add offset param & email extraction (#51)

* add offset param

* [enh]: extract emails

.gitignore

@@ -1,10 +1,10 @@
-/.idea
-**/.DS_Store
 /venv/
-/ven/
+/.idea
 **/__pycache__/
 **/.pytest_cache/
+/.ipynb_checkpoints/
+**/output/
+**/.DS_Store
 *.pyc
 .env
 dist
-/.ipynb_checkpoints/

README.md

@@ -4,21 +4,25 @@
 
 **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 work with us.*  
+*Looking to build a data-focused software product?* **[Book a call](https://calendly.com/zachary-products/15min)** *to
+work with us.*  
 \
-Check out another project we wrote: ***[HomeHarvest](https://github.com/ZacharyHampton/HomeHarvest)** – a Python package for real estate scraping*
+Check out another project we wrote: ***[HomeHarvest](https://github.com/ZacharyHampton/HomeHarvest)** – a Python package
-## Features
+for real estate scraping*
 
+## Features
 
 - Scrapes job postings from **LinkedIn**, **Indeed** & **ZipRecruiter** simultaneously
 - Aggregates the job postings in a Pandas DataFrame
 - Proxy support (HTTP/S, SOCKS)
 
-[Video Guide for JobSpy](https://www.youtube.com/watch?v=RuP1HrAZnxs&pp=ygUgam9icyBzY3JhcGVyIGJvdCBsaW5rZWRpbiBpbmRlZWQ%3D) - Updated for release v1.1.3
+[Video Guide for JobSpy](https://www.youtube.com/watch?v=RuP1HrAZnxs&pp=ygUgam9icyBzY3JhcGVyIGJvdCBsaW5rZWRpbiBpbmRlZWQ%3D) -
+Updated for release v1.1.3
 
 ![jobspy](https://github.com/cullenwatson/JobSpy/assets/78247585/ec7ef355-05f6-4fd3-8161-a817e31c5c57)
 
 ### Installation
+
 ```
 pip install --upgrade python-jobspy
 ```
@@ -39,10 +43,9 @@ jobs: pd.DataFrame = scrape_jobs(
 
     country_indeed='USA'  # only needed for indeed
 
-    # use if you want to use a proxy (3 types)
+    # use if you want to use a proxy
-    # proxy="socks5://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
     # proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
-    # proxy="https://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
+    # offset=25 # use if you want to start at a specific offset
 )
 
 # formatting for pandas
@@ -51,17 +54,22 @@ pd.set_option('display.max_rows', None)
 pd.set_option('display.width', None)
 pd.set_option('display.max_colwidth', 50)  # set to 0 to see full job url / desc
 
-#1 display in Jupyter Notebook (1. pip install jupyter 2. jupyter notebook)
+# 1 output to console
-display(jobs)
+print(jobs)
 
-#2 output to console
+# 2 display in Jupyter Notebook (1. pip install jupyter 2. jupyter notebook)
-#print(jobs)
+# display(jobs)
 
 # 3 output to .csv
 # jobs.to_csv('jobs.csv', index=False)
+
+# 4 output to .xlsx
+# jobs.to_xlsx('jobs.xlsx', index=False)
+
 ```
 
 ### Output
+
 ```
 SITE           TITLE                             COMPANY_NAME      CITY          STATE  JOB_TYPE  INTERVAL  MIN_AMOUNT  MAX_AMOUNT  JOB_URL                                            DESCRIPTION
 indeed         Software Engineer                 AMERICAN SYSTEMS  Arlington     VA     None      yearly    200000      150000      https://www.indeed.com/viewjob?jk=5e409e577046...  THIS POSITION COMES WITH A 10K SIGNING BONUS!...
@@ -71,7 +79,9 @@ linkedin       Full-Stack Software Engineer      Rain              New York
 zip_recruiter Software Engineer - New Grad       ZipRecruiter      Santa Monica  CA     fulltime  yearly    130000      150000      https://www.ziprecruiter.com/jobs/ziprecruiter...  We offer a hybrid work environment. Most US-ba...
 zip_recruiter Software Developer                 TEKsystems        Phoenix       AZ     fulltime  hourly    65          75          https://www.ziprecruiter.com/jobs/teksystems-0...  Top Skills' Details• 6 years of Java developme...
 ```
+
 ### Parameters for `scrape_jobs()`
+
 ```plaintext
 Required
 ├── site_type (List[enum]): linkedin, zip_recruiter, indeed
@@ -85,10 +95,11 @@ Optional
 ├── 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
 ├── country_indeed (enum): filters the country on Indeed (see below for correct spelling)
+├── offset (enum): starts the search from an offset (e.g. 25 will start the search from the 25th result)
 ```
 
- 
 ### JobPost Schema
+
 ```plaintext
 JobPost
 ├── title (str)
@@ -109,14 +120,15 @@ JobPost
 ```
 
 ### Exceptions
+
 The following exceptions may be raised when using JobSpy:
+
 * `LinkedInException`
 * `IndeedException`
 * `ZipRecruiterException`
 
 ## Supported Countries for Job Searching
 
-
 ### **LinkedIn**
 
 LinkedIn searches globally & uses only the `location` parameter.
@@ -125,15 +137,15 @@ LinkedIn searches globally & uses only the `location` parameter.
 
 ZipRecruiter searches for jobs in **US/Canada** & uses only the `location` parameter.
 
-
 ### **Indeed**
-Indeed supports most countries, but the `country_indeed` parameter is required. Additionally, use the `location` parameter to narrow down the location, e.g. city & state if necessary.
+
+Indeed supports most countries, but the `country_indeed` parameter is required. Additionally, use the `location`
+parameter to narrow down the location, e.g. city & state if necessary.
 
 You can specify the following countries when searching on Indeed (use the exact name):
 
-
 |                      |              |            |                |
-|------|------|------|------|
+|----------------------|--------------|------------|----------------|
 | Argentina            | Australia    | Austria    | Bahrain        |
 | Belgium              | Brazil       | Canada     | Chile          |
 | China                | Colombia     | Costa Rica | Czech Republic |
@@ -156,12 +168,14 @@ You can specify the following countries when searching on Indeed (use the exact
 ---
 
 **Q: Encountering issues with your queries?**  
-**A:** Try reducing the number of `results_wanted` and/or broadening the filters. If problems persist, [submit an issue](https://github.com/cullenwatson/JobSpy/issues).
+**A:** Try reducing the number of `results_wanted` and/or broadening the filters. If problems
+persist, [submit an issue](https://github.com/cullenwatson/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. Currently, *
+*LinkedIn** is particularly aggressive with blocking. We recommend:
 
 - Waiting a few seconds between requests.
 - Trying a VPN or proxy to change your IP address.
@@ -170,6 +184,7 @@ You can specify the following countries when searching on Indeed (use the exact
 
 **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_Demo.py

@@ -0,0 +1,31 @@
+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)

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "python-jobspy"
-version = "1.1.7"
+version = "1.1.8"
 description = "Job scraper for LinkedIn, Indeed & ZipRecruiter"
 authors = ["Zachary Hampton <zachary@zacharysproducts.com>", "Cullen Watson <cullen@cullen.ai>"]
 homepage = "https://github.com/cullenwatson/JobSpy"

src/jobspy/__init__.py

@@ -1,8 +1,7 @@
 import pandas as pd
 import concurrent.futures
 from concurrent.futures import ThreadPoolExecutor
-from typing import List, Tuple, NamedTuple, Dict, Optional
+from typing import List, Tuple, Optional
-import traceback
 
 from .jobs import JobType, Location
 from .scrapers.indeed import IndeedScraper
@@ -38,6 +37,7 @@ def scrape_jobs(
         country_indeed: str = "usa",
         hyperlinks: bool = False,
         proxy: Optional[str] = None,
+        offset: Optional[int] = 0
 ) -> pd.DataFrame:
     """
     Simultaneously scrapes job data from multiple job sites.
@@ -49,8 +49,8 @@ def scrape_jobs(
             if value_str in job_type.value:
                 return job_type
         raise Exception(f"Invalid job type: {value_str}")
-    job_type = get_enum_from_value(job_type) if job_type else None
 
+    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)]
@@ -72,6 +72,7 @@ def scrape_jobs(
         job_type=job_type,
         easy_apply=easy_apply,
         results_wanted=results_wanted,
+        offset=offset
     )
 
     def scrape_site(site: Site) -> Tuple[str, JobResponse]:
@@ -149,17 +150,19 @@ def scrape_jobs(
     if jobs_dfs:
         jobs_df = pd.concat(jobs_dfs, ignore_index=True)
         desired_order: List[str] = [
+            "job_url_hyper" if hyperlinks else "job_url",
             "site",
             "title",
             "company",
             "location",
-            "date_posted",
             "job_type",
+            "date_posted",
             "interval",
+            "benefits",
             "min_amount",
             "max_amount",
             "currency",
-            "job_url_hyper" if hyperlinks else "job_url",
+            "emails",
             "description",
         ]
         jobs_formatted_df = jobs_df[desired_order]

src/jobspy/jobs/__init__.py

@@ -170,7 +170,7 @@ class CompensationInterval(Enum):
 
 
 class Compensation(BaseModel):
-    interval: CompensationInterval
+    interval: Optional[CompensationInterval] = None
     min_amount: int = None
     max_amount: int = None
     currency: Optional[str] = "USD"
@@ -186,6 +186,8 @@ class JobPost(BaseModel):
     job_type: Optional[JobType] = None
     compensation: Optional[Compensation] = None
     date_posted: Optional[date] = None
+    benefits: Optional[str] = None
+    emails: Optional[list[str]] = None
 
 
 class JobResponse(BaseModel):

src/jobspy/scrapers/__init__.py

@@ -18,6 +18,7 @@ class ScraperInput(BaseModel):
     is_remote: bool = False
     job_type: Optional[JobType] = None
     easy_apply: bool = None  # linkedin
+    offset: int = 0
 
     results_wanted: int = 15
 

src/jobspy/scrapers/indeed/__init__.py

@@ -8,7 +8,6 @@ import re
 import math
 import io
 import json
-import traceback
 from datetime import datetime
 from typing import Optional
 
@@ -27,7 +26,8 @@ from ...jobs import (
     JobResponse,
     JobType,
 )
-from .. import Scraper, ScraperInput, Site, Country
+from .. import Scraper, ScraperInput, Site
+from ...utils import extract_emails_from_text
 
 
 class IndeedScraper(Scraper):
@@ -35,6 +35,8 @@ class IndeedScraper(Scraper):
         """
         Initializes IndeedScraper with the Indeed job search url
         """
+        self.url = None
+        self.country = None
         site = Site(Site.INDEED)
         super().__init__(site, proxy=proxy)
 
@@ -61,7 +63,7 @@ class IndeedScraper(Scraper):
             "q": scraper_input.search_term,
             "l": scraper_input.location,
             "filter": 0,
-            "start": 0 + page * 10,
+            "start": scraper_input.offset + page * 10,
         }
         if scraper_input.distance:
             params["radius"] = scraper_input.distance
@@ -76,7 +78,7 @@ class IndeedScraper(Scraper):
             params["sc"] = "0kf:" + "".join(sc_values) + ";"
         try:
             response = session.get(
-                self.url + "/jobs",
+                f"{self.url}/jobs",
                 params=params,
                 allow_redirects=True,
                 proxy=self.proxy,
@@ -137,9 +139,10 @@ class IndeedScraper(Scraper):
             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 = BeautifulSoup(f, "html.parser")
+                soup_io = BeautifulSoup(f, "html.parser")
-                li_elements = soup.find_all("li")
+                li_elements = soup_io.find_all("li")
                 if description is None and li_elements:
                     description = " ".join(li.text for li in li_elements)
 
@@ -152,6 +155,7 @@ class IndeedScraper(Scraper):
                     state=job.get("jobLocationState"),
                     country=self.country,
                 ),
+                emails=extract_emails_from_text(description),
                 job_type=job_type,
                 compensation=compensation,
                 date_posted=date_posted,
@@ -206,7 +210,7 @@ class IndeedScraper(Scraper):
         )
         return job_response
 
-    def get_description(self, job_page_url: str, session: tls_client.Session) -> str:
+    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:
@@ -249,13 +253,17 @@ class IndeedScraper(Scraper):
                     label = taxonomy["attributes"][0].get("label")
                     if label:
                         job_type_str = label.replace("-", "").replace(" ", "").lower()
-                        return IndeedScraper.get_enum_from_value(job_type_str)
+                        return IndeedScraper.get_enum_from_job_type(job_type_str)
         return None
 
     @staticmethod
-    def get_enum_from_value(value_str):
+    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:
-            if value_str in job_type.value:
+        """
+        for job_type in JobType:
+            if job_type_str in job_type.value:
                 return job_type
         return None
 

src/jobspy/scrapers/linkedin/__init__.py

@@ -4,14 +4,16 @@ jobspy.scrapers.linkedin
 
 This module contains routines to scrape LinkedIn.
 """
-from typing import Optional, Tuple
+from typing import Optional
 from datetime import datetime
-import traceback
 
 import requests
-from requests.exceptions import Timeout, ProxyError
+import time
+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 .. import Scraper, ScraperInput, Site
 from ..exceptions import LinkedInException
@@ -20,17 +22,20 @@ from ...jobs import (
     Location,
     JobResponse,
     JobType,
-    Compensation,
-    CompensationInterval,
 )
+from ...utils import extract_emails_from_text
 
 
 class LinkedInScraper(Scraper):
+    MAX_RETRIES = 3
+    DELAY = 10
+
     def __init__(self, proxy: Optional[str] = None):
         """
         Initializes LinkedInScraper with the LinkedIn job search url
         """
         site = Site(Site.LINKEDIN)
+        self.country = "worldwide"
         self.url = "https://www.linkedin.com"
         super().__init__(site, proxy=proxy)
 
@@ -40,12 +45,12 @@ class LinkedInScraper(Scraper):
         :param scraper_input:
         :return: job_response
         """
-        self.country = "worldwide"
         job_list: list[JobPost] = []
         seen_urls = set()
-        page, processed_jobs, job_count = 0, 0, 0
+        url_lock = Lock()
+        page = scraper_input.offset // 25 + 25 if scraper_input.offset else 0
 
-        def job_type_code(job_type):
+        def job_type_code(job_type_enum):
             mapping = {
                 JobType.FULL_TIME: "F",
                 JobType.PART_TIME: "P",
@@ -54,10 +59,9 @@ class LinkedInScraper(Scraper):
                 JobType.TEMPORARY: "T",
             }
 
-            return mapping.get(job_type, "")
+            return mapping.get(job_type_enum, "")
 
-        with requests.Session() as session:
+        while len(job_list) < scraper_input.results_wanted and page < 1000:
-            while len(job_list) < scraper_input.results_wanted:
             params = {
                 "keywords": scraper_input.search_term,
                 "location": scraper_input.location,
@@ -66,78 +70,101 @@ class LinkedInScraper(Scraper):
                 "f_JT": job_type_code(scraper_input.job_type)
                 if scraper_input.job_type
                 else None,
-                    "pageNum": page,
+                "pageNum": 0,
+                page: page + scraper_input.offset,
                 "f_AL": "true" if scraper_input.easy_apply else None,
             }
 
             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 = session.get(
+                    response = requests.get(
-                        f"{self.url}/jobs/search",
+                        f"{self.url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
                         params=params,
                         allow_redirects=True,
                         proxies=self.proxy,
                         timeout=10,
                     )
                     response.raise_for_status()
+
+                    break
                 except requests.HTTPError as e:
-                    raise LinkedInException(
+                    if hasattr(e, 'response') and e.response is not None:
-                        f"bad response status code: {response.status_code}"
+                        if e.response.status_code == 429:
-                    )
+                            time.sleep(self.DELAY)
+                            retries += 1
+                            continue
+                        else:
+                            raise LinkedInException(f"bad response status code: {e.response.status_code}")
+                    else:
+                        raise
                 except ProxyError as e:
                     raise LinkedInException("bad proxy")
-                except (ProxyError, Exception) as e:
+                except Exception as e:
                     raise LinkedInException(str(e))
+            else:
+                # Raise an exception if the maximum number of retries is reached
+                raise LinkedInException("Max retries reached, failed to get a valid response")
 
             soup = BeautifulSoup(response.text, "html.parser")
 
-                if page == 0:
+            with ThreadPoolExecutor(max_workers=5) as executor:
-                    job_count_text = soup.find(
+                futures = []
-                        "span", class_="results-context-header__job-count"
+                for job_card in soup.find_all("div", class_="base-search-card"):
-                    ).text
+                    job_url = None
-                    job_count = int("".join(filter(str.isdigit, job_count_text)))
+                    href_tag = job_card.find("a", class_="base-card__full-link")
-
+                    if href_tag and "href" in href_tag.attrs:
-                for job_card in soup.find_all(
+                        href = href_tag.attrs["href"].split("?")[0]
-                    "div",
+                        job_id = href.split("-")[-1]
-                    class_="base-card relative w-full hover:no-underline focus:no-underline base-card--link base-search-card base-search-card--link job-search-card",
-                ):
-                    processed_jobs += 1
-                    data_entity_urn = job_card.get("data-entity-urn", "")
-                    job_id = (
-                        data_entity_urn.split(":")[-1] if data_entity_urn else "N/A"
-                    )
                         job_url = f"{self.url}/jobs/view/{job_id}"
+
+                    with url_lock:
                         if job_url in seen_urls:
                             continue
                         seen_urls.add(job_url)
-                    job_info = job_card.find("div", class_="base-search-card__info")
-                    if job_info is None:
-                        continue
-                    title_tag = job_info.find("h3", class_="base-search-card__title")
-                    title = title_tag.text.strip() if title_tag else "N/A"
 
-                    company_tag = job_info.find("a", class_="hidden-nested-link")
+                    futures.append(executor.submit(self.process_job, job_card, job_url))
-                    company = company_tag.text.strip() if company_tag else "N/A"
 
-                    metadata_card = job_info.find(
+                for future in as_completed(futures):
-                        "div", class_="base-search-card__metadata"
+                    try:
-                    )
+                        job_post = future.result()
-                    location: Location = self.get_location(metadata_card)
+                        if job_post:
+                            job_list.append(job_post)
+                    except Exception as e:
+                        raise LinkedInException("Exception occurred while processing jobs")
+            page += 25
 
-                    datetime_tag = metadata_card.find(
+        job_list = job_list[: scraper_input.results_wanted]
-                        "time", class_="job-search-card__listdate"
+        return JobResponse(jobs=job_list)
-                    )
+
-                    description, job_type = self.get_description(job_url)
+    def process_job(self, job_card: Tag, job_url: str) -> Optional[JobPost]:
-                    if datetime_tag:
+        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 = company_a_tag.get_text(strip=True) if company_a_tag else "N/A"
+
+        metadata_card = job_card.find("div", class_="base-search-card__metadata")
+        location = self.get_location(metadata_card)
+
+        datetime_tag = metadata_card.find("time", class_="job-search-card__listdate") if metadata_card else None
+        date_posted = None
+        if datetime_tag and "datetime" in datetime_tag.attrs:
             datetime_str = datetime_tag["datetime"]
             try:
                 date_posted = datetime.strptime(datetime_str, "%Y-%m-%d")
             except Exception as e:
                 date_posted = None
-                    else:
+        benefits_tag = job_card.find("span", class_="result-benefits__text")
-                        date_posted = None
+        benefits = " ".join(benefits_tag.get_text().split()) if benefits_tag else None
 
-                    job_post = JobPost(
+        description, job_type = self.get_job_description(job_url)
+
+        return JobPost(
             title=title,
             description=description,
             company_name=company,
@@ -145,26 +172,12 @@ class LinkedInScraper(Scraper):
             date_posted=date_posted,
             job_url=job_url,
             job_type=job_type,
-                        compensation=Compensation(
+            benefits=benefits,
-                            interval=CompensationInterval.YEARLY, currency=None
+            emails=extract_emails_from_text(description)
-                        ),
         )
-                    job_list.append(job_post)
-                    if processed_jobs >= job_count:
-                        break
-                    if len(job_list) >= scraper_input.results_wanted:
-                        break
-                if processed_jobs >= job_count:
-                    break
-                if len(job_list) >= scraper_input.results_wanted:
-                    break
 
-                page += 1
+    def get_job_description(self, job_page_url: str) -> tuple[None, None] | tuple[
-
+        str | None, tuple[str | None, JobType | None]]:
-        job_list = job_list[: scraper_input.results_wanted]
-        return JobResponse(jobs=job_list)
-
-    def get_description(self, job_page_url: str) -> Optional[str]:
         """
         Retrieves job description by going to the job page url
         :param job_page_url:
@@ -181,19 +194,19 @@ class LinkedInScraper(Scraper):
             "div", class_=lambda x: x and "show-more-less-html__markup" in x
         )
 
-        text_content = None
+        description = None
         if div_content:
-            text_content = " ".join(div_content.get_text().split()).strip()
+            description = " ".join(div_content.get_text().split()).strip()
 
         def get_job_type(
-            soup: BeautifulSoup,
+                soup_job_type: BeautifulSoup,
-        ) -> Tuple[Optional[str], Optional[JobType]]:
+        ) -> JobType | None:
             """
             Gets the job type from job page
-            :param soup:
+            :param soup_job_type:
             :return: JobType
             """
-            h3_tag = soup.find(
+            h3_tag = soup_job_type.find(
                 "h3",
                 class_="description__job-criteria-subheader",
                 string=lambda text: "Employment type" in text,
@@ -212,7 +225,7 @@ class LinkedInScraper(Scraper):
 
             return LinkedInScraper.get_enum_from_value(employment_type)
 
-        return text_content, get_job_type(soup)
+        return description, get_job_type(soup)
 
     @staticmethod
     def get_enum_from_value(value_str):

src/jobspy/scrapers/ziprecruiter/__init__.py

@@ -7,10 +7,9 @@ This module contains routines to scrape ZipRecruiter.
 import math
 import json
 import re
-import traceback
+from datetime import datetime, date
-from datetime import datetime
+from typing import Optional, Tuple, Any
-from typing import Optional, Tuple
+from urllib.parse import urlparse, parse_qs, urlunparse
-from urllib.parse import urlparse, parse_qs
 
 import tls_client
 import requests
@@ -29,6 +28,7 @@ from ...jobs import (
     JobType,
     Country,
 )
+from ...utils import extract_emails_from_text
 
 
 class ZipRecruiterScraper(Scraper):
@@ -48,18 +48,17 @@ class ZipRecruiterScraper(Scraper):
 
     def find_jobs_in_page(
             self, scraper_input: ScraperInput, page: int
-    ) -> tuple[list[JobPost], int | None]:
+    ) -> list[JobPost]:
         """
         Scrapes a page of ZipRecruiter for jobs with scraper_input criteria
         :param scraper_input:
         :param page:
-        :param session:
+        :return: jobs found on page
-        :return: jobs found on page, total number of jobs found for search
         """
         job_list: list[JobPost] = []
         try:
             response = self.session.get(
-                self.url + "/jobs-search",
+                f"{self.url}/jobs-search",
                 headers=ZipRecruiterScraper.headers(),
                 params=ZipRecruiterScraper.add_params(scraper_input, page),
                 allow_redirects=True,
@@ -92,8 +91,6 @@ class ZipRecruiterScraper(Scraper):
             page_variant = "html_1"
             jobs_list = soup.find_all("li", {"class": "job-listing"})
             # print('type 1 html', len(jobs_list))
-            # with open("zip_method_8.html", "w") as f:
-            #     f.write(soup.prettify())
 
         with ThreadPoolExecutor(max_workers=10) as executor:
             if page_variant == "javascript":
@@ -119,8 +116,9 @@ class ZipRecruiterScraper(Scraper):
         :param scraper_input:
         :return: job_response
         """
+        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, 1)
+        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)
         )
@@ -128,7 +126,7 @@ class ZipRecruiterScraper(Scraper):
         with ThreadPoolExecutor(max_workers=10) as executor:
             futures: list[Future] = [
                 executor.submit(self.find_jobs_in_page, scraper_input, page)
-                for page in range(2, pages_to_process + 1)
+                for page in range(start_page + 1, start_page + pages_to_process + 2)
             ]
 
             for future in futures:
@@ -144,8 +142,9 @@ class ZipRecruiterScraper(Scraper):
         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
         """
-        job_url = job.find("a", {"class": "job_link"})["href"]
+        job_url = self.cleanurl(job.find("a", {"class": "job_link"})["href"])
         if job_url in self.seen_urls:
             return None
 
@@ -153,7 +152,7 @@ class ZipRecruiterScraper(Scraper):
         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
+        # 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()
 
@@ -176,6 +175,7 @@ class ZipRecruiterScraper(Scraper):
             compensation=ZipRecruiterScraper.get_compensation(job),
             date_posted=date_posted,
             job_url=job_url,
+            emails=extract_emails_from_text(description),
         )
         return job_post
 
@@ -185,12 +185,12 @@ class ZipRecruiterScraper(Scraper):
         :param job: BeautifulSoup Tag for one job post
         :return JobPost
         """
-        job_url = job.find("a", class_="job_link")["href"]
+        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
+        # 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()
 
@@ -221,10 +221,10 @@ class ZipRecruiterScraper(Scraper):
 
     def process_job_javascript(self, job: dict) -> JobPost:
         title = job.get("Title")
-        job_url = job.get("JobURL")
+        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
+        # job_url = updated_job_url if updated_job_url else job_url
         if description is None:
             description = BeautifulSoup(
                 job.get("Snippet", "").strip(), "html.parser"
@@ -272,7 +272,6 @@ class ZipRecruiterScraper(Scraper):
             date_posted = date_posted_obj.date()
         else:
             date_posted = date.today()
-        job_url = job.get("JobURL")
 
         return JobPost(
             title=title,
@@ -323,7 +322,7 @@ class ZipRecruiterScraper(Scraper):
         return None, response.url
 
     @staticmethod
-    def add_params(scraper_input, page) -> Optional[str]:
+    def add_params(scraper_input, page) -> dict[str, str | Any]:
         params = {
             "search": scraper_input.search_term,
             "location": scraper_input.location,
@@ -368,7 +367,7 @@ class ZipRecruiterScraper(Scraper):
         return CompensationInterval(interval_str)
 
     @staticmethod
-    def get_date_posted(job: BeautifulSoup) -> Optional[datetime.date]:
+    def get_date_posted(job: Tag) -> Optional[datetime.date]:
         """
         Extracts the date a job was posted
         :param job
@@ -394,7 +393,7 @@ class ZipRecruiterScraper(Scraper):
         return None
 
     @staticmethod
-    def get_compensation(job: BeautifulSoup) -> Optional[Compensation]:
+    def get_compensation(job: Tag) -> Optional[Compensation]:
         """
         Parses the compensation tag from the job BeautifulSoup object
         :param job
@@ -435,7 +434,7 @@ class ZipRecruiterScraper(Scraper):
         return create_compensation_object(pay)
 
     @staticmethod
-    def get_location(job: BeautifulSoup) -> Location:
+    def get_location(job: Tag) -> Location:
         """
         Extracts the job location from BeatifulSoup object
         :param job:
@@ -462,3 +461,9 @@ class ZipRecruiterScraper(Scraper):
         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"
         }
+
+    @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

@@ -1,4 +1,5 @@
 from ..jobspy import scrape_jobs
+import pandas as pd
 
 
 def test_all():
@@ -7,4 +8,5 @@ def test_all():
         search_term="software engineer",
         results_wanted=5,
     )
-    assert result is not None and result.errors.empty is True
+
+    assert isinstance(result, pd.DataFrame) and not result.empty, "Result should be a non-empty DataFrame"

src/tests/test_indeed.py

@@ -1,4 +1,5 @@
 from ..jobspy import scrape_jobs
+import pandas as pd
 
 
 def test_indeed():
@@ -6,4 +7,4 @@ def test_indeed():
         site_name="indeed",
         search_term="software engineer",
     )
-    assert result is not None and result.errors.empty is True
+    assert isinstance(result, pd.DataFrame) and not result.empty, "Result should be a non-empty DataFrame"

src/tests/test_linkedin.py

@@ -1,4 +1,5 @@
 from ..jobspy import scrape_jobs
+import pandas as pd
 
 
 def test_linkedin():
@@ -6,4 +7,4 @@ def test_linkedin():
         site_name="linkedin",
         search_term="software engineer",
     )
-    assert result is not None and result.errors.empty is True
+    assert isinstance(result, pd.DataFrame) and not result.empty, "Result should be a non-empty DataFrame"

src/tests/test_ziprecruiter.py

@@ -1,4 +1,5 @@
 from ..jobspy import scrape_jobs
+import pandas as pd
 
 
 def test_ziprecruiter():
@@ -7,4 +8,4 @@ def test_ziprecruiter():
         search_term="software engineer",
     )
 
-    assert result is not None and result.errors.empty is True
+    assert isinstance(result, pd.DataFrame) and not result.empty, "Result should be a non-empty DataFrame"