docs:readme

minor
enh:remove log by default
2026-03-05 12:04:33 -08:00 · 2025-02-21 12:53:59 -06:00 · 2025-02-21 12:35:31 -06:00 · 2025-02-21 12:31:04 -06:00 · 2025-02-21 12:29:54 -06:00 · 2025-02-21 12:29:28 -06:00
32 changed files with 3431 additions and 2188 deletions
--- a/.github/workflows/publish-to-pypi.yml
+++ b/.github/workflows/publish-to-pypi.yml
@@ -1,33 +1,50 @@
 name: Publish Python 🐍 distributions 📦 to PyPI
-on: push
+on:
+  pull_request:
+    types:
+      - closed
+
+permissions:
+  contents: write

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

+    if: github.event.pull_request.merged == true && github.event.pull_request.base.ref == 'main'
+
    steps:
      - uses: actions/checkout@v3
+
      - name: Set up Python
        uses: actions/setup-python@v4
        with:
          python-version: "3.10"

+      - name: Install dependencies
+        run: pip install toml
+
+      - name: Increment version
+        run: python increment_version.py
+
+      - name: Commit version increment
+        run: |
+          git config --global user.name 'github-actions'
+          git config --global user.email 'github-actions@github.com'
+          git add pyproject.toml
+          git commit -m 'Increment version'
+
+      - name: Push changes
+        run: git push
+
      - name: Install poetry
-        run: >-
-          python3 -m
-          pip install
-          poetry
-          --user
+        run: pip install poetry --user

      - name: Build distribution 📦
-        run: >-
-          python3 -m
-          poetry
-          build
+        run: poetry build

      - name: Publish distribution 📦 to PyPI
-        if: startsWith(github.ref, 'refs/tags')
        uses: pypa/gh-action-pypi-publish@release/v1
        with:
-          password: ${{ secrets.PYPI_API_TOKEN }}
+          password: ${{ secrets.PYPI_API_TOKEN }}
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -0,0 +1,7 @@
+repos:
+- repo: https://github.com/psf/black
+  rev: 24.2.0
+  hooks:
+  - id: black
+    language_version: python
+    args: [--line-length=88, --quiet]
--- a/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**, & **Bayt** 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)

@@ -33,22 +25,26 @@ import csv
 from jobspy import scrape_jobs

 jobs = scrape_jobs(
-    site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"],
+    site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor", "google", "bayt"],
    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 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...
@@ -60,66 +56,84 @@ zip_recruiter Software Developer                 TEKsystems        Phoenix
 ### 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
+|    (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
-├── 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)
+│
+├── 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 +165,84 @@ 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 can only fetch 900 jobs from the endpoint we're using on a given search.  
-* LinkedIn is the most restrictive and usually rate limits on around the 10th page  
-* ZipRecruiter is okay but has a 5 second delay in between each page to avoid rate limiting.
+* 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
+├── 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
+└── is_remote
+
+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
+```
--- 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/increment_version.py
+++ b/increment_version.py
@@ -0,0 +1,21 @@
+import toml
+
+def increment_version(version):
+    major, minor, patch = map(int, version.split('.'))
+    patch += 1
+    return f"{major}.{minor}.{patch}"
+
+# Load pyproject.toml
+with open('pyproject.toml', 'r') as file:
+    pyproject = toml.load(file)
+
+# Increment the version
+current_version = pyproject['tool']['poetry']['version']
+new_version = increment_version(current_version)
+pyproject['tool']['poetry']['version'] = new_version
+
+# Save the updated pyproject.toml
+with open('pyproject.toml', 'w') as file:
+    toml.dump(pyproject, file)
+
+print(f"Version updated from {current_version} to {new_version}")
--- a/poetry.lock
+++ b/poetry.lock
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,30 +1,35 @@
+[build-system]
+requires = [ "poetry-core",]
+build-backend = "poetry.core.masonry.api"
+
 [tool.poetry]
 name = "python-jobspy"
-version = "1.1.48"
+version = "1.1.76"
 description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
-authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
+authors = [ "Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>",]
 homepage = "https://github.com/Bunsly/JobSpy"
 readme = "README.md"
+keywords = [ "jobs-scraper", "linkedin", "indeed", "glassdoor", "ziprecruiter",]
+[[tool.poetry.packages]]
+include = "jobspy"
+from = "src"

-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"
-
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"
+black = "*"
+pre-commit = "*"
--- a/src/init.py
+++ b/src/init.py
--- a/src/jobspy/init.py
+++ b/src/jobspy/init.py
@@ -1,25 +1,31 @@
+from __future__ import annotations
+
 import pandas as pd
 from typing import Tuple
 from concurrent.futures import ThreadPoolExecutor, as_completed

 from .jobs import JobType, Location
-from .scrapers.utils import logger
+from .scrapers.utils import set_logger_level, extract_salary, create_logger
 from .scrapers.indeed import IndeedScraper
 from .scrapers.ziprecruiter import ZipRecruiterScraper
 from .scrapers.glassdoor import GlassdoorScraper
+from .scrapers.google import GoogleJobsScraper
 from .scrapers.linkedin import LinkedInScraper
-from .scrapers import ScraperInput, Site, JobResponse, Country
+from .scrapers.bayt import BaytScraper
+from .scrapers import SalarySource, ScraperInput, Site, JobResponse, Country
 from .scrapers.exceptions import (
    LinkedInException,
    IndeedException,
    ZipRecruiterException,
    GlassdoorException,
+    GoogleJobsException,
 )


 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,
@@ -28,24 +34,30 @@ def scrape_jobs(
    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,
    **kwargs,
 ) -> pd.DataFrame:
    """
    Simultaneously scrapes job data from multiple job sites.
-    :return: results_wanted: pandas dataframe containing job data
+    :return: pandas dataframe containing job data
    """
    SCRAPER_MAPPING = {
        Site.LINKEDIN: LinkedInScraper,
        Site.INDEED: IndeedScraper,
        Site.ZIP_RECRUITER: ZipRecruiterScraper,
        Site.GLASSDOOR: GlassdoorScraper,
+        Site.GOOGLE: GoogleJobsScraper,
+        Site.BAYT: BaytScraper,
    }
+    set_logger_level(verbose)

    def map_str_to_site(site_name: str) -> Site:
        return Site[site_name.upper()]
@@ -70,12 +82,14 @@ def scrape_jobs(
                for site in site_name
            ]
        return site_types
+
    country_enum = Country.from_string(country_indeed)

    scraper_input = ScraperInput(
        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,
@@ -86,15 +100,16 @@ def scrape_jobs(
        results_wanted=results_wanted,
        linkedin_company_ids=linkedin_company_ids,
        offset=offset,
-        hours_old=hours_old
+        hours_old=hours_old,
    )

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

    site_to_jobs_dict = {}
@@ -112,14 +127,28 @@ def scrape_jobs(
            site_value, scraped_data = future.result()
            site_to_jobs_dict[site_value] = scraped_data

+    def convert_to_annual(job_data: dict):
+        if job_data["interval"] == "hourly":
+            job_data["min_amount"] *= 2080
+            job_data["max_amount"] *= 2080
+        if job_data["interval"] == "monthly":
+            job_data["min_amount"] *= 12
+            job_data["max_amount"] *= 12
+        if job_data["interval"] == "weekly":
+            job_data["min_amount"] *= 52
+            job_data["max_amount"] *= 52
+        if job_data["interval"] == "daily":
+            job_data["min_amount"] *= 260
+            job_data["max_amount"] *= 260
+        job_data["interval"] = "yearly"
+
    jobs_dfs: list[pd.DataFrame] = []

    for site, job_response in site_to_jobs_dict.items():
        for job in job_response.jobs:
            job_data = job.dict()
-            job_data[
-                "job_url_hyper"
-            ] = f'<a href="{job_data["job_url"]}">{job_data["job_url"]}</a>'
+            job_url = job_data["job_url"]
+            job_data["job_url_hyper"] = f'<a href="{job_url}">{job_url}</a>'
            job_data["site"] = site
            job_data["company"] = job_data["company_name"]
            job_data["job_type"] = (
@@ -145,62 +174,86 @@ 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")
-            else:
-                job_data["interval"] = None
-                job_data["min_amount"] = None
-                job_data["max_amount"] = None
-                job_data["currency"] = None
+                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:
+                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
+            )
            job_df = pd.DataFrame([job_data])
            jobs_dfs.append(job_df)

    if jobs_dfs:
        # Step 1: Filter out all-NA columns from each DataFrame before concatenation
-        filtered_dfs = [df.dropna(axis=1, how='all') for df in jobs_dfs]
-        
+        filtered_dfs = [df.dropna(axis=1, how="all") for df in jobs_dfs]
+
        # Step 2: Concatenate the filtered DataFrames
        jobs_df = pd.concat(filtered_dfs, ignore_index=True)
-        
+
        # Desired column order
        desired_order = [
+            "id",
            "site",
            "job_url_hyper" if hyperlinks else "job_url",
            "job_url_direct",
            "title",
            "company",
            "location",
-            "job_type",
            "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_industry",
            "company_num_employees",
            "company_revenue",
            "company_description",
-            "logo_photo_url",
-            "banner_photo_url",
-            "ceo_name",
-            "ceo_photo_url",
        ]
-        
+
        # Step 3: Ensure all desired columns are present, adding missing ones as empty
        for column in desired_order:
            if column not in jobs_df.columns:
                jobs_df[column] = None  # Add missing columns as empty
-        
+
        # Reorder the DataFrame according to the desired order
        jobs_df = jobs_df[desired_order]
-        
+
        # Step 4: Sort the DataFrame as required
-        return jobs_df.sort_values(by=['site', 'date_posted'], ascending=[True, False])
+        return jobs_df.sort_values(
+            by=["site", "date_posted"], ascending=[True, False]
+        ).reset_index(drop=True)
    else:
        return pd.DataFrame()
--- a/src/jobspy/jobs/init.py
+++ b/src/jobspy/jobs/init.py
@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from typing import Optional
 from datetime import date
 from enum import Enum
@@ -90,7 +92,8 @@ class Country(Enum):
    JAPAN = ("japan", "jp")
    KUWAIT = ("kuwait", "kw")
    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")
@@ -115,7 +118,7 @@ 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")
@@ -156,7 +159,7 @@ class Country(Enum):
        """Convert a string to the corresponding Country enum."""
        country_str = country_str.strip().lower()
        for country in cls:
-            country_names = country.value[0].split(',')
+            country_names = country.value[0].split(",")
            if country_str in country_names:
                return country
        valid_countries = [country.value for country in cls]
@@ -178,7 +181,10 @@ class Location(BaseModel):
            location_parts.append(self.state)
        if isinstance(self.country, str):
            location_parts.append(self.country)
-        elif self.country and self.country not in (Country.US_CANADA, Country.WORLDWIDE):
+        elif self.country and self.country not in (
+            Country.US_CANADA,
+            Country.WORLDWIDE,
+        ):
            country_name = self.country.value[0]
            if "," in country_name:
                country_name = country_name.split(",")[0]
@@ -221,6 +227,7 @@ class DescriptionFormat(Enum):


 class JobPost(BaseModel):
+    id: str | None = None
    title: str
    company_name: str | None
    job_url: str
@@ -236,18 +243,25 @@ class JobPost(BaseModel):
    date_posted: date | None = None
    emails: list[str] | None = None
    is_remote: bool | None = None
+    listing_type: str | None = None
+
+    # linkedin specific
+    job_level: str | None = None
+
+    # linkedin and indeed specific
+    company_industry: str | None = None

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

+    # linkedin only atm
+    job_function: str | None = None
+

 class JobResponse(BaseModel):
    jobs: list[JobPost] = []
--- a/src/jobspy/scrapers/init.py
+++ b/src/jobspy/scrapers/init.py
@@ -1,10 +1,14 @@
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+
 from ..jobs import (
    Enum,
    BaseModel,
    JobType,
    JobResponse,
    Country,
-    DescriptionFormat
+    DescriptionFormat,
 )


@@ -13,11 +17,19 @@ class Site(Enum):
    INDEED = "indeed"
    ZIP_RECRUITER = "zip_recruiter"
    GLASSDOOR = "glassdoor"
+    GOOGLE = "google"
+    BAYT = "bayt"
+
+
+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
@@ -34,9 +46,13 @@ class ScraperInput(BaseModel):
    hours_old: int | None = None


-class Scraper:
-    def __init__(self, site: Site, proxy: list[str] | None = None):
+class Scraper(ABC):
+    def __init__(
+        self, site: Site, proxies: list[str] | None = None, ca_cert: str | None = None
+    ):
        self.site = site
-        self.proxy = (lambda p: {"http": p, "https": p} if p else None)(proxy)
+        self.proxies = proxies
+        self.ca_cert = ca_cert

+    @abstractmethod
    def scrape(self, scraper_input: ScraperInput) -> JobResponse: ...
--- a/src/jobspy/scrapers/bayt/init.py
+++ b/src/jobspy/scrapers/bayt/init.py
@@ -0,0 +1,145 @@
+"""
+jobspy.scrapers.bayt
+~~~~~~~~~~~~~~~~~~~
+
+This module contains routines to scrape Bayt.
+"""
+
+from __future__ import annotations
+
+import random
+import time
+
+from bs4 import BeautifulSoup
+
+from .. import Scraper, ScraperInput, Site
+from ..utils import create_logger, create_session
+from ...jobs import JobPost, JobResponse, Location, Country
+
+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
+    ):
+        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/src/jobspy/scrapers/exceptions.py
+++ b/src/jobspy/scrapers/exceptions.py
@@ -24,3 +24,13 @@ 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")
--- a/src/jobspy/scrapers/glassdoor/init.py
+++ b/src/jobspy/scrapers/glassdoor/init.py
@@ -4,21 +4,23 @@ jobspy.scrapers.glassdoor

 This module contains routines to scrape Glassdoor.
 """
-import json
-import re

+from __future__ import annotations
+
+import re
+import json
 import requests
-from typing import Optional
+from typing import Optional, Tuple
 from datetime import datetime, timedelta
 from concurrent.futures import ThreadPoolExecutor, as_completed
-from ..utils import extract_emails_from_text

+from .constants import fallback_token, query_template, headers
 from .. import Scraper, ScraperInput, Site
+from ..utils import extract_emails_from_text, create_logger
 from ..exceptions import GlassdoorException
 from ..utils import (
    create_session,
    markdown_converter,
-    logger
 )
 from ...jobs import (
    JobPost,
@@ -27,17 +29,21 @@ from ...jobs import (
    Location,
    JobResponse,
    JobType,
-    DescriptionFormat
+    DescriptionFormat,
 )

+log = create_logger("Glassdoor")
+

 class GlassdoorScraper(Scraper):
-    def __init__(self, proxy: Optional[str] = None):
+    def __init__(
+        self, proxies: list[str] | str | None = None, ca_cert: str | None = None
+    ):
        """
        Initializes GlassdoorScraper with the Glassdoor job search url
        """
        site = Site(Site.GLASSDOOR)
-        super().__init__(site, proxy=proxy)
+        super().__init__(site, proxies=proxies, ca_cert=ca_cert)

        self.base_url = None
        self.country = None
@@ -57,39 +63,39 @@ class GlassdoorScraper(Scraper):
        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)
+        self.session = create_session(
+            proxies=self.proxies, ca_cert=self.ca_cert, has_retry=True
+        )
        token = self._get_csrf_token()
-        self.headers['gd-csrf-token'] = token if token else self.fallback_token
+        headers["gd-csrf-token"] = token if token else fallback_token
+        self.session.headers.update(headers)

        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')
+            log.error("Glassdoor: location not parsed")
            return JobResponse(jobs=[])
-        all_jobs: list[JobPost] = []
+        job_list: list[JobPost] = []
        cursor = None

-        for page in range(
-            1 + (scraper_input.offset // self.jobs_per_page),
-            min(
-                (scraper_input.results_wanted // self.jobs_per_page) + 2,
-                self.max_pages + 1,
-            ),
-        ):
-            logger.info(f'Glassdoor search page: {page}')
+        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
                )
-                all_jobs.extend(jobs)
-                if not jobs or len(all_jobs) >= scraper_input.results_wanted:
-                    all_jobs = all_jobs[: scraper_input.results_wanted]
+                job_list.extend(jobs)
+                if not jobs or len(job_list) >= scraper_input.results_wanted:
+                    job_list = job_list[: scraper_input.results_wanted]
                    break
            except Exception as e:
-                logger.error(f'Glassdoor: {str(e)}')
+                log.error(f"Glassdoor: {str(e)}")
                break
-        return JobResponse(jobs=all_jobs)
+        return JobResponse(jobs=job_list)

    def _fetch_jobs_page(
        self,
@@ -98,39 +104,47 @@ class GlassdoorScraper(Scraper):
        location_type: str,
        page_num: int,
        cursor: str | None,
-    ) -> (list[JobPost], 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
-            )
+            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
+                f"{self.base_url}/graph",
+                timeout_seconds=15,
+                data=payload,
            )
            if response.status_code != 200:
-                raise GlassdoorException(f"bad response status code: {response.status_code}")
+                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)}')
+        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}
+            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}')
+                    raise GlassdoorException(f"Glassdoor generated an exception: {exc}")

        return jobs, self.get_cursor_for_page(
            res_json["data"]["jobListings"]["paginationCursors"], page_num + 1
@@ -140,7 +154,7 @@ class GlassdoorScraper(Scraper):
        """
        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)
+        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
@@ -153,19 +167,20 @@ class GlassdoorScraper(Scraper):
        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}'
+        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']
+        company_id = job_data["jobview"]["header"]["employer"]["id"]
        location_name = job["header"].get("locationName", "")
        location_type = job["header"].get("locationType", "")
        age_in_days = job["header"].get("ageInDays")
        is_remote, location = False, None
-        date_posted = (datetime.now() - timedelta(days=age_in_days)).date() if age_in_days is not None else 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
@@ -177,9 +192,20 @@ class GlassdoorScraper(Scraper):
            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=f"{self.base_url}Overview/W-EI_IE{company_id}.htm" if company_id else None,
+            company_url=company_url if company_id else None,
            company_name=company_name,
            date_posted=date_posted,
            job_url=job_url,
@@ -188,6 +214,8 @@ class GlassdoorScraper(Scraper):
            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):
@@ -201,7 +229,7 @@ class GlassdoorScraper(Scraper):
                "variables": {
                    "jl": job_id,
                    "queryString": "q",
-                    "pageTypeEnum": "SERP"
+                    "pageTypeEnum": "SERP",
                },
                "query": """
                query JobDetailQuery($jl: Long!, $queryString: String, $pageTypeEnum: PageTypeEnum) {
@@ -216,28 +244,32 @@ class GlassdoorScraper(Scraper):
                        __typename
                    }
                }
-                """
+                """,
            }
        ]
-        res = requests.post(url, json=body, headers=self.headers)
+        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']
-        return markdown_converter(desc) if self.scraper_input.description_format == DescriptionFormat.MARKDOWN else desc
+        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)
+        res = self.session.get(url)
        if res.status_code != 200:
            if res.status_code == 429:
-                logger.error(f'429 Response - Blocked by Glassdoor for too many requests')
+                err = f"429 Response - Blocked by Glassdoor for too many requests"
+                log.error(err)
                return None, None
            else:
-                logger.error(f'Glassdoor response status code {res.status_code}')
+                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()

@@ -248,7 +280,7 @@ class GlassdoorScraper(Scraper):
            location_type = "CITY"
        elif location_type == "S":
            location_type = "STATE"
-        elif location_type == 'N':
+        elif location_type == "N":
            location_type = "COUNTRY"
        return int(items[0]["locationId"]), location_type

@@ -259,7 +291,9 @@ class GlassdoorScraper(Scraper):
        page_num: int,
        cursor: str | None = None,
    ) -> str:
-        fromage = max(self.scraper_input.hours_old // 24, 1) if self.scraper_input.hours_old else None
+        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"})
@@ -278,9 +312,9 @@ class GlassdoorScraper(Scraper):
                "pageNumber": page_num,
                "pageCursor": cursor,
                "fromage": fromage,
-                "sort": "date"
+                "sort": "date",
            },
-            "query": self.query_template
+            "query": query_template,
        }
        if self.scraper_input.job_type:
            payload["variables"]["filterParams"].append(
@@ -328,188 +362,3 @@ class GlassdoorScraper(Scraper):
        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/glassdoor/constants.py
+++ b/src/jobspy/scrapers/glassdoor/constants.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/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
+        }
+"""
+fallback_token = "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok"
--- a/src/jobspy/scrapers/google/init.py
+++ b/src/jobspy/scrapers/google/init.py
@@ -0,0 +1,247 @@
+"""
+jobspy.scrapers.google
+~~~~~~~~~~~~~~~~~~~
+
+This module contains routines to scrape Google.
+"""
+
+from __future__ import annotations
+
+import math
+import re
+import json
+from typing import Tuple
+from datetime import datetime, timedelta
+
+from .constants import headers_jobs, headers_initial, async_param
+from .. import Scraper, ScraperInput, Site
+from ..utils import extract_emails_from_text, create_logger, extract_job_type
+from ..utils import (
+    create_session,
+)
+from ...jobs import (
+    JobPost,
+    JobResponse,
+    Location,
+    JobType,
+)
+
+log = create_logger("Google")
+
+
+class GoogleJobsScraper(Scraper):
+    def __init__(
+        self, proxies: list[str] | str | None = None, ca_cert: 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 = self._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 = self._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
+
+    @staticmethod
+    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 = GoogleJobsScraper._find_job_info(value)
+                    if result:
+                        return result
+        elif isinstance(jobs_data, list):
+            for item in jobs_data:
+                result = GoogleJobsScraper._find_job_info(item)
+                if result:
+                    return result
+        return None
+
+    @staticmethod
+    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/src/jobspy/scrapers/google/constants.py
+++ b/src/jobspy/scrapers/google/constants.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/src/jobspy/scrapers/indeed/init.py
+++ b/src/jobspy/scrapers/indeed/init.py
@@ -4,18 +4,21 @@ jobspy.scrapers.indeed

 This module contains routines to scrape Indeed.
 """
+
+from __future__ import annotations
+
 import math
-from concurrent.futures import ThreadPoolExecutor, Future
+from typing import Tuple
 from datetime import datetime

-import requests
-
+from .constants import job_search_query, api_headers
 from .. import Scraper, ScraperInput, Site
 from ..utils import (
    extract_emails_from_text,
    get_enum_from_job_type,
    markdown_converter,
-    logger
+    create_session,
+    create_logger,
 )
 from ...jobs import (
    JobPost,
@@ -24,15 +27,24 @@ from ...jobs import (
    Location,
    JobResponse,
    JobType,
-    DescriptionFormat
+    DescriptionFormat,
 )

+log = create_logger("Indeed")
+

 class IndeedScraper(Scraper):
-    def __init__(self, proxy: str | None = None):
+    def __init__(
+        self, proxies: list[str] | str | None = None, ca_cert: 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
@@ -41,8 +53,6 @@ class IndeedScraper(Scraper):
        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:
        """
@@ -53,31 +63,31 @@ class IndeedScraper(Scraper):
        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
+        self.headers = 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}')
+        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:
-                logger.info(f'Indeed found no jobs on page: {page}')
+                log.info(f"found no jobs on page: {page}")
                break
            job_list += jobs
            page += 1
-        return JobResponse(jobs=job_list[:scraper_input.results_wanted])
+        return JobResponse(
+            jobs=job_list[
+                scraper_input.offset : scraper_input.offset
+                + scraper_input.results_wanted
+            ]
+        )

-    def _scrape_page(self, cursor: str | None) -> (list[JobPost], str | None):
+    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:
@@ -86,32 +96,49 @@ class IndeedScraper(Scraper):
        jobs = []
        new_cursor = None
        filters = self._build_filters()
-        query = self.job_search_query.format(
-            what=self.scraper_input.search_term,
-            location=self.scraper_input.location if self.scraper_input.location else self.scraper_input.country.value[0].split(',')[-1],
-            radius=self.scraper_input.distance,
+        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
+            cursor=f'cursor: "{cursor}"' if cursor else "",
+            filters=filters,
        )
        payload = {
-            'query': query,
+            "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)')
+        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']
+        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)

-        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):
@@ -128,7 +155,18 @@ class IndeedScraper(Scraper):
                  start: "{start}h"
                }}
            }}
-            """.format(start=self.scraper_input.hours_old)
+            """.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",
@@ -146,7 +184,7 @@ class IndeedScraper(Scraper):
                keys.append("DSQF7")

            if keys:
-                keys_str = '", "'.join(keys)  # Prepare your keys string
+                keys_str = '", "'.join(keys)
                filters_str = f"""
                filters: {{
                  composite: {{
@@ -171,45 +209,61 @@ class IndeedScraper(Scraper):
        if job_url in self.seen_urls:
            return
        self.seen_urls.add(job_url)
-        description = job['description']['html']
-        description = markdown_converter(description) if self.scraper_input.description_format == DescriptionFormat.MARKDOWN else description
+        description = job["description"]["html"]
+        if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
+            description = markdown_converter(description)

-        job_type = self._get_job_type(job['attributes'])
+        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 {}
+        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}{job['employer']['relativeCompanyPageUrl']}" if job[
-                'employer'] else None,
-            company_url_direct=employer['links']['corporateWebsite'] if employer else None,
-
+            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),
+            compensation=self._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,
+            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,
+            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
+            ),
        )

    @staticmethod
@@ -221,47 +275,64 @@ class IndeedScraper(Scraper):
        """
        job_types: list[JobType] = []
        for attribute in attributes:
-            job_type_str = attribute['label'].replace("-", "").replace(" ", "").lower()
+            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:
+    def _get_compensation(compensation: dict) -> Compensation | None:
        """
        Parses the job to get compensation
        :param job:
-        :param job:
        :return: compensation object
        """
-        comp = job['compensation']['baseSalary']
-        if comp:
-            interval = IndeedScraper._get_compensation_interval(comp['unitOfWork'])
-            if interval:
-                return Compensation(
-                    interval=interval,
-                    min_amount=round(comp['range'].get('min'), 2) if comp['range'].get('min') is not None else None,
-                    max_amount=round(comp['range'].get('max'), 2) if comp['range'].get('max') is not None else None,
-                    currency=job['compensation']['currencyCode']
-                )
+        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 = IndeedScraper._get_compensation_interval(comp["unitOfWork"])
+        if not interval:
+            return None
+        min_range = comp["range"].get("min")
+        max_range = comp["range"].get("max")
+        return Compensation(
+            interval=interval,
+            min_amount=int(min_range) if min_range is not None else None,
+            max_amount=int(max_range) if max_range is not None else None,
+            currency=(
+                compensation["estimated"]["currencyCode"]
+                if compensation["estimated"]
+                else 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']
+        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']
+            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_description = any(keyword in description.lower() for keyword in remote_keywords)
        is_remote_in_location = any(
-            keyword in job['location']['formatted']['long'].lower()
+            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
+        return (
+            is_remote_in_attributes or is_remote_in_description or is_remote_in_location
+        )

    @staticmethod
    def _get_compensation_interval(interval: str) -> CompensationInterval:
@@ -270,105 +341,10 @@ class IndeedScraper(Scraper):
            "YEAR": "YEARLY",
            "HOUR": "HOURLY",
            "WEEK": "WEEKLY",
-            "MONTH": "MONTHLY"
+            "MONTH": "MONTHLY",
        }
        mapped_interval = interval_mapping.get(interval.upper(), None)
        if mapped_interval and mapped_interval in CompensationInterval.__members__:
            return CompensationInterval[mapped_interval]
        else:
            raise ValueError(f"Unsupported interval: {interval}")
-
-    api_headers = {
-        'Host': 'apis.indeed.com',
-        'content-type': 'application/json',
-        'indeed-api-key': '161092c2017b5bbab13edb12461a62d5a833871e7cad6d9d475304573de67ac8',
-        'accept': 'application/json',
-        'indeed-locale': 'en-US',
-        'accept-language': 'en-US,en;q=0.9',
-        'user-agent': 'Mozilla/5.0 (iPhone; CPU iPhone OS 16_6_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/15E148 Indeed App 193.1',
-        'indeed-app-info': 'appv=193.1; appid=com.indeed.jobsearch; osv=16.6.1; os=ios; dtype=phone',
-    }
-    job_search_query = """
-        query GetJobData {{
-          jobSearch(
-            what: "{what}"
-            location: {{ where: "{location}", radius: {radius}, radiusUnit: MILES }}
-            includeSponsoredResults: NONE
-            limit: 100
-            sort: DATE
-            {cursor}
-            {filters}
-          ) {{
-            pageInfo {{
-              nextCursor
-            }}
-            results {{
-              trackingKey
-              job {{
-                key
-                title
-                datePublished
-                dateOnIndeed
-                description {{
-                  html
-                }}
-                location {{
-                  countryName
-                  countryCode
-                  admin1Code
-                  city
-                  postalCode
-                  streetAddress
-                  formatted {{
-                    short
-                    long
-                  }}
-                }}
-                compensation {{
-                  baseSalary {{
-                    unitOfWork
-                    range {{
-                      ... on Range {{
-                        min
-                        max
-                      }}
-                    }}
-                  }}
-                  currencyCode
-                }}
-                attributes {{
-                  key
-                  label
-                }}
-                employer {{
-                  relativeCompanyPageUrl
-                  name
-                  dossier {{
-                      employerDetails {{
-                        addresses
-                        industry
-                        employeesLocalizedLabel
-                        revenueLocalizedLabel
-                        briefDescription
-                        ceoName
-                        ceoPhotoUrl
-                      }}
-                      images {{
-                            headerImageUrl
-                            squareLogoUrl
-                      }}
-                      links {{
-                        corporateWebsite
-                    }}
-                  }}
-                }}
-                recruit {{
-                  viewJobUrl
-                  detailedSalary
-                  workSchedule
-                }}
-              }}
-            }}
-          }}
-        }}
-        """
--- a/src/jobspy/scrapers/indeed/constants.py
+++ b/src/jobspy/scrapers/indeed/constants.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/src/jobspy/scrapers/linkedin/init.py
+++ b/src/jobspy/scrapers/linkedin/init.py
@@ -4,19 +4,24 @@ jobspy.scrapers.linkedin

 This module contains routines to scrape LinkedIn.
 """
+
+from __future__ import annotations
+
+import math
 import time
 import random
+import regex as re
 from typing import Optional
 from datetime import datetime

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

+from .constants import headers
 from .. import Scraper, ScraperInput, Site
 from ..exceptions import LinkedInException
-from ..utils import create_session
+from ..utils import create_session, remove_attributes, create_logger
 from ...jobs import (
    JobPost,
    Location,
@@ -24,16 +29,17 @@ from ...jobs import (
    JobType,
    Country,
    Compensation,
-    DescriptionFormat
+    DescriptionFormat,
 )
 from ..utils import (
-    logger,
    extract_emails_from_text,
    get_enum_from_job_type,
    currency_parser,
-    markdown_converter
+    markdown_converter,
 )

+log = create_logger("LinkedIn")
+

 class LinkedInScraper(Scraper):
    base_url = "https://www.linkedin.com"
@@ -41,13 +47,25 @@ class LinkedInScraper(Scraper):
    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
+    ):
        """
        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:
        """
@@ -57,55 +75,64 @@ 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
+            scraper_input.hours_old * 3600 if scraper_input.hours_old else None
+        )
+        continue_search = (
+            lambda: len(job_list) < scraper_input.results_wanted and start < 1000
        )
-        continue_search = lambda: len(job_list) < scraper_input.results_wanted and page < 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)
-                if scraper_input.job_type
-                else None,
+                "f_JT": (
+                    self.job_type_code(scraper_input.job_type)
+                    if scraper_input.job_type
+                    else None
+                ),
                "pageNum": 0,
-                "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)) if scraper_input.linkedin_company_ids else None,
+                "f_C": (
+                    ",".join(map(str, scraper_input.linkedin_company_ids))
+                    if scraper_input.linkedin_company_ids
+                    else None
+                ),
            }
            if seconds_old is not None:
                params["f_TPR"] = f"r{seconds_old}"

            params = {k: v for k, v in params.items() if v is not None}
            try:
-                response = session.get(
+                response = self.session.get(
                    f"{self.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):
                    if response.status_code == 429:
-                        logger.error(f'429 Response - Blocked by LinkedIn for too many requests')
+                        err = (
+                            f"429 Response - Blocked by LinkedIn for too many requests"
+                        )
                    else:
-                        logger.error(f'LinkedIn response status code {response.status_code}')
+                        err = f"LinkedIn response status code {response.status_code}"
+                        err += f" - {response.text}"
+                    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")
@@ -114,35 +141,36 @@ 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:
-                    job_post = self._process_job(job_card, job_url, scraper_input.linkedin_fetch_description)
-                    if job_post:
-                        job_list.append(job_post)
-                    if not continue_search():
-                       break
-                except Exception as e:
-                    raise LinkedInException(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) -> Optional[JobPost]:
-        salary_tag = job_card.find('span', class_='job-search-card__salary-info')
+    def _process_job(
+        self, job_card: Tag, job_id: str, full_descr: bool
+    ) -> Optional[JobPost]:
+        salary_tag = job_card.find("span", class_="job-search-card__salary-info")

        compensation = None
        if salary_tag:
@@ -178,46 +206,51 @@ 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)

        return JobPost(
+            id=f"li-{job_id}",
            title=title,
            company_name=company,
            company_url=company_url,
            location=location,
            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(job_details.get("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(
@@ -225,15 +258,37 @@ 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": self._parse_job_level(soup),
+            "company_industry": self._parse_company_industry(soup),
+            "job_type": self._parse_job_type(soup),
+            "job_url_direct": self._parse_job_url_direct(soup),
+            "company_logo": company_logo,
+            "job_function": job_function,
+        }

    def _get_location(self, metadata_card: Optional[Tag]) -> Location:
        """
@@ -257,11 +312,8 @@ class LinkedInScraper(Scraper):
                )
            elif len(parts) == 3:
                city, state, country = parts
-                location = Location(
-                    city=city,
-                    state=state,
-                    country=Country.from_string(country)
-                )
+                country = Country.from_string(country)
+                location = Location(city=city, state=state, country=country)
        return location

    @staticmethod
@@ -289,6 +341,69 @@ class LinkedInScraper(Scraper):

        return [get_enum_from_job_type(employment_type)] if employment_type else []

+    @staticmethod
+    def _parse_job_level(soup_job_level: BeautifulSoup) -> str | None:
+        """
+        Gets the job level from job page
+        :param soup_job_level:
+        :return: str
+        """
+        h3_tag = soup_job_level.find(
+            "h3",
+            class_="description__job-criteria-subheader",
+            string=lambda text: "Seniority level" in text,
+        )
+        job_level = None
+        if h3_tag:
+            job_level_span = h3_tag.find_next_sibling(
+                "span",
+                class_="description__job-criteria-text description__job-criteria-text--criteria",
+            )
+            if job_level_span:
+                job_level = job_level_span.get_text(strip=True)
+
+        return job_level
+
+    @staticmethod
+    def _parse_company_industry(soup_industry: BeautifulSoup) -> str | None:
+        """
+        Gets the company industry from job page
+        :param soup_industry:
+        :return: str
+        """
+        h3_tag = soup_industry.find(
+            "h3",
+            class_="description__job-criteria-subheader",
+            string=lambda text: "Industries" in text,
+        )
+        industry = None
+        if h3_tag:
+            industry_span = h3_tag.find_next_sibling(
+                "span",
+                class_="description__job-criteria-text description__job-criteria-text--criteria",
+            )
+            if industry_span:
+                industry = industry_span.get_text(strip=True)
+
+        return industry
+
+    def _parse_job_url_direct(self, soup: BeautifulSoup) -> str | None:
+        """
+        Gets the job url direct from job page
+        :param soup:
+        :return: str
+        """
+        job_url_direct = None
+        job_url_direct_content = soup.find("code", id="applyUrl")
+        if job_url_direct_content:
+            job_url_direct_match = self.job_url_direct_regex.search(
+                job_url_direct_content.decode_contents().strip()
+            )
+            if job_url_direct_match:
+                job_url_direct = unquote(job_url_direct_match.group())
+
+        return job_url_direct
+
    @staticmethod
    def job_type_code(job_type_enum: JobType) -> str:
        return {
@@ -298,12 +413,3 @@ class LinkedInScraper(Scraper):
            JobType.CONTRACT: "C",
            JobType.TEMPORARY: "T",
        }.get(job_type_enum, "")
-
-    headers = {
-        "authority": "www.linkedin.com",
-        "accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7",
-        "accept-language": "en-US,en;q=0.9",
-        "cache-control": "max-age=0",
-        "upgrade-insecure-requests": "1",
-        "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36",
-    }
--- a/src/jobspy/scrapers/linkedin/constants.py
+++ b/src/jobspy/scrapers/linkedin/constants.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/src/jobspy/scrapers/utils.py
+++ b/src/jobspy/scrapers/utils.py
@@ -1,22 +1,154 @@
+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 ..jobs import JobType
+from ..jobs import CompensationInterval, JobType

-logger = logging.getLogger("JobSpy")
-logger.propagate = False
-if not logger.handlers:
-    logger.setLevel(logging.INFO)
-    console_handler = logging.StreamHandler()
-    formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
-    console_handler.setFormatter(formatter)
-    logger.addHandler(console_handler)
+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}
+        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):
@@ -33,32 +165,6 @@ def extract_emails_from_text(text: str) -> list[str] | None:
    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.
@@ -73,17 +179,110 @@ def get_enum_from_job_type(job_type_str: str) -> JobType | None:
 def currency_parser(cur_str):
    # Remove any non-numerical characters
    # except for ',' '.' or '-' (e.g. EUR)
-    cur_str = re.sub("[^-0-9.,]", '', cur_str)
+    cur_str = re.sub("[^-0-9.,]", "", cur_str)
    # Remove any 000s separators (either , or .)
-    cur_str = re.sub("[.,]", '', cur_str[:-3]) + cur_str[-3:]
+    cur_str = re.sub("[.,]", "", cur_str[:-3]) + cur_str[-3:]

-    if '.' in list(cur_str[-3:]):
+    if "." in list(cur_str[-3:]):
        num = float(cur_str)
-    elif ',' in list(cur_str[-3:]):
-        num = float(cur_str.replace(',', '.'))
+    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
--- a/src/jobspy/scrapers/ziprecruiter/init.py
+++ b/src/jobspy/scrapers/ziprecruiter/init.py
@@ -4,19 +4,27 @@ jobspy.scrapers.ziprecruiter

 This module contains routines to scrape ZipRecruiter.
 """
+
+from __future__ import annotations
+
+import json
 import math
+import re
 import time
+from concurrent.futures import ThreadPoolExecutor
 from datetime import datetime
 from typing import Optional, Tuple, Any

-from concurrent.futures import ThreadPoolExecutor
+from bs4 import BeautifulSoup

+from .constants import headers
 from .. import Scraper, ScraperInput, Site
 from ..utils import (
-    logger,
    extract_emails_from_text,
    create_session,
-    markdown_converter
+    markdown_converter,
+    remove_attributes,
+    create_logger,
 )
 from ...jobs import (
    JobPost,
@@ -25,22 +33,28 @@ from ...jobs import (
    JobResponse,
    JobType,
    Country,
-    DescriptionFormat
+    DescriptionFormat,
 )

+log = create_logger("ZipRecruiter")
+

 class ZipRecruiterScraper(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
+    ):
        """
        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
@@ -62,7 +76,7 @@ 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
            )
@@ -88,25 +102,22 @@ class ZipRecruiterScraper(Scraper):
        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:
-                    logger.error(f'429 Response - Blocked by ZipRecruiter for too many requests')
+                    err = "429 Response - Blocked by ZipRecruiter for too many requests"
                else:
-                    logger.error(f'ZipRecruiter response status code {res.status_code}')
+                    err = f"ZipRecruiter response status code {res.status_code}"
+                    err += f" with response: {res.text}"  # ZipRecruiter likely not available in EU
+                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()
        jobs_list = res_data.get("jobs", [])
        next_continue_token = res_data.get("continue", None)
@@ -127,7 +138,12 @@ class ZipRecruiterScraper(Scraper):
        self.seen_urls.add(job_url)

        description = job.get("job_description", "").strip()
-        description = markdown_converter(description) if self.scraper_input.description_format == DescriptionFormat.MARKDOWN else description
+        listing_type = job.get("buyer_type", "")
+        description = (
+            markdown_converter(description)
+            if self.scraper_input.description_format == DescriptionFormat.MARKDOWN
+            else description
+        )
        company = job.get("hiring_company", {}).get("name")
        country_value = "usa" if job.get("job_country") == "US" else "canada"
        country_enum = Country.from_string(country_value)
@@ -138,33 +154,90 @@ class ZipRecruiterScraper(Scraper):
        job_type = self._get_job_type_enum(
            job.get("employment_type", "").replace("_", "").lower()
        )
-        date_posted = datetime.fromisoformat(job['posted_time'].rstrip("Z")).date()
+        date_posted = datetime.fromisoformat(job["posted_time"].rstrip("Z")).date()
+        comp_interval = job.get("compensation_interval")
+        comp_interval = "yearly" if comp_interval == "annual" else comp_interval
+        comp_min = int(job["compensation_min"]) if "compensation_min" in job else None
+        comp_max = int(job["compensation_max"]) if "compensation_max" in job else None
+        comp_currency = job.get("compensation_currency")
+        description_full, job_url_direct = self._get_descr(job_url)
+
        return JobPost(
+            id=f'zr-{job["listing_key"]}',
            title=title,
            company_name=company,
            location=location,
            job_type=job_type,
            compensation=Compensation(
-                interval="yearly"
-                if job.get("compensation_interval") == "annual"
-                else job.get("compensation_interval"),
-                min_amount=int(job["compensation_min"])
-                if "compensation_min" in job
-                else None,
-                max_amount=int(job["compensation_max"])
-                if "compensation_max" in job
-                else None,
-                currency=job.get("compensation_currency"),
+                interval=comp_interval,
+                min_amount=comp_min,
+                max_amount=comp_max,
+                currency=comp_currency,
            ),
            date_posted=date_posted,
            job_url=job_url,
-            description=description,
+            description=description_full if description_full else description,
            emails=extract_emails_from_text(description) if description else None,
+            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
+            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)
+
+            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"
-        self.session.post(f"{self.api_url}/jobs-app/event", data=data, headers=self.headers)
+        """
+        Sends a session event to the API with device properties.
+        """
+        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"),
+        ]
+
+        url = f"{self.api_url}/jobs-app/event"
+        self.session.post(url, data=data)

    @staticmethod
    def _get_job_type_enum(job_type_str: str) -> list[JobType] | None:
@@ -180,29 +253,15 @@ class ZipRecruiterScraper(Scraper):
            "location": scraper_input.location,
        }
        if scraper_input.hours_old:
-            fromage = max(scraper_input.hours_old // 24, 1) if scraper_input.hours_old else None
-            params['days'] = fromage
-        job_type_map = {
-            JobType.FULL_TIME: 'full_time',
-            JobType.PART_TIME: 'part_time'
-        }
+            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:
-            params['employment_type'] = job_type_map[scraper_input.job_type] if scraper_input.job_type in job_type_map else scraper_input.job_type.value[0]
+            job_type = 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
+            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",
-    }
--- a/src/jobspy/scrapers/ziprecruiter/constants.py
+++ b/src/jobspy/scrapers/ziprecruiter/constants.py
@@ -0,0 +1,10 @@
+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",
+}
--- 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	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
Cullen Watson	80213f28d2	chore: version	2024-03-11 09:43:12 -05:00
Cullen Watson	ada38532c3	fix: indeed empty location term	2024-03-11 09:42:43 -05:00
Cullen Watson	3b0017964c	fix: indeed empty search term	2024-03-11 09:21:11 -05:00
VitaminB16	94d8f555fd	format: Apply Black formatter to the codebase (#127 )	2024-03-10 23:36:27 -05:00
Cullen Watson	e8b4b376b8	docs: readme	2024-03-09 13:40:34 -06:00
Cullen Watson	54ac1bad16	docs: readme	2024-03-09 01:49:05 -06:00