id)
+            description = job_details.get("description")
+        is_remote = is_job_remote(title, description, location)

        return JobPost(
+            id=f"li-{job_id}",
            title=title,
            company_name=company,
            company_url=company_url,
            location=location,
+            is_remote=is_remote,
            date_posted=date_posted,
-            job_url=job_url,
+            job_url=f"{self.base_url}/jobs/view/{job_id}",
            compensation=compensation,
-            job_type=job_type,
-            description=description,
-            emails=extract_emails_from_text(description) if description else None,
+            job_type=job_details.get("job_type"),
+            job_level=job_details.get("job_level", "").lower(),
+            company_industry=job_details.get("company_industry"),
+            description=job_details.get("description"),
+            job_url_direct=job_details.get("job_url_direct"),
+            emails=extract_emails_from_text(description),
+            company_logo=job_details.get("company_logo"),
+            job_function=job_details.get("job_function"),
        )

-    def _get_job_description(
-        self, job_page_url: str
-    ) -> tuple[None, None] | tuple[str | None, tuple[str | None, JobType | None]]:
+    def _get_job_details(self, job_id: str) -> dict:
        """
-        Retrieves job description by going to the job page url
+        Retrieves job description and other job details by going to the job page url
        :param job_page_url:
-        :return: description or None
+        :return: dict
        """
        try:
-            session = create_session(is_tls=False, has_retry=True)
-            response = session.get(
-                job_page_url, headers=self.headers, timeout=5, proxies=self.proxy
+            response = self.session.get(
+                f"{self.base_url}/jobs/view/{job_id}", timeout=5
            )
            response.raise_for_status()
        except:
-            return None, None
-        if response.url == "https://www.linkedin.com/signup":
-            return None, None
+            return {}
+        if "linkedin.com/signup" in response.url:
+            return {}

        soup = BeautifulSoup(response.text, "html.parser")
        div_content = soup.find(
@@ -243,17 +263,37 @@ class LinkedInScraper(Scraper):
        )
        description = None
        if div_content is not None:
-
-            def remove_attributes(tag):
-                for attr in list(tag.attrs):
-                    del tag[attr]
-                return tag
-
            div_content = remove_attributes(div_content)
            description = div_content.prettify(formatter="html")
            if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
                description = markdown_converter(description)
-        return description, self._parse_job_type(soup)
+
+        h3_tag = soup.find(
+            "h3", text=lambda text: text and "Job function" in text.strip()
+        )
+
+        job_function = None
+        if h3_tag:
+            job_function_span = h3_tag.find_next(
+                "span", class_="description__job-criteria-text"
+            )
+            if job_function_span:
+                job_function = job_function_span.text.strip()
+
+        company_logo = (
+            logo_image.get("data-delayed-url")
+            if (logo_image := soup.find("img", {"class": "artdeco-entity-image"}))
+            else None
+        )
+        return {
+            "description": description,
+            "job_level": parse_job_level(soup),
+            "company_industry": parse_company_industry(soup),
+            "job_type": parse_job_type(soup),
+            "job_url_direct": self._parse_job_url_direct(soup),
+            "company_logo": company_logo,
+            "job_function": job_function,
+        }

    def _get_location(self, metadata_card: Optional[Tag]) -> Location:
        """
@@ -281,46 +321,19 @@ class LinkedInScraper(Scraper):
                location = Location(city=city, state=state, country=country)
        return location

-    @staticmethod
-    def _parse_job_type(soup_job_type: BeautifulSoup) -> list[JobType] | None:
+    def _parse_job_url_direct(self, soup: BeautifulSoup) -> str | None:
        """
-        Gets the job type from job page
-        :param soup_job_type:
-        :return: JobType
+        Gets the job url direct from job page
+        :param soup:
+        :return: str
        """
-        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",
+        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 employment_type_span:
-                employment_type = employment_type_span.get_text(strip=True)
-                employment_type = employment_type.lower()
-                employment_type = employment_type.replace("-", "")
+            if job_url_direct_match:
+                job_url_direct = unquote(job_url_direct_match.group())

-        return [get_enum_from_job_type(employment_type)] if employment_type else []
-
-    @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",
-    }
+        return job_url_direct
--- a/jobspy/linkedin/constant.py
+++ b/jobspy/linkedin/constant.py
@@ -0,0 +1,8 @@
+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/jobspy/linkedin/util.py
+++ b/jobspy/linkedin/util.py
@@ -0,0 +1,96 @@
+from bs4 import BeautifulSoup
+
+from jobspy.model import JobType, Location
+from jobspy.util import get_enum_from_job_type
+
+
+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, "")
+
+
+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_level(soup_job_level: BeautifulSoup) -> str | None:
+    """
+    Gets the job level from job page
+    :param soup_job_level:
+    :return: str
+    """
+    h3_tag = soup_job_level.find(
+        "h3",
+        class_="description__job-criteria-subheader",
+        string=lambda text: "Seniority level" in text,
+    )
+    job_level = None
+    if h3_tag:
+        job_level_span = h3_tag.find_next_sibling(
+            "span",
+            class_="description__job-criteria-text description__job-criteria-text--criteria",
+        )
+        if job_level_span:
+            job_level = job_level_span.get_text(strip=True)
+
+    return job_level
+
+
+def parse_company_industry(soup_industry: BeautifulSoup) -> str | None:
+    """
+    Gets the company industry from job page
+    :param soup_industry:
+    :return: str
+    """
+    h3_tag = soup_industry.find(
+        "h3",
+        class_="description__job-criteria-subheader",
+        string=lambda text: "Industries" in text,
+    )
+    industry = None
+    if h3_tag:
+        industry_span = h3_tag.find_next_sibling(
+            "span",
+            class_="description__job-criteria-text description__job-criteria-text--criteria",
+        )
+        if industry_span:
+            industry = industry_span.get_text(strip=True)
+
+    return industry
+
+
+def is_job_remote(title: dict, description: str, location: Location) -> bool:
+    """
+    Searches the title, location, and description to check if job is remote
+    """
+    remote_keywords = ["remote", "work from home", "wfh"]
+    location = location.display_location()
+    full_string = f'{title} {description} {location}'.lower()
+    is_remote = any(keyword in full_string for keyword in remote_keywords)
+    return is_remote
--- a/src/jobspy/jobs/init.py
+++ b/src/jobspy/jobs/init.py
@@ -1,5 +1,6 @@
 from __future__ import annotations

+from abc import ABC, abstractmethod
 from typing import Optional
 from datetime import date
 from enum import Enum
@@ -67,17 +68,22 @@ class Country(Enum):
    AUSTRALIA = ("australia", "au", "com.au")
    AUSTRIA = ("austria", "at", "at")
    BAHRAIN = ("bahrain", "bh")
+    BANGLADESH = ("bangladesh", "bd")  # Added Bangladesh
    BELGIUM = ("belgium", "be", "fr:be")
+    BULGARIA = ("bulgaria", "bg")
    BRAZIL = ("brazil", "br", "com.br")
    CANADA = ("canada", "ca", "ca")
    CHILE = ("chile", "cl")
    CHINA = ("china", "cn")
    COLOMBIA = ("colombia", "co")
    COSTARICA = ("costa rica", "cr")
+    CROATIA = ("croatia", "hr")
+    CYPRUS = ("cyprus", "cy")
    CZECHREPUBLIC = ("czech republic,czechia", "cz")
    DENMARK = ("denmark", "dk")
    ECUADOR = ("ecuador", "ec")
    EGYPT = ("egypt", "eg")
+    ESTONIA = ("estonia", "ee")
    FINLAND = ("finland", "fi")
    FRANCE = ("france", "fr", "fr")
    GERMANY = ("germany", "de", "de")
@@ -91,8 +97,11 @@ class Country(Enum):
    ITALY = ("italy", "it", "it")
    JAPAN = ("japan", "jp")
    KUWAIT = ("kuwait", "kw")
+    LATVIA = ("latvia", "lv")
+    LITHUANIA = ("lithuania", "lt")
    LUXEMBOURG = ("luxembourg", "lu")
-    MALAYSIA = ("malaysia", "malaysia")
+    MALAYSIA = ("malaysia", "malaysia:my", "com")
+    MALTA = ("malta", "malta:mt", "mt")
    MEXICO = ("mexico", "mx", "com.mx")
    MOROCCO = ("morocco", "ma")
    NETHERLANDS = ("netherlands", "nl", "nl")
@@ -110,6 +119,8 @@ class Country(Enum):
    ROMANIA = ("romania", "ro")
    SAUDIARABIA = ("saudi arabia", "sa")
    SINGAPORE = ("singapore", "sg", "sg")
+    SLOVAKIA = ("slovakia", "sk")
+    SLOVENIA = ("slovenia", "sl")
    SOUTHAFRICA = ("south africa", "za")
    SOUTHKOREA = ("south korea", "kr")
    SPAIN = ("spain", "es", "es")
@@ -117,7 +128,7 @@ class Country(Enum):
    SWITZERLAND = ("switzerland", "ch", "de:ch")
    TAIWAN = ("taiwan", "tw")
    THAILAND = ("thailand", "th")
-    TURKEY = ("turkey", "tr")
+    TURKEY = ("türkiye,turkey", "tr")
    UKRAINE = ("ukraine", "ua")
    UNITEDARABEMIRATES = ("united arab emirates", "ae")
    UK = ("uk,united kingdom", "uk:gb", "co.uk")
@@ -226,6 +237,7 @@ class DescriptionFormat(Enum):


 class JobPost(BaseModel):
+    id: str | None = None
    title: str
    company_name: str | None
    job_url: str
@@ -241,18 +253,83 @@ class JobPost(BaseModel):
    date_posted: date | None = None
    emails: list[str] | None = None
    is_remote: bool | None = None
+    listing_type: str | None = None

-    # indeed specific
-    company_addresses: str | None = None
+    # LinkedIn specific
+    job_level: str | None = None
+
+    # LinkedIn and Indeed specific
    company_industry: str | None = None
+
+    # Indeed specific
+    company_addresses: str | None = None
    company_num_employees: str | None = None
    company_revenue: str | None = None
    company_description: str | None = None
-    ceo_name: str | None = None
-    ceo_photo_url: str | None = None
-    logo_photo_url: str | None = None
+    company_logo: str | None = None
    banner_photo_url: str | None = None

+    # LinkedIn only atm
+    job_function: str | None = None
+
+    # Naukri specific
+    skills: list[str] | None = None  #from tagsAndSkills
+    experience_range: str | None = None  #from experienceText
+    company_rating: float | None = None  #from ambitionBoxData.AggregateRating
+    company_reviews_count: int | None = None  #from ambitionBoxData.ReviewsCount
+    vacancy_count: int | None = None  #from vacancy
+    work_from_home_type: str | None = None  #from clusters.wfhType (e.g., "Hybrid", "Remote")

 class JobResponse(BaseModel):
    jobs: list[JobPost] = []
+
+
+class Site(Enum):
+    LINKEDIN = "linkedin"
+    INDEED = "indeed"
+    ZIP_RECRUITER = "zip_recruiter"
+    GLASSDOOR = "glassdoor"
+    GOOGLE = "google"
+    BAYT = "bayt"
+    NAUKRI = "naukri"
+    BDJOBS = "bdjobs"  # Add this line
+
+
+class SalarySource(Enum):
+    DIRECT_DATA = "direct_data"
+    DESCRIPTION = "description"
+
+
+class ScraperInput(BaseModel):
+    site_type: list[Site]
+    search_term: str | None = None
+    google_search_term: str | None = None
+
+    location: str | None = None
+    country: Country | None = Country.USA
+    distance: int | None = None
+    is_remote: bool = False
+    job_type: JobType | None = None
+    easy_apply: bool | None = None
+    offset: int = 0
+    linkedin_fetch_description: bool = False
+    linkedin_company_ids: list[int] | None = None
+    description_format: DescriptionFormat | None = DescriptionFormat.MARKDOWN
+
+    request_timeout: int = 60
+
+    results_wanted: int = 15
+    hours_old: int | None = None
+
+
+class Scraper(ABC):
+    def __init__(
+        self, site: Site, proxies: list[str] | None = None, ca_cert: str | None = None, user_agent: str | None = None
+    ):
+        self.site = site
+        self.proxies = proxies
+        self.ca_cert = ca_cert
+        self.user_agent = user_agent
+
+    @abstractmethod
+    def scrape(self, scraper_input: ScraperInput) -> JobResponse: ...
--- a/jobspy/naukri/init.py
+++ b/jobspy/naukri/init.py
@@ -0,0 +1,301 @@
+from __future__ import annotations
+
+import math
+import random
+import time
+from datetime import datetime, date, timedelta
+from typing import Optional
+
+import regex as re
+import requests
+
+from jobspy.exception import NaukriException
+from jobspy.naukri.constant import headers as naukri_headers
+from jobspy.naukri.util import (
+    is_job_remote,
+    parse_job_type,
+    parse_company_industry,
+)
+from jobspy.model import (
+    JobPost,
+    Location,
+    JobResponse,
+    Country,
+    Compensation,
+    DescriptionFormat,
+    Scraper,
+    ScraperInput,
+    Site,
+)
+from jobspy.util import (
+    extract_emails_from_text,
+    currency_parser,
+    markdown_converter,
+    create_session,
+    create_logger,
+)
+
+log = create_logger("Naukri")
+
+class Naukri(Scraper):
+    base_url = "https://www.naukri.com/jobapi/v3/search"
+    delay = 3
+    band_delay = 4
+    jobs_per_page = 20  
+
+    def __init__(
+        self, proxies: list[str] | str | None = None, ca_cert: str | None = None, user_agent: str | None = None
+    ):
+        """
+        Initializes NaukriScraper with the Naukri API URL
+        """
+        super().__init__(Site.NAUKRI, proxies=proxies, ca_cert=ca_cert)
+        self.session = create_session(
+            proxies=self.proxies,
+            ca_cert=ca_cert,
+            is_tls=False,
+            has_retry=True,
+            delay=5,
+            clear_cookies=True,
+        )
+        self.session.headers.update(naukri_headers)
+        self.scraper_input = None
+        self.country = "India"  #naukri is india-focused by default
+        log.info("Naukri scraper initialized")
+
+    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
+        """
+        Scrapes Naukri API for jobs with scraper_input criteria
+        :param scraper_input:
+        :return: job_response
+        """
+        self.scraper_input = scraper_input
+        job_list: list[JobPost] = []
+        seen_ids = set()
+        start = scraper_input.offset or 0
+        page = (start // self.jobs_per_page) + 1
+        request_count = 0
+        seconds_old = (
+            scraper_input.hours_old * 3600 if scraper_input.hours_old else None
+        )
+        continue_search = (
+            lambda: len(job_list) < scraper_input.results_wanted and page <= 50  # Arbitrary limit
+        )
+
+        while continue_search():
+            request_count += 1
+            log.info(
+                f"Scraping page {request_count} / {math.ceil(scraper_input.results_wanted / self.jobs_per_page)} "
+                f"for search term: {scraper_input.search_term}"
+            )
+            params = {
+                "noOfResults": self.jobs_per_page,
+                "urlType": "search_by_keyword",
+                "searchType": "adv",
+                "keyword": scraper_input.search_term,
+                "pageNo": page,
+                "k": scraper_input.search_term,
+                "seoKey": f"{scraper_input.search_term.lower().replace(' ', '-')}-jobs",
+                "src": "jobsearchDesk",
+                "latLong": "",
+                "location": scraper_input.location,
+                "remote": "true" if scraper_input.is_remote else None,
+            }
+            if seconds_old:
+                params["days"] = seconds_old // 86400  # Convert to days
+
+            params = {k: v for k, v in params.items() if v is not None}
+            try:
+                log.debug(f"Sending request to {self.base_url} with params: {params}")
+                response = self.session.get(self.base_url, params=params, timeout=10)
+                if response.status_code not in range(200, 400):
+                    err = f"Naukri API response status code {response.status_code} - {response.text}"
+                    log.error(err)
+                    return JobResponse(jobs=job_list)
+                data = response.json()
+                job_details = data.get("jobDetails", [])
+                log.info(f"Received {len(job_details)} job entries from API")
+                if not job_details:
+                    log.warning("No job details found in API response")
+                    break
+            except Exception as e:
+                log.error(f"Naukri API request failed: {str(e)}")
+                return JobResponse(jobs=job_list)
+
+            for job in job_details:
+                job_id = job.get("jobId")
+                if not job_id or job_id in seen_ids:
+                    continue
+                seen_ids.add(job_id)
+                log.debug(f"Processing job ID: {job_id}")
+
+                try:
+                    fetch_desc = scraper_input.linkedin_fetch_description
+                    job_post = self._process_job(job, job_id, fetch_desc)
+                    if job_post:
+                        job_list.append(job_post)
+                        log.info(f"Added job: {job_post.title} (ID: {job_id})")
+                    if not continue_search():
+                        break
+                except Exception as e:
+                    log.error(f"Error processing job ID {job_id}: {str(e)}")
+                    raise NaukriException(str(e))
+
+            if continue_search():
+                time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
+                page += 1
+
+        job_list = job_list[:scraper_input.results_wanted]
+        log.info(f"Scraping completed. Total jobs collected: {len(job_list)}")
+        return JobResponse(jobs=job_list)
+
+    def _process_job(
+        self, job: dict, job_id: str, full_descr: bool
+    ) -> Optional[JobPost]:
+        """
+        Processes a single job from API response into a JobPost object
+        """
+        title = job.get("title", "N/A")
+        company = job.get("companyName", "N/A")
+        company_url = f"https://www.naukri.com/{job.get('staticUrl', '')}" if job.get("staticUrl") else None
+
+        location = self._get_location(job.get("placeholders", []))
+        compensation = self._get_compensation(job.get("placeholders", []))
+        date_posted = self._parse_date(job.get("footerPlaceholderLabel"), job.get("createdDate"))
+
+        job_url = f"https://www.naukri.com{job.get('jdURL', f'/job/{job_id}')}"
+        description = job.get("jobDescription") if full_descr else None
+        if description and self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
+            description = markdown_converter(description)
+
+        job_type = parse_job_type(description) if description else None
+        company_industry = parse_company_industry(description) if description else None
+        is_remote = is_job_remote(title, description or "", location)
+        company_logo = job.get("logoPathV3") or job.get("logoPath")
+
+        # Naukri-specific fields
+        skills = job.get("tagsAndSkills", "").split(",") if job.get("tagsAndSkills") else None
+        experience_range = job.get("experienceText")
+        ambition_box = job.get("ambitionBoxData", {})
+        company_rating = float(ambition_box.get("AggregateRating")) if ambition_box.get("AggregateRating") else None
+        company_reviews_count = ambition_box.get("ReviewsCount")
+        vacancy_count = job.get("vacancy")
+        work_from_home_type = self._infer_work_from_home_type(job.get("placeholders", []), title, description or "")
+
+        job_post = JobPost(
+            id=f"nk-{job_id}",
+            title=title,
+            company_name=company,
+            company_url=company_url,
+            location=location,
+            is_remote=is_remote,
+            date_posted=date_posted,
+            job_url=job_url,
+            compensation=compensation,
+            job_type=job_type,
+            company_industry=company_industry,
+            description=description,
+            emails=extract_emails_from_text(description or ""),
+            company_logo=company_logo,
+            skills=skills,
+            experience_range=experience_range,
+            company_rating=company_rating,
+            company_reviews_count=company_reviews_count,
+            vacancy_count=vacancy_count,
+            work_from_home_type=work_from_home_type,
+        )
+        log.debug(f"Processed job: {title} at {company}")
+        return job_post
+
+    def _get_location(self, placeholders: list[dict]) -> Location:
+        """
+        Extracts location data from placeholders
+        """
+        location = Location(country=Country.INDIA)
+        for placeholder in placeholders:
+            if placeholder.get("type") == "location":
+                location_str = placeholder.get("label", "")
+                parts = location_str.split(", ")
+                city = parts[0] if parts else None
+                state = parts[1] if len(parts) > 1 else None
+                location = Location(city=city, state=state, country=Country.INDIA)
+                log.debug(f"Parsed location: {location.display_location()}")
+                break
+        return location
+
+    def _get_compensation(self, placeholders: list[dict]) -> Optional[Compensation]:
+        """
+        Extracts compensation data from placeholders, handling Indian salary formats (Lakhs, Crores)
+        """
+        for placeholder in placeholders:
+            if placeholder.get("type") == "salary":
+                salary_text = placeholder.get("label", "").strip()
+                if salary_text == "Not disclosed":
+                    log.debug("Salary not disclosed")
+                    return None
+
+                # Handle Indian salary formats (e.g., "12-16 Lacs P.A.", "1-5 Cr")
+                salary_match = re.match(r"(\d+(?:\.\d+)?)\s*-\s*(\d+(?:\.\d+)?)\s*(Lacs|Lakh|Cr)\s*(P\.A\.)?", salary_text, re.IGNORECASE)
+                if salary_match:
+                    min_salary, max_salary, unit = salary_match.groups()[:3]
+                    min_salary, max_salary = float(min_salary), float(max_salary)
+                    currency = "INR"
+
+                    # Convert to base units (INR)
+                    if unit.lower() in ("lacs", "lakh"):
+                        min_salary *= 100000  # 1 Lakh = 100,000 INR
+                        max_salary *= 100000
+                    elif unit.lower() == "cr":
+                        min_salary *= 10000000  # 1 Crore = 10,000,000 INR
+                        max_salary *= 10000000
+
+                    log.debug(f"Parsed salary: {min_salary} - {max_salary} INR")
+                    return Compensation(
+                        min_amount=int(min_salary),
+                        max_amount=int(max_salary),
+                        currency=currency,
+                    )
+                else:
+                    log.debug(f"Could not parse salary: {salary_text}")
+                    return None
+        return None
+
+    def _parse_date(self, label: str, created_date: int) -> Optional[date]:
+        """
+        Parses date from footerPlaceholderLabel or createdDate, returning a date object
+        """
+        today = datetime.now()
+        if not label:
+            if created_date:
+                return datetime.fromtimestamp(created_date / 1000).date()  # Convert to date
+            return None
+        label = label.lower()
+        if "today" in label or "just now" in label or "few hours" in label:
+            log.debug("Date parsed as today")
+            return today.date()
+        elif "ago" in label:
+            match = re.search(r"(\d+)\s*day", label)
+            if match:
+                days = int(match.group(1))
+                parsed_date = (today - timedelta(days = days)).date()
+                log.debug(f"Date parsed: {days} days ago -> {parsed_date}")
+                return parsed_date
+        elif created_date:
+            parsed_date = datetime.fromtimestamp(created_date / 1000).date()
+            log.debug(f"Date parsed from timestamp: {parsed_date}")
+            return parsed_date
+        log.debug("No date parsed")
+        return None
+
+    def _infer_work_from_home_type(self, placeholders: list[dict], title: str, description: str) -> Optional[str]:
+        """
+        Infers work-from-home type from job data (e.g., 'Hybrid', 'Remote', 'Work from office')
+        """
+        location_str = next((p["label"] for p in placeholders if p["type"] == "location"), "").lower()
+        if "hybrid" in location_str or "hybrid" in title.lower() or "hybrid" in description.lower():
+            return "Hybrid"
+        elif "remote" in location_str or "remote" in title.lower() or "remote" in description.lower():
+            return "Remote"
+        elif "work from office" in description.lower() or not ("remote" in description.lower() or "hybrid" in description.lower()):
+            return "Work from office"
+        return None
--- a/jobspy/naukri/constant.py
+++ b/jobspy/naukri/constant.py
@@ -0,0 +1,11 @@
+headers = {
+    "authority": "www.naukri.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",
+    "appid": "109",
+    "systemid": "Naukri",
+    "Nkparam": "Ppy0YK9uSHqPtG3bEejYc04RTpUN2CjJOrqA68tzQt0SKJHXZKzz9M8cZtKLVkoOuQmfe4cTb1r2CwfHaxW5Tg==",
+    "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/jobspy/naukri/util.py
+++ b/jobspy/naukri/util.py
@@ -0,0 +1,34 @@
+from __future__ import annotations
+
+from bs4 import BeautifulSoup
+from jobspy.model import JobType, Location
+from jobspy.util import get_enum_from_job_type
+
+
+def parse_job_type(soup: BeautifulSoup) -> list[JobType] | None:
+    """
+    Gets the job type from the job page
+    """
+    job_type_tag = soup.find("span", class_="job-type")
+    if job_type_tag:
+        job_type_str = job_type_tag.get_text(strip=True).lower().replace("-", "")
+        return [get_enum_from_job_type(job_type_str)] if job_type_str else None
+    return None
+
+
+def parse_company_industry(soup: BeautifulSoup) -> str | None:
+    """
+    Gets the company industry from the job page
+    """
+    industry_tag = soup.find("span", class_="industry")
+    return industry_tag.get_text(strip=True) if industry_tag else None
+
+
+def is_job_remote(title: str, description: str, location: Location) -> bool:
+    """
+    Searches the title, description, and location to check if the job is remote
+    """
+    remote_keywords = ["remote", "work from home", "wfh"]
+    location_str = location.display_location()
+    full_string = f"{title} {description} {location_str}".lower()
+    return any(keyword in full_string for keyword in remote_keywords)
--- a/jobspy/util.py
+++ b/jobspy/util.py
@@ -0,0 +1,354 @@
+from __future__ import annotations
+
+import logging
+import re
+from itertools import cycle
+
+import numpy as np
+import requests
+import tls_client
+import urllib3
+from markdownify import markdownify as md
+from requests.adapters import HTTPAdapter, Retry
+
+from jobspy.model import CompensationInterval, JobType, Site
+
+urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
+
+
+def create_logger(name: str):
+    logger = logging.getLogger(f"JobSpy:{name}")
+    logger.propagate = False
+    if not logger.handlers:
+        logger.setLevel(logging.INFO)
+        console_handler = logging.StreamHandler()
+        format = "%(asctime)s - %(levelname)s - %(name)s - %(message)s"
+        formatter = logging.Formatter(format)
+        console_handler.setFormatter(formatter)
+        logger.addHandler(console_handler)
+    return logger
+
+
+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}
+        if proxy.startswith("socks5://"):
+            return {"http": proxy, "https": proxy}
+        return {"http": f"http://{proxy}", "https": f"http://{proxy}"}
+
+
+class RequestsRotating(RotatingProxySession, requests.Session):
+    def __init__(self, proxies=None, has_retry=False, delay=1, clear_cookies=False):
+        RotatingProxySession.__init__(self, proxies=proxies)
+        requests.Session.__init__(self)
+        self.clear_cookies = clear_cookies
+        self.allow_redirects = True
+        self.setup_session(has_retry, delay)
+
+    def setup_session(self, has_retry, delay):
+        if has_retry:
+            retries = Retry(
+                total=3,
+                connect=3,
+                status=3,
+                status_forcelist=[500, 502, 503, 504, 429],
+                backoff_factor=delay,
+            )
+            adapter = HTTPAdapter(max_retries=retries)
+            self.mount("http://", adapter)
+            self.mount("https://", adapter)
+
+    def request(self, method, url, **kwargs):
+        if self.clear_cookies:
+            self.cookies.clear()
+
+        if self.proxy_cycle:
+            next_proxy = next(self.proxy_cycle)
+            if next_proxy["http"] != "http://localhost":
+                self.proxies = next_proxy
+            else:
+                self.proxies = {}
+        return requests.Session.request(self, method, url, **kwargs)
+
+
+class TLSRotating(RotatingProxySession, tls_client.Session):
+    def __init__(self, proxies=None):
+        RotatingProxySession.__init__(self, proxies=proxies)
+        tls_client.Session.__init__(self, random_tls_extension_order=True)
+
+    def execute_request(self, *args, **kwargs):
+        if self.proxy_cycle:
+            next_proxy = next(self.proxy_cycle)
+            if next_proxy["http"] != "http://localhost":
+                self.proxies = next_proxy
+            else:
+                self.proxies = {}
+        response = tls_client.Session.execute_request(self, *args, **kwargs)
+        response.ok = response.status_code in range(200, 400)
+        return response
+
+
+def create_session(
+    *,
+    proxies: dict | str | None = None,
+    ca_cert: 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,
+        )
+
+    if ca_cert:
+        session.verify = ca_cert
+
+    return session
+
+
+def set_logger_level(verbose: int):
+    """
+    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:
+        for logger_name in logging.root.manager.loggerDict:
+            if logger_name.startswith("JobSpy:"):
+                logging.getLogger(logger_name).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)
+
+
+def remove_attributes(tag):
+    for attr in list(tag.attrs):
+        del tag[attr]
+    return tag
+
+
+def extract_salary(
+    salary_str,
+    lower_limit=1000,
+    upper_limit=700000,
+    hourly_threshold=350,
+    monthly_threshold=30000,
+    enforce_annual_salary=False,
+):
+    """
+    Extracts salary information from a string and returns the salary interval, min and max salary values, and currency.
+    (TODO: Needs test cases as the regex is complicated and may not cover all edge cases)
+    """
+    if not salary_str:
+        return None, None, None, None
+
+    annual_max_salary = None
+    min_max_pattern = r"\$(\d+(?:,\d+)?(?:\.\d+)?)([kK]?)\s*[-—–]\s*(?:\$)?(\d+(?:,\d+)?(?:\.\d+)?)([kK]?)"
+
+    def to_int(s):
+        return int(float(s.replace(",", "")))
+
+    def convert_hourly_to_annual(hourly_wage):
+        return hourly_wage * 2080
+
+    def convert_monthly_to_annual(monthly_wage):
+        return monthly_wage * 12
+
+    match = re.search(min_max_pattern, salary_str)
+
+    if match:
+        min_salary = to_int(match.group(1))
+        max_salary = to_int(match.group(3))
+        # Handle 'k' suffix for min and max salaries independently
+        if "k" in match.group(2).lower() or "k" in match.group(4).lower():
+            min_salary *= 1000
+            max_salary *= 1000
+
+        # Convert to annual if less than the hourly threshold
+        if min_salary < hourly_threshold:
+            interval = CompensationInterval.HOURLY.value
+            annual_min_salary = convert_hourly_to_annual(min_salary)
+            if max_salary < hourly_threshold:
+                annual_max_salary = convert_hourly_to_annual(max_salary)
+
+        elif min_salary < monthly_threshold:
+            interval = CompensationInterval.MONTHLY.value
+            annual_min_salary = convert_monthly_to_annual(min_salary)
+            if max_salary < monthly_threshold:
+                annual_max_salary = convert_monthly_to_annual(max_salary)
+
+        else:
+            interval = CompensationInterval.YEARLY.value
+            annual_min_salary = min_salary
+            annual_max_salary = max_salary
+
+        # Ensure salary range is within specified limits
+        if not annual_max_salary:
+            return None, None, None, None
+        if (
+            lower_limit <= annual_min_salary <= upper_limit
+            and lower_limit <= annual_max_salary <= upper_limit
+            and annual_min_salary < annual_max_salary
+        ):
+            if enforce_annual_salary:
+                return interval, annual_min_salary, annual_max_salary, "USD"
+            else:
+                return interval, min_salary, max_salary, "USD"
+    return None, None, None, None
+
+
+def extract_job_type(description: str):
+    if not description:
+        return []
+
+    keywords = {
+        JobType.FULL_TIME: r"full\s?time",
+        JobType.PART_TIME: r"part\s?time",
+        JobType.INTERNSHIP: r"internship",
+        JobType.CONTRACT: r"contract",
+    }
+
+    listing_types = []
+    for key, pattern in keywords.items():
+        if re.search(pattern, description, re.IGNORECASE):
+            listing_types.append(key)
+
+    return listing_types if listing_types else None
+
+
+def map_str_to_site(site_name: str) -> Site:
+    return Site[site_name.upper()]
+
+
+def get_enum_from_value(value_str):
+    for job_type in JobType:
+        if value_str in job_type.value:
+            return job_type
+    raise Exception(f"Invalid job type: {value_str}")
+
+
+def convert_to_annual(job_data: dict):
+    if job_data["interval"] == "hourly":
+        job_data["min_amount"] *= 2080
+        job_data["max_amount"] *= 2080
+    if job_data["interval"] == "monthly":
+        job_data["min_amount"] *= 12
+        job_data["max_amount"] *= 12
+    if job_data["interval"] == "weekly":
+        job_data["min_amount"] *= 52
+        job_data["max_amount"] *= 52
+    if job_data["interval"] == "daily":
+        job_data["min_amount"] *= 260
+        job_data["max_amount"] *= 260
+    job_data["interval"] = "yearly"
+
+
+desired_order = [
+    "id",
+    "site",
+    "job_url",
+    "job_url_direct",
+    "title",
+    "company",
+    "location",
+    "date_posted",
+    "job_type",
+    "salary_source",
+    "interval",
+    "min_amount",
+    "max_amount",
+    "currency",
+    "is_remote",
+    "job_level",
+    "job_function",
+    "listing_type",
+    "emails",
+    "description",
+    "company_industry",
+    "company_url",
+    "company_logo",
+    "company_url_direct",
+    "company_addresses",
+    "company_num_employees",
+    "company_revenue",
+    "company_description",
+    # naukri-specific fields
+    "skills",
+    "experience_range",
+    "company_rating",
+    "company_reviews_count",
+    "vacancy_count",
+    "work_from_home_type",
+]
--- a/src/jobspy/scrapers/ziprecruiter/init.py
+++ b/src/jobspy/scrapers/ziprecruiter/init.py
@@ -1,49 +1,54 @@
-"""
-jobspy.scrapers.ziprecruiter
-~~~~~~~~~~~~~~~~~~~
-
-This module contains routines to scrape ZipRecruiter.
-"""
-
 from __future__ import annotations

+import json
 import math
+import re
 import time
-from datetime import datetime
-from typing import Optional, Tuple, Any
-
 from concurrent.futures import ThreadPoolExecutor
+from datetime import datetime

-from .. import Scraper, ScraperInput, Site
-from ..utils import (
-    logger,
+from bs4 import BeautifulSoup
+
+from jobspy.ziprecruiter.constant import headers, get_cookie_data
+from jobspy.util import (
    extract_emails_from_text,
    create_session,
    markdown_converter,
+    remove_attributes,
+    create_logger,
 )
-from ...jobs import (
+from jobspy.model import (
    JobPost,
    Compensation,
    Location,
    JobResponse,
-    JobType,
    Country,
    DescriptionFormat,
+    Scraper,
+    ScraperInput,
+    Site,
 )
+from jobspy.ziprecruiter.util import get_job_type_enum, add_params
+
+log = create_logger("ZipRecruiter")


-class ZipRecruiterScraper(Scraper):
+class ZipRecruiter(Scraper):
    base_url = "https://www.ziprecruiter.com"
    api_url = "https://api.ziprecruiter.com"

-    def __init__(self, proxy: Optional[str] = None):
+    def __init__(
+        self, proxies: list[str] | str | None = None, ca_cert: str | None = None, user_agent: 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(proxy)
+        self.session = create_session(proxies=proxies, ca_cert=ca_cert)
+        self.session.headers.update(headers)
        self._get_cookies()
-        super().__init__(Site.ZIP_RECRUITER, proxy=proxy)

        self.delay = 5
        self.jobs_per_page = 20
@@ -65,7 +70,7 @@ class ZipRecruiterScraper(Scraper):
                break
            if page > 1:
                time.sleep(self.delay)
-            logger.info(f"ZipRecruiter search page: {page}")
+            log.info(f"search page: {page} / {max_pages}")
            jobs_on_page, continue_token = self._find_jobs_in_page(
                scraper_input, continue_token
            )
@@ -79,7 +84,7 @@ class ZipRecruiterScraper(Scraper):

    def _find_jobs_in_page(
        self, scraper_input: ScraperInput, continue_token: str | None = None
-    ) -> Tuple[list[JobPost], Optional[str]]:
+    ) -> tuple[list[JobPost], str | None]:
        """
        Scrapes a page of ZipRecruiter for jobs with scraper_input criteria
        :param scraper_input:
@@ -87,26 +92,24 @@ class ZipRecruiterScraper(Scraper):
        :return: jobs found on page
        """
        jobs_list = []
-        params = self._add_params(scraper_input)
+        params = add_params(scraper_input)
        if continue_token:
            params["continue_from"] = continue_token
        try:
-            res = self.session.get(
-                f"{self.api_url}/jobs-app/jobs", headers=self.headers, params=params
-            )
+            res = self.session.get(f"{self.api_url}/jobs-app/jobs", 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)
+                log.error(err)
                return jobs_list, ""
        except Exception as e:
            if "Proxy responded with" in str(e):
-                logger.error(f"Indeed: Bad proxy")
+                log.error(f"Indeed: Bad proxy")
            else:
-                logger.error(f"Indeed: {str(e)}")
+                log.error(f"Indeed: {str(e)}")
            return jobs_list, ""

        res_data = res.json()
@@ -129,6 +132,7 @@ class ZipRecruiterScraper(Scraper):
        self.seen_urls.add(job_url)

        description = job.get("job_description", "").strip()
+        listing_type = job.get("buyer_type", "")
        description = (
            markdown_converter(description)
            if self.scraper_input.description_format == DescriptionFormat.MARKDOWN
@@ -141,7 +145,7 @@ class ZipRecruiterScraper(Scraper):
        location = Location(
            city=job.get("job_city"), state=job.get("job_state"), country=country_enum
        )
-        job_type = self._get_job_type_enum(
+        job_type = get_job_type_enum(
            job.get("employment_type", "").replace("_", "").lower()
        )
        date_posted = datetime.fromisoformat(job["posted_time"].rstrip("Z")).date()
@@ -150,7 +154,10 @@ class ZipRecruiterScraper(Scraper):
        comp_min = int(job["compensation_min"]) if "compensation_min" in job else None
        comp_max = int(job["compensation_max"]) if "compensation_max" in job else None
        comp_currency = job.get("compensation_currency")
+        description_full, job_url_direct = self._get_descr(job_url)
+
        return JobPost(
+            id=f'zr-{job["listing_key"]}',
            title=title,
            company_name=company,
            location=location,
@@ -163,49 +170,50 @@ class ZipRecruiterScraper(Scraper):
            ),
            date_posted=date_posted,
            job_url=job_url,
-            description=description,
+            description=description_full if description_full else description,
            emails=extract_emails_from_text(description) if description else None,
+            job_url_direct=job_url_direct,
+            listing_type=listing_type,
        )

+    def _get_descr(self, job_url):
+        res = self.session.get(job_url, allow_redirects=True)
+        description_full = job_url_direct = None
+        if res.ok:
+            soup = BeautifulSoup(res.text, "html.parser")
+            job_descr_div = soup.find("div", class_="job_description")
+            company_descr_section = soup.find("section", class_="company_description")
+            job_description_clean = (
+                remove_attributes(job_descr_div).prettify(formatter="html")
+                if job_descr_div
+                else ""
+            )
+            company_description_clean = (
+                remove_attributes(company_descr_section).prettify(formatter="html")
+                if company_descr_section
+                else ""
+            )
+            description_full = job_description_clean + company_description_clean
+
+            try:
+                script_tag = soup.find("script", type="application/json")
+                if script_tag:
+                    job_json = json.loads(script_tag.string)
+                    job_url_val = job_json["model"].get("saveJobURL", "")
+                    m = re.search(r"job_url=(.+)", job_url_val)
+                    if m:
+                        job_url_direct = m.group(1)
+            except:
+                job_url_direct = None
+
+            if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
+                description_full = markdown_converter(description_full)
+
+        return description_full, job_url_direct
+
    def _get_cookies(self):
-        data = "event_type=session&logged_in=false&number_of_retry=1&property=model%3AiPhone&property=os%3AiOS&property=locale%3Aen_us&property=app_build_number%3A4734&property=app_version%3A91.0&property=manufacturer%3AApple&property=timestamp%3A2024-01-12T12%3A04%3A42-06%3A00&property=screen_height%3A852&property=os_version%3A16.6.1&property=source%3Ainstall&property=screen_width%3A393&property=device_model%3AiPhone%2014%20Pro&property=brand%3AApple"
+        """
+        Sends a session event to the API with device properties.
+        """
        url = f"{self.api_url}/jobs-app/event"
-        self.session.post(url, data=data, headers=self.headers)
-
-    @staticmethod
-    def _get_job_type_enum(job_type_str: str) -> list[JobType] | None:
-        for job_type in JobType:
-            if job_type_str in job_type.value:
-                return [job_type]
-        return None
-
-    @staticmethod
-    def _add_params(scraper_input) -> dict[str, str | Any]:
-        params = {
-            "search": scraper_input.search_term,
-            "location": scraper_input.location,
-        }
-        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:
-            job_type = scraper_input.job_type
-            params["employment_type"] = job_type_map.get(job_type, job_type.value[0])
-        if scraper_input.easy_apply:
-            params["zipapply"] = 1
-        if scraper_input.is_remote:
-            params["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}
-
-    headers = {
-        "Host": "api.ziprecruiter.com",
-        "accept": "*/*",
-        "x-zr-zva-override": "100000000;vid:ZT1huzm_EQlDTVEc",
-        "x-pushnotificationid": "0ff4983d38d7fc5b3370297f2bcffcf4b3321c418f5c22dd152a0264707602a0",
-        "x-deviceid": "D77B3A92-E589-46A4-8A39-6EF6F1D86006",
-        "user-agent": "Job Search/87.0 (iPhone; CPU iOS 16_6_1 like Mac OS X)",
-        "authorization": "Basic YTBlZjMyZDYtN2I0Yy00MWVkLWEyODMtYTI1NDAzMzI0YTcyOg==",
-        "accept-language": "en-US,en;q=0.9",
-    }
+        self.session.post(url, data=get_cookie_data)
--- a/jobspy/ziprecruiter/constant.py
+++ b/jobspy/ziprecruiter/constant.py
@@ -0,0 +1,29 @@
+headers = {
+    "Host": "api.ziprecruiter.com",
+    "accept": "*/*",
+    "x-zr-zva-override": "100000000;vid:ZT1huzm_EQlDTVEc",
+    "x-pushnotificationid": "0ff4983d38d7fc5b3370297f2bcffcf4b3321c418f5c22dd152a0264707602a0",
+    "x-deviceid": "D77B3A92-E589-46A4-8A39-6EF6F1D86006",
+    "user-agent": "Job Search/87.0 (iPhone; CPU iOS 16_6_1 like Mac OS X)",
+    "authorization": "Basic YTBlZjMyZDYtN2I0Yy00MWVkLWEyODMtYTI1NDAzMzI0YTcyOg==",
+    "accept-language": "en-US,en;q=0.9",
+}
+
+get_cookie_data = [
+    ("event_type", "session"),
+    ("logged_in", "false"),
+    ("number_of_retry", "1"),
+    ("property", "model:iPhone"),
+    ("property", "os:iOS"),
+    ("property", "locale:en_us"),
+    ("property", "app_build_number:4734"),
+    ("property", "app_version:91.0"),
+    ("property", "manufacturer:Apple"),
+    ("property", "timestamp:2025-01-12T12:04:42-06:00"),
+    ("property", "screen_height:852"),
+    ("property", "os_version:16.6.1"),
+    ("property", "source:install"),
+    ("property", "screen_width:393"),
+    ("property", "device_model:iPhone 14 Pro"),
+    ("property", "brand:Apple"),
+]
--- a/jobspy/ziprecruiter/util.py
+++ b/jobspy/ziprecruiter/util.py
@@ -0,0 +1,31 @@
+from jobspy.model import JobType
+
+
+def add_params(scraper_input) -> dict[str, str | int]:
+    params: dict[str, str | int] = {
+        "search": scraper_input.search_term,
+        "location": scraper_input.location,
+    }
+    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:
+        job_type = scraper_input.job_type
+        params["employment_type"] = job_type_map.get(job_type, job_type.value[0])
+
+    if scraper_input.easy_apply:
+        params["zipapply"] = 1
+    if scraper_input.is_remote:
+        params["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}
+
+
+def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
+    for job_type in JobType:
+        if job_type_str in job_type.value:
+            return [job_type]
+    return None
--- a/poetry.lock
+++ b/poetry.lock
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,35 +1,33 @@
+[build-system]
+requires = [ "poetry-core",]
+build-backend = "poetry.core.masonry.api"
+
 [tool.poetry]
 name = "python-jobspy"
-version = "1.1.50"
-description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
-authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
-homepage = "https://github.com/Bunsly/JobSpy"
+version = "1.1.82"
+description = "Job scraper for LinkedIn, Indeed, Glassdoor, ZipRecruiter & Bayt"
+authors = ["Cullen Watson <cullen@cullenwatson.com>", "Zachary Hampton <zachary@zacharysproducts.com>"]
+homepage = "https://github.com/cullenwatson/JobSpy"
 readme = "README.md"
+keywords = [ "jobs-scraper", "linkedin", "indeed", "glassdoor", "ziprecruiter", "bayt", "naukri"]
+[[tool.poetry.packages]]
+include = "jobspy"

-packages = [
-    { include = "jobspy", from = "src" }
-]
+[tool.black]
+line-length = 88

 [tool.poetry.dependencies]
 python = "^3.10"
 requests = "^2.31.0"
 beautifulsoup4 = "^4.12.2"
 pandas = "^2.1.0"
-NUMPY = "1.24.2"
+NUMPY = "1.26.3"
 pydantic = "^2.3.0"
 tls-client = "^1.0.1"
-markdownify = "^0.11.6"
-
+markdownify = "^0.13.1"
+regex = "^2024.4.28"

 [tool.poetry.group.dev.dependencies]
-pytest = "^7.4.1"
 jupyter = "^1.0.0"
-black = "^24.2.0"
-pre-commit = "^3.6.2"
-
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"
-
-[tool.black]
-line-length = 88
+black = "*"
+pre-commit = "*"
--- a/src/init.py
+++ b/src/init.py
--- a/src/jobspy/scrapers/init.py
+++ b/src/jobspy/scrapers/init.py
@@ -1,44 +0,0 @@
-from __future__ import annotations
-
-from ..jobs import (
-    Enum,
-    BaseModel,
-    JobType,
-    JobResponse,
-    Country,
-    DescriptionFormat,
-)
-
-
-class Site(Enum):
-    LINKEDIN = "linkedin"
-    INDEED = "indeed"
-    ZIP_RECRUITER = "zip_recruiter"
-    GLASSDOOR = "glassdoor"
-
-
-class ScraperInput(BaseModel):
-    site_type: list[Site]
-    search_term: str | None = None
-
-    location: str | None = None
-    country: Country | None = Country.USA
-    distance: int | None = None
-    is_remote: bool = False
-    job_type: JobType | None = None
-    easy_apply: bool | None = None
-    offset: int = 0
-    linkedin_fetch_description: bool = False
-    linkedin_company_ids: list[int] | None = None
-    description_format: DescriptionFormat | None = DescriptionFormat.MARKDOWN
-
-    results_wanted: int = 15
-    hours_old: int | None = None
-
-
-class Scraper:
-    def __init__(self, site: Site, proxy: list[str] | None = None):
-        self.site = site
-        self.proxy = (lambda p: {"http": p, "https": p} if p else None)(proxy)
-
-    def scrape(self, scraper_input: ScraperInput) -> JobResponse: ...
--- a/src/jobspy/scrapers/glassdoor/init.py
+++ b/src/jobspy/scrapers/glassdoor/init.py
@@ -1,534 +0,0 @@
-"""
-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, proxy: Optional[str] = None):
-        """
-        Initializes GlassdoorScraper with the Glassdoor job search url
-        """
-        site = Site(Site.GLASSDOOR)
-        super().__init__(site, proxy=proxy)
-
-        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(self.proxy, is_tls=True, has_retry=True)
-        token = self._get_csrf_token()
-        self.headers["gd-csrf-token"] = token if token else self.fallback_token
-
-        location_id, location_type = self._get_location(
-            scraper_input.location, scraper_input.is_remote
-        )
-        if location_type is None:
-            logger.error("Glassdoor: location not parsed")
-            return JobResponse(jobs=[])
-        all_jobs: list[JobPost] = []
-        cursor = None
-
-        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(
-            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}"
-        session = create_session(self.proxy, has_retry=True)
-        res = self.session.get(url, headers=self.headers)
-        if res.status_code != 200:
-            if res.status_code == 429:
-                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
@@ -1,424 +0,0 @@
-"""
-jobspy.scrapers.indeed
-~~~~~~~~~~~~~~~~~~~
-
-This module contains routines to scrape Indeed.
-"""
-
-from __future__ import annotations
-
-import math
-from typing import Tuple
-from datetime import datetime
-from concurrent.futures import ThreadPoolExecutor, Future
-
-import requests
-
-from .. import Scraper, ScraperInput, Site
-from ..utils import (
-    extract_emails_from_text,
-    get_enum_from_job_type,
-    markdown_converter,
-    logger,
-)
-from ...jobs import (
-    JobPost,
-    Compensation,
-    CompensationInterval,
-    Location,
-    JobResponse,
-    JobType,
-    DescriptionFormat,
-)
-
-
-class IndeedScraper(Scraper):
-    def __init__(self, proxy: str | None = None):
-        """
-        Initializes IndeedScraper with the Indeed API url
-        """
-        self.scraper_input = None
-        self.jobs_per_page = 100
-        self.num_workers = 10
-        self.seen_urls = set()
-        self.headers = None
-        self.api_country_code = None
-        self.base_url = None
-        self.api_url = "https://apis.indeed.com/graphql"
-        site = Site(Site.INDEED)
-        super().__init__(site, proxy=proxy)
-
-    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
-        """
-        Scrapes Indeed for jobs with scraper_input criteria
-        :param scraper_input:
-        :return: job_response
-        """
-        self.scraper_input = scraper_input
-        domain, self.api_country_code = self.scraper_input.country.indeed_domain_value
-        self.base_url = f"https://{domain}.indeed.com"
-        self.headers = self.api_headers.copy()
-        self.headers["indeed-co"] = self.scraper_input.country.indeed_domain_value
-        job_list = []
-        page = 1
-
-        cursor = None
-        offset_pages = math.ceil(self.scraper_input.offset / 100)
-        for _ in range(offset_pages):
-            logger.info(f"Indeed skipping search page: {page}")
-            __, cursor = self._scrape_page(cursor)
-            if not __:
-                logger.info(f"Indeed found no jobs on page: {page}")
-                break
-
-        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])
-
-    def _scrape_page(self, cursor: str | None) -> Tuple[list[JobPost], str | None]:
-        """
-        Scrapes a page of Indeed for jobs with scraper_input criteria
-        :param cursor:
-        :return: jobs found on page, next page cursor
-        """
-        jobs = []
-        new_cursor = None
-        filters = self._build_filters()
-        query = self.job_search_query.format(
-            what=(
-                f'what: "{self.scraper_input.search_term}"'
-                if self.scraper_input.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 = requests.post(
-            self.api_url,
-            headers=api_headers,
-            json=payload,
-            proxies=self.proxy,
-            timeout=10,
-        )
-        if response.status_code != 200:
-            logger.info(
-                f"Indeed responded with status code: {response.status_code} (submit GitHub issue if this appears to be a beg)"
-            )
-            return jobs, new_cursor
-        data = response.json()
-        jobs = data["data"]["jobSearch"]["results"]
-        new_cursor = data["data"]["jobSearch"]["pageInfo"]["nextCursor"]
-
-        with ThreadPoolExecutor(max_workers=self.num_workers) as executor:
-            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
-
-    def _build_filters(self):
-        """
-        Builds the filters dict for job type/is_remote. If hours_old is provided, composite filter for job_type/is_remote is not possible.
-        IndeedApply: filters: { keyword: { field: "indeedApplyScope", keys: ["DESKTOP"] } }
-        """
-        filters_str = ""
-        if self.scraper_input.hours_old:
-            filters_str = """
-            filters: {{
-                date: {{
-                  field: "dateOnIndeed",
-                  start: "{start}h"
-                }}
-            }}
-            """.format(
-                start=self.scraper_input.hours_old
-            )
-        elif self.scraper_input.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(
-            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(attributes: list) -> list[JobType]:
-        """
-        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:
-        :param job:
-        :return: compensation object
-        """
-        comp = job["compensation"]["baseSalary"]
-        if not comp:
-            return None
-        interval = IndeedScraper._get_compensation_interval(comp["unitOfWork"])
-        if not interval:
-            return None
-        min_range = comp["range"].get("min")
-        max_range = comp["range"].get("max")
-        return Compensation(
-            interval=interval,
-            min_amount=round(min_range, 2) if min_range is not None else None,
-            max_amount=round(max_range, 2) if max_range is not None else None,
-            currency=job["compensation"]["currencyCode"],
-        )
-
-    @staticmethod
-    def _is_job_remote(job: dict, description: str) -> bool:
-        """
-        Searches the description, location, and attributes to check if job is remote
-        """
-        remote_keywords = ["remote", "work from home", "wfh"]
-        is_remote_in_attributes = any(
-            any(keyword in attr["label"].lower() for keyword in remote_keywords)
-            for attr in job["attributes"]
-        )
-        is_remote_in_description = any(
-            keyword in description.lower() for keyword in remote_keywords
-        )
-        is_remote_in_location = any(
-            keyword in job["location"]["formatted"]["long"].lower()
-            for keyword in remote_keywords
-        )
-        return (
-            is_remote_in_attributes or is_remote_in_description or is_remote_in_location
-        )
-
-    @staticmethod
-    def _get_compensation_interval(interval: str) -> CompensationInterval:
-        interval_mapping = {
-            "DAY": "DAILY",
-            "YEAR": "YEARLY",
-            "HOUR": "HOURLY",
-            "WEEK": "WEEKLY",
-            "MONTH": "MONTHLY",
-        }
-        mapped_interval = interval_mapping.get(interval.upper(), None)
-        if mapped_interval and mapped_interval in CompensationInterval.__members__:
-            return CompensationInterval[mapped_interval]
-        else:
-            raise ValueError(f"Unsupported interval: {interval}")
-
-    api_headers = {
-        "Host": "apis.indeed.com",
-        "content-type": "application/json",
-        "indeed-api-key": "161092c2017b5bbab13edb12461a62d5a833871e7cad6d9d475304573de67ac8",
-        "accept": "application/json",
-        "indeed-locale": "en-US",
-        "accept-language": "en-US,en;q=0.9",
-        "user-agent": "Mozilla/5.0 (iPhone; CPU iPhone OS 16_6_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/15E148 Indeed App 193.1",
-        "indeed-app-info": "appv=193.1; appid=com.indeed.jobsearch; osv=16.6.1; os=ios; dtype=phone",
-    }
-    job_search_query = """
-        query GetJobData {{
-          jobSearch(
-            {what}
-            {location}
-            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/utils.py
+++ b/src/jobspy/scrapers/utils.py
@@ -1,96 +0,0 @@
-from __future__ import annotations
-
-import re
-import logging
-import requests
-import tls_client
-import numpy as np
-from markdownify import markdownify as md
-from requests.adapters import HTTPAdapter, Retry
-
-from ..jobs import JobType
-
-logger = logging.getLogger("JobSpy")
-logger.propagate = False
-if not logger.handlers:
-    logger.setLevel(logging.INFO)
-    console_handler = logging.StreamHandler()
-    format = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
-    formatter = logging.Formatter(format)
-    console_handler.setFormatter(formatter)
-    logger.addHandler(console_handler)
-
-
-def 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 create_session(
-    proxy: dict | None = None,
-    is_tls: bool = True,
-    has_retry: bool = False,
-    delay: int = 1,
-) -> requests.Session:
-    """
-    Creates a requests session with optional tls, proxy, and retry settings.
-    :return: A session object
-    """
-    if is_tls:
-        session = tls_client.Session(random_tls_extension_order=True)
-        session.proxies = proxy
-    else:
-        session = requests.Session()
-        session.allow_redirects = True
-        if proxy:
-            session.proxies.update(proxy)
-        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)
-
-            session.mount("http://", adapter)
-            session.mount("https://", adapter)
-    return session
-
-
-def get_enum_from_job_type(job_type_str: str) -> JobType | None:
-    """
-    Given a string, returns the corresponding JobType enum member if a match is found.
-    """
-    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/tests/init.py
+++ b/src/tests/init.py
--- a/src/tests/test_all.py
+++ b/src/tests/test_all.py
@@ -1,14 +0,0 @@
-from ..jobspy import scrape_jobs
-import pandas as pd
-
-
-def test_all():
-    result = scrape_jobs(
-        site_name=["linkedin", "indeed", "zip_recruiter", "glassdoor"],
-        search_term="software engineer",
-        results_wanted=5,
-    )
-
-    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
@@ -1,11 +0,0 @@
-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
@@ -1,11 +0,0 @@
-from ..jobspy import scrape_jobs
-import pandas as pd
-
-
-def test_indeed():
-    result = scrape_jobs(
-        site_name="indeed", 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_linkedin.py
+++ b/src/tests/test_linkedin.py
@@ -1,12 +0,0 @@
-from ..jobspy import scrape_jobs
-import pandas as pd
-
-
-def test_linkedin():
-    result = scrape_jobs(
-        site_name="linkedin",
-        search_term="software engineer",
-    )
-    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
@@ -1,13 +0,0 @@
-from ..jobspy import scrape_jobs
-import pandas as pd
-
-
-def test_ziprecruiter():
-    result = scrape_jobs(
-        site_name="zip_recruiter",
-        search_term="software engineer",
-    )
-
-    assert (
-        isinstance(result, pd.DataFrame) and not result.empty
-    ), "Result should be a non-empty DataFrame"
Author	SHA1	Message	Date
Cullen Watson	abd5878238	chore:readme	2025-07-28 17:15:09 +02:00
itsShrizon	ae2b1ea42c	Bdjobs Fixed (#280 )	2025-07-28 10:05:10 -05:00
Cullen Watson	53b3b41385	fix: glassdoor ua	2025-07-28 16:55:51 +02:00
Lê Trọng Tài	9aae02453d	issue#270: glassdoor 403 response by rotating user-agent and updating headers (#274 )	2025-07-28 09:55:05 -05:00
Piotr Geca	94d413bad1	support for socks5 proxies (#266 ) Co-authored-by: Piotr Geca <piotr.geca@npl.co.uk>	2025-04-10 15:53:28 -05:00
Cullen Watson	61205bcc77	chore: version	2025-03-27 21:59:47 -05:00
Nikhil Sasi	f1602eca70	Fix date parsing error: prevent negative days by using timedelta (#264 ) subtracting extracted "days" from label with current day causes negative days datetime class rejects negative day association Use timedelta for proper date limitation Co-authored-by: NIKHIL S <nikhil_s@nikhilMac.local>	2025-03-27 21:58:42 -05:00
Cullen Watson	d4d52d05f5	chore:version	2025-03-21 17:35:23 -05:00
Liju Thomas	0946cb3373	feat: add naukri.com support (#259 )	2025-03-21 17:23:07 -05:00
prudvisorra-aifa	051981689f	Update util.py (#256 )	2025-03-17 11:51:19 -05:00
Cullen Watson	903b7e6f1b	fix(linkedin):is remote	2025-03-06 13:38:28 -06:00
Cullen Watson	6782b9884e	fix:workflow	2025-03-01 14:49:31 -06:00
Cullen Watson	94c74d60f2	enh:workflow manual run	2025-03-01 14:47:24 -06:00
Cullen Watson	5463e5a664	chore:version	2025-03-01 14:38:25 -06:00
arkhy	ed139e7e6b	added missing EU countries and languages (#250 ) Co-authored-by: Kate Arkhangelskaya <ekar559e@tu-dresden.de>	2025-03-01 14:30:08 -06:00
Cullen Watson	5bd199d0a5	Merge branch 'main' of https://github.com/Bunsly/JobSpy	2025-02-21 14:15:06 -06:00
Cullen Watson	4ec308a302	refactor:organize code	2025-02-21 14:14:55 -06:00
Cullen Watson	7cb0c518fc	docs:readme	2025-02-21 12:53:59 -06:00
Cullen Watson	df70d4bc2e	minor	2025-02-21 12:35:31 -06:00
Cullen Watson	3006063875	enh:remove log by default	2025-02-21 12:31:04 -06:00
Abdulrahman Hisham	1be009b8bc	Adding Bayt.com Scraper to current codebase (#246 )	2025-02-21 12:29:54 -06:00
Cullen Watson	81ed9b3ddf	enh:remove log by default	2025-02-21 12:29:28 -06:00
Abdulrahman Al Muaitah	11a9e9a56a	Fixed Bayt scraper integration	2025-02-21 20:10:02 +04:00
Abdulrahman Al Muaitah	c6ade14784	Added Bayt Scraper integration	2025-02-21 15:31:29 +04:00
Cullen Watson	13c74a0fed	docs:readme	2025-02-09 13:42:18 -06:00
Cullen Watson	333e9e6760	docs:readme	2025-01-17 21:44:49 -06:00
github-actions	04032a0f91	Increment version	2024-12-04 22:55:06 +00:00
Cullen Watson	496896d0b5	enh:fix yml (#225 )	2024-12-04 16:54:52 -06:00
Cullen Watson	87ba1ad1bf	fix yml	2024-12-04 16:52:15 -06:00
Jason Geffner	4e7ac9a583	Fix Google job search (#223 ) The previous regex did not capture all expected matches in the returned content	2024-12-04 16:45:59 -06:00
Cullen Watson	e44d13e1cf	enh:auto update version	2024-12-04 16:29:38 -06:00
Cullen Watson	d52e366ef7	docs:readme	2024-11-26 15:51:26 -06:00
Cullen Watson	395ebf0017	docs:readme	2024-11-26 15:49:12 -06:00
Cullen Watson	63fddd9b7f	docs:readme	2024-11-26 15:48:22 -06:00
Cullen Watson	58956868ae	docs:readme	2024-11-26 15:47:10 -06:00
Cullen Watson	4fce836222	docs:readme	2024-10-28 03:53:59 -05:00
Cullen Watson	5ba25e7a7c	docs:readme	2024-10-28 03:42:19 -05:00
Cullen Watson	f7cb3e9206	docs:readme	2024-10-28 03:36:21 -05:00
Cullen Watson	3ad3f121f7	docs:readme	2024-10-28 03:34:52 -05:00
Cullen Watson	ff3c782912	docs:readme	2024-10-25 18:12:08 -05:00
Cullen Watson	338d854b96	fix(google): search (#216 )	2024-10-25 14:54:14 -05:00
Cullen Watson	811d4c40b4	chore:version	2024-10-24 15:28:25 -05:00
Cullen Watson	dba92d22c2	chore:version	2024-10-24 15:27:16 -05:00
Cullen Watson	10a3592a0f	docs:file	2024-10-24 15:26:49 -05:00
Cullen Watson	b7905cc756	docs:file	2024-10-24 15:24:18 -05:00
Cullen Watson	6867d58829	docs:readme	2024-10-24 15:22:31 -05:00
Cullen Watson	f6248c8386	enh: google jobs (#214 )	2024-10-24 15:19:40 -05:00
Cullen Watson	f395597fdd	fix(indeed): offset	2024-10-22 19:25:07 -05:00
Cullen Watson	6372e41bd9	chore:version	2024-10-20 00:19:31 -05:00
Olzhas Arystanov	6c869decb8	build(deps): bump markdownify to 0.13.1 (#211 )	2024-10-20 00:18:44 -05:00
Cullen Watson	9f4083380d	indeed:remove tpe (#210 )	2024-10-19 18:01:59 -05:00
Olzhas Arystanov	9207ab56f6	fix: extract tests out of src (#209 )	2024-10-19 16:56:38 -05:00
Cullen Watson	757a94853e	chore:version	2024-10-08 17:49:06 -05:00
Marcel Gozalbo Baró	6bc191d5c7	FEATURE: Add the "ca_cert" setting for providing a Certification Authority certificate in order to use proxies requiring it. (#204 )	2024-10-08 17:46:46 -05:00
Cullen Watson	0cc34287f7	fix:turkey	2024-10-02 01:31:00 -05:00
Anton Pikhteryev	923979093b	Add Malta for linkedin country support (#198 )	2024-09-19 20:41:22 -05:00
Cullen Watson	286f0e4487	docs:readme	2024-09-18 18:49:41 -05:00
Cullen Watson	f7b29d43a2	fix(indeed):sort relevance not date (#197 )	2024-09-18 18:42:25 -05:00
Cullen Watson	6f1490458c	fix key error (#186 )	2024-08-14 02:54:40 -05:00
Cullen Watson	6bb7d81ba8	change linkedin ep (#185 )	2024-08-14 02:39:43 -05:00
Cullen Watson	0e046432d1	fix:variable bug (#181 )	2024-08-05 12:47:55 -05:00
Cullen Watson	209e0e65b6	fix:malaysia indeed (#180 )	2024-08-03 22:48:53 -05:00
Cullen Watson	8570c0651e	fix:key error (#176 )	2024-07-21 13:05:18 -05:00
Cullen Watson	8678b0bbe4	enh: test on pr (#174 )	2024-07-19 14:25:25 -05:00
Cullen Watson	60d4d911c9	lock file (#173 )	2024-07-17 21:21:22 -05:00
Lluís Salord Quetglas	2a0cba8c7e	FEAT: Optional convertion to annual and know salary source (#170 )	2024-07-17 21:05:33 -05:00
Mason DePalma	de70189fa2	Update pyproject.toml (#172 ) Changed Numpy to the most recent version so the package can properly install	2024-07-17 20:54:08 -05:00
Cullen Watson	b55c0eb86d	docs:readme	2024-07-16 19:24:38 -05:00
Cullen Watson	88c95c4ad5	enh: estimated salary (#169 )	2024-07-16 19:20:34 -05:00
Cullen Watson	d8d33d602f	docs: readme	2024-07-15 21:30:11 -05:00
Cullen Watson	6330c14879	minor fix	2024-07-15 21:19:01 -05:00
Ali Bakhshi Ilani	48631ea271	Add company industry and job level to linkedin scraper (#166 )	2024-07-15 21:07:39 -05:00
Cullen Watson	edffe18e65	enh: listing source (#168 )	2024-07-15 20:30:04 -05:00
Lluís Salord Quetglas	0988230a24	FEAT: Add Glassdoor logo data if available (#167 )	2024-07-15 20:25:18 -05:00
Cullen Watson	d000a81eb3	Salary parse (#163 )	2024-06-09 17:45:38 -05:00
Cullen Watson	ccb0c17660	enh: ziprecruiter full description (#162 )	2024-06-09 16:21:01 -05:00
Cullen Watson	df339610fa	docs: readme	2024-05-29 19:32:32 -05:00
Cullen Watson	c501006bd8	docs: readme	2024-05-28 16:04:26 -05:00
Cullen Watson	89a3ee231c	enh(li): job function (#160 )	2024-05-28 16:01:29 -05:00
Cullen	6439f71433	chore: version	2024-05-28 15:39:24 -05:00
adamagassi	7f6271b2e0	LinkedIn scraper fixes: (#159 ) Correct initial page offset calculation Separate page variable from request counter Fix job offset starting value Increment offset by number of jobs returned instead of expected value	2024-05-28 15:38:13 -05:00
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