Description format (#107)

* fix(ziprecruiter): pagination

* chore: version

README.md

@@ -4,17 +4,14 @@
 
 **Not technical?** Try out the web scraping tool on our site at [usejobspy.com](https://usejobspy.com).
 
-*Looking to build a data-focused software product?* **[Book a call](https://calendly.com/zachary-products/15min)** *to
+*Looking to build a data-focused software product?* **[Book a call](https://bunsly.com/)** *to
 work with us.*
-\
-Check out another project we wrote: ***[HomeHarvest](https://github.com/ZacharyHampton/HomeHarvest)** – a Python package
-for real estate scraping*
 
 ## Features
 
-- Scrapes job postings from **LinkedIn**, **Indeed** & **ZipRecruiter** simultaneously
+- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, & **ZipRecruiter** simultaneously
 - Aggregates the job postings in a Pandas DataFrame
-- Proxy support (HTTP/S, SOCKS)
+- Proxy support
 
 [Video Guide for JobSpy](https://www.youtube.com/watch?v=RuP1HrAZnxs&pp=ygUgam9icyBzY3JhcGVyIGJvdCBsaW5rZWRpbiBpbmRlZWQ%3D) -
 Updated for release v1.1.3
@@ -24,7 +21,7 @@ Updated for release v1.1.3
 ### Installation
 
 ```
-pip install --upgrade python-jobspy
+pip install python-jobspy
 ```
 
 _Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_
@@ -32,40 +29,20 @@ _Python version >= [3.10](https://www.python.org/downloads/release/python-3100/)
 ### Usage
 
 ```python
+import csv
 from jobspy import scrape_jobs
-import pandas as pd
 
-jobs: pd.DataFrame = scrape_jobs(
-    site_name=["indeed", "linkedin", "zip_recruiter"],
+jobs = scrape_jobs(
+    site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"],
     search_term="software engineer",
     location="Dallas, TX",
-    results_wanted=10,
-
-    country_indeed='USA'  # only needed for indeed
-
-    # use if you want to use a proxy
-    # proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
-    # offset=25 # use if you want to start at a specific offset
+    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
 )
-
-# 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 display in Jupyter Notebook (1. pip install jupyter 2. jupyter notebook)
-# display(jobs)
-
-# 3 output to .csv
-# jobs.to_csv('jobs.csv', index=False)
-
-# 4 output to .xlsx
-# jobs.to_xlsx('jobs.xlsx', index=False)
-
+print(f"Found {len(jobs)} jobs")
+print(jobs.head())
+jobs.to_csv("jobs.csv", quoting=csv.QUOTE_NONNUMERIC, escapechar="\\", index=False) # to_xlsx
 ```
 
 ### Output
@@ -84,18 +61,22 @@ zip_recruiter Software Developer                 TEKsystems        Phoenix
 
 ```plaintext
 Required
-├── site_type (List[enum]): linkedin, zip_recruiter, indeed
+├── site_type (List[enum]): linkedin, zip_recruiter, indeed, glassdoor
 └── search_term (str)
 Optional
 ├── location (int)
 ├── distance (int): in miles
 ├── job_type (enum): fulltime, parttime, internship, contract
-├── proxy (str): in format 'http://user:pass@host:port' or [https, socks]
+├── proxy (str): in format 'http://user:pass@host:port'
 ├── 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 LinkedIn
+├── 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 (all but LinkedIn rounds up to next day)
 ```
 
 ### JobPost Schema
@@ -104,19 +85,23 @@ Optional
 JobPost
 ├── title (str)
 ├── company (str)
+├── company_url (str)
 ├── job_url (str)
 ├── location (object)
 │   ├── country (str)
 │   ├── city (str)
 │   ├── state (str)
 ├── description (str)
-├── job_type (enum): fulltime, parttime, internship, contract
+├── job_type (str): fulltime, parttime, internship, contract
 ├── compensation (object)
-│   ├── interval (enum): yearly, monthly, weekly, daily, hourly
+│   ├── interval (str): yearly, monthly, weekly, daily, hourly
 │   ├── min_amount (int)
 │   ├── max_amount (int)
 │   └── currency (enum)
 └── date_posted (date)
+└── emails (str)
+└── num_urgent_words (int)
+└── is_remote (bool)
 ```
 
 ### Exceptions
@@ -126,67 +111,64 @@ The following exceptions may be raised when using JobSpy:
 * `LinkedInException`
 * `IndeedException`
 * `ZipRecruiterException`
+* `GlassdoorException`
 
 ## Supported Countries for Job Searching
 
 ### **LinkedIn**
 
-LinkedIn searches globally & uses only the `location` parameter.
+LinkedIn searches globally & uses only the `location` parameter. You can only fetch 1000 jobs max from the LinkedIn endpoint we're using
 
 ### **ZipRecruiter**
 
 ZipRecruiter searches for jobs in **US/Canada** & uses only the `location` parameter.
 
-### **Indeed**
+### **Indeed / Glassdoor**
 
-Indeed supports most countries, but the `country_indeed` parameter is required. Additionally, use the `location`
+Indeed & Glassdoor supports most countries, but the `country_indeed` parameter is required. Additionally, use the `location`
 parameter to narrow down the location, e.g. city & state if necessary. 
 
-You can specify the following countries when searching on Indeed (use the exact name):
+You can specify the following countries when searching on Indeed (use the exact name, * indicates support for Glassdoor):
 
 |                      |              |            |                |
 |----------------------|--------------|------------|----------------|
-| Argentina            | Australia    | Austria    | Bahrain        |
-| Belgium              | Brazil       | Canada     | Chile          |
+| Argentina            | Australia*   | Austria*   | Bahrain        |
+| Belgium*             | Brazil*      | Canada*    | Chile          |
 | China                | Colombia     | Costa Rica | Czech Republic |
 | Denmark              | Ecuador      | Egypt      | Finland        |
-| France               | Germany      | Greece     | Hong Kong      |
-| Hungary              | India        | Indonesia  | Ireland        |
-| Israel               | Italy        | Japan      | Kuwait         |
-| Luxembourg           | Malaysia     | Mexico     | Morocco        |
-| Netherlands          | New Zealand  | Nigeria    | Norway         |
+| France*              | Germany*     | Greece     | Hong Kong*     |
+| Hungary              | India*       | Indonesia  | Ireland*       |
+| Israel               | Italy*       | Japan      | Kuwait         |
+| Luxembourg           | Malaysia     | Mexico*    | Morocco        |
+| Netherlands*         | New Zealand* | Nigeria    | Norway         |
 | Oman                 | Pakistan     | Panama     | Peru           |
 | Philippines          | Poland       | Portugal   | Qatar          |
-| Romania              | Saudi Arabia | Singapore  | South Africa   |
-| South Korea          | Spain        | Sweden     | Switzerland    |
+| Romania              | Saudi Arabia | Singapore* | South Africa   |
+| South Korea          | Spain*       | Sweden     | Switzerland*   |
 | Taiwan               | Thailand     | Turkey     | Ukraine        |
-| United Arab Emirates | UK           | USA        | Uruguay        |
+| United Arab Emirates | UK*          | USA*       | Uruguay        |
 | Venezuela            | Vietnam      |            |                |
 
+
+Glassdoor can only fetch 900 jobs from the endpoint we're using on a given search.
 ## Frequently Asked Questions
 
 ---
 
 **Q: Encountering issues with your queries?**  
 **A:** Try reducing the number of `results_wanted` and/or broadening the filters. If problems
-persist, [submit an issue](https://github.com/cullenwatson/JobSpy/issues).
+persist, [submit an issue](https://github.com/Bunsly/JobSpy/issues).
 
 ---
 
 **Q: Received a response code 429?**  
-**A:** This indicates that you have been blocked by the job board site for sending too many requests. Currently, *
-*LinkedIn** is particularly aggressive with blocking. We recommend:
+**A:** This indicates that you have been blocked by the job board site for sending too many requests. All of the job board sites are aggressive with blocking. We recommend:
 
-- Waiting a few seconds between requests.
+- Waiting some time between scrapes (site-dependent).
 - Trying a VPN or proxy to change your IP address.
 
 ---
 
-**Q: Experiencing a "Segmentation fault: 11" on macOS Catalina?**  
-**A:** This is due to `tls_client` dependency not supporting your architecture. Solutions and workarounds include:
-
-- Upgrade to a newer version of MacOS
-- Reach out to the maintainers of [tls_client](https://github.com/bogdanfinn/tls-client) for fixes
 
 
   

examples/JobSpy_AllSites.py

@@ -0,0 +1,30 @@
+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)

examples/JobSpy_Demo.py

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

examples/JobSpy_LongScrape.py

@@ -0,0 +1,77 @@
+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}")

poetry.lock

@@ -524,6 +524,17 @@ files = [
     {file = "fqdn-1.5.1.tar.gz", hash = "sha256:105ed3677e767fb5ca086a0c1f4bb66ebc3c100be518f0e0d755d9eae164d89f"},
 ]
 
+[[package]]
+name = "html2text"
+version = "2020.1.16"
+description = "Turn HTML into equivalent Markdown-structured text."
+optional = false
+python-versions = ">=3.5"
+files = [
+    {file = "html2text-2020.1.16-py3-none-any.whl", hash = "sha256:c7c629882da0cf377d66f073329ccf34a12ed2adf0169b9285ae4e63ef54c82b"},
+    {file = "html2text-2020.1.16.tar.gz", hash = "sha256:e296318e16b059ddb97f7a8a1d6a5c1d7af4544049a01e261731d2d5cc277bbb"},
+]
+
 [[package]]
 name = "idna"
 version = "3.4"
@@ -1243,36 +1254,39 @@ test = ["pytest", "pytest-console-scripts", "pytest-jupyter", "pytest-tornasync"
 
 [[package]]
 name = "numpy"
-version = "1.25.2"
+version = "1.24.2"
 description = "Fundamental package for array computing in Python"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.8"
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+    {file = "numpy-1.24.2-cp311-cp311-win32.whl", hash = "sha256:e428c4fbfa085f947b536706a2fc349245d7baa8334f0c5723c56a10595f9b95"},
+    {file = "numpy-1.24.2-cp311-cp311-win_amd64.whl", hash = "sha256:557d42778a6869c2162deb40ad82612645e21d79e11c1dc62c6e82a2220ffb04"},
+    {file = "numpy-1.24.2-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:d0a2db9d20117bf523dde15858398e7c0858aadca7c0f088ac0d6edd360e9ad2"},
+    {file = "numpy-1.24.2-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:c72a6b2f4af1adfe193f7beb91ddf708ff867a3f977ef2ec53c0ffb8283ab9f5"},
+    {file = "numpy-1.24.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c29e6bd0ec49a44d7690ecb623a8eac5ab8a923bce0bea6293953992edf3a76a"},
+    {file = "numpy-1.24.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2eabd64ddb96a1239791da78fa5f4e1693ae2dadc82a76bc76a14cbb2b966e96"},
+    {file = "numpy-1.24.2-cp38-cp38-win32.whl", hash = "sha256:e3ab5d32784e843fc0dd3ab6dcafc67ef806e6b6828dc6af2f689be0eb4d781d"},
+    {file = "numpy-1.24.2-cp38-cp38-win_amd64.whl", hash = "sha256:76807b4063f0002c8532cfeac47a3068a69561e9c8715efdad3c642eb27c0756"},
+    {file = "numpy-1.24.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:4199e7cfc307a778f72d293372736223e39ec9ac096ff0a2e64853b866a8e18a"},
+    {file = "numpy-1.24.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:adbdce121896fd3a17a77ab0b0b5eedf05a9834a18699db6829a64e1dfccca7f"},
+    {file = "numpy-1.24.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:889b2cc88b837d86eda1b17008ebeb679d82875022200c6e8e4ce6cf549b7acb"},
+    {file = "numpy-1.24.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f64bb98ac59b3ea3bf74b02f13836eb2e24e48e0ab0145bbda646295769bd780"},
+    {file = "numpy-1.24.2-cp39-cp39-win32.whl", hash = "sha256:63e45511ee4d9d976637d11e6c9864eae50e12dc9598f531c035265991910468"},
+    {file = "numpy-1.24.2-cp39-cp39-win_amd64.whl", hash = "sha256:a77d3e1163a7770164404607b7ba3967fb49b24782a6ef85d9b5f54126cc39e5"},
+    {file = "numpy-1.24.2-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:92011118955724465fb6853def593cf397b4a1367495e0b59a7e69d40c4eb71d"},
+    {file = "numpy-1.24.2-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f9006288bcf4895917d02583cf3411f98631275bc67cce355a7f39f8c14338fa"},
+    {file = "numpy-1.24.2-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:150947adbdfeceec4e5926d956a06865c1c690f2fd902efede4ca6fe2e657c3f"},
+    {file = "numpy-1.24.2.tar.gz", hash = "sha256:003a9f530e880cb2cd177cba1af7220b9aa42def9c4afc2a2fc3ee6be7eb2b22"},
 ]
 
 [[package]]
@@ -2257,13 +2271,13 @@ test = ["flake8", "isort", "pytest"]
 
 [[package]]
 name = "tls-client"
-version = "0.2.1"
+version = "1.0"
 description = "Advanced Python HTTP Client."
 optional = false
 python-versions = "*"
 files = [
-    { file = "tls_client-0.2.1-py3-none-any.whl", hash = "sha256:124a710952b979d5e20b4e2b7879b7958d6e48a259d0f5b83101055eb173f0bd" },
-    { file = "tls_client-0.2.1.tar.gz", hash = "sha256:473fb4c671d9d4ca6b818548ab6e955640dd589767bfce520830c5618c2f2e2b" },
+    {file = "tls_client-1.0-py3-none-any.whl", hash = "sha256:f1183f5e18cb31914bd62d11b350a33ea0293ea80fb91d69a3072821dece3e66"},
+    {file = "tls_client-1.0.tar.gz", hash = "sha256:7f6de48ad4a0ef69b72682c76ce604155971e07b4bfb2148a36276194ae3e7a0"},
 ]
 
 [[package]]
@@ -2432,4 +2446,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "0c50057af9ebbbe5c124c81758b41f05c05636739c3d1747e1bac74e75a046cb"
+content-hash = "40cdc19a57cba0d21ff4f0fcfa53e14a073fcccd9f2a871440e056ab6e8fade0"

pyproject.toml

@@ -1,9 +1,9 @@
 [tool.poetry]
 name = "python-jobspy"
-version = "1.1.12"
-description = "Job scraper for LinkedIn, Indeed & ZipRecruiter"
-authors = ["Zachary Hampton <zachary@zacharysproducts.com>", "Cullen Watson <cullen@cullen.ai>"]
-homepage = "https://github.com/cullenwatson/JobSpy"
+version = "1.1.45"
+description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
+authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
+homepage = "https://github.com/Bunsly/JobSpy"
 readme = "README.md"
 
 packages = [
@@ -13,10 +13,12 @@ packages = [
 [tool.poetry.dependencies]
 python = "^3.10"
 requests = "^2.31.0"
-tls-client = "^0.2.1"
+tls-client = "*"
 beautifulsoup4 = "^4.12.2"
 pandas = "^2.1.0"
+NUMPY = "1.24.2"
 pydantic = "^2.3.0"
+html2text = "^2020.1.16"
 
 
 [tool.poetry.group.dev.dependencies]

src/jobspy/__init__.py

@@ -1,48 +1,53 @@
 import pandas as pd
-import concurrent.futures
-from concurrent.futures import ThreadPoolExecutor
-from typing import List, Tuple, Optional
+from typing import Tuple
+from concurrent.futures import ThreadPoolExecutor, as_completed
 
 from .jobs import JobType, Location
 from .scrapers.indeed import IndeedScraper
 from .scrapers.ziprecruiter import ZipRecruiterScraper
+from .scrapers.glassdoor import GlassdoorScraper
 from .scrapers.linkedin import LinkedInScraper
 from .scrapers import ScraperInput, Site, JobResponse, Country
 from .scrapers.exceptions import (
     LinkedInException,
     IndeedException,
     ZipRecruiterException,
+    GlassdoorException,
 )
 
-SCRAPER_MAPPING = {
-    Site.LINKEDIN: LinkedInScraper,
-    Site.INDEED: IndeedScraper,
-    Site.ZIP_RECRUITER: ZipRecruiterScraper,
-}
-
-
-def _map_str_to_site(site_name: str) -> Site:
-    return Site[site_name.upper()]
-
 
 def scrape_jobs(
-        site_name: str | List[str] | Site | List[Site],
-        search_term: str,
-        location: str = "",
-        distance: int = None,
+    site_name: str | list[str] | Site | list[Site] | None = None,
+    search_term: str | None = None,
+    location: str | None = None,
+    distance: int | None = None,
     is_remote: bool = False,
-        job_type: str = None,
-        easy_apply: bool = False,  # linkedin
+    job_type: str | None = None,
+    easy_apply: bool | None = None,
     results_wanted: int = 15,
     country_indeed: str = "usa",
     hyperlinks: bool = False,
-        proxy: Optional[str] = None,
-        offset: Optional[int] = 0
+    proxy: 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,
+    **kwargs,
 ) -> pd.DataFrame:
     """
     Simultaneously scrapes job data from multiple job sites.
     :return: results_wanted: pandas dataframe containing job data
     """
+    SCRAPER_MAPPING = {
+        Site.LINKEDIN: LinkedInScraper,
+        Site.INDEED: IndeedScraper,
+        Site.ZIP_RECRUITER: ZipRecruiterScraper,
+        Site.GLASSDOOR: GlassdoorScraper,
+    }
+
+    def map_str_to_site(site_name: str) -> Site:
+        return Site[site_name.upper()]
 
     def get_enum_from_value(value_str):
         for job_type in JobType:
@@ -52,18 +57,22 @@ def scrape_jobs(
 
     job_type = get_enum_from_value(job_type) if job_type else None
 
-    if type(site_name) == str:
-        site_type = [_map_str_to_site(site_name)]
-    else:  #: if type(site_name) == list
-        site_type = [
-            _map_str_to_site(site) if type(site) == str else site_name
+    def get_site_type():
+        site_types = list(Site)
+        if isinstance(site_name, str):
+            site_types = [map_str_to_site(site_name)]
+        elif isinstance(site_name, Site):
+            site_types = [site_name]
+        elif isinstance(site_name, list):
+            site_types = [
+                map_str_to_site(site) if isinstance(site, str) else site
                 for site in site_name
             ]
-
+        return site_types
     country_enum = Country.from_string(country_indeed)
 
     scraper_input = ScraperInput(
-        site_type=site_type,
+        site_type=get_site_type(),
         country=country_enum,
         search_term=search_term,
         location=location,
@@ -71,46 +80,36 @@ def scrape_jobs(
         is_remote=is_remote,
         job_type=job_type,
         easy_apply=easy_apply,
+        description_format=description_format,
+        linkedin_fetch_description=linkedin_fetch_description,
         results_wanted=results_wanted,
-        offset=offset
+        linkedin_company_ids=linkedin_company_ids,
+        offset=offset,
+        hours_old=hours_old
     )
 
     def scrape_site(site: Site) -> Tuple[str, JobResponse]:
         scraper_class = SCRAPER_MAPPING[site]
         scraper = scraper_class(proxy=proxy)
-
-        try:
         scraped_data: JobResponse = scraper.scrape(scraper_input)
-        except (LinkedInException, IndeedException, ZipRecruiterException) as lie:
-            raise lie
-        except Exception as e:
-            # unhandled exceptions
-            if site == Site.LINKEDIN:
-                raise LinkedInException()
-            if site == Site.INDEED:
-                raise IndeedException()
-            if site == Site.ZIP_RECRUITER:
-                raise ZipRecruiterException()
-            else:
-                raise e
         return site.value, scraped_data
 
     site_to_jobs_dict = {}
 
     def worker(site):
-        site_value, scraped_data = scrape_site(site)
-        return site_value, scraped_data
+        site_val, scraped_info = scrape_site(site)
+        return site_val, scraped_info
 
     with ThreadPoolExecutor() as executor:
         future_to_site = {
             executor.submit(worker, site): site for site in scraper_input.site_type
         }
 
-        for future in concurrent.futures.as_completed(future_to_site):
+        for future in as_completed(future_to_site):
             site_value, scraped_data = future.result()
             site_to_jobs_dict[site_value] = scraped_data
 
-    jobs_dfs: List[pd.DataFrame] = []
+    jobs_dfs: list[pd.DataFrame] = []
 
     for site, job_response in site_to_jobs_dict.items():
         for job in job_response.jobs:
@@ -120,13 +119,18 @@ def scrape_jobs(
             ] = f'<a href="{job_data["job_url"]}">{job_data["job_url"]}</a>'
             job_data["site"] = site
             job_data["company"] = job_data["company_name"]
-            if job_data["job_type"]:
-                # Take the first value from the job type tuple
-                job_data["job_type"] = job_data["job_type"].value[0]
-            else:
-                job_data["job_type"] = None
-
-            job_data["location"] = Location(**job_data["location"]).display_location()
+            job_data["job_type"] = (
+                ", ".join(job_type.value[0] for job_type in job_data["job_type"])
+                if job_data["job_type"]
+                else None
+            )
+            job_data["emails"] = (
+                ", ".join(job_data["emails"]) if job_data["emails"] else None
+            )
+            if job_data["location"]:
+                job_data["location"] = Location(
+                    **job_data["location"]
+                ).display_location()
 
             compensation_obj = job_data.get("compensation")
             if compensation_obj and isinstance(compensation_obj, dict):
@@ -149,25 +153,25 @@ def scrape_jobs(
 
     if jobs_dfs:
         jobs_df = pd.concat(jobs_dfs, ignore_index=True)
-        desired_order: List[str] = [
+        desired_order: list[str] = [
             "job_url_hyper" if hyperlinks else "job_url",
             "site",
             "title",
             "company",
+            "company_url",
             "location",
             "job_type",
             "date_posted",
             "interval",
-            "benefits",
             "min_amount",
             "max_amount",
             "currency",
+            "is_remote",
+            "num_urgent_words",
+            "benefits",
             "emails",
-            "job_url_hyper" if hyperlinks else "job_url",
             "description",
         ]
-        jobs_formatted_df = jobs_df[desired_order]
+        return jobs_df[desired_order].sort_values(by=['site', 'date_posted'], ascending=[True, False])
     else:
-        jobs_formatted_df = pd.DataFrame()
-
-    return jobs_formatted_df
+        return pd.DataFrame()

src/jobspy/jobs/__init__.py

@@ -1,8 +1,7 @@
-from typing import Union, Optional
+from typing import Optional
 from datetime import date
 from enum import Enum
-
-from pydantic import BaseModel, validator
+from pydantic import BaseModel
 
 
 class JobType(Enum):
@@ -37,10 +36,16 @@ class JobType(Enum):
         "повназайнятість",
         "toànthờigian",
     )
-    PART_TIME = ("parttime", "teilzeit")
+    PART_TIME = ("parttime", "teilzeit", "částečnýúvazek", "deltid")
     CONTRACT = ("contract", "contractor")
     TEMPORARY = ("temporary",)
-    INTERNSHIP = ("internship", "prácticas", "ojt(onthejobtraining)", "praktikum")
+    INTERNSHIP = (
+        "internship",
+        "prácticas",
+        "ojt(onthejobtraining)",
+        "praktikum",
+        "praktik",
+    )
 
     PER_DIEM = ("perdiem",)
     NIGHTS = ("nights",)
@@ -50,40 +55,46 @@ class JobType(Enum):
 
 
 class Country(Enum):
-    ARGENTINA = ("argentina", "ar")
-    AUSTRALIA = ("australia", "au")
-    AUSTRIA = ("austria", "at")
+    """
+    Gets the subdomain for Indeed and Glassdoor.
+    The second item in the tuple is the subdomain for Indeed
+    The third item in the tuple is the subdomain (and tld if there's a ':' separator) for Glassdoor
+    """
+
+    ARGENTINA = ("argentina", "ar", "com.ar")
+    AUSTRALIA = ("australia", "au", "com.au")
+    AUSTRIA = ("austria", "at", "at")
     BAHRAIN = ("bahrain", "bh")
-    BELGIUM = ("belgium", "be")
-    BRAZIL = ("brazil", "br")
-    CANADA = ("canada", "ca")
+    BELGIUM = ("belgium", "be", "fr:be")
+    BRAZIL = ("brazil", "br", "com.br")
+    CANADA = ("canada", "ca", "ca")
     CHILE = ("chile", "cl")
     CHINA = ("china", "cn")
     COLOMBIA = ("colombia", "co")
     COSTARICA = ("costa rica", "cr")
-    CZECHREPUBLIC = ("czech republic", "cz")
+    CZECHREPUBLIC = ("czech republic,czechia", "cz")
     DENMARK = ("denmark", "dk")
     ECUADOR = ("ecuador", "ec")
     EGYPT = ("egypt", "eg")
     FINLAND = ("finland", "fi")
-    FRANCE = ("france", "fr")
-    GERMANY = ("germany", "de")
+    FRANCE = ("france", "fr", "fr")
+    GERMANY = ("germany", "de", "de")
     GREECE = ("greece", "gr")
-    HONGKONG = ("hong kong", "hk")
+    HONGKONG = ("hong kong", "hk", "com.hk")
     HUNGARY = ("hungary", "hu")
-    INDIA = ("india", "in")
+    INDIA = ("india", "in", "co.in")
     INDONESIA = ("indonesia", "id")
-    IRELAND = ("ireland", "ie")
+    IRELAND = ("ireland", "ie", "ie")
     ISRAEL = ("israel", "il")
-    ITALY = ("italy", "it")
+    ITALY = ("italy", "it", "it")
     JAPAN = ("japan", "jp")
     KUWAIT = ("kuwait", "kw")
     LUXEMBOURG = ("luxembourg", "lu")
     MALAYSIA = ("malaysia", "malaysia")
-    MEXICO = ("mexico", "mx")
+    MEXICO = ("mexico", "mx", "com.mx")
     MOROCCO = ("morocco", "ma")
-    NETHERLANDS = ("netherlands", "nl")
-    NEWZEALAND = ("new zealand", "nz")
+    NETHERLANDS = ("netherlands", "nl", "nl")
+    NEWZEALAND = ("new zealand", "nz", "co.nz")
     NIGERIA = ("nigeria", "ng")
     NORWAY = ("norway", "no")
     OMAN = ("oman", "om")
@@ -96,19 +107,19 @@ class Country(Enum):
     QATAR = ("qatar", "qa")
     ROMANIA = ("romania", "ro")
     SAUDIARABIA = ("saudi arabia", "sa")
-    SINGAPORE = ("singapore", "sg")
+    SINGAPORE = ("singapore", "sg", "sg")
     SOUTHAFRICA = ("south africa", "za")
     SOUTHKOREA = ("south korea", "kr")
-    SPAIN = ("spain", "es")
+    SPAIN = ("spain", "es", "es")
     SWEDEN = ("sweden", "se")
-    SWITZERLAND = ("switzerland", "ch")
+    SWITZERLAND = ("switzerland", "ch", "de:ch")
     TAIWAN = ("taiwan", "tw")
     THAILAND = ("thailand", "th")
     TURKEY = ("turkey", "tr")
     UKRAINE = ("ukraine", "ua")
     UNITEDARABEMIRATES = ("united arab emirates", "ae")
-    UK = ("uk", "uk")
-    USA = ("usa", "www")
+    UK = ("uk,united kingdom", "uk", "co.uk")
+    USA = ("usa,us,united states", "www", "com")
     URUGUAY = ("uruguay", "uy")
     VENEZUELA = ("venezuela", "ve")
     VIETNAM = ("vietnam", "vn")
@@ -116,34 +127,43 @@ class Country(Enum):
     # internal for ziprecruiter
     US_CANADA = ("usa/ca", "www")
 
-    # internal for linkeind
+    # internal for linkedin
     WORLDWIDE = ("worldwide", "www")
 
-    def __new__(cls, country, domain):
-        obj = object.__new__(cls)
-        obj._value_ = country
-        obj.domain = domain
-        return obj
+    @property
+    def indeed_domain_value(self):
+        return self.value[1]
 
     @property
-    def domain_value(self):
-        return self.domain
+    def glassdoor_domain_value(self):
+        if len(self.value) == 3:
+            subdomain, _, domain = self.value[2].partition(":")
+            if subdomain and domain:
+                return f"{subdomain}.glassdoor.{domain}"
+            else:
+                return f"www.glassdoor.{self.value[2]}"
+        else:
+            raise Exception(f"Glassdoor is not available for {self.name}")
+
+    def get_url(self):
+        return f"https://{self.glassdoor_domain_value}/"
 
     @classmethod
     def from_string(cls, country_str: str):
         """Convert a string to the corresponding Country enum."""
         country_str = country_str.strip().lower()
         for country in cls:
-            if country.value == country_str:
+            country_names = country.value[0].split(',')
+            if country_str in country_names:
                 return country
         valid_countries = [country.value for country in cls]
         raise ValueError(
-            f"Invalid country string: '{country_str}'. Valid countries (only include this param for Indeed) are: {', '.join(valid_countries)}"
+            f"Invalid country string: '{country_str}'. Valid countries are: {', '.join([country[0] for country in valid_countries])}"
         )
 
 
 class Location(BaseModel):
-    country: Country = None
+    country: Country | None = None
     city: Optional[str] = None
     state: Optional[str] = None
 
@@ -154,10 +174,13 @@ class Location(BaseModel):
         if self.state:
             location_parts.append(self.state)
         if self.country and self.country not in (Country.US_CANADA, Country.WORLDWIDE):
-            if self.country.value in ("usa", "uk"):
-                location_parts.append(self.country.value.upper())
+            country_name = self.country.value[0]
+            if "," in country_name:
+                country_name = country_name.split(",")[0]
+            if country_name in ("usa", "uk"):
+                location_parts.append(country_name.upper())
             else:
-                location_parts.append(self.country.value.title())
+                location_parts.append(country_name.title())
         return ", ".join(location_parts)
 
 
@@ -168,26 +191,47 @@ class CompensationInterval(Enum):
     DAILY = "daily"
     HOURLY = "hourly"
 
+    @classmethod
+    def get_interval(cls, pay_period):
+        interval_mapping = {
+            "YEAR": cls.YEARLY,
+            "HOUR": cls.HOURLY,
+        }
+        if pay_period in interval_mapping:
+            return interval_mapping[pay_period].value
+        else:
+            return cls[pay_period].value if pay_period in cls.__members__ else None
+
 
 class Compensation(BaseModel):
     interval: Optional[CompensationInterval] = None
-    min_amount: int = None
-    max_amount: int = None
+    min_amount: float | None = None
+    max_amount: float | None = None
     currency: Optional[str] = "USD"
 
 
+class DescriptionFormat(Enum):
+    MARKDOWN = "markdown"
+    HTML = "html"
+
+
 class JobPost(BaseModel):
     title: str
     company_name: str
     job_url: str
     location: Optional[Location]
 
-    description: Optional[str] = None
-    job_type: Optional[JobType] = None
-    compensation: Optional[Compensation] = None
-    date_posted: Optional[date] = None
-    benefits: Optional[str] = None
-    emails: Optional[list[str]] = None
+    description: str | None = None
+    company_url: str | None = None
+
+    job_type: list[JobType] | None = None
+    compensation: Compensation | None = None
+    date_posted: date | None = None
+    benefits: str | None = None
+    emails: list[str] | None = None
+    num_urgent_words: int | None = None
+    is_remote: bool | None = None
+    # company_industry: str | None = None
 
 
 class JobResponse(BaseModel):

src/jobspy/scrapers/__init__.py

@@ -1,32 +1,42 @@
-from ..jobs import Enum, BaseModel, JobType, JobResponse, Country
-from typing import List, Optional, Any
+from ..jobs import (
+    Enum,
+    BaseModel,
+    JobType,
+    JobResponse,
+    Country,
+    DescriptionFormat
+)
 
 
 class Site(Enum):
     LINKEDIN = "linkedin"
     INDEED = "indeed"
     ZIP_RECRUITER = "zip_recruiter"
+    GLASSDOOR = "glassdoor"
 
 
 class ScraperInput(BaseModel):
-    site_type: List[Site]
-    search_term: str
+    site_type: list[Site]
+    search_term: str | None = None
 
-    location: str = None
-    country: Optional[Country] = Country.USA
-    distance: Optional[int] = None
+    location: str | None = None
+    country: Country | None = Country.USA
+    distance: int | None = None
     is_remote: bool = False
-    job_type: Optional[JobType] = None
-    easy_apply: bool = None  # linkedin
+    job_type: JobType | None = None
+    easy_apply: bool | None = None
     offset: int = 0
+    linkedin_fetch_description: bool = False
+    linkedin_company_ids: list[int] | None = None
+    description_format: DescriptionFormat | None = DescriptionFormat.MARKDOWN
 
     results_wanted: int = 15
+    hours_old: int | None = None
 
 
 class Scraper:
-    def __init__(self, site: Site, proxy: Optional[List[str]] = None):
+    def __init__(self, site: Site, proxy: list[str] | None = None):
         self.site = site
         self.proxy = (lambda p: {"http": p, "https": p} if p else None)(proxy)
 
-    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
-        ...
+    def scrape(self, scraper_input: ScraperInput) -> JobResponse: ...

src/jobspy/scrapers/exceptions.py

@@ -7,12 +7,20 @@ This module contains the set of Scrapers' exceptions.
 
 
 class LinkedInException(Exception):
-    """Failed to scrape LinkedIn"""
+    def __init__(self, message=None):
+        super().__init__(message or "An error occurred with LinkedIn")
 
 
 class IndeedException(Exception):
-    """Failed to scrape Indeed"""
+    def __init__(self, message=None):
+        super().__init__(message or "An error occurred with Indeed")
 
 
 class ZipRecruiterException(Exception):
-    """Failed to scrape ZipRecruiter"""
+    def __init__(self, message=None):
+        super().__init__(message or "An error occurred with ZipRecruiter")
+
+
+class GlassdoorException(Exception):
+    def __init__(self, message=None):
+        super().__init__(message or "An error occurred with Glassdoor")

src/jobspy/scrapers/glassdoor/__init__.py

@@ -0,0 +1,500 @@
+"""
+jobspy.scrapers.glassdoor
+~~~~~~~~~~~~~~~~~~~
+
+This module contains routines to scrape Glassdoor.
+"""
+import json
+import requests
+from typing import Optional
+from datetime import datetime, timedelta
+from concurrent.futures import ThreadPoolExecutor, as_completed
+from ..utils import count_urgent_words, extract_emails_from_text
+
+from .. import Scraper, ScraperInput, Site
+from ..exceptions import GlassdoorException
+from ..utils import (
+    create_session,
+    markdown_converter,
+    logger
+)
+from ...jobs import (
+    JobPost,
+    Compensation,
+    CompensationInterval,
+    Location,
+    JobResponse,
+    JobType,
+    DescriptionFormat
+)
+
+
+class GlassdoorScraper(Scraper):
+    def __init__(self, proxy: Optional[str] = None):
+        """
+        Initializes GlassdoorScraper with the Glassdoor job search url
+        """
+        site = Site(Site.GLASSDOOR)
+        super().__init__(site, proxy=proxy)
+
+        self.base_url = None
+        self.country = None
+        self.session = None
+        self.scraper_input = None
+        self.jobs_per_page = 30
+        self.seen_urls = set()
+
+    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
+        """
+        Scrapes Glassdoor for jobs with scraper_input criteria.
+        :param scraper_input: Information about job search criteria.
+        :return: JobResponse containing a list of jobs.
+        """
+        self.scraper_input = scraper_input
+        self.scraper_input.results_wanted = min(900, scraper_input.results_wanted)
+        self.base_url = self.scraper_input.country.get_url()
+
+        location_id, location_type = self._get_location(
+            scraper_input.location, scraper_input.is_remote
+        )
+        if location_type is None:
+            return JobResponse(jobs=[])
+        all_jobs: list[JobPost] = []
+        cursor = None
+        max_pages = 30
+        self.session = create_session(self.proxy, is_tls=False, has_retry=True)
+        self.session.get(self.base_url)
+
+        try:
+            for page in range(
+                1 + (scraper_input.offset // self.jobs_per_page),
+                min(
+                    (scraper_input.results_wanted // self.jobs_per_page) + 2,
+                    max_pages + 1,
+                ),
+            ):
+                try:
+                    jobs, cursor = self._fetch_jobs_page(
+                        scraper_input, location_id, location_type, page, cursor
+                    )
+                    all_jobs.extend(jobs)
+                    if len(all_jobs) >= scraper_input.results_wanted:
+                        all_jobs = all_jobs[: scraper_input.results_wanted]
+                        break
+                except Exception as e:
+                    raise GlassdoorException(str(e))
+        except Exception as e:
+            raise GlassdoorException(str(e))
+        return JobResponse(jobs=all_jobs)
+
+    def _fetch_jobs_page(
+        self,
+        scraper_input: ScraperInput,
+        location_id: int,
+        location_type: str,
+        page_num: int,
+        cursor: str | None,
+    ) -> (list[JobPost], str | None):
+        """
+        Scrapes a page of Glassdoor for jobs with scraper_input criteria
+        """
+        self.scraper_input = scraper_input
+        try:
+            payload = self._add_payload(
+                location_id, location_type, page_num, cursor
+            )
+            response = self.session.post(
+                f"{self.base_url}/graph", headers=self.headers, timeout=10, data=payload
+            )
+            if response.status_code != 200:
+                raise GlassdoorException(
+                    f"bad response status code: {response.status_code}"
+                )
+            res_json = response.json()[0]
+            if "errors" in res_json:
+                raise ValueError("Error encountered in API response")
+        except Exception as e:
+            raise GlassdoorException(str(e))
+
+        jobs_data = res_json["data"]["jobListings"]["jobListings"]
+
+        jobs = []
+        with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
+            future_to_job_data = {executor.submit(self._process_job, job): job for job in jobs_data}
+            for future in as_completed(future_to_job_data):
+                try:
+                    job_post = future.result()
+                    if job_post:
+                        jobs.append(job_post)
+                except Exception as exc:
+                    raise GlassdoorException(f'Glassdoor generated an exception: {exc}')
+
+        return jobs, self.get_cursor_for_page(
+            res_json["data"]["jobListings"]["paginationCursors"], page_num + 1
+        )
+
+    def _process_job(self, job_data):
+        """
+        Processes a single job and fetches its description.
+        """
+        job_id = job_data["jobview"]["job"]["listingId"]
+        job_url = f'{self.base_url}job-listing/j?jl={job_id}'
+        if job_url in self.seen_urls:
+            return None
+        self.seen_urls.add(job_url)
+        job = job_data["jobview"]
+        title = job["job"]["jobTitleText"]
+        company_name = job["header"]["employerNameFromSearch"]
+        company_id = job_data['jobview']['header']['employer']['id']
+        location_name = job["header"].get("locationName", "")
+        location_type = job["header"].get("locationType", "")
+        age_in_days = job["header"].get("ageInDays")
+        is_remote, location = False, None
+        date_posted = (datetime.now() - timedelta(days=age_in_days)).date() if age_in_days is not None else None
+
+        if location_type == "S":
+            is_remote = True
+        else:
+            location = self.parse_location(location_name)
+
+        compensation = self.parse_compensation(job["header"])
+        try:
+            description = self._fetch_job_description(job_id)
+        except:
+            description = None
+        return JobPost(
+            title=title,
+            company_url=f"{self.base_url}Overview/W-EI_IE{company_id}.htm" if company_id else None,
+            company_name=company_name,
+            date_posted=date_posted,
+            job_url=job_url,
+            location=location,
+            compensation=compensation,
+            is_remote=is_remote,
+            description=description,
+            emails=extract_emails_from_text(description) if description else None,
+            num_urgent_words=count_urgent_words(description) if description else None,
+        )
+
+    def _fetch_job_description(self, job_id):
+        """
+        Fetches the job description for a single job ID.
+        """
+        url = f"{self.base_url}/graph"
+        body = [
+            {
+                "operationName": "JobDetailQuery",
+                "variables": {
+                    "jl": job_id,
+                    "queryString": "q",
+                    "pageTypeEnum": "SERP"
+                },
+                "query": """
+                query JobDetailQuery($jl: Long!, $queryString: String, $pageTypeEnum: PageTypeEnum) {
+                    jobview: jobView(
+                        listingId: $jl
+                        contextHolder: {queryString: $queryString, pageTypeEnum: $pageTypeEnum}
+                    ) {
+                        job {
+                            description
+                            __typename
+                        }
+                        __typename
+                    }
+                }
+                """
+            }
+        ]
+        res = requests.post(url, json=body, headers=self.headers)
+        if res.status_code != 200:
+            return None
+        data = res.json()[0]
+        desc = data['data']['jobview']['job']['description']
+        return markdown_converter(desc) if self.scraper_input.description_format == DescriptionFormat.MARKDOWN else 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 = 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')
+                return None, None
+            else:
+                logger.error(f'Glassdoor response status code {res.status_code}')
+                return None, None
+        items = res.json()
+
+        if not items:
+            raise ValueError(f"Location '{location}' not found on Glassdoor")
+        location_type = items[0]["locationType"]
+        if location_type == "C":
+            location_type = "CITY"
+        elif location_type == "S":
+            location_type = "STATE"
+        elif location_type == 'N':
+            location_type = "COUNTRY"
+        return int(items[0]["locationId"]), location_type
+
+    def _add_payload(
+        self,
+        location_id: int,
+        location_type: str,
+        page_num: int,
+        cursor: str | None = None,
+    ) -> str:
+        fromage = max(self.scraper_input.hours_old // 24, 1) if self.scraper_input.hours_old else None
+        filter_params = []
+        if self.scraper_input.easy_apply:
+            filter_params.append({"filterKey": "applicationType", "values": "1"})
+        if fromage:
+            filter_params.append({"filterKey": "fromAge", "values": str(fromage)})
+        payload = {
+            "operationName": "JobSearchResultsQuery",
+            "variables": {
+                "excludeJobListingIds": [],
+                "filterParams": filter_params,
+                "keyword": self.scraper_input.search_term,
+                "numJobsToShow": 30,
+                "locationType": location_type,
+                "locationId": int(location_id),
+                "parameterUrlInput": f"IL.0,12_I{location_type}{location_id}",
+                "pageNumber": page_num,
+                "pageCursor": cursor,
+                "fromage": fromage,
+                "sort": "date"
+            },
+            "query": """
+            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
+            }
+            """
+        }
+        if self.scraper_input.job_type:
+            payload["variables"]["filterParams"].append(
+                {"filterKey": "jobType", "values": self.scraper_input.job_type.value[0]}
+            )
+        return json.dumps([payload])
+
+    @staticmethod
+    def parse_compensation(data: dict) -> Optional[Compensation]:
+        pay_period = data.get("payPeriod")
+        adjusted_pay = data.get("payPeriodAdjustedPay")
+        currency = data.get("payCurrency", "USD")
+        if not pay_period or not adjusted_pay:
+            return None
+
+        interval = None
+        if pay_period == "ANNUAL":
+            interval = CompensationInterval.YEARLY
+        elif pay_period:
+            interval = CompensationInterval.get_interval(pay_period)
+        min_amount = int(adjusted_pay.get("p10") // 1)
+        max_amount = int(adjusted_pay.get("p90") // 1)
+        return Compensation(
+            interval=interval,
+            min_amount=min_amount,
+            max_amount=max_amount,
+            currency=currency,
+        )
+
+    @staticmethod
+    def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
+        for job_type in JobType:
+            if job_type_str in job_type.value:
+                return [job_type]
+
+    @staticmethod
+    def parse_location(location_name: str) -> Location | None:
+        if not location_name or location_name == "Remote":
+            return
+        city, _, state = location_name.partition(", ")
+        return Location(city=city, state=state)
+
+    @staticmethod
+    def get_cursor_for_page(pagination_cursors, page_num):
+        for cursor_data in pagination_cursors:
+            if cursor_data["pageNumber"] == page_num:
+                return cursor_data["cursor"]
+
+    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",
+        "gd-csrf-token": "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok",
+        "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",
+    }

src/jobspy/scrapers/indeed/__init__.py

@@ -6,18 +6,24 @@ This module contains routines to scrape Indeed.
 """
 import re
 import math
-import io
 import json
+import requests
+from typing import Any
 from datetime import datetime
-from typing import Optional
 
-import tls_client
-import urllib.parse
 from bs4 import BeautifulSoup
 from bs4.element import Tag
 from concurrent.futures import ThreadPoolExecutor, Future
 
 from ..exceptions import IndeedException
+from ..utils import (
+    count_urgent_words,
+    extract_emails_from_text,
+    create_session,
+    get_enum_from_job_type,
+    markdown_converter,
+    logger
+)
 from ...jobs import (
     JobPost,
     Compensation,
@@ -25,88 +31,99 @@ from ...jobs import (
     Location,
     JobResponse,
     JobType,
+    DescriptionFormat
 )
 from .. import Scraper, ScraperInput, Site
 
-def extract_emails_from_text(text: str) -> Optional[list[str]]:
-    if not text:
-        return None
-    email_regex = re.compile(r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}")
-    return email_regex.findall(text)
-
 
 class IndeedScraper(Scraper):
-    def __init__(self, proxy: Optional[str] = None):
+    def __init__(self, proxy: str | None = None):
         """
         Initializes IndeedScraper with the Indeed job search url
         """
-        self.url = None
-        self.country = None
+        self.scraper_input = None
+        self.jobs_per_page = 25
+        self.num_workers = 10
+        self.seen_urls = set()
+        self.base_url = None
+        self.api_url = "https://apis.indeed.com/graphql"
         site = Site(Site.INDEED)
         super().__init__(site, proxy=proxy)
 
-        self.jobs_per_page = 15
-        self.seen_urls = set()
+    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
+        """
+        Scrapes Indeed for jobs with scraper_input criteria
+        :param scraper_input:
+        :return: job_response
+        """
+        self.scraper_input = scraper_input
+        job_list = self._scrape_page()
+        pages_processed = 1
 
-    def scrape_page(
-            self, scraper_input: ScraperInput, page: int, session: tls_client.Session
-    ) -> tuple[list[JobPost], int]:
+        while len(self.seen_urls) < scraper_input.results_wanted:
+            pages_to_process = math.ceil((scraper_input.results_wanted - len(self.seen_urls)) / self.jobs_per_page)
+            new_jobs = False
+
+            with ThreadPoolExecutor(max_workers=10) as executor:
+                futures: list[Future] = [
+                    executor.submit(self._scrape_page, page + pages_processed)
+                    for page in range(pages_to_process)
+                ]
+
+                for future in futures:
+                    jobs = future.result()
+                    if jobs:
+                        job_list += jobs
+                        new_jobs = True
+                    if len(self.seen_urls) >= scraper_input.results_wanted:
+                        break
+
+            pages_processed += pages_to_process
+            if not new_jobs:
+                break
+
+
+        if len(self.seen_urls) > scraper_input.results_wanted:
+            job_list = job_list[:scraper_input.results_wanted]
+
+        return JobResponse(jobs=job_list)
+
+    def _scrape_page(self, page: int=0) -> list[JobPost]:
         """
         Scrapes a page of Indeed for jobs with scraper_input criteria
-        :param scraper_input:
         :param page:
-        :param session:
         :return: jobs found on page, total number of jobs found for search
         """
-        self.country = scraper_input.country
-        domain = self.country.domain_value
-        self.url = f"https://{domain}.indeed.com"
+        job_list = []
+        domain = self.scraper_input.country.indeed_domain_value
+        self.base_url = f"https://{domain}.indeed.com"
 
-        job_list: list[JobPost] = []
-
-        params = {
-            "q": scraper_input.search_term,
-            "l": scraper_input.location,
-            "filter": 0,
-            "start": scraper_input.offset + page * 10,
-        }
-        if scraper_input.distance:
-            params["radius"] = scraper_input.distance
-
-        sc_values = []
-        if scraper_input.is_remote:
-            sc_values.append("attr(DSQF7)")
-        if scraper_input.job_type:
-            sc_values.append("jt({})".format(scraper_input.job_type.value))
-
-        if sc_values:
-            params["sc"] = "0kf:" + "".join(sc_values) + ";"
         try:
+            session = create_session(self.proxy)
             response = session.get(
-                f"{self.url}/jobs",
-                params=params,
-                allow_redirects=True,
-                proxy=self.proxy,
-                timeout_seconds=10,
+                f"{self.base_url}/m/jobs",
+                headers=self.headers,
+                params=self._add_params(page),
             )
             if response.status_code not in range(200, 400):
-                raise IndeedException(
-                    f"bad response with status code: {response.status_code}"
-                )
+                if response.status_code == 429:
+                    logger.error(f'429 Response - Blocked by Indeed for too many requests')
+                else:
+                    logger.error(f'Indeed response status code {response.status_code}')
+                return job_list
+
         except Exception as e:
             if "Proxy responded with" in str(e):
-                raise IndeedException("bad proxy")
-            raise IndeedException(str(e))
+                logger.error(f'Indeed: Bad proxy')
+            else:
+                logger.error(f'Indeed: {str(e)}')
+            return job_list
 
         soup = BeautifulSoup(response.content, "html.parser")
         if "did not match any jobs" in response.text:
-            raise IndeedException("Parsing exception: Search did not match any jobs")
-
-        jobs = IndeedScraper.parse_jobs(
-            soup
-        )  #: can raise exception, handled by main scrape function
-        total_num_jobs = IndeedScraper.total_jobs(soup)
+            return job_list
 
+        jobs = IndeedScraper._parse_jobs(soup)
         if (
             not jobs.get("metaData", {})
             .get("mosaicProviderJobCardsModel", {})
@@ -114,11 +131,128 @@ class IndeedScraper(Scraper):
         ):
             raise IndeedException("No jobs found.")
 
-        def process_job(job) -> Optional[JobPost]:
-            job_url = f'{self.url}/jobs/viewjob?jk={job["jobkey"]}'
-            job_url_client = f'{self.url}/viewjob?jk={job["jobkey"]}'
+        jobs = jobs["metaData"]["mosaicProviderJobCardsModel"]["results"]
+        job_keys = [job['jobkey'] for job in jobs]
+        jobs_detailed = self._get_job_details(job_keys)
+
+        with ThreadPoolExecutor(max_workers=self.num_workers) as executor:
+            job_results: list[Future] = [
+                executor.submit(self._process_job, job, job_detailed['job']) for job, job_detailed in zip(jobs, jobs_detailed)
+            ]
+
+        job_list = [result.result() for result in job_results if result.result()]
+
+        return job_list
+
+    def _process_job(self, job: dict, job_detailed: dict) -> JobPost | None:
+        job_url = f'{self.base_url}/m/jobs/viewjob?jk={job["jobkey"]}'
+        job_url_client = f'{self.base_url}/viewjob?jk={job["jobkey"]}'
         if job_url in self.seen_urls:
             return None
+        self.seen_urls.add(job_url)
+        description = job_detailed['description']['html']
+        description = markdown_converter(description) if self.scraper_input.description_format == DescriptionFormat.MARKDOWN else description
+        job_type = self._get_job_type(job)
+        timestamp_seconds = job["pubDate"] / 1000
+        date_posted = datetime.fromtimestamp(timestamp_seconds)
+        date_posted = date_posted.strftime("%Y-%m-%d")
+        return JobPost(
+            title=job["normTitle"],
+            description=description,
+            company_name=job["company"],
+            company_url=f"{self.base_url}{job_detailed['employer']['relativeCompanyPageUrl']}" if job_detailed[
+                'employer'] else None,
+            location=Location(
+                city=job.get("jobLocationCity"),
+                state=job.get("jobLocationState"),
+                country=self.scraper_input.country,
+            ),
+            job_type=job_type,
+            compensation=self._get_compensation(job, job_detailed),
+            date_posted=date_posted,
+            job_url=job_url_client,
+            emails=extract_emails_from_text(description) if description else None,
+            num_urgent_words=count_urgent_words(description) if description else None,
+            is_remote=self._is_job_remote(job, job_detailed, description)
+        )
+
+    def _get_job_details(self, job_keys: list[str]) -> dict:
+        """
+        Queries the GraphQL endpoint for detailed job information for the given job keys.
+        """
+        job_keys_gql = '[' + ', '.join(f'"{key}"' for key in job_keys) + ']'
+        payload = dict(self.api_payload)
+        payload["query"] = self.api_payload["query"].format(job_keys_gql=job_keys_gql)
+        response = requests.post(self.api_url, headers=self.api_headers, json=payload, proxies=self.proxy)
+        if response.status_code == 200:
+            return response.json()['data']['jobData']['results']
+        else:
+            return {}
+
+    def _add_params(self, page: int) -> dict[str, str | Any]:
+        fromage = max(self.scraper_input.hours_old // 24, 1) if self.scraper_input.hours_old else None
+        params = {
+            "q": self.scraper_input.search_term,
+            "l": self.scraper_input.location if self.scraper_input.location else self.scraper_input.country.value[0].split(',')[-1],
+            "filter": 0,
+            "start": self.scraper_input.offset + page * 10,
+            "sort": "date",
+            "fromage": fromage,
+        }
+        if self.scraper_input.distance:
+            params["radius"] = self.scraper_input.distance
+
+        sc_values = []
+        if self.scraper_input.is_remote:
+            sc_values.append("attr(DSQF7)")
+        if self.scraper_input.job_type:
+            sc_values.append("jt({})".format(self.scraper_input.job_type.value[0]))
+
+        if sc_values:
+            params["sc"] = "0kf:" + "".join(sc_values) + ";"
+
+        if self.scraper_input.easy_apply:
+            params['iafilter'] = 1
+
+        return params
+
+    @staticmethod
+    def _get_job_type(job: dict) -> list[JobType] | None:
+        """
+        Parses the job to get list of job types
+        :param job:
+        :return:
+        """
+        job_types: list[JobType] = []
+        for taxonomy in job["taxonomyAttributes"]:
+            if taxonomy["label"] == "job-types":
+                for i in range(len(taxonomy["attributes"])):
+                    label = taxonomy["attributes"][i].get("label")
+                    if label:
+                        job_type_str = label.replace("-", "").replace(" ", "").lower()
+                        job_type = get_enum_from_job_type(job_type_str)
+                        if job_type:
+                            job_types.append(job_type)
+        return job_types
+
+    @staticmethod
+    def _get_compensation(job: dict, job_detailed: dict) -> Compensation:
+        """
+        Parses the job to get
+        :param job:
+        :param job_detailed:
+        :return: compensation object
+        """
+        comp = job_detailed['compensation']['baseSalary']
+        if comp:
+            interval = IndeedScraper._get_correct_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_detailed['compensation']['currencyCode']
+                )
 
         extracted_salary = job.get("extractedSalary")
         compensation = None
@@ -137,154 +271,16 @@ class IndeedScraper(Scraper):
                     max_amount=int(extracted_salary.get("max")),
                     currency=currency,
                 )
-
-            job_type = IndeedScraper.get_job_type(job)
-            timestamp_seconds = job["pubDate"] / 1000
-            date_posted = datetime.fromtimestamp(timestamp_seconds)
-            date_posted = date_posted.strftime("%Y-%m-%d")
-
-            description = self.get_description(job_url, session)
-            emails = extract_emails_from_text(description)
-            with io.StringIO(job["snippet"]) as f:
-                soup_io = BeautifulSoup(f, "html.parser")
-                li_elements = soup_io.find_all("li")
-                if description is None and li_elements:
-                    description = " ".join(li.text for li in li_elements)
-
-            job_post = JobPost(
-                title=job["normTitle"],
-                description=description,
-                company_name=job["company"],
-                location=Location(
-                    city=job.get("jobLocationCity"),
-                    state=job.get("jobLocationState"),
-                    country=self.country,
-                ),
-                emails=extract_emails_from_text(description),
-                job_type=job_type,
-                compensation=compensation,
-                date_posted=date_posted,
-                job_url=job_url_client,
-            )
-            return job_post
-
-        with ThreadPoolExecutor(max_workers=1) as executor:
-            job_results: list[Future] = [
-                executor.submit(process_job, job)
-                for job in jobs["metaData"]["mosaicProviderJobCardsModel"]["results"]
-            ]
-
-        job_list = [result.result() for result in job_results if result.result()]
-
-        return job_list, total_num_jobs
-
-    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
-        """
-        Scrapes Indeed for jobs with scraper_input criteria
-        :param scraper_input:
-        :return: job_response
-        """
-        session = tls_client.Session(
-            client_identifier="chrome112", random_tls_extension_order=True
-        )
-
-        pages_to_process = (
-                math.ceil(scraper_input.results_wanted / self.jobs_per_page) - 1
-        )
-
-        #: get first page to initialize session
-        job_list, total_results = self.scrape_page(scraper_input, 0, session)
-
-        with ThreadPoolExecutor(max_workers=1) as executor:
-            futures: list[Future] = [
-                executor.submit(self.scrape_page, scraper_input, page, session)
-                for page in range(1, pages_to_process + 1)
-            ]
-
-            for future in futures:
-                jobs, _ = future.result()
-
-                job_list += jobs
-
-        if len(job_list) > scraper_input.results_wanted:
-            job_list = job_list[: scraper_input.results_wanted]
-
-        job_response = JobResponse(
-            jobs=job_list,
-            total_results=total_results,
-        )
-        return job_response
-
-    def get_description(self, job_page_url: str, session: tls_client.Session) -> Optional[str]:
-        """
-        Retrieves job description by going to the job page url
-        :param job_page_url:
-        :param session:
-        :return: description
-        """
-        parsed_url = urllib.parse.urlparse(job_page_url)
-        params = urllib.parse.parse_qs(parsed_url.query)
-        jk_value = params.get("jk", [None])[0]
-        formatted_url = f"{self.url}/viewjob?jk={jk_value}&spa=1"
-
-        try:
-            response = session.get(
-                formatted_url, allow_redirects=True, timeout_seconds=5, proxy=self.proxy
-            )
-        except Exception as e:
-            return None
-
-        if response.status_code not in range(200, 400):
-            return None
-
-        raw_description = response.json()["body"]["jobInfoWrapperModel"][
-            "jobInfoModel"
-        ]["sanitizedJobDescription"]
-        with io.StringIO(raw_description) as f:
-            soup = BeautifulSoup(f, "html.parser")
-            text_content = " ".join(soup.get_text().split()).strip()
-            return text_content
+        return compensation
 
     @staticmethod
-    def get_job_type(job: dict) -> Optional[JobType]:
-        """
-        Parses the job to get JobTypeIndeed
-        :param job:
-        :return:
-        """
-        for taxonomy in job["taxonomyAttributes"]:
-            if taxonomy["label"] == "job-types":
-                if len(taxonomy["attributes"]) > 0:
-                    label = taxonomy["attributes"][0].get("label")
-                    if label:
-                        job_type_str = label.replace("-", "").replace(" ", "").lower()
-                        return IndeedScraper.get_enum_from_job_type(job_type_str)
-        return None
-
-    @staticmethod
-    def get_enum_from_job_type(job_type_str):
-        """
-        Given a string, returns the corresponding JobType enum member if a match is found.
-        for job_type in JobType:
-        """
-        for job_type in JobType:
-            if job_type_str in job_type.value:
-                return job_type
-        return None
-
-    @staticmethod
-    def parse_jobs(soup: BeautifulSoup) -> dict:
+    def _parse_jobs(soup: BeautifulSoup) -> dict:
         """
         Parses the jobs from the soup object
         :param soup:
         :return: jobs
         """
-
-        def find_mosaic_script() -> Optional[Tag]:
-            """
-            Finds jobcards script tag
-            :return: script_tag
-            """
+        def find_mosaic_script() -> Tag | None:
             script_tags = soup.find_all("script")
 
             for tag in script_tags:
@@ -297,7 +293,6 @@ class IndeedScraper(Scraper):
             return None
 
         script_tag = find_mosaic_script()
-
         if script_tag:
             script_str = script_tag.string
             pattern = r'window.mosaic.providerData\["mosaic-provider-jobcards"\]\s*=\s*({.*?});'
@@ -310,23 +305,113 @@ class IndeedScraper(Scraper):
                 raise IndeedException("Could not find mosaic provider job cards data")
         else:
             raise IndeedException(
-                "Could not find a script tag containing mosaic provider data"
+                "Could not find any results for the search"
             )
 
     @staticmethod
-    def total_jobs(soup: BeautifulSoup) -> int:
-        """
-        Parses the total jobs for that search from soup object
-        :param soup:
-        :return: total_num_jobs
-        """
-        script = soup.find("script", string=lambda t: t and "window._initialData" in t)
+    def _is_job_remote(job: dict, job_detailed: dict, description: str) -> bool:
+        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_detailed['attributes']
+        )
+        is_remote_in_description = any(keyword in description.lower() for keyword in remote_keywords)
+        is_remote_in_location = any(
+            keyword in job_detailed['location']['formatted']['long'].lower()
+            for keyword in remote_keywords
+        )
+        is_remote_in_taxonomy = any(
+            taxonomy["label"] == "remote" and len(taxonomy["attributes"]) > 0
+            for taxonomy in job.get("taxonomyAttributes", [])
+        )
+        return is_remote_in_attributes or is_remote_in_description or is_remote_in_location or is_remote_in_taxonomy
 
-        pattern = re.compile(r"window._initialData\s*=\s*({.*})\s*;", re.DOTALL)
-        match = pattern.search(script.string)
-        total_num_jobs = 0
-        if match:
-            json_str = match.group(1)
-            data = json.loads(json_str)
-            total_num_jobs = int(data["searchTitleBarModel"]["totalNumResults"])
-        return total_num_jobs
+    @staticmethod
+    def _get_correct_interval(interval: str) -> CompensationInterval:
+        interval_mapping = {
+            "DAY": "DAILY",
+            "YEAR": "YEARLY",
+            "HOUR": "HOURLY",
+            "WEEK": "WEEKLY",
+            "MONTH": "MONTHLY"
+        }
+        mapped_interval = interval_mapping.get(interval.upper(), None)
+        if mapped_interval and mapped_interval in CompensationInterval.__members__:
+            return CompensationInterval[mapped_interval]
+        else:
+            raise ValueError(f"Unsupported interval: {interval}")
+
+    headers =  {
+      'Host': 'www.indeed.com',
+      'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
+      'sec-fetch-site': 'same-origin',
+      'sec-fetch-dest': 'document',
+      'accept-language': 'en-US,en;q=0.9',
+      'sec-fetch-mode': 'navigate',
+      '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 192.0',
+      'referer': 'https://www.indeed.com/m/jobs?q=software%20intern&l=Dallas%2C%20TX&from=serpso&rq=1&rsIdx=3',
+    }
+    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',
+        'indeed-co': 'US',
+    }
+    api_payload = {
+        "query": """
+        query GetJobData {{
+          jobData(input: {{
+            jobKeys: {job_keys_gql}
+          }}) {{
+            results {{
+              job {{
+                key
+                title
+                description {{
+                  html
+                }}
+                location {{
+                  countryName
+                  countryCode
+                  city
+                  postalCode
+                  streetAddress
+                  formatted {{
+                    short
+                    long
+                  }}
+                }}
+                compensation {{
+                  baseSalary {{
+                    unitOfWork
+                    range {{
+                      ... on Range {{
+                        min
+                        max
+                      }}
+                    }}
+                  }}
+                  currencyCode
+                }}
+                attributes {{
+                  label
+                }}
+                employer {{
+                  relativeCompanyPageUrl
+                }}
+                recruit {{
+                  viewJobUrl
+                  detailedSalary
+                  workSchedule
+                }}
+              }}
+            }}
+          }}
+        }}
+        """
+    }

src/jobspy/scrapers/linkedin/__init__.py

@@ -4,46 +4,51 @@ jobspy.scrapers.linkedin
 
 This module contains routines to scrape LinkedIn.
 """
+import time
+import random
 from typing import Optional
 from datetime import datetime
 
 import requests
-import time
-import re
 from requests.exceptions import ProxyError
-from concurrent.futures import ThreadPoolExecutor, as_completed
-from bs4 import BeautifulSoup
-from bs4.element import Tag
 from threading import Lock
+from bs4.element import Tag
+from bs4 import BeautifulSoup
+from urllib.parse import urlparse, urlunparse
 
 from .. import Scraper, ScraperInput, Site
 from ..exceptions import LinkedInException
+from ..utils import create_session
 from ...jobs import (
     JobPost,
     Location,
     JobResponse,
     JobType,
+    Country,
+    Compensation,
+    DescriptionFormat
+)
+from ..utils import (
+    logger,
+    count_urgent_words,
+    extract_emails_from_text,
+    get_enum_from_job_type,
+    currency_parser,
+    markdown_converter
 )
 
 
-def extract_emails_from_text(text: str) -> Optional[list[str]]:
-    if not text:
-        return None
-    email_regex = re.compile(r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}")
-    return email_regex.findall(text)
-
-
 class LinkedInScraper(Scraper):
-    MAX_RETRIES = 3
-    DELAY = 10
+    base_url = "https://www.linkedin.com"
+    delay = 3
 
     def __init__(self, proxy: Optional[str] = None):
         """
         Initializes LinkedInScraper with the LinkedIn job search url
         """
+        self.scraper_input = None
         site = Site(Site.LINKEDIN)
         self.country = "worldwide"
-        self.url = "https://www.linkedin.com"
         super().__init__(site, proxy=proxy)
 
     def scrape(self, scraper_input: ScraperInput) -> JobResponse:
@@ -52,202 +57,195 @@ class LinkedInScraper(Scraper):
         :param scraper_input:
         :return: job_response
         """
+        self.scraper_input = scraper_input
         job_list: list[JobPost] = []
         seen_urls = set()
         url_lock = Lock()
         page = scraper_input.offset // 25 + 25 if scraper_input.offset else 0
+        seconds_old = (
+            scraper_input.hours_old * 3600
+            if scraper_input.hours_old
+            else None
+        )
+        continue_search = lambda: len(job_list) < scraper_input.results_wanted and page < 1000
 
-        def job_type_code(job_type_enum):
-            mapping = {
-                JobType.FULL_TIME: "F",
-                JobType.PART_TIME: "P",
-                JobType.INTERNSHIP: "I",
-                JobType.CONTRACT: "C",
-                JobType.TEMPORARY: "T",
-            }
-
-            return mapping.get(job_type_enum, "")
-
-        while len(job_list) < scraper_input.results_wanted and page < 1000:
+        while continue_search():
+            session = create_session(is_tls=False, has_retry=True, delay=5)
             params = {
                 "keywords": scraper_input.search_term,
                 "location": scraper_input.location,
                 "distance": scraper_input.distance,
                 "f_WT": 2 if scraper_input.is_remote else None,
-                "f_JT": job_type_code(scraper_input.job_type)
+                "f_JT": self.job_type_code(scraper_input.job_type)
                 if scraper_input.job_type
                 else None,
                 "pageNum": 0,
-                page: page + scraper_input.offset,
+                "start": page + scraper_input.offset,
                 "f_AL": "true" if scraper_input.easy_apply else None,
+                "f_C": ','.join(map(str, scraper_input.linkedin_company_ids)) if scraper_input.linkedin_company_ids else None,
+                "f_TPR": f"r{seconds_old}",
             }
 
             params = {k: v for k, v in params.items() if v is not None}
-
-            params = {k: v for k, v in params.items() if v is not None}
-            retries = 0
-            while retries < self.MAX_RETRIES:
             try:
-                    response = requests.get(
-                        f"{self.url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
+                response = 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,
                 )
-                    response.raise_for_status()
-
-                    break
-                except requests.HTTPError as e:
-                    if hasattr(e, 'response') and e.response is not None:
-                        if e.response.status_code == 429:
-                            time.sleep(self.DELAY)
-                            retries += 1
-                            continue
+                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')
                     else:
-                            raise LinkedInException(f"bad response status code: {e.response.status_code}")
-                    else:
-                        raise
-                except ProxyError as e:
-                    raise LinkedInException("bad proxy")
+                        logger.error(f'LinkedIn response status code {response.status_code}')
+                    return JobResponse(job_list=job_list)
             except Exception as e:
-                    raise LinkedInException(str(e))
+                if "Proxy responded with" in str(e):
+                    logger.error(f'Indeed: Bad proxy')
                 else:
-                # Raise an exception if the maximum number of retries is reached
-                raise LinkedInException("Max retries reached, failed to get a valid response")
+                    logger.error(f'Indeed: {str(e)}')
+                return JobResponse(job_list=job_list)
 
             soup = BeautifulSoup(response.text, "html.parser")
+            job_cards = soup.find_all("div", class_="base-search-card")
+            if len(job_cards) == 0:
+                return JobResponse(jobs=job_list)
 
-            with ThreadPoolExecutor(max_workers=5) as executor:
-                futures = []
-                for job_card in soup.find_all("div", class_="base-search-card"):
+            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.url}/jobs/view/{job_id}"
+                    job_url = f"{self.base_url}/jobs/view/{job_id}"
 
                 with url_lock:
                     if job_url in seen_urls:
                         continue
                     seen_urls.add(job_url)
-
-                    futures.append(executor.submit(self.process_job, job_card, job_url))
-
-                for future in as_completed(futures):
                 try:
-                        job_post = future.result()
+                    job_post = self._process_job(job_card, job_url, scraper_input.linkedin_fetch_description)
                     if job_post:
                         job_list.append(job_post)
+                    if not continue_search():
+                       break
                 except Exception as e:
-                        raise LinkedInException("Exception occurred while processing jobs")
+                    raise LinkedInException(str(e))
+
+            if continue_search():
+                time.sleep(random.uniform(self.delay, self.delay + 2))
                 page += 25
 
         job_list = job_list[: scraper_input.results_wanted]
         return JobResponse(jobs=job_list)
 
-    def process_job(self, job_card: Tag, job_url: str) -> Optional[JobPost]:
+    def _process_job(self, job_card: Tag, job_url: str, full_descr: bool) -> Optional[JobPost]:
+        salary_tag = job_card.find('span', class_='job-search-card__salary-info')
+
+        compensation = None
+        if salary_tag:
+            salary_text = salary_tag.get_text(separator=" ").strip()
+            salary_values = [currency_parser(value) for value in salary_text.split("-")]
+            salary_min = salary_values[0]
+            salary_max = salary_values[1]
+            currency = salary_text[0] if salary_text[0] != "$" else "USD"
+
+            compensation = Compensation(
+                min_amount=int(salary_min),
+                max_amount=int(salary_max),
+                currency=currency,
+            )
+
         title_tag = job_card.find("span", class_="sr-only")
         title = title_tag.get_text(strip=True) if title_tag else "N/A"
 
         company_tag = job_card.find("h4", class_="base-search-card__subtitle")
         company_a_tag = company_tag.find("a") if company_tag else None
+        company_url = (
+            urlunparse(urlparse(company_a_tag.get("href"))._replace(query=""))
+            if company_a_tag and company_a_tag.has_attr("href")
+            else ""
+        )
         company = company_a_tag.get_text(strip=True) if company_a_tag else "N/A"
 
         metadata_card = job_card.find("div", class_="base-search-card__metadata")
-        location = self.get_location(metadata_card)
+        location = self._get_location(metadata_card)
 
-        datetime_tag = metadata_card.find("time", class_="job-search-card__listdate") if metadata_card else None
-        date_posted = None
+        datetime_tag = (
+            metadata_card.find("time", class_="job-search-card__listdate")
+            if metadata_card
+            else None
+        )
+        date_posted = description = job_type = 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 Exception as e:
+            except:
                 date_posted = None
         benefits_tag = job_card.find("span", class_="result-benefits__text")
         benefits = " ".join(benefits_tag.get_text().split()) if benefits_tag else None
-
-        description, job_type = self.get_job_description(job_url)
+        if full_descr:
+            description, job_type = self._get_job_description(job_url)
 
         return JobPost(
             title=title,
-            description=description,
             company_name=company,
+            company_url=company_url,
             location=location,
             date_posted=date_posted,
             job_url=job_url,
-            job_type=job_type,
+            compensation=compensation,
             benefits=benefits,
-            emails=extract_emails_from_text(description)
+            job_type=job_type,
+            description=description,
+            emails=extract_emails_from_text(description) if description else None,
+            num_urgent_words=count_urgent_words(description) if description else None,
         )
 
-    def get_job_description(self, job_page_url: str) -> tuple[None, None] | tuple[
-        str | None, tuple[str | None, JobType | None]]:
+    def _get_job_description(
+        self, job_page_url: str
+    ) -> tuple[None, None] | tuple[str | None, tuple[str | None, JobType | None]]:
         """
         Retrieves job description by going to the job page url
         :param job_page_url:
         :return: description or None
         """
         try:
-            response = requests.get(job_page_url, timeout=5, proxies=self.proxy)
+            session = create_session(is_tls=False, has_retry=True)
+            response = session.get(job_page_url, headers=self.headers, timeout=5, proxies=self.proxy)
             response.raise_for_status()
-        except Exception as e:
+        except:
+            return None, None
+        if response.url == "https://www.linkedin.com/signup":
             return None, None
 
         soup = BeautifulSoup(response.text, "html.parser")
         div_content = soup.find(
             "div", class_=lambda x: x and "show-more-less-html__markup" in x
         )
-
         description = None
-        if div_content:
-            description = " ".join(div_content.get_text().split()).strip()
+        if div_content is not None:
+            def remove_attributes(tag):
+                for attr in list(tag.attrs):
+                    del tag[attr]
+                return tag
+            div_content = remove_attributes(div_content)
+            description = div_content.prettify(formatter="html")
+            if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
+                description = markdown_converter(description)
+        return description, self._parse_job_type(soup)
 
-        def get_job_type(
-                soup_job_type: BeautifulSoup,
-        ) -> JobType | None:
-            """
-            Gets the job type from job page
-            :param soup_job_type:
-            :return: JobType
-            """
-            h3_tag = soup_job_type.find(
-                "h3",
-                class_="description__job-criteria-subheader",
-                string=lambda text: "Employment type" in text,
-            )
-
-            employment_type = None
-            if h3_tag:
-                employment_type_span = h3_tag.find_next_sibling(
-                    "span",
-                    class_="description__job-criteria-text description__job-criteria-text--criteria",
-                )
-                if employment_type_span:
-                    employment_type = employment_type_span.get_text(strip=True)
-                    employment_type = employment_type.lower()
-                    employment_type = employment_type.replace("-", "")
-
-            return LinkedInScraper.get_enum_from_value(employment_type)
-
-        return description, get_job_type(soup)
-
-    @staticmethod
-    def get_enum_from_value(value_str):
-        for job_type in JobType:
-            if value_str in job_type.value:
-                return job_type
-        return None
-
-    def get_location(self, metadata_card: Optional[Tag]) -> Location:
+    def _get_location(self, metadata_card: Optional[Tag]) -> Location:
         """
         Extracts the location data from the job metadata card.
         :param metadata_card
         :return: location
         """
-        location = Location(country=self.country)
+        location = Location(country=Country.from_string(self.country))
         if metadata_card is not None:
             location_tag = metadata_card.find(
                 "span", class_="job-search-card__location"
@@ -259,13 +257,57 @@ class LinkedInScraper(Scraper):
                 location = Location(
                     city=city,
                     state=state,
-                    country=self.country,
+                    country=Country.from_string(self.country),
+                )
+            elif len(parts) == 3:
+                city, state, country = parts
+                location = Location(
+                    city=city,
+                    state=state,
+                    country=Country.from_string(country)
                 )
-
         return location
 
-def extract_emails_from_text(text: str) -> Optional[list[str]]:
-    if not text:
-        return None
-    email_regex = re.compile(r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}")
-    return email_regex.findall(text)
+    @staticmethod
+    def _parse_job_type(soup_job_type: BeautifulSoup) -> list[JobType] | None:
+        """
+        Gets the job type from job page
+        :param soup_job_type:
+        :return: JobType
+        """
+        h3_tag = soup_job_type.find(
+            "h3",
+            class_="description__job-criteria-subheader",
+            string=lambda text: "Employment type" in text,
+        )
+        employment_type = None
+        if h3_tag:
+            employment_type_span = h3_tag.find_next_sibling(
+                "span",
+                class_="description__job-criteria-text description__job-criteria-text--criteria",
+            )
+            if employment_type_span:
+                employment_type = employment_type_span.get_text(strip=True)
+                employment_type = employment_type.lower()
+                employment_type = employment_type.replace("-", "")
+
+        return [get_enum_from_job_type(employment_type)] if employment_type else []
+
+    @staticmethod
+    def job_type_code(job_type_enum: JobType) -> str:
+        return {
+            JobType.FULL_TIME: "F",
+            JobType.PART_TIME: "P",
+            JobType.INTERNSHIP: "I",
+            JobType.CONTRACT: "C",
+            JobType.TEMPORARY: "T",
+        }.get(job_type_enum, "")
+
+    headers = {
+        "authority": "www.linkedin.com",
+        "accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7",
+        "accept-language": "en-US,en;q=0.9",
+        "cache-control": "max-age=0",
+        "upgrade-insecure-requests": "1",
+        "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36",
+    }

src/jobspy/scrapers/utils.py

@@ -0,0 +1,109 @@
+import re
+import logging
+import numpy as np
+
+import html2text
+import tls_client
+import requests
+from requests.adapters import HTTPAdapter, Retry
+
+from ..jobs import JobType
+
+text_maker = html2text.HTML2Text()
+logger = logging.getLogger("JobSpy")
+logger.propagate = False
+if not logger.handlers:
+    logger.setLevel(logging.ERROR)
+    console_handler = logging.StreamHandler()
+    console_handler.setLevel(logging.ERROR)
+    formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+    console_handler.setFormatter(formatter)
+    logger.addHandler(console_handler)
+
+
+def count_urgent_words(description: str) -> int:
+    """
+    Count the number of urgent words or phrases in a job description.
+    """
+    urgent_patterns = re.compile(
+        r"\burgen(t|cy)|\bimmediate(ly)?\b|start asap|\bhiring (now|immediate(ly)?)\b",
+        re.IGNORECASE,
+    )
+    matches = re.findall(urgent_patterns, description)
+    count = len(matches)
+
+    return count
+
+
+def markdown_converter(description_html: str):
+    if description_html is None:
+        return ""
+    text_maker.ignore_links = False
+    try:
+        markdown = text_maker.handle(description_html)
+        return markdown.strip()
+    except AssertionError as e:
+        return ""
+
+
+def extract_emails_from_text(text: str) -> list[str] | None:
+    if not text:
+        return None
+    email_regex = re.compile(r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}")
+    return email_regex.findall(text)
+
+
+def create_session(proxy: dict | None = None, is_tls: bool = True, has_retry: bool = False, delay: int = 1) -> requests.Session:
+    """
+    Creates a requests session with optional tls, proxy, and retry settings.
+    :return: A session object
+    """
+    if is_tls:
+        session = tls_client.Session(random_tls_extension_order=True)
+        session.proxies = proxy
+    else:
+        session = requests.Session()
+        session.allow_redirects = True
+        if proxy:
+            session.proxies.update(proxy)
+        if has_retry:
+            retries = Retry(total=3,
+                            connect=3,
+                            status=3,
+                            status_forcelist=[500, 502, 503, 504, 429],
+                            backoff_factor=delay)
+            adapter = HTTPAdapter(max_retries=retries)
+
+            session.mount('http://', adapter)
+            session.mount('https://', adapter)
+    return session
+
+
+def get_enum_from_job_type(job_type_str: str) -> JobType | None:
+    """
+    Given a string, returns the corresponding JobType enum member if a match is found.
+    """
+    res = None
+    for job_type in JobType:
+        if job_type_str in job_type.value:
+            res = job_type
+    return res
+
+
+def currency_parser(cur_str):
+    # Remove any non-numerical characters
+    # except for ',' '.' or '-' (e.g. EUR)
+    cur_str = re.sub("[^-0-9.,]", '', cur_str)
+    # Remove any 000s separators (either , or .)
+    cur_str = re.sub("[.,]", '', cur_str[:-3]) + cur_str[-3:]
+
+    if '.' in list(cur_str[-3:]):
+        num = float(cur_str)
+    elif ',' in list(cur_str[-3:]):
+        num = float(cur_str.replace(',', '.'))
+    else:
+        num = float(cur_str)
+
+    return np.round(num, 2)
+
+

src/jobspy/scrapers/ziprecruiter/__init__.py

@@ -5,470 +5,206 @@ jobspy.scrapers.ziprecruiter
 This module contains routines to scrape ZipRecruiter.
 """
 import math
-import json
-import re
-from datetime import datetime, date
+import time
+from datetime import datetime
 from typing import Optional, Tuple, Any
-from urllib.parse import urlparse, parse_qs, urlunparse
 
-import tls_client
-import requests
-from bs4 import BeautifulSoup
-from bs4.element import Tag
-from concurrent.futures import ThreadPoolExecutor, Future
+from concurrent.futures import ThreadPoolExecutor
 
 from .. import Scraper, ScraperInput, Site
-from ..exceptions import ZipRecruiterException
+from ..utils import (
+    logger,
+    count_urgent_words,
+    extract_emails_from_text,
+    create_session,
+    markdown_converter
+)
 from ...jobs import (
     JobPost,
     Compensation,
-    CompensationInterval,
     Location,
     JobResponse,
     JobType,
     Country,
+    DescriptionFormat
 )
 
-def extract_emails_from_text(text: str) -> Optional[list[str]]:
-    if not text:
-        return None
-    email_regex = re.compile(r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}")
-    return email_regex.findall(text)
-
 
 class ZipRecruiterScraper(Scraper):
+    base_url = "https://www.ziprecruiter.com"
+    api_url = "https://api.ziprecruiter.com"
+
     def __init__(self, proxy: Optional[str] = None):
         """
-        Initializes LinkedInScraper with the ZipRecruiter job search url
+        Initializes ZipRecruiterScraper with the ZipRecruiter job search url
         """
-        site = Site(Site.ZIP_RECRUITER)
-        self.url = "https://www.ziprecruiter.com"
-        super().__init__(site, proxy=proxy)
+        self.scraper_input = None
+        self.session = create_session(proxy)
+        self._get_cookies()
+        super().__init__(Site.ZIP_RECRUITER, proxy=proxy)
 
+        self.delay = 5
         self.jobs_per_page = 20
         self.seen_urls = set()
-        self.session = tls_client.Session(
-            client_identifier="chrome112", random_tls_extension_order=True
-        )
-
-    def find_jobs_in_page(
-            self, scraper_input: ScraperInput, page: int
-    ) -> list[JobPost]:
-        """
-        Scrapes a page of ZipRecruiter for jobs with scraper_input criteria
-        :param scraper_input:
-        :param page:
-        :return: jobs found on page
-        """
-        job_list: list[JobPost] = []
-        try:
-            response = self.session.get(
-                f"{self.url}/jobs-search",
-                headers=ZipRecruiterScraper.headers(),
-                params=ZipRecruiterScraper.add_params(scraper_input, page),
-                allow_redirects=True,
-                proxy=self.proxy,
-                timeout_seconds=10,
-            )
-            if response.status_code != 200:
-                raise ZipRecruiterException(
-                    f"bad response status code: {response.status_code}"
-                )
-        except Exception as e:
-            if "Proxy responded with non 200 code" in str(e):
-                raise ZipRecruiterException("bad proxy")
-            raise ZipRecruiterException(str(e))
-        else:
-            soup = BeautifulSoup(response.text, "html.parser")
-            js_tag = soup.find("script", {"id": "js_variables"})
-
-        if js_tag:
-            page_json = json.loads(js_tag.string)
-            jobs_list = page_json.get("jobList")
-            if jobs_list:
-                page_variant = "javascript"
-                # print('type javascript', len(jobs_list))
-            else:
-                page_variant = "html_2"
-                jobs_list = soup.find_all("div", {"class": "job_content"})
-                # print('type 2 html', len(jobs_list))
-        else:
-            page_variant = "html_1"
-            jobs_list = soup.find_all("li", {"class": "job-listing"})
-            # print('type 1 html', len(jobs_list))
-
-        with ThreadPoolExecutor(max_workers=10) as executor:
-            if page_variant == "javascript":
-                job_results = [
-                    executor.submit(self.process_job_javascript, job)
-                    for job in jobs_list
-                ]
-            elif page_variant == "html_1":
-                job_results = [
-                    executor.submit(self.process_job_html_1, job) for job in jobs_list
-                ]
-            elif page_variant == "html_2":
-                job_results = [
-                    executor.submit(self.process_job_html_2, job) for job in jobs_list
-                ]
-
-        job_list = [result.result() for result in job_results if result.result()]
-        return job_list
 
     def scrape(self, scraper_input: ScraperInput) -> JobResponse:
         """
-        Scrapes ZipRecruiter for jobs with scraper_input criteria
+        Scrapes ZipRecruiter for jobs with scraper_input criteria.
+        :param scraper_input: Information about job search criteria.
+        :return: JobResponse containing a list of jobs.
+        """
+        self.scraper_input = scraper_input
+        job_list: list[JobPost] = []
+        continue_token = None
+
+        max_pages = math.ceil(scraper_input.results_wanted / self.jobs_per_page)
+        for page in range(1, max_pages + 1):
+            if len(job_list) >= scraper_input.results_wanted:
+                break
+            if page > 1:
+                time.sleep(self.delay)
+
+            jobs_on_page, continue_token = self._find_jobs_in_page(
+                scraper_input, continue_token
+            )
+            if jobs_on_page:
+                job_list.extend(jobs_on_page)
+            else:
+                break
+            if not continue_token:
+                break
+        return JobResponse(jobs=job_list[: scraper_input.results_wanted])
+
+    def _find_jobs_in_page(
+        self, scraper_input: ScraperInput, continue_token: str | None = None
+    ) -> Tuple[list[JobPost], Optional[str]]:
+        """
+        Scrapes a page of ZipRecruiter for jobs with scraper_input criteria
         :param scraper_input:
-        :return: job_response
+        :param continue_token:
+        :return: jobs found on page
         """
-        start_page = (scraper_input.offset // self.jobs_per_page) + 1 if scraper_input.offset else 1
-        #: get first page to initialize session
-        job_list: list[JobPost] = self.find_jobs_in_page(scraper_input, start_page)
-        pages_to_process = max(
-            3, math.ceil(scraper_input.results_wanted / self.jobs_per_page)
+        jobs_list = []
+        params = self._add_params(scraper_input)
+        if continue_token:
+            params["continue_from"] = continue_token
+        try:
+            res= self.session.get(
+                f"{self.api_url}/jobs-app/jobs",
+                headers=self.headers,
+                params=params
             )
+            if res.status_code not in range(200, 400):
+                if res.status_code == 429:
+                    logger.error(f'429 Response - Blocked by ZipRecruiter for too many requests')
+                else:
+                    logger.error(f'ZipRecruiter response status code {res.status_code}')
+                return jobs_list, ""
+        except Exception as e:
+            if "Proxy responded with" in str(e):
+                logger.error(f'Indeed: Bad proxy')
+            else:
+                logger.error(f'Indeed: {str(e)}')
+            return jobs_list, ""
 
-        with ThreadPoolExecutor(max_workers=10) as executor:
-            futures: list[Future] = [
-                executor.submit(self.find_jobs_in_page, scraper_input, page)
-                for page in range(start_page + 1, start_page + pages_to_process + 2)
-            ]
 
-            for future in futures:
-                jobs = future.result()
+        res_data = res.json()
+        jobs_list = res_data.get("jobs", [])
+        next_continue_token = res_data.get("continue", None)
+        with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
+            job_results = [executor.submit(self._process_job, job) for job in jobs_list]
 
-                job_list += jobs
+        job_list = list(filter(None, (result.result() for result in job_results)))
+        return job_list, next_continue_token
 
-        job_list = job_list[: scraper_input.results_wanted]
-        return JobResponse(jobs=job_list)
-
-    def process_job_html_1(self, job: Tag) -> Optional[JobPost]:
+    def _process_job(self, job: dict) -> JobPost | None:
         """
-        Parses a job from the job content tag
-        :param job: BeautifulSoup Tag for one job post
-        :return JobPost
-        TODO this method isnt finished due to not encountering this type of html often
+        Processes an individual job dict from the response
         """
-        job_url = self.cleanurl(job.find("a", {"class": "job_link"})["href"])
+        title = job.get("name")
+        job_url = f"{self.base_url}/jobs//j?lvk={job['listing_key']}"
         if job_url in self.seen_urls:
-            return None
+            return
+        self.seen_urls.add(job_url)
 
-        title = job.find("h2", {"class": "title"}).text
-        company = job.find("a", {"class": "company_name"}).text.strip()
+        description = job.get("job_description", "").strip()
+        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)
 
-        description, updated_job_url = self.get_description(job_url)
-        # job_url = updated_job_url if updated_job_url else job_url
-        if description is None:
-            description = job.find("p", {"class": "job_snippet"}).text.strip()
-
-        job_type_element = job.find("li", {"class": "perk_item perk_type"})
-        job_type = None
-        if job_type_element:
-            job_type_text = (
-                job_type_element.text.strip().lower().replace("_", "").replace(" ", "")
-            )
-            job_type = ZipRecruiterScraper.get_job_type_enum(job_type_text)
-
-        date_posted = ZipRecruiterScraper.get_date_posted(job)
-
-        job_post = JobPost(
-            title=title,
-            description=description,
-            company_name=company,
-            location=ZipRecruiterScraper.get_location(job),
-            job_type=job_type,
-            compensation=ZipRecruiterScraper.get_compensation(job),
-            date_posted=date_posted,
-            job_url=job_url,
-            emails=extract_emails_from_text(description),
-        )
-        return job_post
-
-    def process_job_html_2(self, job: Tag) -> Optional[JobPost]:
-        """
-        Parses a job from the job content tag for a second variat of HTML that ZR uses
-        :param job: BeautifulSoup Tag for one job post
-        :return JobPost
-        """
-        job_url = self.cleanurl(job.find("a", class_="job_link")["href"])
-        title = job.find("h2", class_="title").text
-        company = job.find("a", class_="company_name").text.strip()
-
-        description, updated_job_url = self.get_description(job_url)
-        # job_url = updated_job_url if updated_job_url else job_url
-        if description is None:
-            description = job.find("p", class_="job_snippet").get_text().strip()
-
-        job_type_text = job.find("li", class_="perk_item perk_type")
-        job_type = None
-        if job_type_text:
-            job_type_text = (
-                job_type_text.get_text()
-                .strip()
-                .lower()
-                .replace("-", "")
-                .replace(" ", "")
-            )
-            job_type = ZipRecruiterScraper.get_job_type_enum(job_type_text)
-        date_posted = ZipRecruiterScraper.get_date_posted(job)
-
-        job_post = JobPost(
-            title=title,
-            description=description,
-            company_name=company,
-            location=ZipRecruiterScraper.get_location(job),
-            job_type=job_type,
-            compensation=ZipRecruiterScraper.get_compensation(job),
-            date_posted=date_posted,
-            job_url=job_url,
-        )
-        return job_post
-
-    def process_job_javascript(self, job: dict) -> JobPost:
-        title = job.get("Title")
-        job_url = self.cleanurl(job.get("JobURL"))
-
-        description, updated_job_url = self.get_description(job_url)
-        # job_url = updated_job_url if updated_job_url else job_url
-        if description is None:
-            description = BeautifulSoup(
-                job.get("Snippet", "").strip(), "html.parser"
-            ).get_text()
-
-        company = job.get("OrgName")
         location = Location(
-            city=job.get("City"), state=job.get("State"), country=Country.US_CANADA
+            city=job.get("job_city"), state=job.get("job_state"), country=country_enum
         )
-        job_type = ZipRecruiterScraper.get_job_type_enum(
-            job.get("EmploymentType", "").replace("-", "").lower()
+        job_type = self._get_job_type_enum(
+            job.get("employment_type", "").replace("_", "").lower()
         )
-
-        formatted_salary = job.get("FormattedSalaryShort", "")
-        salary_parts = formatted_salary.split(" ")
-
-        min_salary_str = salary_parts[0][1:].replace(",", "")
-        if "." in min_salary_str:
-            min_amount = int(float(min_salary_str) * 1000)
-        else:
-            min_amount = int(min_salary_str.replace("K", "000"))
-
-        if len(salary_parts) >= 3 and salary_parts[2].startswith("$"):
-            max_salary_str = salary_parts[2][1:].replace(",", "")
-            if "." in max_salary_str:
-                max_amount = int(float(max_salary_str) * 1000)
-            else:
-                max_amount = int(max_salary_str.replace("K", "000"))
-        else:
-            max_amount = 0
-
-        compensation = Compensation(
-            interval=CompensationInterval.YEARLY,
-            min_amount=min_amount,
-            max_amount=max_amount,
-            currency="USD/CAD",
-        )
-        save_job_url = job.get("SaveJobURL", "")
-        posted_time_match = re.search(
-            r"posted_time=(\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}Z)", save_job_url
-        )
-        if posted_time_match:
-            date_time_str = posted_time_match.group(1)
-            date_posted_obj = datetime.strptime(date_time_str, "%Y-%m-%dT%H:%M:%SZ")
-            date_posted = date_posted_obj.date()
-        else:
-            date_posted = date.today()
-
+        date_posted = datetime.fromisoformat(job['posted_time'].rstrip("Z")).date()
         return JobPost(
             title=title,
-            description=description,
             company_name=company,
             location=location,
             job_type=job_type,
-            compensation=compensation,
+            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"),
+            ),
             date_posted=date_posted,
             job_url=job_url,
+            description=description,
+            emails=extract_emails_from_text(description) if description else None,
+            num_urgent_words=count_urgent_words(description) if description else None,
         )
-        return job_post
+
+    def _get_cookies(self):
+        data="event_type=session&logged_in=false&number_of_retry=1&property=model%3AiPhone&property=os%3AiOS&property=locale%3Aen_us&property=app_build_number%3A4734&property=app_version%3A91.0&property=manufacturer%3AApple&property=timestamp%3A2024-01-12T12%3A04%3A42-06%3A00&property=screen_height%3A852&property=os_version%3A16.6.1&property=source%3Ainstall&property=screen_width%3A393&property=device_model%3AiPhone%2014%20Pro&property=brand%3AApple"
+        self.session.post(f"{self.api_url}/jobs-app/event", data=data, headers=self.headers)
 
     @staticmethod
-    def get_job_type_enum(job_type_str: str) -> Optional[JobType]:
+    def _get_job_type_enum(job_type_str: str) -> list[JobType] | None:
         for job_type in JobType:
             if job_type_str in job_type.value:
-                a = True
-                return job_type
+                return [job_type]
         return None
 
-    def get_description(self, job_page_url: str) -> Tuple[Optional[str], Optional[str]]:
-        """
-        Retrieves job description by going to the job page url
-        :param job_page_url:
-        :param session:
-        :return: description or None, response url
-        """
-        try:
-            response = requests.get(
-                job_page_url,
-                headers=ZipRecruiterScraper.headers(),
-                allow_redirects=True,
-                timeout=5,
-                proxies=self.proxy,
-            )
-            if response.status_code not in range(200, 400):
-                return None, None
-        except Exception as e:
-            return None, None
-
-        html_string = response.content
-        soup_job = BeautifulSoup(html_string, "html.parser")
-
-        job_description_div = soup_job.find("div", {"class": "job_description"})
-        if job_description_div:
-            return job_description_div.text.strip(), response.url
-        return None, response.url
-
     @staticmethod
-    def add_params(scraper_input, page) -> dict[str, str | Any]:
+    def _add_params(scraper_input) -> dict[str, str | Any]:
         params = {
             "search": scraper_input.search_term,
             "location": scraper_input.location,
-            "page": page,
-            "form": "jobs-landing",
         }
-        job_type_value = None
+        if scraper_input.hours_old:
+            fromage = max(scraper_input.hours_old // 24, 1) if scraper_input.hours_old else None
+            params['days'] = fromage
+        job_type_map = {
+            JobType.FULL_TIME: 'full_time',
+            JobType.PART_TIME: 'part_time'
+        }
         if scraper_input.job_type:
-            if scraper_input.job_type.value == "fulltime":
-                job_type_value = "full_time"
-            elif scraper_input.job_type.value == "parttime":
-                job_type_value = "part_time"
-            else:
-                job_type_value = scraper_input.job_type.value
-
-        if job_type_value:
-            params[
-                "refine_by_employment"
-            ] = f"employment_type:employment_type:{job_type_value}"
-
+            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]
+        if scraper_input.easy_apply:
+            params['zipapply'] = 1
         if scraper_input.is_remote:
-            params["refine_by_location_type"] = "only_remote"
-
+            params["remote"] = 1
         if scraper_input.distance:
             params["radius"] = scraper_input.distance
+        return {k: v for k, v in params.items() if v is not None}
 
-        return params
-
-    @staticmethod
-    def get_interval(interval_str: str):
-        """
-         Maps the interval alias to its appropriate CompensationInterval.
-        :param interval_str
-        :return: CompensationInterval
-        """
-        interval_alias = {"annually": CompensationInterval.YEARLY}
-        interval_str = interval_str.lower()
-
-        if interval_str in interval_alias:
-            return interval_alias[interval_str]
-
-        return CompensationInterval(interval_str)
-
-    @staticmethod
-    def get_date_posted(job: Tag) -> Optional[datetime.date]:
-        """
-        Extracts the date a job was posted
-        :param job
-        :return: date the job was posted or None
-        """
-        button = job.find(
-            "button", {"class": "action_input save_job zrs_btn_secondary_200"}
-        )
-        if not button:
-            return None
-
-        url_time = button.get("data-href", "")
-        url_components = urlparse(url_time)
-        params = parse_qs(url_components.query)
-        posted_time_str = params.get("posted_time", [None])[0]
-
-        if posted_time_str:
-            posted_date = datetime.strptime(
-                posted_time_str, "%Y-%m-%dT%H:%M:%SZ"
-            ).date()
-            return posted_date
-
-        return None
-
-    @staticmethod
-    def get_compensation(job: Tag) -> Optional[Compensation]:
-        """
-        Parses the compensation tag from the job BeautifulSoup object
-        :param job
-        :return: Compensation object or None
-        """
-        pay_element = job.find("li", {"class": "perk_item perk_pay"})
-        if pay_element is None:
-            return None
-        pay = pay_element.find("div", {"class": "value"}).find("span").text.strip()
-
-        def create_compensation_object(pay_string: str) -> Compensation:
-            """
-            Creates a Compensation object from a pay_string
-            :param pay_string
-            :return: compensation
-            """
-            interval = ZipRecruiterScraper.get_interval(pay_string.split()[-1])
-
-            amounts = []
-            for amount in pay_string.split("to"):
-                amount = amount.replace(",", "").strip("$ ").split(" ")[0]
-                if "K" in amount:
-                    amount = amount.replace("K", "")
-                    amount = int(float(amount)) * 1000
-                else:
-                    amount = int(float(amount))
-                amounts.append(amount)
-
-            compensation = Compensation(
-                interval=interval,
-                min_amount=min(amounts),
-                max_amount=max(amounts),
-                currency="USD/CAD",
-            )
-
-            return compensation
-
-        return create_compensation_object(pay)
-
-    @staticmethod
-    def get_location(job: Tag) -> Location:
-        """
-        Extracts the job location from BeatifulSoup object
-        :param job:
-        :return: location
-        """
-        location_link = job.find("a", {"class": "company_location"})
-        if location_link is not None:
-            location_string = location_link.text.strip()
-            parts = location_string.split(", ")
-            if len(parts) == 2:
-                city, state = parts
-            else:
-                city, state = None, None
-        else:
-            city, state = None, None
-        return Location(city=city, state=state, country=Country.US_CANADA)
-
-    @staticmethod
-    def headers() -> dict:
-        """
-        Returns headers needed for requests
-        :return: dict - Dictionary containing headers
-        """
-        return {
-            "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.97 Safari/537.36"
+    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",
     }
-
-    @staticmethod
-    def cleanurl(url):
-        parsed_url = urlparse(url)
-
-        return urlunparse((parsed_url.scheme, parsed_url.netloc, parsed_url.path, parsed_url.params, '', ''))

src/tests/test_all.py

@@ -4,9 +4,11 @@ import pandas as pd
 
 def test_all():
     result = scrape_jobs(
-        site_name=["linkedin", "indeed", "zip_recruiter"],
+        site_name=["linkedin", "indeed", "zip_recruiter", "glassdoor"],
         search_term="software engineer",
         results_wanted=5,
     )
 
-    assert isinstance(result, pd.DataFrame) and not result.empty, "Result should be a non-empty DataFrame"
+    assert (
+        isinstance(result, pd.DataFrame) and not result.empty
+    ), "Result should be a non-empty DataFrame"

src/tests/test_glassdoor.py

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

src/tests/test_indeed.py

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

src/tests/test_linkedin.py

@@ -7,4 +7,6 @@ def test_linkedin():
         site_name="linkedin",
         search_term="software engineer",
     )
-    assert isinstance(result, pd.DataFrame) and not result.empty, "Result should be a non-empty DataFrame"
+    assert (
+        isinstance(result, pd.DataFrame) and not result.empty
+    ), "Result should be a non-empty DataFrame"

src/tests/test_ziprecruiter.py

@@ -8,4 +8,6 @@ def test_ziprecruiter():
         search_term="software engineer",
     )
 
-    assert isinstance(result, pd.DataFrame) and not result.empty, "Result should be a non-empty DataFrame"
+    assert (
+        isinstance(result, pd.DataFrame) and not result.empty
+    ), "Result should be a non-empty DataFrame"