Fix GlassDoor Country Vietnam(#122)

README.md

@@ -104,15 +104,6 @@ JobPost
 └── is_remote (bool)
 ```
 
-### Exceptions
-
-The following exceptions may be raised when using JobSpy:
-
-* `LinkedInException`
-* `IndeedException`
-* `ZipRecruiterException`
-* `GlassdoorException`
-
 ## Supported Countries for Job Searching
 
 ### **LinkedIn**
@@ -147,7 +138,7 @@ You can specify the following countries when searching on Indeed (use the exact
 | South Korea          | Spain*       | Sweden     | Switzerland*   |
 | Taiwan               | Thailand     | Turkey     | Ukraine        |
 | United Arab Emirates | UK*          | USA*       | Uruguay        |
-| Venezuela            | Vietnam      |            |                |
+| Venezuela            | Vietnam*     |            |                |
 
 
 Glassdoor can only fetch 900 jobs from the endpoint we're using on a given search.
@@ -167,8 +158,4 @@ persist, [submit an issue](https://github.com/Bunsly/JobSpy/issues).
 - Waiting some time between scrapes (site-dependent).
 - Trying a VPN or proxy to change your IP address.
 
----
-
-
-
-  
+---

poetry.lock

@@ -524,17 +524,6 @@ 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"
@@ -1037,6 +1026,21 @@ files = [
     {file = "jupyterlab_widgets-3.0.8.tar.gz", hash = "sha256:d428ab97b8d87cc7c54cbf37644d6e0f0e662f23876e05fa460a73ec3257252a"},
 ]
 
+[[package]]
+name = "markdownify"
+version = "0.11.6"
+description = "Convert HTML to markdown."
+optional = false
+python-versions = "*"
+files = [
+    {file = "markdownify-0.11.6-py3-none-any.whl", hash = "sha256:ba35fe289d5e9073bcd7d2cad629278fe25f1a93741fcdc0bfb4f009076d8324"},
+    {file = "markdownify-0.11.6.tar.gz", hash = "sha256:009b240e0c9f4c8eaf1d085625dcd4011e12f0f8cec55dedf9ea6f7655e49bfe"},
+]
+
+[package.dependencies]
+beautifulsoup4 = ">=4.9,<5"
+six = ">=1.15,<2"
+
 [[package]]
 name = "markupsafe"
 version = "2.1.3"
@@ -2271,13 +2275,13 @@ test = ["flake8", "isort", "pytest"]
 
 [[package]]
 name = "tls-client"
-version = "1.0"
+version = "1.0.1"
 description = "Advanced Python HTTP Client."
 optional = false
 python-versions = "*"
 files = [
-    {file = "tls_client-1.0-py3-none-any.whl", hash = "sha256:f1183f5e18cb31914bd62d11b350a33ea0293ea80fb91d69a3072821dece3e66"},
-    {file = "tls_client-1.0.tar.gz", hash = "sha256:7f6de48ad4a0ef69b72682c76ce604155971e07b4bfb2148a36276194ae3e7a0"},
+    {file = "tls_client-1.0.1-py3-none-any.whl", hash = "sha256:2f8915c0642c2226c9e33120072a2af082812f6310d32f4ea4da322db7d3bb1c"},
+    {file = "tls_client-1.0.1.tar.gz", hash = "sha256:dad797f3412bb713606e0765d489f547ffb580c5ffdb74aed47a183ce8505ff5"},
 ]
 
 [[package]]
@@ -2446,4 +2450,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "40cdc19a57cba0d21ff4f0fcfa53e14a073fcccd9f2a871440e056ab6e8fade0"
+content-hash = "ba7f7cc9b6833a4a6271981f90610395639dd8b9b3db1370cbd1149d70cc9632"

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "python-jobspy"
-version = "1.1.45"
+version = "1.1.47"
 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"
@@ -13,12 +13,12 @@ packages = [
 [tool.poetry.dependencies]
 python = "^3.10"
 requests = "^2.31.0"
-tls-client = "*"
 beautifulsoup4 = "^4.12.2"
 pandas = "^2.1.0"
 NUMPY = "1.24.2"
 pydantic = "^2.3.0"
-html2text = "^2020.1.16"
+tls-client = "^1.0.1"
+markdownify = "^0.11.6"
 
 
 [tool.poetry.group.dev.dependencies]

src/jobspy/__init__.py

@@ -152,8 +152,14 @@ def scrape_jobs(
             jobs_dfs.append(job_df)
 
     if jobs_dfs:
-        jobs_df = pd.concat(jobs_dfs, ignore_index=True)
-        desired_order: list[str] = [
+        # Step 1: Filter out all-NA columns from each DataFrame before concatenation
+        filtered_dfs = [df.dropna(axis=1, how='all') for df in jobs_dfs]
+        
+        # Step 2: Concatenate the filtered DataFrames
+        jobs_df = pd.concat(filtered_dfs, ignore_index=True)
+        
+        # Desired column order
+        desired_order = [
             "job_url_hyper" if hyperlinks else "job_url",
             "site",
             "title",
@@ -172,6 +178,16 @@ def scrape_jobs(
             "emails",
             "description",
         ]
-        return jobs_df[desired_order].sort_values(by=['site', 'date_posted'], ascending=[True, False])
+        
+        # Step 3: Ensure all desired columns are present, adding missing ones as empty
+        for column in desired_order:
+            if column not in jobs_df.columns:
+                jobs_df[column] = None  # Add missing columns as empty
+        
+        # Reorder the DataFrame according to the desired order
+        jobs_df = jobs_df[desired_order]
+        
+        # Step 4: Sort the DataFrame as required
+        return jobs_df.sort_values(by=['site', 'date_posted'], ascending=[True, False])
     else:
         return pd.DataFrame()

src/jobspy/jobs/__init__.py

@@ -122,7 +122,7 @@ class Country(Enum):
     USA = ("usa,us,united states", "www", "com")
     URUGUAY = ("uruguay", "uy")
     VENEZUELA = ("venezuela", "ve")
-    VIETNAM = ("vietnam", "vn")
+    VIETNAM = ("vietnam", "vn", "com")
 
     # internal for ziprecruiter
     US_CANADA = ("usa/ca", "www")
@@ -145,7 +145,7 @@ class Country(Enum):
         else:
             raise Exception(f"Glassdoor is not available for {self.name}")
 
-    def get_url(self):
+    def get_glassdoor_url(self):
         return f"https://{self.glassdoor_domain_value}/"
 
     @classmethod

src/jobspy/scrapers/glassdoor/__init__.py

@@ -5,6 +5,8 @@ jobspy.scrapers.glassdoor
 This module contains routines to scrape Glassdoor.
 """
 import json
+import re
+
 import requests
 from typing import Optional
 from datetime import datetime, timedelta
@@ -42,6 +44,7 @@ class GlassdoorScraper(Scraper):
         self.session = None
         self.scraper_input = None
         self.jobs_per_page = 30
+        self.max_pages = 30
         self.seen_urls = set()
 
     def scrape(self, scraper_input: ScraperInput) -> JobResponse:
@@ -52,39 +55,40 @@ class GlassdoorScraper(Scraper):
         """
         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()
+        self.base_url = self.scraper_input.country.get_glassdoor_url()
+
+        self.session = create_session(self.proxy, is_tls=True, has_retry=True)
+        token = self._get_csrf_token()
+        self.headers['gd-csrf-token'] = token if token else self.fallback_token
 
         location_id, location_type = self._get_location(
             scraper_input.location, scraper_input.is_remote
         )
         if location_type is None:
+            logger.error('Glassdoor: location not parsed')
             return JobResponse(jobs=[])
         all_jobs: list[JobPost] = []
         cursor = None
-        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))
+        for page in range(
+            1 + (scraper_input.offset // self.jobs_per_page),
+            min(
+                (scraper_input.results_wanted // self.jobs_per_page) + 2,
+                self.max_pages + 1,
+            ),
+        ):
+            logger.info(f'Glassdoor search page: {page}')
+            try:
+                jobs, cursor = self._fetch_jobs_page(
+                    scraper_input, location_id, location_type, page, cursor
+                )
+                all_jobs.extend(jobs)
+                if not jobs or len(all_jobs) >= scraper_input.results_wanted:
+                    all_jobs = all_jobs[: scraper_input.results_wanted]
+                    break
+            except Exception as e:
+                logger.error(f'Glassdoor: {str(e)}')
+                break
         return JobResponse(jobs=all_jobs)
 
     def _fetch_jobs_page(
@@ -98,27 +102,26 @@ class GlassdoorScraper(Scraper):
         """
         Scrapes a page of Glassdoor for jobs with scraper_input criteria
         """
+        jobs = []
         self.scraper_input = scraper_input
         try:
             payload = self._add_payload(
                 location_id, location_type, page_num, cursor
             )
             response = self.session.post(
-                f"{self.base_url}/graph", headers=self.headers, timeout=10, data=payload
+                f"{self.base_url}/graph", headers=self.headers, timeout_seconds=15, data=payload
             )
             if response.status_code != 200:
-                raise GlassdoorException(
-                    f"bad response status code: {response.status_code}"
-                )
+                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))
+        except (requests.exceptions.ReadTimeout, GlassdoorException, ValueError, Exception) as e:
+            logger.error(f'Glassdoor: {str(e)}')
+            return jobs, None
 
         jobs_data = res_json["data"]["jobListings"]["jobListings"]
 
-        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):
@@ -133,6 +136,18 @@ class GlassdoorScraper(Scraper):
             res_json["data"]["jobListings"]["paginationCursors"], page_num + 1
         )
 
+    def _get_csrf_token(self):
+        """
+        Fetches csrf token needed for API by visiting a generic page
+        """
+        res = self.session.get(f'{self.base_url}/Job/computer-science-jobs.htm', headers=self.headers)
+        pattern = r'"token":\s*"([^"]+)"'
+        matches = re.findall(pattern, res.text)
+        token = None
+        if matches:
+            token = matches[0]
+        return token
+
     def _process_job(self, job_data):
         """
         Processes a single job and fetches its description.
@@ -217,7 +232,7 @@ class GlassdoorScraper(Scraper):
             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)
+        res = self.session.get(url, headers=self.headers)
         if res.status_code != 200:
             if res.status_code == 429:
                 logger.error(f'429 Response - Blocked by Glassdoor for too many requests')
@@ -266,7 +281,74 @@ class GlassdoorScraper(Scraper):
                 "fromage": fromage,
                 "sort": "date"
             },
-            "query": """
+            "query": self.query_template
+        }
+        if self.scraper_input.job_type:
+            payload["variables"]["filterParams"].append(
+                {"filterKey": "jobType", "values": self.scraper_input.job_type.value[0]}
+            )
+        return json.dumps([payload])
+
+    @staticmethod
+    def parse_compensation(data: dict) -> Optional[Compensation]:
+        pay_period = data.get("payPeriod")
+        adjusted_pay = data.get("payPeriodAdjustedPay")
+        currency = data.get("payCurrency", "USD")
+        if not pay_period or not adjusted_pay:
+            return None
+
+        interval = None
+        if pay_period == "ANNUAL":
+            interval = CompensationInterval.YEARLY
+        elif pay_period:
+            interval = CompensationInterval.get_interval(pay_period)
+        min_amount = int(adjusted_pay.get("p10") // 1)
+        max_amount = int(adjusted_pay.get("p90") // 1)
+        return Compensation(
+            interval=interval,
+            min_amount=min_amount,
+            max_amount=max_amount,
+            currency=currency,
+        )
+
+    @staticmethod
+    def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
+        for job_type in JobType:
+            if job_type_str in job_type.value:
+                return [job_type]
+
+    @staticmethod
+    def parse_location(location_name: str) -> Location | None:
+        if not location_name or location_name == "Remote":
+            return
+        city, _, state = location_name.partition(", ")
+        return Location(city=city, state=state)
+
+    @staticmethod
+    def get_cursor_for_page(pagination_cursors, page_num):
+        for cursor_data in pagination_cursors:
+            if cursor_data["pageNumber"] == page_num:
+                return cursor_data["cursor"]
+
+    fallback_token = "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok"
+    headers = {
+        "authority": "www.glassdoor.com",
+        "accept": "*/*",
+        "accept-language": "en-US,en;q=0.9",
+        "apollographql-client-name": "job-search-next",
+        "apollographql-client-version": "4.65.5",
+        "content-type": "application/json",
+        "origin": "https://www.glassdoor.com",
+        "referer": "https://www.glassdoor.com/",
+        "sec-ch-ua": '"Chromium";v="118", "Google Chrome";v="118", "Not=A?Brand";v="99"',
+        "sec-ch-ua-mobile": "?0",
+        "sec-ch-ua-platform": '"macOS"',
+        "sec-fetch-dest": "empty",
+        "sec-fetch-mode": "cors",
+        "sec-fetch-site": "same-origin",
+        "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/118.0.0.0 Safari/537.36",
+    }
+    query_template = """
             query JobSearchResultsQuery(
                 $excludeJobListingIds: [Long!], 
                 $keyword: String, 
@@ -431,70 +513,4 @@ class GlassdoorScraper(Scraper):
                 }
                 __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

@@ -15,7 +15,6 @@ 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,
@@ -63,8 +62,7 @@ class IndeedScraper(Scraper):
         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:
+            with ThreadPoolExecutor(max_workers=self.num_workers) as executor:
                 futures: list[Future] = [
                     executor.submit(self._scrape_page, page + pages_processed)
                     for page in range(pages_to_process)
@@ -82,7 +80,6 @@ class IndeedScraper(Scraper):
             if not new_jobs:
                 break
 
-
         if len(self.seen_urls) > scraper_input.results_wanted:
             job_list = job_list[:scraper_input.results_wanted]
 
@@ -94,10 +91,11 @@ class IndeedScraper(Scraper):
         :param page:
         :return: jobs found on page, total number of jobs found for search
         """
+        logger.info(f'Indeed search page: {page + 1}')
         job_list = []
         domain = self.scraper_input.country.indeed_domain_value
         self.base_url = f"https://{domain}.indeed.com"
-
+        
         try:
             session = create_session(self.proxy)
             response = session.get(
@@ -124,12 +122,15 @@ class IndeedScraper(Scraper):
             return job_list
 
         jobs = IndeedScraper._parse_jobs(soup)
+        if not jobs:
+            return []
         if (
             not jobs.get("metaData", {})
             .get("mosaicProviderJobCardsModel", {})
             .get("results")
         ):
-            raise IndeedException("No jobs found.")
+            logger.error("Indeed - No jobs found.")
+            return []
 
         jobs = jobs["metaData"]["mosaicProviderJobCardsModel"]["results"]
         job_keys = [job['jobkey'] for job in jobs]
@@ -139,7 +140,6 @@ class IndeedScraper(Scraper):
             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
@@ -302,11 +302,11 @@ class IndeedScraper(Scraper):
                 jobs = json.loads(m.group(1).strip())
                 return jobs
             else:
-                raise IndeedException("Could not find mosaic provider job cards data")
+                logger.warning(f'Indeed: Could not find mosaic provider job cards data')
+                return {}
         else:
-            raise IndeedException(
-                "Could not find any results for the search"
-            )
+            logger.warning(f"Indeed: Could not parse any jobs on the page")
+            return {}
 
     @staticmethod
     def _is_job_remote(job: dict, job_detailed: dict, description: str) -> bool:

src/jobspy/scrapers/linkedin/__init__.py

@@ -9,8 +9,6 @@ import random
 from typing import Optional
 from datetime import datetime
 
-import requests
-from requests.exceptions import ProxyError
 from threading import Lock
 from bs4.element import Tag
 from bs4 import BeautifulSoup
@@ -41,15 +39,16 @@ from ..utils import (
 class LinkedInScraper(Scraper):
     base_url = "https://www.linkedin.com"
     delay = 3
+    band_delay = 4
+    jobs_per_page = 25
 
     def __init__(self, proxy: Optional[str] = None):
         """
         Initializes LinkedInScraper with the LinkedIn job search url
         """
+        super().__init__(Site(Site.LINKEDIN), proxy=proxy)
         self.scraper_input = None
-        site = Site(Site.LINKEDIN)
         self.country = "worldwide"
-        super().__init__(site, proxy=proxy)
 
     def scrape(self, scraper_input: ScraperInput) -> JobResponse:
         """
@@ -68,8 +67,8 @@ class LinkedInScraper(Scraper):
             else None
         )
         continue_search = lambda: len(job_list) < scraper_input.results_wanted and page < 1000
-
         while continue_search():
+            logger.info(f'LinkedIn search page: {page // 25 + 1}')
             session = create_session(is_tls=False, has_retry=True, delay=5)
             params = {
                 "keywords": scraper_input.search_term,
@@ -83,8 +82,9 @@ class LinkedInScraper(Scraper):
                 "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}",
             }
+            if seconds_old is not None:
+                params["f_TPR"] = f"r{seconds_old}"
 
             params = {k: v for k, v in params.items() if v is not None}
             try:
@@ -101,13 +101,13 @@ class LinkedInScraper(Scraper):
                         logger.error(f'429 Response - Blocked by LinkedIn for too many requests')
                     else:
                         logger.error(f'LinkedIn response status code {response.status_code}')
-                    return JobResponse(job_list=job_list)
+                    return JobResponse(jobs=job_list)
             except Exception as e:
                 if "Proxy responded with" in str(e):
-                    logger.error(f'Indeed: Bad proxy')
+                    logger.error(f'LinkedIn: Bad proxy')
                 else:
-                    logger.error(f'Indeed: {str(e)}')
-                return JobResponse(job_list=job_list)
+                    logger.error(f'LinkedIn: {str(e)}')
+                return JobResponse(jobs=job_list)
 
             soup = BeautifulSoup(response.text, "html.parser")
             job_cards = soup.find_all("div", class_="base-search-card")
@@ -136,8 +136,8 @@ class LinkedInScraper(Scraper):
                     raise LinkedInException(str(e))
 
             if continue_search():
-                time.sleep(random.uniform(self.delay, self.delay + 2))
-                page += 25
+                time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
+                page += self.jobs_per_page
 
         job_list = job_list[: scraper_input.results_wanted]
         return JobResponse(jobs=job_list)

src/jobspy/scrapers/utils.py

@@ -1,21 +1,19 @@
-import re
 import logging
-import numpy as np
+import re
 
-import html2text
-import tls_client
+import numpy as np
 import requests
+import tls_client
+from markdownify import markdownify as md
 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)
+    logger.setLevel(logging.INFO)
     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)
@@ -37,13 +35,9 @@ def count_urgent_words(description: str) -> int:
 
 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 ""
+        return None
+    markdown = md(description_html)
+    return markdown.strip()
 
 
 def extract_emails_from_text(text: str) -> list[str] | None:

src/jobspy/scrapers/ziprecruiter/__init__.py

@@ -63,7 +63,7 @@ class ZipRecruiterScraper(Scraper):
                 break
             if page > 1:
                 time.sleep(self.delay)
-
+            logger.info(f'ZipRecruiter search page: {page}')
             jobs_on_page, continue_token = self._find_jobs_in_page(
                 scraper_input, continue_token
             )