readd proxy support for zip (#64)

* enh(indeed): mult job types

* feat(jobs):  urgent kws

* fix(indeed): use new session obj per request

* fix: emails as comma separated in output

* fix: put num urgent words in output

* chore: readme

.github/workflows/publish-to-pypi.yml

@@ -7,27 +7,27 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v3
+      - uses: actions/checkout@v3
-    - name: Set up Python
+      - name: Set up Python
-      uses: actions/setup-python@v4
+        uses: actions/setup-python@v4
-      with:
+        with:
-        python-version: "3.10"
+          python-version: "3.10"
 
-    - name: Install poetry
+      - name: Install poetry
-      run: >-
+        run: >-
-        python3 -m
+          python3 -m
-        pip install
+          pip install
-        poetry
+          poetry
-        --user
+          --user
 
-    - name: Build distribution 📦
+      - name: Build distribution 📦
-      run: >-
+        run: >-
-        python3 -m
+          python3 -m
-        poetry
+          poetry
-        build
+          build
 
-    - name: Publish distribution 📦 to PyPI
+      - name: Publish distribution 📦 to PyPI
-      if: startsWith(github.ref, 'refs/tags')
+        if: startsWith(github.ref, 'refs/tags')
-      uses: pypa/gh-action-pypi-publish@release/v1
+        uses: pypa/gh-action-pypi-publish@release/v1
-      with:
+        with:
-        password: ${{ secrets.PYPI_API_TOKEN }}
+          password: ${{ secrets.PYPI_API_TOKEN }}

.gitignore

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

README.md

@@ -1,63 +1,53 @@
 <img src="https://github.com/cullenwatson/JobSpy/assets/78247585/ae185b7e-e444-4712-8bb9-fa97f53e896b" width="400">
 
 **JobSpy** is a simple, yet comprehensive, job scraping library.
-## Features
 
+**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/bunsly/15min)** *to
+work with us.*  
+\
+Check out another project we wrote: ***[HomeHarvest](https://github.com/Bunsly/HomeHarvest)** – a Python package
+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=-yS3mgI5H-4)
-
 
+[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 python-jobspy
 ```
-  
+
-  _Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_ 
+_Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_
 
 ### Usage
 
 ```python
 from jobspy import scrape_jobs
-import pandas as pd
 
-jobs: pd.DataFrame = scrape_jobs(
+jobs = scrape_jobs(
     site_name=["indeed", "linkedin", "zip_recruiter"],
     search_term="software engineer",
     location="Dallas, TX",
     results_wanted=10,
-    
+    country_indeed='USA'  # only needed for indeed
-    country_indeed='USA' # only needed for indeed
-    
-    # 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",
 )
-
+print(f"Found {len(jobs)} jobs")
-pd.set_option('display.max_columns', None)
+print(jobs.head())
-pd.set_option('display.max_rows', None)
+jobs.to_csv("jobs.csv", index=False) # / to_xlsx
-pd.set_option('display.width', None)
-pd.set_option('display.max_colwidth', 50)  # set to 0 to see full job url / desc
-
-#1 output
-print(jobs)
-print(errors)
-
-#2 display in Jupyter Notebook
-#display(jobs)
-#display(errors)
-
-#3 output to .csv
-#result.jobs.to_csv('result.jobs.csv', 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!...
@@ -67,7 +57,9 @@ 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
@@ -76,14 +68,16 @@ 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]
 ├── is_remote (bool)
 ├── 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
+├── 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)
 ```
 
- 
 ### JobPost Schema
+
 ```plaintext
 JobPost
 ├── title (str)
@@ -94,69 +88,85 @@ JobPost
 │   ├── 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
+
+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
+LinkedIn searches globally & uses only the `location` parameter.
 
 ### **ZipRecruiter**
 
-ZipRecruiter searches for jobs in US/Canada & uses only the `location` parameter
+ZipRecruiter searches for jobs in **US/Canada** & uses only the `location` parameter.
-
 
 ### **Indeed**
-For Indeed, the `country_indeed` parameter is required. Additionally, use the `location` parameter and include the city or state if necessary.
 
-You can specify the following countries when searching on Indeed (use the exact name): 
+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 |
+| Argentina            | Australia    | Austria    | Bahrain        |
-| Belgium | Brazil | Canada | Chile |
+| Belgium              | Brazil       | Canada     | Chile          |
-| China | Colombia | Costa Rica | Czech Republic |
+| China                | Colombia     | Costa Rica | Czech Republic |
-| Denmark | Ecuador | Egypt | Finland |
+| Denmark              | Ecuador      | Egypt      | Finland        |
-| France | Germany | Greece | Hong Kong |
+| France               | Germany      | Greece     | Hong Kong      |
-| Hungary | India | Indonesia | Ireland |
+| Hungary              | India        | Indonesia  | Ireland        |
-| Israel | Italy | Japan | Kuwait |
+| Israel               | Italy        | Japan      | Kuwait         |
-| Luxembourg | Malaysia | Mexico | Morocco |
+| Luxembourg           | Malaysia     | Mexico     | Morocco        |
-| Netherlands | New Zealand | Nigeria | Norway |
+| Netherlands          | New Zealand  | Nigeria    | Norway         |
-| Oman | Pakistan | Panama | Peru |
+| Oman                 | Pakistan     | Panama     | Peru           |
-| Philippines | Poland | Portugal | Qatar |
+| Philippines          | Poland       | Portugal   | Qatar          |
-| Romania | Saudi Arabia | Singapore | South Africa |
+| Romania              | Saudi Arabia | Singapore  | South Africa   |
-| South Korea | Spain | Sweden | Switzerland |
+| South Korea          | Spain        | Sweden     | Switzerland    |
-| Taiwan | Thailand | Turkey | Ukraine |
+| Taiwan               | Thailand     | Turkey     | Ukraine        |
-| United Arab Emirates | UK | USA | Uruguay |
+| United Arab Emirates | UK           | USA        | Uruguay        |
-| Venezuela | Vietnam |  |  |
+| Venezuela            | Vietnam      |            |                |
 
 ## 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](#).
+**A:** Try reducing the number of `results_wanted` and/or broadening the filters. If problems
+persist, [submit an issue](https://github.com/Bunsly/JobSpy/issues).
 
 ---
 
 **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, **ZipRecruiter** 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.
-- Trying a VPN to change your IP address.
+- Trying a VPN or proxy to change your IP address.
-
-**Note:** Proxy support is in development and coming soon!
 
 ---
 
+**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.ipynb

@@ -9,7 +9,7 @@
    "source": [
     "from jobspy import scrape_jobs\n",
     "import pandas as pd\n",
-    "from IPython.display import display, HTML\n"
+    "from IPython.display import display, HTML"
    ]
   },
   {
@@ -34,18 +34,16 @@
    "source": [
     "# example 1 (no hyperlinks, USA)\n",
     "jobs = scrape_jobs(\n",
-    "    site_name=[\"linkedin\", \"zip_recruiter\"],\n",
+    "    site_name=[\"linkedin\"],\n",
     "    location='san francisco',\n",
     "    search_term=\"engineer\",\n",
     "    results_wanted=5,\n",
     "\n",
     "    # use if you want to use a proxy\n",
-    "    # proxy=\"socks5://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001\",\n",
+    "    # proxy=\"socks5://jobspy:5a4vpWtj4EeJ2hoYzk@us.smartproxy.com:10001\",\n",
-    "    # proxy=\"http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001\",\n",
+    "    proxy=\"http://jobspy:5a4vpWtj4EeJ2hoYzk@us.smartproxy.com:10001\",\n",
-    "    # proxy=\"https://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001\",\n",
+    "    #proxy=\"https://jobspy:5a4vpWtj4EeJ2hoYzk@us.smartproxy.com:10001\",\n",
-    "\n",
     ")\n",
-    "\n",
     "display(jobs)"
    ]
   },
@@ -97,9 +95,6 @@
     "    hyperlinks=True,\n",
     "    results_wanted=5,\n",
     "    easy_apply=True\n",
-    "\n",
-    "\n",
-    "\n",
     ")"
    ]
   },
@@ -125,11 +120,10 @@
    "outputs": [],
    "source": [
     "# example 4 - international indeed (no zip_recruiter)\n",
-    "result = scrape_jobs(\n",
+    "jobs = scrape_jobs(\n",
     "    site_name=[\"indeed\"],\n",
-    "    location='berlin',\n",
     "    search_term=\"engineer\",\n",
-    "    country_indeed = \"Germany\",\n",
+    "    country_indeed = \"China\",\n",
     "    hyperlinks=True\n",
     ")"
    ]
@@ -165,7 +159,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.11"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,

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)

poetry.lock

@@ -1053,6 +1053,16 @@ files = [
     {file = "MarkupSafe-2.1.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:5bbe06f8eeafd38e5d0a4894ffec89378b6c6a625ff57e3028921f8ff59318ac"},
     {file = "MarkupSafe-2.1.3-cp311-cp311-win32.whl", hash = "sha256:dd15ff04ffd7e05ffcb7fe79f1b98041b8ea30ae9234aed2a9168b5797c3effb"},
     {file = "MarkupSafe-2.1.3-cp311-cp311-win_amd64.whl", hash = "sha256:134da1eca9ec0ae528110ccc9e48041e0828d79f24121a1a146161103c76e686"},
+    {file = "MarkupSafe-2.1.3-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:f698de3fd0c4e6972b92290a45bd9b1536bffe8c6759c62471efaa8acb4c37bc"},
+    {file = "MarkupSafe-2.1.3-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:aa57bd9cf8ae831a362185ee444e15a93ecb2e344c8e52e4d721ea3ab6ef1823"},
+    {file = "MarkupSafe-2.1.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ffcc3f7c66b5f5b7931a5aa68fc9cecc51e685ef90282f4a82f0f5e9b704ad11"},
+    {file = "MarkupSafe-2.1.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:47d4f1c5f80fc62fdd7777d0d40a2e9dda0a05883ab11374334f6c4de38adffd"},
+    {file = "MarkupSafe-2.1.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:1f67c7038d560d92149c060157d623c542173016c4babc0c1913cca0564b9939"},
+    {file = "MarkupSafe-2.1.3-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:9aad3c1755095ce347e26488214ef77e0485a3c34a50c5a5e2471dff60b9dd9c"},
+    {file = "MarkupSafe-2.1.3-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:14ff806850827afd6b07a5f32bd917fb7f45b046ba40c57abdb636674a8b559c"},
+    {file = "MarkupSafe-2.1.3-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:8f9293864fe09b8149f0cc42ce56e3f0e54de883a9de90cd427f191c346eb2e1"},
+    {file = "MarkupSafe-2.1.3-cp312-cp312-win32.whl", hash = "sha256:715d3562f79d540f251b99ebd6d8baa547118974341db04f5ad06d5ea3eb8007"},
+    {file = "MarkupSafe-2.1.3-cp312-cp312-win_amd64.whl", hash = "sha256:1b8dd8c3fd14349433c79fa8abeb573a55fc0fdd769133baac1f5e07abf54aeb"},
     {file = "MarkupSafe-2.1.3-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:8e254ae696c88d98da6555f5ace2279cf7cd5b3f52be2b5cf97feafe883b58d2"},
     {file = "MarkupSafe-2.1.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cb0932dc158471523c9637e807d9bfb93e06a95cbf010f1a38b98623b929ef2b"},
     {file = "MarkupSafe-2.1.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9402b03f1a1b4dc4c19845e5c749e3ab82d5078d16a2a4c2cd2df62d57bb0707"},
@@ -1243,36 +1253,39 @@ 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"
 files = [
-    {file = "numpy-1.25.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:db3ccc4e37a6873045580d413fe79b68e47a681af8db2e046f1dacfa11f86eb3"},
+    {file = "numpy-1.24.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:eef70b4fc1e872ebddc38cddacc87c19a3709c0e3e5d20bf3954c147b1dd941d"},
-    {file = "numpy-1.25.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:90319e4f002795ccfc9050110bbbaa16c944b1c37c0baeea43c5fb881693ae1f"},
+    {file = "numpy-1.24.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e8d2859428712785e8a8b7d2b3ef0a1d1565892367b32f915c4a4df44d0e64f5"},
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+    {file = "numpy-1.24.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6524630f71631be2dabe0c541e7675db82651eb998496bbe16bc4f77f0772253"},
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+    {file = "numpy-1.24.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a51725a815a6188c662fb66fb32077709a9ca38053f0274640293a14fdd22978"},
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+    {file = "numpy-1.24.2-cp310-cp310-win32.whl", hash = "sha256:2620e8592136e073bd12ee4536149380695fbe9ebeae845b81237f986479ffc9"},
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+    {file = "numpy-1.24.2-cp310-cp310-win_amd64.whl", hash = "sha256:97cf27e51fa078078c649a51d7ade3c92d9e709ba2bfb97493007103c741f1d0"},
-    {file = "numpy-1.25.2-cp310-cp310-win_amd64.whl", hash = "sha256:834b386f2b8210dca38c71a6e0f4fd6922f7d3fcff935dbe3a570945acb1b545"},
+    {file = "numpy-1.24.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:7de8fdde0003f4294655aa5d5f0a89c26b9f22c0a58790c38fae1ed392d44a5a"},
-    {file = "numpy-1.25.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:c5462d19336db4560041517dbb7759c21d181a67cb01b36ca109b2ae37d32418"},
+    {file = "numpy-1.24.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:4173bde9fa2a005c2c6e2ea8ac1618e2ed2c1c6ec8a7657237854d42094123a0"},
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+    {file = "numpy-1.24.2.tar.gz", hash = "sha256:003a9f530e880cb2cd177cba1af7220b9aa42def9c4afc2a2fc3ee6be7eb2b22"},
 ]
 
 [[package]]
@@ -2432,4 +2445,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "0c50057af9ebbbe5c124c81758b41f05c05636739c3d1747e1bac74e75a046cb"
+content-hash = "f966f3979873eec2c3b13460067f5aa414c69aa8ab5cd3239c1cfa564fcb5deb"

pyproject.toml

@@ -1,8 +1,9 @@
 [tool.poetry]
 name = "python-jobspy"
-version = "1.1.3"
+version = "1.1.22"
 description = "Job scraper for LinkedIn, Indeed & ZipRecruiter"
-authors = ["Zachary Hampton <zachary@zacharysproducts.com>", "Cullen Watson <cullen@cullen.ai>"]
+authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
+homepage = "https://github.com/Bunsly/JobSpy"
 readme = "README.md"
 
 packages = [
@@ -15,6 +16,7 @@ requests = "^2.31.0"
 tls-client = "^0.2.1"
 beautifulsoup4 = "^4.12.2"
 pandas = "^2.1.0"
+NUMPY = "1.24.2"
 pydantic = "^2.3.0"
 
 

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 Tuple, Optional
-import traceback
 
 from .jobs import JobType, Location
 from .scrapers.indeed import IndeedScraper
@@ -27,23 +26,32 @@ def _map_str_to_site(site_name: str) -> Site:
 
 
 def scrape_jobs(
-    site_name: str | List[str] | Site | List[Site],
+    site_name: str | list[str] | Site | list[Site],
     search_term: str,
     location: str = "",
     distance: int = None,
     is_remote: bool = False,
-    job_type: JobType = None,
+    job_type: str = None,
     easy_apply: bool = False,  # linkedin
     results_wanted: int = 15,
     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.
     :return: results_wanted: pandas dataframe containing job data
     """
 
+    def get_enum_from_value(value_str):
+        for job_type in JobType:
+            if value_str in job_type.value:
+                return job_type
+        raise Exception(f"Invalid job type: {value_str}")
+
+    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
@@ -64,6 +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]:
@@ -75,13 +84,12 @@ def scrape_jobs(
         except (LinkedInException, IndeedException, ZipRecruiterException) as lie:
             raise lie
         except Exception as e:
-            # unhandled exceptions
             if site == Site.LINKEDIN:
-                raise LinkedInException()
+                raise LinkedInException(str(e))
             if site == Site.INDEED:
-                raise IndeedException()
+                raise IndeedException(str(e))
             if site == Site.ZIP_RECRUITER:
-                raise ZipRecruiterException()
+                raise ZipRecruiterException(str(e))
             else:
                 raise e
         return site.value, scraped_data
@@ -89,8 +97,8 @@ def scrape_jobs(
     site_to_jobs_dict = {}
 
     def worker(site):
-        site_value, scraped_data = scrape_site(site)
+        site_val, scraped_info = scrape_site(site)
-        return site_value, scraped_data
+        return site_val, scraped_info
 
     with ThreadPoolExecutor() as executor:
         future_to_site = {
@@ -101,7 +109,7 @@ def scrape_jobs(
             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:
@@ -111,12 +119,14 @@ 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"]:
+            job_data["job_type"] = (
-                # Take the first value from the job type tuple
+                ", ".join(job_type.value[0] for job_type in job_data["job_type"])
-                job_data["job_type"] = job_data["job_type"].value[0]
+                if job_data["job_type"]
-            else:
+                else None
-                job_data["job_type"] = None
+            )
-
+            job_data["emails"] = (
+                ", ".join(job_data["emails"]) if job_data["emails"] else None
+            )
             job_data["location"] = Location(**job_data["location"]).display_location()
 
             compensation_obj = job_data.get("compensation")
@@ -140,18 +150,22 @@ 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",
             "location",
-            "date_posted",
             "job_type",
+            "date_posted",
             "interval",
             "min_amount",
             "max_amount",
             "currency",
-            "job_url_hyper" if hyperlinks else "job_url",
+            "is_remote",
+            "num_urgent_words",
+            "benefits",
+            "emails",
             "description",
         ]
         jobs_formatted_df = jobs_df[desired_order]

src/jobspy/jobs/__init__.py

@@ -37,10 +37,16 @@ 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",)
@@ -170,9 +176,9 @@ class CompensationInterval(Enum):
 
 
 class Compensation(BaseModel):
-    interval: CompensationInterval
+    interval: Optional[CompensationInterval] = None
-    min_amount: int = None
+    min_amount: int | None = None
-    max_amount: int = None
+    max_amount: int | None = None
     currency: Optional[str] = "USD"
 
 
@@ -182,10 +188,15 @@ class JobPost(BaseModel):
     job_url: str
     location: Optional[Location]
 
-    description: Optional[str] = None
+    description: str | None = None
-    job_type: Optional[JobType] = None
+    job_type: list[JobType] | None = None
-    compensation: Optional[Compensation] = None
+    compensation: Compensation | None = None
-    date_posted: Optional[date] = 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

@@ -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/exceptions.py

@@ -7,12 +7,15 @@ 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")

src/jobspy/scrapers/indeed/__init__.py

@@ -8,17 +8,20 @@ import re
 import math
 import io
 import json
-import traceback
 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,
+)
 from ...jobs import (
     JobPost,
     Compensation,
@@ -27,14 +30,16 @@ from ...jobs import (
     JobResponse,
     JobType,
 )
-from .. import Scraper, ScraperInput, Site, Country
+from .. import Scraper, ScraperInput, Site
 
 
 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
         site = Site(Site.INDEED)
         super().__init__(site, proxy=proxy)
 
@@ -42,26 +47,23 @@ class IndeedScraper(Scraper):
         self.seen_urls = set()
 
     def scrape_page(
-        self, scraper_input: ScraperInput, page: int, session: tls_client.Session
+        self, scraper_input: ScraperInput, page: int
     ) -> tuple[list[JobPost], int]:
         """
         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: list[JobPost] = []
-
         params = {
             "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
@@ -75,11 +77,12 @@ class IndeedScraper(Scraper):
         if sc_values:
             params["sc"] = "0kf:" + "".join(sc_values) + ";"
         try:
+            session = create_session(self.proxy, is_tls=True)
             response = session.get(
-                self.url + "/jobs",
+                f"{self.url}/jobs",
+                headers=self.get_headers(),
                 params=params,
                 allow_redirects=True,
-                proxy=self.proxy,
                 timeout_seconds=10,
             )
             if response.status_code not in range(200, 400):
@@ -107,7 +110,7 @@ class IndeedScraper(Scraper):
         ):
             raise IndeedException("No jobs found.")
 
-        def process_job(job) -> Optional[JobPost]:
+        def process_job(job) -> JobPost | None:
             job_url = f'{self.url}/jobs/viewjob?jk={job["jobkey"]}'
             job_url_client = f'{self.url}/viewjob?jk={job["jobkey"]}'
             if job_url in self.seen_urls:
@@ -126,8 +129,8 @@ class IndeedScraper(Scraper):
                 if interval in CompensationInterval.__members__:
                     compensation = Compensation(
                         interval=CompensationInterval[interval],
-                        min_amount=int(extracted_salary.get("max")),
+                        min_amount=int(extracted_salary.get("min")),
-                        max_amount=int(extracted_salary.get("min")),
+                        max_amount=int(extracted_salary.get("max")),
                         currency=currency,
                     )
 
@@ -136,10 +139,10 @@ class IndeedScraper(Scraper):
             date_posted = datetime.fromtimestamp(timestamp_seconds)
             date_posted = date_posted.strftime("%Y-%m-%d")
 
-            description = self.get_description(job_url, session)
+            description = self.get_description(job_url)
             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)
 
@@ -156,13 +159,18 @@ class IndeedScraper(Scraper):
                 compensation=compensation,
                 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_remote_job(job),
             )
             return job_post
 
+        jobs = jobs["metaData"]["mosaicProviderJobCardsModel"]["results"]
         with ThreadPoolExecutor(max_workers=1) as executor:
             job_results: list[Future] = [
-                executor.submit(process_job, job)
+                executor.submit(process_job, job) for job in jobs
-                for job in jobs["metaData"]["mosaicProviderJobCardsModel"]["results"]
             ]
 
         job_list = [result.result() for result in job_results if result.result()]
@@ -175,20 +183,16 @@ class IndeedScraper(Scraper):
         :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)
+        job_list, total_results = self.scrape_page(scraper_input, 0)
 
         with ThreadPoolExecutor(max_workers=1) as executor:
             futures: list[Future] = [
-                executor.submit(self.scrape_page, scraper_input, page, session)
+                executor.submit(self.scrape_page, scraper_input, page)
                 for page in range(1, pages_to_process + 1)
             ]
 
@@ -206,21 +210,24 @@ 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) -> str | None:
         """
         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"
+        session = create_session(self.proxy)
 
         try:
             response = session.get(
-                formatted_url, allow_redirects=True, timeout_seconds=5, proxy=self.proxy
+                formatted_url,
+                headers=self.get_headers(),
+                allow_redirects=True,
+                timeout_seconds=5,
             )
         except Exception as e:
             return None
@@ -228,36 +235,56 @@ class IndeedScraper(Scraper):
         if response.status_code not in range(200, 400):
             return None
 
-        raw_description = response.json()["body"]["jobInfoWrapperModel"][
+        soup = BeautifulSoup(response.text, "html.parser")
-            "jobInfoModel"
+        script_tag = soup.find(
-        ]["sanitizedJobDescription"]
+            "script", text=lambda x: x and "window._initialData" in x
-        with io.StringIO(raw_description) as f:
+        )
-            soup = BeautifulSoup(f, "html.parser")
+
-            text_content = " ".join(soup.get_text().split()).strip()
+        if not script_tag:
-            return text_content
+            return None
+
+        script_code = script_tag.string
+        match = re.search(r"window\._initialData\s*=\s*({.*?})\s*;", script_code, re.S)
+
+        if not match:
+            return None
+
+        json_string = match.group(1)
+        data = json.loads(json_string)
+        try:
+            job_description = data["jobInfoWrapperModel"]["jobInfoModel"][
+                "sanitizedJobDescription"
+            ]
+        except (KeyError, TypeError, IndexError):
+            return None
+
+        soup = BeautifulSoup(
+            job_description, "html.parser"
+        )
+        text_content = " ".join(
+            soup.get_text(separator=" ").split()
+        ).strip()
+
+        return text_content
 
     @staticmethod
-    def get_job_type(job: dict) -> Optional[JobType]:
+    def get_job_type(job: dict) -> list[JobType] | None:
         """
-        Parses the job to get JobTypeIndeed
+        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":
-                if len(taxonomy["attributes"]) > 0:
+                for i in range(len(taxonomy["attributes"])):
-                    label = taxonomy["attributes"][0].get("label")
+                    label = taxonomy["attributes"][i].get("label")
                     if label:
                         job_type_str = label.replace("-", "").replace(" ", "").lower()
-                        return IndeedScraper.get_enum_from_value(job_type_str)
+                        job_type = get_enum_from_job_type(job_type_str)
-        return None
+                        if job_type:
-
+                            job_types.append(job_type)
-    @staticmethod
+        return job_types
-    def get_enum_from_value(value_str):
-        for job_type in JobType:
-            if value_str in job_type.value:
-                return job_type
-        return None
 
     @staticmethod
     def parse_jobs(soup: BeautifulSoup) -> dict:
@@ -267,7 +294,7 @@ class IndeedScraper(Scraper):
         :return: jobs
         """
 
-        def find_mosaic_script() -> Optional[Tag]:
+        def find_mosaic_script() -> Tag | None:
             """
             Finds jobcards script tag
             :return: script_tag
@@ -317,3 +344,30 @@ class IndeedScraper(Scraper):
             data = json.loads(json_str)
             total_num_jobs = int(data["searchTitleBarModel"]["totalNumResults"])
         return total_num_jobs
+
+    @staticmethod
+    def get_headers():
+        return {
+            "authority": "www.indeed.com",
+            "accept": "*/*",
+            "accept-language": "en-US,en;q=0.9",
+            "referer": "https://www.indeed.com/viewjob?jk=fe6182337d72c7b1&tk=1hcbfcmd0k62t802&from=serp&vjs=3&advn=8132938064490989&adid=408692607&ad=-6NYlbfkN0A3Osc99MJFDKjquSk4WOGT28ALb_ad4QMtrHreCb9ICg6MiSVy9oDAp3evvOrI7Q-O9qOtQTg1EPbthP9xWtBN2cOuVeHQijxHjHpJC65TjDtftH3AXeINjBvAyDrE8DrRaAXl8LD3Fs1e_xuDHQIssdZ2Mlzcav8m5jHrA0fA64ZaqJV77myldaNlM7-qyQpy4AsJQfvg9iR2MY7qeC5_FnjIgjKIy_lNi9OPMOjGRWXA94CuvC7zC6WeiJmBQCHISl8IOBxf7EdJZlYdtzgae3593TFxbkd6LUwbijAfjax39aAuuCXy3s9C4YgcEP3TwEFGQoTpYu9Pmle-Ae1tHGPgsjxwXkgMm7Cz5mBBdJioglRCj9pssn-1u1blHZM4uL1nK9p1Y6HoFgPUU9xvKQTHjKGdH8d4y4ETyCMoNF4hAIyUaysCKdJKitC8PXoYaWhDqFtSMR4Jys8UPqUV&xkcb=SoDD-_M3JLQfWnQTDh0LbzkdCdPP&xpse=SoBa6_I3JLW9FlWZlB0PbzkdCdPP&sjdu=i6xVERweJM_pVUvgf-MzuaunBTY7G71J5eEX6t4DrDs5EMPQdODrX7Nn-WIPMezoqr5wA_l7Of-3CtoiUawcHw",
+            "sec-ch-ua": '"Google Chrome";v="119", "Chromium";v="119", "Not?A_Brand";v="24"',
+            "sec-ch-ua-mobile": "?0",
+            "sec-ch-ua-platform": '"Windows"',
+            "sec-fetch-dest": "empty",
+            "sec-fetch-mode": "cors",
+            "sec-fetch-site": "same-origin",
+            "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36",
+        }
+
+    @staticmethod
+    def is_remote_job(job: dict) -> bool:
+        """
+        :param job:
+        :return: bool
+        """
+        for taxonomy in job.get("taxonomyAttributes", []):
+            if taxonomy["label"] == "remote" and len(taxonomy["attributes"]) > 0:
+                return True
+        return False

src/jobspy/scrapers/linkedin/__init__.py

@@ -4,33 +4,38 @@ 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 ..utils import count_urgent_words, extract_emails_from_text, get_enum_from_job_type
 from ..exceptions import LinkedInException
 from ...jobs import (
     JobPost,
     Location,
     JobResponse,
     JobType,
-    Compensation,
-    CompensationInterval,
 )
 
 
 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",
@@ -54,117 +59,138 @@ 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 = {
-                params = {
+                "keywords": scraper_input.search_term,
-                    "keywords": scraper_input.search_term,
+                "location": scraper_input.location,
-                    "location": scraper_input.location,
+                "distance": scraper_input.distance,
-                    "distance": scraper_input.distance,
+                "f_WT": 2 if scraper_input.is_remote else None,
-                    "f_WT": 2 if scraper_input.is_remote else None,
+                "f_JT": job_type_code(scraper_input.job_type)
-                    "f_JT": job_type_code(scraper_input.job_type)
+                if scraper_input.job_type
-                    if scraper_input.job_type
+                else None,
-                    else None,
+                "pageNum": 0,
-                    "pageNum": page,
+                page: page + scraper_input.offset,
-                    "f_AL": "true" if scraper_input.easy_apply else None,
+                "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}
+
+            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")
+            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:
+                        href = href_tag.attrs["href"].split("?")[0]
+                        job_id = href.split("-")[-1]
+                        job_url = f"{self.url}/jobs/view/{job_id}"
 
-                for job_card in soup.find_all(
+                    with url_lock:
-                    "div",
+                        if job_url in seen_urls:
-                    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",
+                            continue
-                ):
+                        seen_urls.add(job_url)
-                    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}"
-                    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)
-                    datetime_tag = metadata_card.find(
+                    except Exception as e:
-                        "time", class_="job-search-card__listdate"
+                        raise LinkedInException(
-                    )
+                            "Exception occurred while processing jobs"
-                    description, job_type = self.get_description(job_url)
+                        )
-                    if datetime_tag:
+            page += 25
-                        datetime_str = datetime_tag["datetime"]
-                        try:
-                            date_posted = datetime.strptime(datetime_str, "%Y-%m-%d")
-                        except Exception as e:
-                            date_posted = None
-                    else:
-                        date_posted = None
-
-                    job_post = JobPost(
-                        title=title,
-                        description=description,
-                        company_name=company,
-                        location=location,
-                        date_posted=date_posted,
-                        job_url=job_url,
-                        job_type=job_type,
-                        compensation=Compensation(
-                            interval=CompensationInterval.YEARLY, currency=None
-                        ),
-                    )
-                    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
 
         job_list = job_list[: scraper_input.results_wanted]
         return JobResponse(jobs=job_list)
 
-    def get_description(self, job_page_url: str) -> Optional[str]:
+    def process_job(self, job_card: Tag, job_url: str) -> Optional[JobPost]:
+        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
+        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)
+
+        return JobPost(
+            title=title,
+            description=description,
+            company_name=company,
+            location=location,
+            date_posted=date_posted,
+            job_url=job_url,
+            # job_type=[JobType.FULL_TIME],
+            job_type=job_type,
+            benefits=benefits,
+            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]]:
         """
         Retrieves job description by going to the job page url
         :param job_page_url:
@@ -181,19 +207,19 @@ 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]]:
+        ) -> list[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,
@@ -210,16 +236,9 @@ class LinkedInScraper(Scraper):
                     employment_type = employment_type.lower()
                     employment_type = employment_type.replace("-", "")
 
-            return LinkedInScraper.get_enum_from_value(employment_type)
+            return [get_enum_from_job_type(employment_type)]
 
-        return text_content, get_job_type(soup)
+        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:
         """

src/jobspy/scrapers/utils.py

@@ -0,0 +1,63 @@
+import re
+
+import requests
+import tls_client
+from ..jobs import JobType
+
+
+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 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):
+    """
+    Creates a tls client session
+
+    :return: A session object with or without proxies.
+    """
+    if is_tls:
+        session = tls_client.Session(
+            client_identifier="chrome112",
+            random_tls_extension_order=True,
+        )
+        session.proxies = proxy
+        # TODO multiple proxies
+        # if self.proxies:
+        #     session.proxies = {
+        #         "http": random.choice(self.proxies),
+        #         "https": random.choice(self.proxies),
+        #     }
+    else:
+        session = requests.Session()
+        session.allow_redirects = True
+        session.proxies.update(proxy)
+
+    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

src/jobspy/scrapers/ziprecruiter/__init__.py

@@ -5,30 +5,18 @@ jobspy.scrapers.ziprecruiter
 This module contains routines to scrape ZipRecruiter.
 """
 import math
-import json
+import time
 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
 
-import tls_client
-import requests
 from bs4 import BeautifulSoup
-from bs4.element import Tag
+from concurrent.futures import ThreadPoolExecutor
-from concurrent.futures import ThreadPoolExecutor, Future
 
 from .. import Scraper, ScraperInput, Site
 from ..exceptions import ZipRecruiterException
-from ...jobs import (
+from ..utils import count_urgent_words, extract_emails_from_text, create_session
-    JobPost,
+from ...jobs import JobPost, Compensation, Location, JobResponse, JobType
-    Compensation,
-    CompensationInterval,
-    Location,
-    JobResponse,
-    JobType,
-    Country,
-)
 
 
 class ZipRecruiterScraper(Scraper):
@@ -42,29 +30,24 @@ class ZipRecruiterScraper(Scraper):
 
         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(
+    def find_jobs_in_page(self, scraper_input: ScraperInput, continue_token: str | None = None) -> Tuple[list[JobPost], Optional[str]]:
-        self, scraper_input: ScraperInput, page: int
-    ) -> tuple[list[JobPost], int | None]:
         """
         Scrapes a page of ZipRecruiter for jobs with scraper_input criteria
         :param scraper_input:
-        :param page:
+        :param continue_token:
-        :param session:
+        :return: jobs found on page
-        :return: jobs found on page, total number of jobs found for search
         """
-        job_list: list[JobPost] = []
+        params = self.add_params(scraper_input)
+        if continue_token:
+            params['continue'] = continue_token
         try:
-            response = self.session.get(
+            session = create_session(self.proxy, is_tls=False)
-                self.url + "/jobs-search",
+            response = session.get(
-                headers=ZipRecruiterScraper.headers(),
+                f"https://api.ziprecruiter.com/jobs-app/jobs",
-                params=ZipRecruiterScraper.add_params(scraper_input, page),
+                headers=self.headers(),
-                allow_redirects=True,
+                params=self.add_params(scraper_input),
-                proxy=self.proxy,
+                timeout=10,
-                timeout_seconds=10,
             )
             if response.status_code != 200:
                 raise ZipRecruiterException(
@@ -74,194 +57,66 @@ class ZipRecruiterScraper(Scraper):
             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:
+        time.sleep(5)
-            page_json = json.loads(js_tag.string)
+        response_data = response.json()
-            jobs_list = page_json.get("jobList")
+        jobs_list = response_data.get("jobs", [])
-            if jobs_list:
+        next_continue_token = response_data.get('continue', None)
-                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 open("zip_method_8.html", "w") as f:
-            #     f.write(soup.prettify())
 
-        with ThreadPoolExecutor(max_workers=10) as executor:
+        with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
-            if page_variant == "javascript":
+            job_results = [
-                job_results = [
+                executor.submit(self.process_job, job)
-                    executor.submit(self.process_job_javascript, job)
+                for job in jobs_list
-                    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
+        return job_list, next_continue_token
 
     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:
+        :param scraper_input: Information about job search criteria.
-        :return: job_response
+        :return: JobResponse containing a list of jobs.
         """
-        #: get first page to initialize session
+        job_list: list[JobPost] = []
-        job_list: list[JobPost] = self.find_jobs_in_page(scraper_input, 1)
+        continue_token = None
-        pages_to_process = max(
-            3, math.ceil(scraper_input.results_wanted / self.jobs_per_page)
-        )
 
-        with ThreadPoolExecutor(max_workers=10) as executor:
+        max_pages = math.ceil(scraper_input.results_wanted / self.jobs_per_page)
-            futures: list[Future] = [
-                executor.submit(self.find_jobs_in_page, scraper_input, page)
-                for page in range(2, pages_to_process + 1)
-            ]
 
-            for future in futures:
+        for page in range(1, max_pages + 1):
-                jobs = future.result()
+            if len(job_list) >= scraper_input.results_wanted:
+                break
 
-                job_list += jobs
+            jobs_on_page, continue_token = self.find_jobs_in_page(scraper_input, continue_token)
+            if jobs_on_page:
+                job_list.extend(jobs_on_page)
+
+            if not continue_token:
+                break
+
+        if len(job_list) > scraper_input.results_wanted:
+            job_list = job_list[:scraper_input.results_wanted]
 
-        job_list = job_list[: scraper_input.results_wanted]
         return JobResponse(jobs=job_list)
 
-    def process_job_html_1(self, job: Tag) -> Optional[JobPost]:
+    @staticmethod
-        """
+    def process_job(job: dict) -> JobPost:
-        Parses a job from the job content tag
+        """ Processes an individual job dict from the response """
-        :param job: BeautifulSoup Tag for one job post
+        title = job.get("name")
-        :return JobPost
+        job_url = job.get("job_url")
-        """
-        job_url = job.find("a", {"class": "job_link"})["href"]
-        if job_url in self.seen_urls:
-            return None
 
-        title = job.find("h2", {"class": "title"}).text
+        description = BeautifulSoup(
-        company = job.find("a", {"class": "company_name"}).text.strip()
+            job.get("job_description", "").strip(), "html.parser"
+        ).get_text()
 
-        description, updated_job_url = self.get_description(job_url)
+        company = job['hiring_company'].get("name") if "hiring_company" in job else None
-        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,
-        )
-        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 = 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 = 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='usa' if job.get("job_country") == 'US' else 'canada'
         )
         job_type = ZipRecruiterScraper.get_job_type_enum(
-            job.get("EmploymentType", "").replace("-", "").lower()
+            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
@@ -272,62 +127,37 @@ class ZipRecruiterScraper(Scraper):
             date_posted = date_posted_obj.date()
         else:
             date_posted = date.today()
-        job_url = job.get("JobURL")
 
         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
 
     @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) -> Optional[str]:
+    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
@@ -352,107 +182,6 @@ class ZipRecruiterScraper(Scraper):
 
         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: BeautifulSoup) -> 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: BeautifulSoup) -> 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: BeautifulSoup) -> 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:
         """
@@ -460,5 +189,13 @@ class ZipRecruiterScraper(Scraper):
         :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"
+            'Host': 'api.ziprecruiter.com',
+            'Cookie': 'ziprecruiter_browser=018188e0-045b-4ad7-aa50-627a6c3d43aa; ziprecruiter_session=5259b2219bf95b6d2299a1417424bc2edc9f4b38; SplitSV=2016-10-19%3AU2FsdGVkX19f9%2Bx70knxc%2FeR3xXR8lWoTcYfq5QjmLU%3D%0A; __cf_bm=qXim3DtLPbOL83GIp.ddQEOFVFTc1OBGPckiHYxcz3o-1698521532-0-AfUOCkgCZyVbiW1ziUwyefCfzNrJJTTKPYnif1FZGQkT60dMowmSU/Y/lP+WiygkFPW/KbYJmyc+MQSkkad5YygYaARflaRj51abnD+SyF9V; zglobalid=68d49bd5-0326-428e-aba8-8a04b64bc67c.af2d99ff7c03.653d61bb; ziprecruiter_browser=018188e0-045b-4ad7-aa50-627a6c3d43aa; ziprecruiter_session=5259b2219bf95b6d2299a1417424bc2edc9f4b38',
+            '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'
         }

src/tests/test_all.py

@@ -1,4 +1,5 @@
 from ..jobspy import scrape_jobs
+import pandas as pd
 
 
 def test_all():
@@ -7,4 +8,7 @@ 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 +7,6 @@ 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 +7,6 @@ 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 +8,6 @@ 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"