Easy apply (#95 )

* enh(glassdoor): easy apply filter * enh(ziprecruiter): easy apply * enh(indeed): use mobile headers * chore: version
enh(glassdoor): easy apply filter (#92 )
2026-03-05 03:54:31 -08:00 · 2024-02-02 17:47:15 -06:00 · 2024-02-01 19:42:24 -06:00 · 2024-01-28 21:50:41 -06:00 · 2024-01-22 20:22:32 -06:00 · 2024-01-12 12:28:35 -06:00
23 changed files with 1762 additions and 1477 deletions
--- a/.github/workflows/publish-to-pypi.yml
+++ b/.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 }}
--- a/.gitignore
+++ b/.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/
--- a/JobSpy_Demo.ipynb
+++ b/JobSpy_Demo.ipynb
@@ -1,689 +0,0 @@
 {
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "00a94b47-f47b-420f-ba7e-714ef219c006",
   "metadata": {},
   "outputs": [],
   "source": [
    "from jobspy import scrape_jobs\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9f773e6c-d9fc-42cc-b0ef-63b739e78435",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.max_rows', None)\n",
    "pd.set_option('display.width', None)\n",
    "pd.set_option('display.max_colwidth', 50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1253c1f8-9437-492e-9dd3-e7fe51099420",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>site</th>\n",
       "      <th>title</th>\n",
       "      <th>company_name</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>job_type</th>\n",
       "      <th>interval</th>\n",
       "      <th>min_amount</th>\n",
       "      <th>max_amount</th>\n",
       "      <th>job_url</th>\n",
       "      <th>description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>indeed</td>\n",
       "      <td>Mental Health Therapist</td>\n",
       "      <td>Sandstone Care</td>\n",
       "      <td>Broomfield</td>\n",
       "      <td>CO</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>68000</td>\n",
       "      <td>57500</td>\n",
       "      <td>https://www.indeed.com/viewjob?jk=f5f33d72e030...</td>\n",
       "      <td>Mental Health Therapist- Broomfield, CO Locati...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>indeed</td>\n",
       "      <td>.NET Developer</td>\n",
       "      <td>Noir Consulting</td>\n",
       "      <td>Irving</td>\n",
       "      <td>TX</td>\n",
       "      <td>None</td>\n",
       "      <td>yearly</td>\n",
       "      <td>200000</td>\n",
       "      <td>200000</td>\n",
       "      <td>https://www.indeed.com/viewjob?jk=1b22ba65296c...</td>\n",
       "      <td>.NET Software Engineer, C#, WPF - Irving (Tech...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>indeed</td>\n",
       "      <td>Senior Software Engineer</td>\n",
       "      <td>Johns Hopkins Applied Physics Laboratory (APL)</td>\n",
       "      <td>Laurel</td>\n",
       "      <td>MD</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>https://www.indeed.com/viewjob?jk=309eed270a88...</td>\n",
       "      <td>Description Are you a communications systems d...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>indeed</td>\n",
       "      <td>Front End Developer</td>\n",
       "      <td>Verkada</td>\n",
       "      <td>San Mateo</td>\n",
       "      <td>CA</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>285000</td>\n",
       "      <td>120000</td>\n",
       "      <td>https://www.indeed.com/viewjob?jk=a3ea45daca75...</td>\n",
       "      <td>Who We Are Verkada is the largest cloud-based ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>indeed</td>\n",
       "      <td>Software Engineer</td>\n",
       "      <td>Adobe</td>\n",
       "      <td>San Jose</td>\n",
       "      <td>CA</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>142700</td>\n",
       "      <td>73200</td>\n",
       "      <td>https://www.indeed.com/viewjob?jk=0f2dc9901fc7...</td>\n",
       "      <td>Our Company Changing the world through digital...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>indeed</td>\n",
       "      <td>Full Stack Developer</td>\n",
       "      <td>Comcast</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>PA</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>184663</td>\n",
       "      <td>78789</td>\n",
       "      <td>https://www.indeed.com/viewjob?jk=eb5c927221eb...</td>\n",
       "      <td>Make your mark at Comcast - a Fortune 30 globa...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>indeed</td>\n",
       "      <td>Senior Software Engineer</td>\n",
       "      <td>Smart City Solutions</td>\n",
       "      <td></td>\n",
       "      <td>FL</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>100000</td>\n",
       "      <td>85000</td>\n",
       "      <td>https://www.indeed.com/viewjob?jk=ba1945f143a1...</td>\n",
       "      <td>Smart City hiring a full stack software develo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>indeed</td>\n",
       "      <td>Computer Engineer</td>\n",
       "      <td>Honeywell</td>\n",
       "      <td></td>\n",
       "      <td>None</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>https://www.indeed.com/viewjob?jk=5a1da623ee75...</td>\n",
       "      <td>Join a team recognized for leadership, innovat...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>indeed</td>\n",
       "      <td>Software Engineer</td>\n",
       "      <td>Fidelity Investments</td>\n",
       "      <td>Westlake</td>\n",
       "      <td>TX</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>https://www.indeed.com/viewjob?jk=b600392166bb...</td>\n",
       "      <td>Job Description: Software Engineer in Test The...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>indeed</td>\n",
       "      <td>Fpga Engineer</td>\n",
       "      <td>R-DEX Systems, Inc.</td>\n",
       "      <td>Atlanta</td>\n",
       "      <td>GA</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>160000</td>\n",
       "      <td>120000</td>\n",
       "      <td>https://www.indeed.com/viewjob?jk=a7e9d356c333...</td>\n",
       "      <td>Title: Senior DSP/FPGA Firmware Engineer Descr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>linkedin</td>\n",
       "      <td>Software Engineer</td>\n",
       "      <td>Fieldguide</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>https://www.linkedin.com/jobs/view/3696158160</td>\n",
       "      <td>About us:Fieldguide is establishing a new stat...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>linkedin</td>\n",
       "      <td>Software Engineer - Early Career</td>\n",
       "      <td>Lockheed Martin</td>\n",
       "      <td>Sunnyvale</td>\n",
       "      <td>CA</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>https://www.linkedin.com/jobs/view/3693012711</td>\n",
       "      <td>Description:By bringing together people that u...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>linkedin</td>\n",
       "      <td>Software Engineer - Early Career</td>\n",
       "      <td>Lockheed Martin</td>\n",
       "      <td>Edwards</td>\n",
       "      <td>CA</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>https://www.linkedin.com/jobs/view/3700669785</td>\n",
       "      <td>Description:By bringing together people that u...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>linkedin</td>\n",
       "      <td>Software Engineer - Early Career</td>\n",
       "      <td>Lockheed Martin</td>\n",
       "      <td>Fort Worth</td>\n",
       "      <td>TX</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>https://www.linkedin.com/jobs/view/3701770659</td>\n",
       "      <td>Description:By bringing together people that u...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>linkedin</td>\n",
       "      <td>Software Engineer - Early Career</td>\n",
       "      <td>Lockheed Martin</td>\n",
       "      <td>Fort Worth</td>\n",
       "      <td>TX</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>https://www.linkedin.com/jobs/view/3701769637</td>\n",
       "      <td>Description:By bringing together people that u...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>linkedin</td>\n",
       "      <td>Software Engineer - Early Career</td>\n",
       "      <td>Lockheed Martin</td>\n",
       "      <td>Fort Worth</td>\n",
       "      <td>TX</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>https://www.linkedin.com/jobs/view/3701772329</td>\n",
       "      <td>Description:By bringing together people that u...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>linkedin</td>\n",
       "      <td>Software Engineer - Early Career</td>\n",
       "      <td>Lockheed Martin</td>\n",
       "      <td>Fort Worth</td>\n",
       "      <td>TX</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>https://www.linkedin.com/jobs/view/3701775201</td>\n",
       "      <td>Description:By bringing together people that u...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>linkedin</td>\n",
       "      <td>Software Engineer</td>\n",
       "      <td>SpiderOak</td>\n",
       "      <td>Austin</td>\n",
       "      <td>TX</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>https://www.linkedin.com/jobs/view/3707174719</td>\n",
       "      <td>We're only as strong as our weakest link.In th...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>linkedin</td>\n",
       "      <td>Full-Stack Software Engineer</td>\n",
       "      <td>Rain</td>\n",
       "      <td>New York</td>\n",
       "      <td>NY</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>https://www.linkedin.com/jobs/view/3696158877</td>\n",
       "      <td>Rain’s mission is to create the fastest and ea...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>linkedin</td>\n",
       "      <td>Software Engineer</td>\n",
       "      <td>Nike</td>\n",
       "      <td>Portland</td>\n",
       "      <td>OR</td>\n",
       "      <td>contract</td>\n",
       "      <td>yearly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>https://www.linkedin.com/jobs/view/3693340247</td>\n",
       "      <td>Work options: FlexibleWe consider remote, on-p...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>zip_recruiter</td>\n",
       "      <td>Software Engineer - New Grad</td>\n",
       "      <td>ZipRecruiter</td>\n",
       "      <td>Santa Monica</td>\n",
       "      <td>CA</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>130000</td>\n",
       "      <td>150000</td>\n",
       "      <td>https://www.ziprecruiter.com/c/ZipRecruiter/Jo...</td>\n",
       "      <td>Demonstrated foundation in software engineerin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>zip_recruiter</td>\n",
       "      <td>Full Stack Software Engineer</td>\n",
       "      <td>ZipRecruiter</td>\n",
       "      <td>Phoenix</td>\n",
       "      <td>AZ</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>105000</td>\n",
       "      <td>145000</td>\n",
       "      <td>https://www.ziprecruiter.com/c/ZipRecruiter/Jo...</td>\n",
       "      <td>Experience in client side development using Re...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>zip_recruiter</td>\n",
       "      <td>Software Developer | Onsite | Omaha, NE - Omaha</td>\n",
       "      <td>OneStaff Medical</td>\n",
       "      <td>Omaha</td>\n",
       "      <td>NE</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>60000</td>\n",
       "      <td>110000</td>\n",
       "      <td>https://www.ziprecruiter.com/c/OneStaff-Medica...</td>\n",
       "      <td>We are looking for a well-rounded Software Dev...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>zip_recruiter</td>\n",
       "      <td>Senior Software Engineer, Onsite [Real-time]</td>\n",
       "      <td>Raytheon</td>\n",
       "      <td>McKinney</td>\n",
       "      <td>TX</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>116000</td>\n",
       "      <td>153000</td>\n",
       "      <td>https://jsv3.recruitics.com/redirect?rx_cid=34...</td>\n",
       "      <td>By joining the Silent Knight team as a Senior ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>zip_recruiter</td>\n",
       "      <td>Senior Software Engineer - TS/SCI **Minimum $2...</td>\n",
       "      <td>Raytheon</td>\n",
       "      <td>Dallas</td>\n",
       "      <td>TX</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>122000</td>\n",
       "      <td>162000</td>\n",
       "      <td>https://jsv3.recruitics.com/redirect?rx_cid=34...</td>\n",
       "      <td>Object Oriented Programming using C++ with Lin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>zip_recruiter</td>\n",
       "      <td>Software Engineer III (full stack, AI/ML, Djan...</td>\n",
       "      <td>Ayahealthcare</td>\n",
       "      <td>Remote</td>\n",
       "      <td>OR</td>\n",
       "      <td>None</td>\n",
       "      <td>yearly</td>\n",
       "      <td>156000</td>\n",
       "      <td>165000</td>\n",
       "      <td>https://click.appcast.io/track/hcbh0qq?cs=ngp&amp;...</td>\n",
       "      <td>The Software Engineer III will be an integral ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>zip_recruiter</td>\n",
       "      <td>Software Engineer Full Stack</td>\n",
       "      <td>Generac Power Systems</td>\n",
       "      <td>Denver</td>\n",
       "      <td>CO</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>90000</td>\n",
       "      <td>115000</td>\n",
       "      <td>https://www.ziprecruiter.com/c/Generac-Power-S...</td>\n",
       "      <td>As a Software Engineer on the Energy Technolog...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>zip_recruiter</td>\n",
       "      <td>Embedded Software Engineer (Fort Worth, TX or ...</td>\n",
       "      <td>Kubota</td>\n",
       "      <td>Fort Worth</td>\n",
       "      <td>TX</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>122000</td>\n",
       "      <td>167000</td>\n",
       "      <td>https://us62e2.dayforcehcm.com/CandidatePortal...</td>\n",
       "      <td>Work with a cross-functional team to design, t...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>zip_recruiter</td>\n",
       "      <td>Senior Software Engineer (FT)</td>\n",
       "      <td>National Indoor RV Center</td>\n",
       "      <td>Lewisville</td>\n",
       "      <td>TX</td>\n",
       "      <td>fulltime</td>\n",
       "      <td>yearly</td>\n",
       "      <td>125000</td>\n",
       "      <td>0</td>\n",
       "      <td>https://www.ziprecruiter.com/c/National-Indoor...</td>\n",
       "      <td>As a Senior Software Engineer, you will: * Des...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>zip_recruiter</td>\n",
       "      <td>2024 Next Gen IT Program | Software Engineerin...</td>\n",
       "      <td>Southern Glazer's Wine &amp; Spirits</td>\n",
       "      <td>Dallas</td>\n",
       "      <td>TX</td>\n",
       "      <td>None</td>\n",
       "      <td>yearly</td>\n",
       "      <td>70000</td>\n",
       "      <td>0</td>\n",
       "      <td>https://click.appcast.io/track/hdsbnae?cs=b4&amp;j...</td>\n",
       "      <td>Finally, through the work assigned, the analys...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             site                                              title  \\\n",
       "0          indeed                            Mental Health Therapist   \n",
       "1          indeed                                     .NET Developer   \n",
       "2          indeed                           Senior Software Engineer   \n",
       "3          indeed                                Front End Developer   \n",
       "4          indeed                                  Software Engineer   \n",
       "5          indeed                               Full Stack Developer   \n",
       "6          indeed                           Senior Software Engineer   \n",
       "7          indeed                                  Computer Engineer   \n",
       "8          indeed                                  Software Engineer   \n",
       "9          indeed                                      Fpga Engineer   \n",
       "10       linkedin                                  Software Engineer   \n",
       "11       linkedin                   Software Engineer - Early Career   \n",
       "12       linkedin                   Software Engineer - Early Career   \n",
       "13       linkedin                   Software Engineer - Early Career   \n",
       "14       linkedin                   Software Engineer - Early Career   \n",
       "15       linkedin                   Software Engineer - Early Career   \n",
       "16       linkedin                   Software Engineer - Early Career   \n",
       "17       linkedin                                  Software Engineer   \n",
       "18       linkedin                       Full-Stack Software Engineer   \n",
       "19       linkedin                                  Software Engineer   \n",
       "20  zip_recruiter                       Software Engineer - New Grad   \n",
       "21  zip_recruiter                       Full Stack Software Engineer   \n",
       "22  zip_recruiter    Software Developer | Onsite | Omaha, NE - Omaha   \n",
       "23  zip_recruiter       Senior Software Engineer, Onsite [Real-time]   \n",
       "24  zip_recruiter  Senior Software Engineer - TS/SCI **Minimum $2...   \n",
       "25  zip_recruiter  Software Engineer III (full stack, AI/ML, Djan...   \n",
       "26  zip_recruiter                       Software Engineer Full Stack   \n",
       "27  zip_recruiter  Embedded Software Engineer (Fort Worth, TX or ...   \n",
       "28  zip_recruiter                      Senior Software Engineer (FT)   \n",
       "29  zip_recruiter  2024 Next Gen IT Program | Software Engineerin...   \n",
       "\n",
       "                                      company_name           city state  \\\n",
       "0                                   Sandstone Care     Broomfield    CO   \n",
       "1                                  Noir Consulting         Irving    TX   \n",
       "2   Johns Hopkins Applied Physics Laboratory (APL)         Laurel    MD   \n",
       "3                                          Verkada      San Mateo    CA   \n",
       "4                                            Adobe       San Jose    CA   \n",
       "5                                          Comcast   Philadelphia    PA   \n",
       "6                             Smart City Solutions                   FL   \n",
       "7                                        Honeywell                 None   \n",
       "8                             Fidelity Investments       Westlake    TX   \n",
       "9                              R-DEX Systems, Inc.        Atlanta    GA   \n",
       "10                                      Fieldguide  San Francisco    CA   \n",
       "11                                 Lockheed Martin      Sunnyvale    CA   \n",
       "12                                 Lockheed Martin        Edwards    CA   \n",
       "13                                 Lockheed Martin     Fort Worth    TX   \n",
       "14                                 Lockheed Martin     Fort Worth    TX   \n",
       "15                                 Lockheed Martin     Fort Worth    TX   \n",
       "16                                 Lockheed Martin     Fort Worth    TX   \n",
       "17                                       SpiderOak         Austin    TX   \n",
       "18                                            Rain       New York    NY   \n",
       "19                                            Nike       Portland    OR   \n",
       "20                                    ZipRecruiter   Santa Monica    CA   \n",
       "21                                    ZipRecruiter        Phoenix    AZ   \n",
       "22                                OneStaff Medical          Omaha    NE   \n",
       "23                                        Raytheon       McKinney    TX   \n",
       "24                                        Raytheon         Dallas    TX   \n",
       "25                                   Ayahealthcare         Remote    OR   \n",
       "26                           Generac Power Systems         Denver    CO   \n",
       "27                                          Kubota     Fort Worth    TX   \n",
       "28                       National Indoor RV Center     Lewisville    TX   \n",
       "29                Southern Glazer's Wine & Spirits         Dallas    TX   \n",
       "\n",
       "    job_type interval min_amount max_amount  \\\n",
       "0   fulltime   yearly      68000      57500   \n",
       "1       None   yearly     200000     200000   \n",
       "2       None     None       None       None   \n",
       "3   fulltime   yearly     285000     120000   \n",
       "4   fulltime   yearly     142700      73200   \n",
       "5   fulltime   yearly     184663      78789   \n",
       "6   fulltime   yearly     100000      85000   \n",
       "7   fulltime     None       None       None   \n",
       "8       None     None       None       None   \n",
       "9   fulltime   yearly     160000     120000   \n",
       "10  fulltime   yearly       None       None   \n",
       "11  fulltime   yearly       None       None   \n",
       "12  fulltime   yearly       None       None   \n",
       "13  fulltime   yearly       None       None   \n",
       "14  fulltime   yearly       None       None   \n",
       "15  fulltime   yearly       None       None   \n",
       "16  fulltime   yearly       None       None   \n",
       "17  fulltime   yearly       None       None   \n",
       "18  fulltime   yearly       None       None   \n",
       "19  contract   yearly       None       None   \n",
       "20  fulltime   yearly     130000     150000   \n",
       "21  fulltime   yearly     105000     145000   \n",
       "22  fulltime   yearly      60000     110000   \n",
       "23  fulltime   yearly     116000     153000   \n",
       "24  fulltime   yearly     122000     162000   \n",
       "25      None   yearly     156000     165000   \n",
       "26  fulltime   yearly      90000     115000   \n",
       "27  fulltime   yearly     122000     167000   \n",
       "28  fulltime   yearly     125000          0   \n",
       "29      None   yearly      70000          0   \n",
       "\n",
       "                                              job_url  \\\n",
       "0   https://www.indeed.com/viewjob?jk=f5f33d72e030...   \n",
       "1   https://www.indeed.com/viewjob?jk=1b22ba65296c...   \n",
       "2   https://www.indeed.com/viewjob?jk=309eed270a88...   \n",
       "3   https://www.indeed.com/viewjob?jk=a3ea45daca75...   \n",
       "4   https://www.indeed.com/viewjob?jk=0f2dc9901fc7...   \n",
       "5   https://www.indeed.com/viewjob?jk=eb5c927221eb...   \n",
       "6   https://www.indeed.com/viewjob?jk=ba1945f143a1...   \n",
       "7   https://www.indeed.com/viewjob?jk=5a1da623ee75...   \n",
       "8   https://www.indeed.com/viewjob?jk=b600392166bb...   \n",
       "9   https://www.indeed.com/viewjob?jk=a7e9d356c333...   \n",
       "10      https://www.linkedin.com/jobs/view/3696158160   \n",
       "11      https://www.linkedin.com/jobs/view/3693012711   \n",
       "12      https://www.linkedin.com/jobs/view/3700669785   \n",
       "13      https://www.linkedin.com/jobs/view/3701770659   \n",
       "14      https://www.linkedin.com/jobs/view/3701769637   \n",
       "15      https://www.linkedin.com/jobs/view/3701772329   \n",
       "16      https://www.linkedin.com/jobs/view/3701775201   \n",
       "17      https://www.linkedin.com/jobs/view/3707174719   \n",
       "18      https://www.linkedin.com/jobs/view/3696158877   \n",
       "19      https://www.linkedin.com/jobs/view/3693340247   \n",
       "20  https://www.ziprecruiter.com/c/ZipRecruiter/Jo...   \n",
       "21  https://www.ziprecruiter.com/c/ZipRecruiter/Jo...   \n",
       "22  https://www.ziprecruiter.com/c/OneStaff-Medica...   \n",
       "23  https://jsv3.recruitics.com/redirect?rx_cid=34...   \n",
       "24  https://jsv3.recruitics.com/redirect?rx_cid=34...   \n",
       "25  https://click.appcast.io/track/hcbh0qq?cs=ngp&...   \n",
       "26  https://www.ziprecruiter.com/c/Generac-Power-S...   \n",
       "27  https://us62e2.dayforcehcm.com/CandidatePortal...   \n",
       "28  https://www.ziprecruiter.com/c/National-Indoor...   \n",
       "29  https://click.appcast.io/track/hdsbnae?cs=b4&j...   \n",
       "\n",
       "                                          description  \n",
       "0   Mental Health Therapist- Broomfield, CO Locati...  \n",
       "1   .NET Software Engineer, C#, WPF - Irving (Tech...  \n",
       "2   Description Are you a communications systems d...  \n",
       "3   Who We Are Verkada is the largest cloud-based ...  \n",
       "4   Our Company Changing the world through digital...  \n",
       "5   Make your mark at Comcast - a Fortune 30 globa...  \n",
       "6   Smart City hiring a full stack software develo...  \n",
       "7   Join a team recognized for leadership, innovat...  \n",
       "8   Job Description: Software Engineer in Test The...  \n",
       "9   Title: Senior DSP/FPGA Firmware Engineer Descr...  \n",
       "10  About us:Fieldguide is establishing a new stat...  \n",
       "11  Description:By bringing together people that u...  \n",
       "12  Description:By bringing together people that u...  \n",
       "13  Description:By bringing together people that u...  \n",
       "14  Description:By bringing together people that u...  \n",
       "15  Description:By bringing together people that u...  \n",
       "16  Description:By bringing together people that u...  \n",
       "17  We're only as strong as our weakest link.In th...  \n",
       "18  Rain’s mission is to create the fastest and ea...  \n",
       "19  Work options: FlexibleWe consider remote, on-p...  \n",
       "20  Demonstrated foundation in software engineerin...  \n",
       "21  Experience in client side development using Re...  \n",
       "22  We are looking for a well-rounded Software Dev...  \n",
       "23  By joining the Silent Knight team as a Senior ...  \n",
       "24  Object Oriented Programming using C++ with Lin...  \n",
       "25  The Software Engineer III will be an integral ...  \n",
       "26  As a Software Engineer on the Energy Technolog...  \n",
       "27  Work with a cross-functional team to design, t...  \n",
       "28  As a Senior Software Engineer, you will: * Des...  \n",
       "29  Finally, through the work assigned, the analys...  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scrape_jobs(\n",
    "    site_name=[\"indeed\", \"linkedin\", \"zip_recruiter\"],\n",
    "    search_term=\"software engineer\",\n",
    "    results_wanted=10\n",
    ")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
 }
--- a/README.md
+++ b/README.md
@@ -1,48 +1,50 @@
-# <img src="https://github.com/cullenwatson/JobSpy/assets/78247585/2f61a059-9647-4a9c-bfb9-e3a9448bdc6a" style="vertical-align: sub; margin-right: 5px;"> JobSpy
+<img src="https://github.com/cullenwatson/JobSpy/assets/78247585/ae185b7e-e444-4712-8bb9-fa97f53e896b" width="400">
 **JobSpy** is a simple, yet comprehensive, job scraping library.
 **Not technical?** Try out the web scraping tool on our site at [usejobspy.com](https://usejobspy.com).
 *Looking to build a data-focused software product?* **[Book a call](https://bunsly.com/)** *to
 work with us.*
 ## Features
- Scrapes job postings from **LinkedIn**, **Indeed** & **ZipRecruiter** simultaneously
+- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, & **ZipRecruiter** simultaneously
 - Aggregates the job postings in a Pandas DataFrame
-  
+- Proxy support (HTTP/S, SOCKS)
 [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_ 
+pip install python-jobspy
 ```
 _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"],
+    site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"],
    search_term="software engineer",
-    results_wanted=10
+    location="Dallas, TX",
    results_wanted=10,
    country_indeed='USA'  # only needed for indeed / glassdoor
 )
-
+print(f"Found {len(jobs)} jobs")
-if jobs.empty:
+print(jobs.head())
-    print("No jobs found.")
+jobs.to_csv("jobs.csv", index=False) # to_xlsx
 else:
    #1 print
    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
    print(jobs)
    #2 display in Jupyter Notebook
    #display(jobs)
    #3 output to .csv
    #jobs.to_csv('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!...
@@ -52,58 +54,120 @@ 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
+├── site_type (List[enum]): linkedin, zip_recruiter, indeed, glassdoor
 └── search_term (str)
 Optional
 ├── location (int)
 ├── distance (int): in miles
 ├── job_type (enum): fulltime, parttime, internship, contract
 ├── proxy (str): in format 'http://user:pass@host:port' or [https, socks]
 ├── is_remote (bool)
 ├── full_description (bool): fetches full description for Indeed / LinkedIn (much slower)
 ├── results_wanted (int): number of job results to retrieve for each site specified in 'site_type'
-├── easy_apply (bool): filters for jobs on LinkedIn that have the 'Easy Apply' option
+├── easy_apply (bool): filters for jobs that are hosted on the job board site
 ├── 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)
-├── company_name (str)
+├── company (str)
 ├── job_url (str)
 ├── location (object)
 │   ├── country (str)
 │   ├── city (str)
 │   ├── state (str)
 ├── description (str)
-├── job_type (enum)
+├── job_type (str): fulltime, parttime, internship, contract
 ├── compensation (object)
-│   ├── interval (CompensationInterval): yearly, monthly, weekly, daily, hourly
+│   ├── interval (str): yearly, monthly, weekly, daily, hourly
-│   ├── min_amount (float)
+│   ├── min_amount (int)
-│   ├── max_amount (float)
+│   ├── max_amount (int)
-│   └── currency (str)
+│   └── currency (enum)
-└── date_posted (datetime)
+└── 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`
 * `GlassdoorException`
 ## Supported Countries for Job Searching
 ### **LinkedIn**
 LinkedIn searches globally & uses only the `location` parameter. You can only fetch 1000 jobs max from the LinkedIn endpoint we're using
 ### **ZipRecruiter**
 ZipRecruiter searches for jobs in **US/Canada** & uses only the `location` parameter.
 ### **Indeed / Glassdoor**
 Indeed & Glassdoor supports most countries, but the `country_indeed` parameter is required. Additionally, use the `location`
 parameter to narrow down the location, e.g. city & state if necessary. 
 You can specify the following countries when searching on Indeed (use the exact name, * indicates support for Glassdoor):
 |                      |              |            |                |
 |----------------------|--------------|------------|----------------|
 | Argentina            | Australia*   | Austria*   | Bahrain        |
 | Belgium*             | Brazil*      | Canada*    | Chile          |
 | China                | Colombia     | Costa Rica | Czech Republic |
 | Denmark              | Ecuador      | Egypt      | Finland        |
 | France*              | Germany*     | Greece     | Hong Kong*     |
 | Hungary              | India*       | Indonesia  | Ireland*       |
 | Israel               | Italy*       | Japan      | Kuwait         |
 | Luxembourg           | Malaysia     | Mexico*    | Morocco        |
 | Netherlands*         | New Zealand* | Nigeria    | Norway         |
 | Oman                 | Pakistan     | Panama     | Peru           |
 | Philippines          | Poland       | Portugal   | Qatar          |
 | Romania              | Saudi Arabia | Singapore* | South Africa   |
 | South Korea          | Spain*       | Sweden     | Switzerland*   |
 | Taiwan               | Thailand     | Turkey     | Ukraine        |
 | United Arab Emirates | UK*          | USA*       | Uruguay        |
 | Venezuela            | Vietnam      |            |                |
 Glassdoor can only fetch 900 jobs from the endpoint we're using on a given search.
 ## Frequently Asked Questions
 ---
 **Q: Encountering issues with your queries?**  
-**A:** Try reducing the number of `results_wanted` and/or broadening the filters. If problems persist, [submit an issue](#).
+**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
--- a/examples/JobSpy_AllSites.py
+++ b/examples/JobSpy_AllSites.py
@@ -0,0 +1,30 @@
 from jobspy import scrape_jobs
 import pandas as pd
 jobs: pd.DataFrame = scrape_jobs(
    site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"],
    search_term="software engineer",
    location="Dallas, TX",
    results_wanted=25,  # be wary the higher it is, the more likey you'll get blocked (rotating proxy can help tho)
    country_indeed="USA",
    # proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
 )
 # formatting for pandas
 pd.set_option("display.max_columns", None)
 pd.set_option("display.max_rows", None)
 pd.set_option("display.width", None)
 pd.set_option("display.max_colwidth", 50)  # set to 0 to see full job url / desc
 # 1: output to console
 print(jobs)
 # 2: output to .csv
 jobs.to_csv("./jobs.csv", index=False)
 print("outputted to jobs.csv")
 # 3: output to .xlsx
 # jobs.to_xlsx('jobs.xlsx', index=False)
 # 4: display in Jupyter Notebook (1. pip install jupyter 2. jupyter notebook)
 # display(jobs)
--- a/examples/JobSpy_Demo.ipynb
+++ b/examples/JobSpy_Demo.ipynb
@@ -0,0 +1,167 @@
 {
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "00a94b47-f47b-420f-ba7e-714ef219c006",
   "metadata": {},
   "outputs": [],
   "source": [
    "from jobspy import scrape_jobs\n",
    "import pandas as pd\n",
    "from IPython.display import display, HTML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9f773e6c-d9fc-42cc-b0ef-63b739e78435",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.max_rows', None)\n",
    "pd.set_option('display.width', None)\n",
    "pd.set_option('display.max_colwidth', 50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1253c1f8-9437-492e-9dd3-e7fe51099420",
   "metadata": {},
   "outputs": [],
   "source": [
    "# example 1 (no hyperlinks, USA)\n",
    "jobs = scrape_jobs(\n",
    "    site_name=[\"linkedin\"],\n",
    "    location='san francisco',\n",
    "    search_term=\"engineer\",\n",
    "    results_wanted=5,\n",
    "\n",
    "    # use if you want to use a proxy\n",
    "    # proxy=\"socks5://jobspy:5a4vpWtj4EeJ2hoYzk@us.smartproxy.com:10001\",\n",
    "    proxy=\"http://jobspy:5a4vpWtj4EeJ2hoYzk@us.smartproxy.com:10001\",\n",
    "    #proxy=\"https://jobspy:5a4vpWtj4EeJ2hoYzk@us.smartproxy.com:10001\",\n",
    ")\n",
    "display(jobs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6a581b2d-f7da-4fac-868d-9efe143ee20a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# example 2 - remote USA & hyperlinks\n",
    "jobs = scrape_jobs(\n",
    "    site_name=[\"linkedin\", \"zip_recruiter\", \"indeed\"],\n",
    "    # location='san francisco',\n",
    "    search_term=\"software engineer\",\n",
    "    country_indeed=\"USA\",\n",
    "    hyperlinks=True,\n",
    "    is_remote=True,\n",
    "    results_wanted=5, \n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe8289bc-5b64-4202-9a64-7c117c83fd9a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# use if hyperlinks=True\n",
    "html = jobs.to_html(escape=False)\n",
    "# change max-width: 200px to show more or less of the content\n",
    "truncate_width = f'<style>.dataframe td {{ max-width: 200px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }}</style>{html}'\n",
    "display(HTML(truncate_width))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "951c2fe1-52ff-407d-8bb1-068049b36777",
   "metadata": {},
   "outputs": [],
   "source": [
    "# example 3 - with hyperlinks, international - linkedin (no zip_recruiter)\n",
    "jobs = scrape_jobs(\n",
    "    site_name=[\"linkedin\"],\n",
    "    location='berlin',\n",
    "    search_term=\"engineer\",\n",
    "    hyperlinks=True,\n",
    "    results_wanted=5,\n",
    "    easy_apply=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1e37a521-caef-441c-8fc2-2eb5b2e7da62",
   "metadata": {},
   "outputs": [],
   "source": [
    "# use if hyperlinks=True\n",
    "html = jobs.to_html(escape=False)\n",
    "# change max-width: 200px to show more or less of the content\n",
    "truncate_width = f'<style>.dataframe td {{ max-width: 200px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }}</style>{html}'\n",
    "display(HTML(truncate_width))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0650e608-0b58-4bf5-ae86-68348035b16a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# example 4 - international indeed (no zip_recruiter)\n",
    "jobs = scrape_jobs(\n",
    "    site_name=[\"indeed\"],\n",
    "    search_term=\"engineer\",\n",
    "    country_indeed = \"China\",\n",
    "    hyperlinks=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "40913ac8-3f8a-4d7e-ac47-afb88316432b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# use if hyperlinks=True\n",
    "html = jobs.to_html(escape=False)\n",
    "# change max-width: 200px to show more or less of the content\n",
    "truncate_width = f'<style>.dataframe td {{ max-width: 200px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }}</style>{html}'\n",
    "display(HTML(truncate_width))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
 }
--- a/examples/JobSpy_LongScrape.py
+++ b/examples/JobSpy_LongScrape.py
@@ -0,0 +1,77 @@
 from jobspy import scrape_jobs
 import pandas as pd
 import os
 import time
 # creates csv a new filename if the jobs.csv already exists.
 csv_filename = "jobs.csv"
 counter = 1
 while os.path.exists(csv_filename):
    csv_filename = f"jobs_{counter}.csv"
    counter += 1
 # results wanted and offset
 results_wanted = 1000
 offset = 0
 all_jobs = []
 # max retries
 max_retries = 3
 # nuumber of results at each iteration
 results_in_each_iteration = 30
 while len(all_jobs) < results_wanted:
    retry_count = 0
    while retry_count < max_retries:
        print("Doing from", offset, "to", offset + results_in_each_iteration, "jobs")
        try:
            jobs = scrape_jobs(
                site_name=["indeed"],
                search_term="software engineer",
                # New York, NY
                # Dallas, TX
                # Los Angeles, CA
                location="Los Angeles, CA",
                results_wanted=min(results_in_each_iteration, results_wanted - len(all_jobs)),
                country_indeed="USA",
                offset=offset,
                # proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
            )
            # Add the scraped jobs to the list
            all_jobs.extend(jobs.to_dict('records'))
            # Increment the offset for the next page of results
            offset += results_in_each_iteration
            # Add a delay to avoid rate limiting (you can adjust the delay time as needed)
            print(f"Scraped {len(all_jobs)} jobs")
            print("Sleeping secs", 100 * (retry_count + 1))
            time.sleep(100 * (retry_count + 1))  # Sleep for 2 seconds between requests
            break  # Break out of the retry loop if successful
        except Exception as e:
            print(f"Error: {e}")
            retry_count += 1
            print("Sleeping secs before retry", 100 * (retry_count + 1))
            time.sleep(100 * (retry_count + 1))
            if retry_count >= max_retries:
                print("Max retries reached. Exiting.")
                break
 # DataFrame from the collected job data
 jobs_df = pd.DataFrame(all_jobs)
 # Formatting
 pd.set_option("display.max_columns", None)
 pd.set_option("display.max_rows", None)
 pd.set_option("display.width", None)
 pd.set_option("display.max_colwidth", 50)
 print(jobs_df)
 jobs_df.to_csv(csv_filename, index=False)
 print(f"Outputted to {csv_filename}")
--- a/poetry.lock
+++ b/poetry.lock
@@ -1243,36 +1243,39 @@ 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 = [
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    {file = "numpy-1.24.2.tar.gz", hash = "sha256:003a9f530e880cb2cd177cba1af7220b9aa42def9c4afc2a2fc3ee6be7eb2b22"},
 ]
 [[package]]
@@ -2257,13 +2260,13 @@ test = ["flake8", "isort", "pytest"]
 [[package]]
 name = "tls-client"
-version = "0.2.1"
+version = "1.0"
 description = "Advanced Python HTTP Client."
 optional = false
 python-versions = "*"
 files = [
-    {file = "tls_client-0.2.1-py3-none-any.whl", hash = "sha256:124a710952b979d5e20b4e2b7879b7958d6e48a259d0f5b83101055eb173f0bd"},
+    {file = "tls_client-1.0-py3-none-any.whl", hash = "sha256:f1183f5e18cb31914bd62d11b350a33ea0293ea80fb91d69a3072821dece3e66"},
-    {file = "tls_client-0.2.1.tar.gz", hash = "sha256:473fb4c671d9d4ca6b818548ab6e955640dd589767bfce520830c5618c2f2e2b"},
+    {file = "tls_client-1.0.tar.gz", hash = "sha256:7f6de48ad4a0ef69b72682c76ce604155971e07b4bfb2148a36276194ae3e7a0"},
 ]
 [[package]]
@@ -2432,4 +2435,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "0c50057af9ebbbe5c124c81758b41f05c05636739c3d1747e1bac74e75a046cb"
+content-hash = "404a77d78066cbb2ef71015562baf44aa11d12aac29a191c1ccc7758bfda598a"
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,8 +1,9 @@
 [tool.poetry]
 name = "python-jobspy"
-version = "1.0.3"
+version = "1.1.38"
-description = "Job scraper for LinkedIn, Indeed & ZipRecruiter"
+description = "Job scraper for LinkedIn, Indeed, Glassdoor & 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 = [
@@ -12,9 +13,10 @@ packages = [
 [tool.poetry.dependencies]
 python = "^3.10"
 requests = "^2.31.0"
-tls-client = "^0.2.1"
+tls-client = "*"
 beautifulsoup4 = "^4.12.2"
 pandas = "^2.1.0"
 NUMPY = "1.24.2"
 pydantic = "^2.3.0"
--- a/src/jobspy/init.py
+++ b/src/jobspy/init.py
@@ -1,21 +1,26 @@
 import pandas as pd
-from typing import List, Tuple
+import concurrent.futures
 from concurrent.futures import ThreadPoolExecutor
 from typing import Tuple, Optional
-from .jobs import JobType
+from .jobs import JobType, Location
 from .scrapers.indeed import IndeedScraper
 from .scrapers.ziprecruiter import ZipRecruiterScraper
 from .scrapers.glassdoor import GlassdoorScraper
 from .scrapers.linkedin import LinkedInScraper
-from .scrapers import (
+from .scrapers import ScraperInput, Site, JobResponse, Country
-    ScraperInput,
+from .scrapers.exceptions import (
-    Site,
+    LinkedInException,
-    JobResponse,
+    IndeedException,
    ZipRecruiterException,
    GlassdoorException,
 )
 SCRAPER_MAPPING = {
    Site.LINKEDIN: LinkedInScraper,
    Site.INDEED: IndeedScraper,
    Site.ZIP_RECRUITER: ZipRecruiterScraper,
    Site.GLASSDOOR: GlassdoorScraper,
 }
@@ -24,105 +29,158 @@ def _map_str_to_site(site_name: str) -> Site:
 def scrape_jobs(
-    site_name: 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,
    full_description: Optional[bool] = False,
    offset: Optional[int] = 0,
 ) -> pd.DataFrame:
    """
-    Asynchronously scrapes job data from multiple job sites.
+    Simultaneously scrapes job data from multiple job sites.
    :return: results_wanted: pandas dataframe containing job data
    """
-    if type(site_name) == str:
+    def get_enum_from_value(value_str):
-        site_name = _map_str_to_site(site_name)
+        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
        site_type = [
            _map_str_to_site(site) if type(site) == str else site_name
            for site in site_name
        ]
    country_enum = Country.from_string(country_indeed)
    site_type = [site_name] if type(site_name) == Site else site_name
    scraper_input = ScraperInput(
        site_type=site_type,
        country=country_enum,
        search_term=search_term,
        location=location,
        distance=distance,
        is_remote=is_remote,
        job_type=job_type,
        easy_apply=easy_apply,
        full_description=full_description,
        results_wanted=results_wanted,
        offset=offset,
    )
    def scrape_site(site: Site) -> Tuple[str, JobResponse]:
        scraper_class = SCRAPER_MAPPING[site]
-        scraper = scraper_class()
+        scraper = scraper_class(proxy=proxy)
        scraped_data: JobResponse = scraper.scrape(scraper_input)
        try:
            scraped_data: JobResponse = scraper.scrape(scraper_input)
        except (LinkedInException, IndeedException, ZipRecruiterException) as lie:
            raise lie
        except Exception as e:
            if site == Site.LINKEDIN:
                raise LinkedInException(str(e))
            if site == Site.INDEED:
                raise IndeedException(str(e))
            if site == Site.ZIP_RECRUITER:
                raise ZipRecruiterException(str(e))
            if site == Site.GLASSDOOR:
                raise GlassdoorException(str(e))
            else:
                raise e
        return site.value, scraped_data
-    results = {}
+    site_to_jobs_dict = {}
    for site in scraper_input.site_type:
        site_value, scraped_data = scrape_site(site)
        results[site_value] = scraped_data
-    dfs = []
+    def worker(site):
        site_val, scraped_info = scrape_site(site)
        return site_val, scraped_info
-    for site, job_response in results.items():
+    with ThreadPoolExecutor() as executor:
        future_to_site = {
            executor.submit(worker, site): site for site in scraper_input.site_type
        }
        for future in concurrent.futures.as_completed(future_to_site):
            site_value, scraped_data = future.result()
            site_to_jobs_dict[site_value] = scraped_data
    jobs_dfs: list[pd.DataFrame] = []
    for site, job_response in site_to_jobs_dict.items():
        for job in job_response.jobs:
-            data = job.dict()
+            job_data = job.dict()
-            data["site"] = site
+            job_data[
                "job_url_hyper"
            ] = f'<a href="{job_data["job_url"]}">{job_data["job_url"]}</a>'
            job_data["site"] = site
            job_data["company"] = job_data["company_name"]
            job_data["job_type"] = (
                ", ".join(job_type.value[0] for job_type in job_data["job_type"])
                if job_data["job_type"]
                else None
            )
            job_data["emails"] = (
                ", ".join(job_data["emails"]) if job_data["emails"] else None
            )
            if job_data["location"]:
                job_data["location"] = Location(
                    **job_data["location"]
                ).display_location()
-            # Formatting JobType
+            compensation_obj = job_data.get("compensation")
            data["job_type"] = data["job_type"].value if data["job_type"] else None
            # Formatting Location
            location_obj = data.get("location")
            if location_obj and isinstance(location_obj, dict):
                data["city"] = location_obj.get("city", "")
                data["state"] = location_obj.get("state", "")
                data["country"] = location_obj.get("country", "USA")
            else:
                data["city"] = None
                data["state"] = None
                data["country"] = None
            # Formatting Compensation
            compensation_obj = data.get("compensation")
            if compensation_obj and isinstance(compensation_obj, dict):
-                data["interval"] = (
+                job_data["interval"] = (
                    compensation_obj.get("interval").value
                    if compensation_obj.get("interval")
                    else None
                )
-                data["min_amount"] = compensation_obj.get("min_amount")
+                job_data["min_amount"] = compensation_obj.get("min_amount")
-                data["max_amount"] = compensation_obj.get("max_amount")
+                job_data["max_amount"] = compensation_obj.get("max_amount")
-                data["currency"] = compensation_obj.get("currency", "USD")
+                job_data["currency"] = compensation_obj.get("currency", "USD")
            else:
-                data["interval"] = None
+                job_data["interval"] = None
-                data["min_amount"] = None
+                job_data["min_amount"] = None
-                data["max_amount"] = None
+                job_data["max_amount"] = None
-                data["currency"] = None
+                job_data["currency"] = None
-            job_df = pd.DataFrame([data])
+            job_df = pd.DataFrame([job_data])
-            dfs.append(job_df)
+            jobs_dfs.append(job_df)
-    if dfs:
+    if jobs_dfs:
-        df = pd.concat(dfs, ignore_index=True)
+        jobs_df = pd.concat(jobs_dfs, ignore_index=True)
-        desired_order = [
+        desired_order: list[str] = [
            "job_url_hyper" if hyperlinks else "job_url",
            "site",
            "title",
-            "company_name",
+            "company",
-            "city",
+            "company_url",
-            "state",
+            "location",
            "job_type",
            "date_posted",
            "interval",
            "min_amount",
            "max_amount",
-            "job_url",
+            "currency",
            "is_remote",
            "num_urgent_words",
            "benefits",
            "emails",
            "description",
        ]
-        df = df[desired_order]
+        jobs_formatted_df = jobs_df[desired_order]
    else:
-        df = pd.DataFrame()
+        jobs_formatted_df = pd.DataFrame()
-    return df
+    return jobs_formatted_df
--- a/src/jobspy/jobs/init.py
+++ b/src/jobspy/jobs/init.py
@@ -1,29 +1,188 @@
-from typing import Union, Optional
+from typing import Optional
 from datetime import date
 from enum import Enum
-
+from pydantic import BaseModel
 from pydantic import BaseModel, validator
 class JobType(Enum):
-    FULL_TIME = "fulltime"
+    FULL_TIME = (
-    PART_TIME = "parttime"
+        "fulltime",
-    CONTRACT = "contract"
+        "períodointegral",
-    TEMPORARY = "temporary"
+        "estágio/trainee",
-    INTERNSHIP = "internship"
+        "cunormăîntreagă",
        "tiempocompleto",
        "vollzeit",
        "voltijds",
        "tempointegral",
        "全职",
        "plnýúvazek",
        "fuldtid",
        "دوامكامل",
        "kokopäivätyö",
        "tempsplein",
        "vollzeit",
        "πλήρηςαπασχόληση",
        "teljesmunkaidő",
        "tempopieno",
        "tempsplein",
        "heltid",
        "jornadacompleta",
        "pełnyetat",
        "정규직",
        "100%",
        "全職",
        "งานประจำ",
        "tamzamanlı",
        "повназайнятість",
        "toànthờigian",
    )
    PART_TIME = ("parttime", "teilzeit", "částečnýúvazek", "deltid")
    CONTRACT = ("contract", "contractor")
    TEMPORARY = ("temporary",)
    INTERNSHIP = (
        "internship",
        "prácticas",
        "ojt(onthejobtraining)",
        "praktikum",
        "praktik",
    )
-    PER_DIEM = "perdiem"
+    PER_DIEM = ("perdiem",)
-    NIGHTS = "nights"
+    NIGHTS = ("nights",)
-    OTHER = "other"
+    OTHER = ("other",)
-    SUMMER = "summer"
+    SUMMER = ("summer",)
-    VOLUNTEER = "volunteer"
+    VOLUNTEER = ("volunteer",)
 class Country(Enum):
    """
    Gets the subdomain for Indeed and Glassdoor.
    The second item in the tuple is the subdomain for Indeed
    The third item in the tuple is the subdomain (and tld if there's a ':' separator) for Glassdoor
    """
    ARGENTINA = ("argentina", "ar", "com.ar")
    AUSTRALIA = ("australia", "au", "com.au")
    AUSTRIA = ("austria", "at", "at")
    BAHRAIN = ("bahrain", "bh")
    BELGIUM = ("belgium", "be", "fr:be")
    BRAZIL = ("brazil", "br", "com.br")
    CANADA = ("canada", "ca", "ca")
    CHILE = ("chile", "cl")
    CHINA = ("china", "cn")
    COLOMBIA = ("colombia", "co")
    COSTARICA = ("costa rica", "cr")
    CZECHREPUBLIC = ("czech republic,czechia", "cz")
    DENMARK = ("denmark", "dk")
    ECUADOR = ("ecuador", "ec")
    EGYPT = ("egypt", "eg")
    FINLAND = ("finland", "fi")
    FRANCE = ("france", "fr", "fr")
    GERMANY = ("germany", "de", "de")
    GREECE = ("greece", "gr")
    HONGKONG = ("hong kong", "hk", "com.hk")
    HUNGARY = ("hungary", "hu")
    INDIA = ("india", "in", "co.in")
    INDONESIA = ("indonesia", "id")
    IRELAND = ("ireland", "ie", "ie")
    ISRAEL = ("israel", "il")
    ITALY = ("italy", "it", "it")
    JAPAN = ("japan", "jp")
    KUWAIT = ("kuwait", "kw")
    LUXEMBOURG = ("luxembourg", "lu")
    MALAYSIA = ("malaysia", "malaysia")
    MEXICO = ("mexico", "mx", "com.mx")
    MOROCCO = ("morocco", "ma")
    NETHERLANDS = ("netherlands", "nl", "nl")
    NEWZEALAND = ("new zealand", "nz", "co.nz")
    NIGERIA = ("nigeria", "ng")
    NORWAY = ("norway", "no")
    OMAN = ("oman", "om")
    PAKISTAN = ("pakistan", "pk")
    PANAMA = ("panama", "pa")
    PERU = ("peru", "pe")
    PHILIPPINES = ("philippines", "ph")
    POLAND = ("poland", "pl")
    PORTUGAL = ("portugal", "pt")
    QATAR = ("qatar", "qa")
    ROMANIA = ("romania", "ro")
    SAUDIARABIA = ("saudi arabia", "sa")
    SINGAPORE = ("singapore", "sg", "sg")
    SOUTHAFRICA = ("south africa", "za")
    SOUTHKOREA = ("south korea", "kr")
    SPAIN = ("spain", "es", "es")
    SWEDEN = ("sweden", "se")
    SWITZERLAND = ("switzerland", "ch", "de:ch")
    TAIWAN = ("taiwan", "tw")
    THAILAND = ("thailand", "th")
    TURKEY = ("turkey", "tr")
    UKRAINE = ("ukraine", "ua")
    UNITEDARABEMIRATES = ("united arab emirates", "ae")
    UK = ("uk,united kingdom", "uk", "co.uk")
    USA = ("usa,us,united states", "www", "com")
    URUGUAY = ("uruguay", "uy")
    VENEZUELA = ("venezuela", "ve")
    VIETNAM = ("vietnam", "vn")
    # internal for ziprecruiter
    US_CANADA = ("usa/ca", "www")
    # internal for linkedin
    WORLDWIDE = ("worldwide", "www")
    @property
    def indeed_domain_value(self):
        return self.value[1]
    @property
    def glassdoor_domain_value(self):
        if len(self.value) == 3:
            subdomain, _, domain = self.value[2].partition(":")
            if subdomain and domain:
                return f"{subdomain}.glassdoor.{domain}"
            else:
                return f"www.glassdoor.{self.value[2]}"
        else:
            raise Exception(f"Glassdoor is not available for {self.name}")
    def get_url(self):
        return f"https://{self.glassdoor_domain_value}/"
    @classmethod
    def from_string(cls, country_str: str):
        """Convert a string to the corresponding Country enum."""
        country_str = country_str.strip().lower()
        for country in cls:
            country_names = country.value[0].split(',')
            if country_str in country_names:
                return country
        valid_countries = [country.value for country in cls]
        raise ValueError(
            f"Invalid country string: '{country_str}'. Valid countries are: {', '.join([country[0] for country in valid_countries])}"
        )
 class Location(BaseModel):
-    country: str = "USA"
+    country: Country | None = None
-    city: str = None
+    city: Optional[str] = None
    state: Optional[str] = None
    def display_location(self) -> str:
        location_parts = []
        if self.city:
            location_parts.append(self.city)
        if self.state:
            location_parts.append(self.state)
        if self.country and self.country not in (Country.US_CANADA, Country.WORLDWIDE):
            country_name = self.country.value[0]
            if "," in country_name:
                country_name = country_name.split(",")[0]
            if country_name in ("usa", "uk"):
                location_parts.append(country_name.upper())
            else:
                location_parts.append(country_name.title())
        return ", ".join(location_parts)
 class CompensationInterval(Enum):
    YEARLY = "yearly"
@@ -32,12 +191,16 @@ class CompensationInterval(Enum):
    DAILY = "daily"
    HOURLY = "hourly"
    @classmethod
    def get_interval(cls, pay_period):
        return cls[pay_period].value if pay_period in cls.__members__ else None
 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: str = "USD"
+    currency: Optional[str] = "USD"
 class JobPost(BaseModel):
@@ -46,29 +209,18 @@ class JobPost(BaseModel):
    job_url: str
    location: Optional[Location]
-    description: Optional[str] = None
+    description: str | None = None
-    job_type: Optional[JobType] = None
+    company_url: str | None = None
-    compensation: Optional[Compensation] = None
+
-    date_posted: Optional[date] = None
+    job_type: list[JobType] | None = None
    compensation: Compensation | None = None
    date_posted: date | None = None
    benefits: str | None = None
    emails: list[str] | None = None
    num_urgent_words: int | None = None
    is_remote: bool | None = None
    # company_industry: str | None = None
 class JobResponse(BaseModel):
    success: bool
    error: str = None
    total_results: Optional[int] = None
    jobs: list[JobPost] = []
    returned_results: int = None
    @validator("returned_results", pre=True, always=True)
    def set_returned_results(cls, v, values):
        jobs_list = values.get("jobs")
        if v is None:
            if jobs_list is not None:
                return len(jobs_list)
            else:
                return 0
        return v
--- a/src/jobspy/scrapers/init.py
+++ b/src/jobspy/scrapers/init.py
@@ -1,16 +1,12 @@
-from ..jobs import Enum, BaseModel, JobType, JobResponse
+from ..jobs import Enum, BaseModel, JobType, JobResponse, Country
 from typing import List, Optional, Any
 class StatusException(Exception):
    def __init__(self, status_code: int):
        self.status_code = status_code
 class Site(Enum):
    LINKEDIN = "linkedin"
    INDEED = "indeed"
    ZIP_RECRUITER = "zip_recruiter"
    GLASSDOOR = "glassdoor"
 class ScraperInput(BaseModel):
@@ -18,26 +14,21 @@ class ScraperInput(BaseModel):
    search_term: str
    location: str = None
    country: Optional[Country] = Country.USA
    distance: Optional[int] = None
    is_remote: bool = False
    job_type: Optional[JobType] = None
    easy_apply: bool = None  # linkedin
    full_description: bool = False
    offset: int = 0
    results_wanted: int = 15
 class CommonResponse(BaseModel):
    status: Optional[str]
    error: Optional[str]
    linkedin: Optional[Any] = None
    indeed: Optional[Any] = None
    zip_recruiter: Optional[Any] = None
 class Scraper:
-    def __init__(self, site: Site, url: str):
+    def __init__(self, site: Site, proxy: Optional[List[str]] = None):
        self.site = site
-        self.url = url
+        self.proxy = (lambda p: {"http": p, "https": p} if p else None)(proxy)
    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
        ...
--- a/src/jobspy/scrapers/exceptions.py
+++ b/src/jobspy/scrapers/exceptions.py
@@ -0,0 +1,26 @@
 """
 jobspy.scrapers.exceptions
 ~~~~~~~~~~~~~~~~~~~
 This module contains the set of Scrapers' exceptions.
 """
 class LinkedInException(Exception):
    def __init__(self, message=None):
        super().__init__(message or "An error occurred with LinkedIn")
 class IndeedException(Exception):
    def __init__(self, message=None):
        super().__init__(message or "An error occurred with Indeed")
 class ZipRecruiterException(Exception):
    def __init__(self, message=None):
        super().__init__(message or "An error occurred with ZipRecruiter")
 class GlassdoorException(Exception):
    def __init__(self, message=None):
        super().__init__(message or "An error occurred with Glassdoor")
--- a/src/jobspy/scrapers/glassdoor/init.py
+++ b/src/jobspy/scrapers/glassdoor/init.py
@@ -0,0 +1,333 @@
 """
 jobspy.scrapers.glassdoor
 ~~~~~~~~~~~~~~~~~~~
 This module contains routines to scrape Glassdoor.
 """
 import json
 import requests
 from bs4 import BeautifulSoup
 from typing import Optional
 from datetime import datetime, timedelta
 from concurrent.futures import ThreadPoolExecutor, as_completed
 from ..utils import count_urgent_words, extract_emails_from_text
 from .. import Scraper, ScraperInput, Site
 from ..exceptions import GlassdoorException
 from ..utils import create_session, modify_and_get_description
 from ...jobs import (
    JobPost,
    Compensation,
    CompensationInterval,
    Location,
    JobResponse,
    JobType,
 )
 class GlassdoorScraper(Scraper):
    def __init__(self, proxy: Optional[str] = None):
        """
        Initializes GlassdoorScraper with the Glassdoor job search url
        """
        site = Site(Site.GLASSDOOR)
        super().__init__(site, proxy=proxy)
        self.url = None
        self.country = None
        self.jobs_per_page = 30
        self.seen_urls = set()
    def fetch_jobs_page(
        self,
        scraper_input: ScraperInput,
        location_id: int,
        location_type: str,
        page_num: int,
        cursor: str | None,
    ) -> (list[JobPost], str | None):
        """
        Scrapes a page of Glassdoor for jobs with scraper_input criteria
        """
        try:
            payload = self.add_payload(
                scraper_input, location_id, location_type, page_num, cursor
            )
            session = create_session(self.proxy, is_tls=False, has_retry=True)
            response = session.post(
                f"{self.url}/graph", headers=self.headers(), timeout=10, data=payload
            )
            if response.status_code != 200:
                raise GlassdoorException(
                    f"bad response status code: {response.status_code}"
                )
            res_json = response.json()[0]
            if "errors" in res_json:
                raise ValueError("Error encountered in API response")
        except Exception as e:
            raise GlassdoorException(str(e))
        jobs_data = res_json["data"]["jobListings"]["jobListings"]
        jobs = []
        with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
            future_to_job_data = {executor.submit(self.process_job, job): job for job in jobs_data}
            for future in as_completed(future_to_job_data):
                job_data = future_to_job_data[future]
                try:
                    job_post = future.result()
                    if job_post:
                        jobs.append(job_post)
                except Exception as exc:
                    raise GlassdoorException(f'Glassdoor generated an exception: {exc}')
        return jobs, self.get_cursor_for_page(
            res_json["data"]["jobListings"]["paginationCursors"], page_num + 1
        )
    def process_job(self, job_data):
        """Processes a single job and fetches its description."""
        job_id = job_data["jobview"]["job"]["listingId"]
        job_url = f'{self.url}job-listing/j?jl={job_id}'
        if job_url in self.seen_urls:
            return None
        self.seen_urls.add(job_url)
        job = job_data["jobview"]
        title = job["job"]["jobTitleText"]
        company_name = job["header"]["employerNameFromSearch"]
        company_id = job_data['jobview']['header']['employer']['id']
        location_name = job["header"].get("locationName", "")
        location_type = job["header"].get("locationType", "")
        age_in_days = job["header"].get("ageInDays")
        is_remote, location = False, None
        date_posted = (datetime.now() - timedelta(days=age_in_days)).date() if age_in_days else None
        if location_type == "S":
            is_remote = True
        else:
            location = self.parse_location(location_name)
        compensation = self.parse_compensation(job["header"])
        try:
            description = self.fetch_job_description(job_id)
        except Exception as e :
            description = None
        job_post = JobPost(
            title=title,
            company_url=f"{self.url}Overview/W-EI_IE{company_id}.htm" if company_id else None,
            company_name=company_name,
            date_posted=date_posted,
            job_url=job_url,
            location=location,
            compensation=compensation,
            is_remote=is_remote,
            description=description,
            emails=extract_emails_from_text(description) if description else None,
            num_urgent_words=count_urgent_words(description) if description else None,
        )
        return job_post
    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
        """
        Scrapes Glassdoor for jobs with scraper_input criteria.
        :param scraper_input: Information about job search criteria.
        :return: JobResponse containing a list of jobs.
        """
        scraper_input.results_wanted = min(900, scraper_input.results_wanted)
        self.country = scraper_input.country
        self.url = self.country.get_url()
        location_id, location_type = self.get_location(
            scraper_input.location, scraper_input.is_remote
        )
        all_jobs: list[JobPost] = []
        cursor = None
        max_pages = 30
        try:
            for page in range(
                1 + (scraper_input.offset // self.jobs_per_page),
                min(
                    (scraper_input.results_wanted // self.jobs_per_page) + 2,
                    max_pages + 1,
                ),
            ):
                try:
                    jobs, cursor = self.fetch_jobs_page(
                        scraper_input, location_id, location_type, page, cursor
                    )
                    all_jobs.extend(jobs)
                    if len(all_jobs) >= scraper_input.results_wanted:
                        all_jobs = all_jobs[: scraper_input.results_wanted]
                        break
                except Exception as e:
                    raise GlassdoorException(str(e))
        except Exception as e:
            raise GlassdoorException(str(e))
        return JobResponse(jobs=all_jobs)
    def fetch_job_description(self, job_id):
        """Fetches the job description for a single job ID."""
        url = f"{self.url}/graph"
        body = [
            {
                "operationName": "JobDetailQuery",
                "variables": {
                    "jl": job_id,
                    "queryString": "q",
                    "pageTypeEnum": "SERP"
                },
                "query": """
                query JobDetailQuery($jl: Long!, $queryString: String, $pageTypeEnum: PageTypeEnum) {
                    jobview: jobView(
                        listingId: $jl
                        contextHolder: {queryString: $queryString, pageTypeEnum: $pageTypeEnum}
                    ) {
                        job {
                            description
                            __typename
                        }
                        __typename
                    }
                }
                """
            }
        ]
        response = requests.post(url, json=body, headers=GlassdoorScraper.headers())
        if response.status_code != 200:
            return None
        data = response.json()[0]
        desc = data['data']['jobview']['job']['description']
        soup = BeautifulSoup(desc, 'html.parser')
        return modify_and_get_description(soup)
    @staticmethod
    def parse_compensation(data: dict) -> Optional[Compensation]:
        pay_period = data.get("payPeriod")
        adjusted_pay = data.get("payPeriodAdjustedPay")
        currency = data.get("payCurrency", "USD")
        if not pay_period or not adjusted_pay:
            return None
        interval = None
        if pay_period == "ANNUAL":
            interval = CompensationInterval.YEARLY
        elif pay_period:
            interval = CompensationInterval.get_interval(pay_period)
        min_amount = int(adjusted_pay.get("p10") // 1)
        max_amount = int(adjusted_pay.get("p90") // 1)
        return Compensation(
            interval=interval,
            min_amount=min_amount,
            max_amount=max_amount,
            currency=currency,
        )
    def get_location(self, location: str, is_remote: bool) -> (int, str):
        if not location or is_remote:
            return "11047", "STATE"  # remote options
        url = f"{self.url}/findPopularLocationAjax.htm?maxLocationsToReturn=10&term={location}"
        session = create_session(self.proxy, has_retry=True)
        response = session.get(url)
        if response.status_code != 200:
            raise GlassdoorException(
                f"bad response status code: {response.status_code}"
            )
        items = response.json()
        if not items:
            raise ValueError(f"Location '{location}' not found on Glassdoor")
        location_type = items[0]["locationType"]
        if location_type == "C":
            location_type = "CITY"
        elif location_type == "S":
            location_type = "STATE"
        return int(items[0]["locationId"]), location_type
    @staticmethod
    def add_payload(
        scraper_input,
        location_id: int,
        location_type: str,
        page_num: int,
        cursor: str | None = None,
    ) -> str:
        payload = {
            "operationName": "JobSearchResultsQuery",
            "variables": {
                "excludeJobListingIds": [],
                "filterParams": [{"filterKey": "applicationType", "values": "1"}] if scraper_input.easy_apply else [],
                "keyword": scraper_input.search_term,
                "numJobsToShow": 30,
                "locationType": location_type,
                "locationId": int(location_id),
                "parameterUrlInput": f"IL.0,12_I{location_type}{location_id}",
                "pageNumber": page_num,
                "pageCursor": cursor,
            },
            "query": "query JobSearchResultsQuery($excludeJobListingIds: [Long!], $keyword: String, $locationId: Int, $locationType: LocationTypeEnum, $numJobsToShow: Int!, $pageCursor: String, $pageNumber: Int, $filterParams: [FilterParams], $originalPageUrl: String, $seoFriendlyUrlInput: String, $parameterUrlInput: String, $seoUrl: Boolean) {\n  jobListings(\n    contextHolder: {searchParams: {excludeJobListingIds: $excludeJobListingIds, keyword: $keyword, locationId: $locationId, locationType: $locationType, numPerPage: $numJobsToShow, pageCursor: $pageCursor, pageNumber: $pageNumber, filterParams: $filterParams, originalPageUrl: $originalPageUrl, seoFriendlyUrlInput: $seoFriendlyUrlInput, parameterUrlInput: $parameterUrlInput, seoUrl: $seoUrl, searchType: SR}}\n  ) {\n    companyFilterOptions {\n      id\n      shortName\n      __typename\n    }\n    filterOptions\n    indeedCtk\n    jobListings {\n      ...JobView\n      __typename\n    }\n    jobListingSeoLinks {\n      linkItems {\n        position\n        url\n        __typename\n      }\n      __typename\n    }\n    jobSearchTrackingKey\n    jobsPageSeoData {\n      pageMetaDescription\n      pageTitle\n      __typename\n    }\n    paginationCursors {\n      cursor\n      pageNumber\n      __typename\n    }\n    indexablePageForSeo\n    searchResultsMetadata {\n      searchCriteria {\n        implicitLocation {\n          id\n          localizedDisplayName\n          type\n          __typename\n        }\n        keyword\n        location {\n          id\n          shortName\n          localizedShortName\n          localizedDisplayName\n          type\n          __typename\n        }\n        __typename\n      }\n      footerVO {\n        countryMenu {\n          childNavigationLinks {\n            id\n            link\n            textKey\n            __typename\n          }\n          __typename\n        }\n        __typename\n      }\n      helpCenterDomain\n      helpCenterLocale\n      jobAlert {\n        jobAlertExists\n        __typename\n      }\n      jobSerpFaq {\n        questions {\n          answer\n          question\n          __typename\n        }\n        __typename\n      }\n      jobSerpJobOutlook {\n        occupation\n        paragraph\n        __typename\n      }\n      showMachineReadableJobs\n      __typename\n    }\n    serpSeoLinksVO {\n      relatedJobTitlesResults\n      searchedJobTitle\n      searchedKeyword\n      searchedLocationIdAsString\n      searchedLocationSeoName\n      searchedLocationType\n      topCityIdsToNameResults {\n        key\n        value\n        __typename\n      }\n      topEmployerIdsToNameResults {\n        key\n        value\n        __typename\n      }\n      topEmployerNameResults\n      topOccupationResults\n      __typename\n    }\n    totalJobsCount\n    __typename\n  }\n}\n\nfragment JobView on JobListingSearchResult {\n  jobview {\n    header {\n      adOrderId\n      advertiserType\n      adOrderSponsorshipLevel\n      ageInDays\n      divisionEmployerName\n      easyApply\n      employer {\n        id\n        name\n        shortName\n        __typename\n      }\n      employerNameFromSearch\n      goc\n      gocConfidence\n      gocId\n      jobCountryId\n      jobLink\n      jobResultTrackingKey\n      jobTitleText\n      locationName\n      locationType\n      locId\n      needsCommission\n      payCurrency\n      payPeriod\n      payPeriodAdjustedPay {\n        p10\n        p50\n        p90\n        __typename\n      }\n      rating\n      salarySource\n      savedJobId\n      sponsored\n      __typename\n    }\n    job {\n      descriptionFragments\n      importConfigId\n      jobTitleId\n      jobTitleText\n      listingId\n      __typename\n    }\n    jobListingAdminDetails {\n      cpcVal\n      importConfigId\n      jobListingId\n      jobSourceId\n      userEligibleForAdminJobDetails\n      __typename\n    }\n    overview {\n      shortName\n      squareLogoUrl\n      __typename\n    }\n    __typename\n  }\n  __typename\n}\n",
        }
        job_type_filters = {
            JobType.FULL_TIME: "fulltime",
            JobType.PART_TIME: "parttime",
            JobType.CONTRACT: "contract",
            JobType.INTERNSHIP: "internship",
            JobType.TEMPORARY: "temporary",
        }
        if scraper_input.job_type in job_type_filters:
            filter_value = job_type_filters[scraper_input.job_type]
            payload["variables"]["filterParams"].append(
                {"filterKey": "jobType", "values": filter_value}
            )
        return json.dumps([payload])
    @staticmethod
    def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
        for job_type in JobType:
            if job_type_str in job_type.value:
                return [job_type]
    @staticmethod
    def parse_location(location_name: str) -> Location | None:
        if not location_name or location_name == "Remote":
            return
        city, _, state = location_name.partition(", ")
        return Location(city=city, state=state)
    @staticmethod
    def get_cursor_for_page(pagination_cursors, page_num):
        for cursor_data in pagination_cursors:
            if cursor_data["pageNumber"] == page_num:
                return cursor_data["cursor"]
    @staticmethod
    def headers() -> dict:
        """
        Returns headers needed for requests
        :return: dict - Dictionary containing headers
        """
        return {
            "authority": "www.glassdoor.com",
            "accept": "*/*",
            "accept-language": "en-US,en;q=0.9",
            "apollographql-client-name": "job-search-next",
            "apollographql-client-version": "4.65.5",
            "content-type": "application/json",
            "cookie": 'gdId=91e2dfc4-c8b5-4fa7-83d0-11512b80262c; G_ENABLED_IDPS=google; trs=https%3A%2F%2Fwww.redhat.com%2F:referral:referral:2023-07-05+09%3A50%3A14.862:undefined:undefined; g_state={"i_p":1688587331651,"i_l":1}; _cfuvid=.7llazxhYFZWi6EISSPdVjtqF0NMVwzxr_E.cB1jgLs-1697828392979-0-604800000; GSESSIONID=undefined; JSESSIONID=F03DD1B5EE02DB6D842FE42B142F88F3; cass=1; jobsClicked=true; indeedCtk=1hd77b301k79i801; asst=1697829114.2; G_AUTHUSER_H=0; uc=8013A8318C98C517FE6DD0024636DFDEF978FC33266D93A2FAFEF364EACA608949D8B8FA2DC243D62DE271D733EB189D809ABE5B08D7B1AE865D217BD4EEBB97C282F5DA5FEFE79C937E3F6110B2A3A0ADBBA3B4B6DF5A996FEE00516100A65FCB11DA26817BE8D1C1BF6CFE36B5B68A3FDC2CFEC83AB797F7841FBB157C202332FC7E077B56BD39B167BDF3D9866E3B; AWSALB=zxc/Yk1nbWXXT6HjNyn3H4h4950ckVsFV/zOrq5LSoChYLE1qV+hDI8Axi3fUa9rlskndcO0M+Fw+ZnJ+AQ2afBFpyOd1acouLMYgkbEpqpQaWhY6/Gv4QH1zBcJ; AWSALBCORS=zxc/Yk1nbWXXT6HjNyn3H4h4950ckVsFV/zOrq5LSoChYLE1qV+hDI8Axi3fUa9rlskndcO0M+Fw+ZnJ+AQ2afBFpyOd1acouLMYgkbEpqpQaWhY6/Gv4QH1zBcJ; gdsid=1697828393025:1697830776351:668396EDB9E6A832022D34414128093D; at=HkH8Hnqi9uaMC7eu0okqyIwqp07ht9hBvE1_St7E_hRqPvkO9pUeJ1Jcpds4F3g6LL5ADaCNlxrPn0o6DumGMfog8qI1-zxaV_jpiFs3pugntw6WpVyYWdfioIZ1IDKupyteeLQEM1AO4zhGjY_rPZynpsiZBPO_B1au94sKv64rv23yvP56OiWKKfI-8_9hhLACEwWvM-Az7X-4aE2QdFt93VJbXbbGVf07bdDZfimsIkTtgJCLSRhU1V0kEM1Efyu66vo3m77gFFaMW7lxyYnb36I5PdDtEXBm3aL-zR7-qa5ywd94ISEivgqQOA4FPItNhqIlX4XrfD1lxVz6rfPaoTIDi4DI6UMCUjwyPsuv8mn0rYqDfRnmJpZ97fJ5AnhrknAd_6ZWN5v1OrxJczHzcXd8LO820QPoqxzzG13bmSTXLwGSxMUCtSrVsq05hicimQ3jpRt0c1dA4OkTNqF7_770B9JfcHcM8cr8-C4IL56dnOjr9KBGfN1Q2IvZM2cOBRbV7okiNOzKVZ3qJ24AE34WA2F3U6Whiu6H8nIuGG5hSNkVygY6CtglNZfFF9p8pJAZm79PngrrBv-CXFBZmhYLFo46lmFetDkiJ6mirtez4tKpzTIYjIp4_JAkiZFwbLJ2QGH4mK8kyyW0lZiX1DTuQec50N_5wvRo0Gt7nlKxzLsApMnaNhuQeH5ygh_pa381ORo9mQGi0EYF9zk00pa2--z4PtjfQ8KFq36GgpxKy5-o4qgqygZj8F01L8r-FiX2G4C7PREMIpAyHX2A4-_JxA1IS2j12EyqKTLqE9VcP06qm2Z-YuIW3ctmpMxy5G9_KiEiGv17weizhSFnl6SbpAEY-2VSmQ5V6jm3hoMp2jemkuGCRkZeFstLDEPxlzFN7WM; __cf_bm=zGaVjIJw4irf40_7UVw54B6Ohm271RUX4Tc8KVScrbs-1697830777-0-AYv2GnKTnnCU+cY9xHbJunO0DwlLDO6SIBnC/s/qldpKsGK0rRAjD6y8lbyATT/KlS7g29OZaN4fbd0lrJg0KmWbIybZIzfWVLHSYePVuOhu; asst=1697829114.2; at=dFhXf64wsf2TlnWy41xLs7skJkuxgKToEGcjGtDfUvW4oEAJ4tTIR5dKQ8wbwT75aIaGgdCfvcb-da7vwrCGWscCncmfLFQpJ9l-LLwoRfk-pMsxHhd77wvf-W7I0HSm7-Q5lQJqI9WyNGRxOa-RpzBTf4L8_Et4-3FzjPaAoYY5pY1FhuwXbN5asGOAMW-p8cjpbfn3PumlIYuckguWnjrcY2F31YJ_1noeoHM9tCGpymANbqGXRkG6aXY7yCfVXtdgZU1K5SMeaSPZIuF_iLUxjc_corzpNiH6qq7BIAmh-e5Aa-g7cwpZcln1fmwTVw4uTMZf1eLIMTa9WzgqZNkvG-sGaq_XxKA_Wai6xTTkOHfRgm4632Ba2963wdJvkGmUUa3tb_L4_wTgk3eFnHp5JhghLfT2Pe3KidP-yX__vx8JOsqe3fndCkKXgVz7xQKe1Dur-sMNlGwi4LXfguTT2YUI8C5Miq3pj2IHc7dC97eyyAiAM4HvyGWfaXWZcei6oIGrOwMvYgy0AcwFry6SIP2SxLT5TrxinRRuem1r1IcOTJsMJyUPp1QsZ7bOyq9G_0060B4CPyovw5523hEuqLTM-R5e5yavY6C_1DHUyE15C3mrh7kdvmlGZeflnHqkFTEKwwOftm-Mv-CKD5Db9ABFGNxKB2FH7nDH67hfOvm4tGNMzceBPKYJ3wciTt9jK3wy39_7cOYVywfrZ-oLhw_XtsbGSSeGn3HytrfgSADAh2sT0Gg6eCC9Xy1vh-Za337SVLUDXZ73W2xJxxUHBkFzZs8L_Xndo5DsbpWhVs9IYUGyraJdqB3SLgDbAppIBCJl4fx6_DG8-xOQPBvuFMlTROe1JVdHOzXI1GElwFDTuH1pjkg4I2G0NhAbE06Y-1illQE; gdsid=1697828393025:1697831731408:99C30D94108AC3030D61C736DDCDF11C',
            "gd-csrf-token": "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok",
            "origin": "https://www.glassdoor.com",
            "referer": "https://www.glassdoor.com/",
            "sec-ch-ua": '"Chromium";v="118", "Google Chrome";v="118", "Not=A?Brand";v="99"',
            "sec-ch-ua-mobile": "?0",
            "sec-ch-ua-platform": '"macOS"',
            "sec-fetch-dest": "empty",
            "sec-fetch-mode": "cors",
            "sec-fetch-site": "same-origin",
            "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/118.0.0.0 Safari/537.36",
        }
--- a/src/jobspy/scrapers/indeed/init.py
+++ b/src/jobspy/scrapers/indeed/init.py
@@ -1,15 +1,29 @@
 """
 jobspy.scrapers.indeed
 ~~~~~~~~~~~~~~~~~~~
 This module contains routines to scrape Indeed.
 """
 import re
 import math
 import io
 import json
 from typing import Any
 from datetime import datetime
 from typing import Optional
 import tls_client
 import urllib.parse
 from bs4 import BeautifulSoup
 from bs4.element import Tag
 from concurrent.futures import ThreadPoolExecutor, Future
 from ..exceptions import IndeedException
 from ..utils import (
    count_urgent_words,
    extract_emails_from_text,
    create_session,
    get_enum_from_job_type,
    modify_and_get_description
 )
 from ...jobs import (
    JobPost,
    Compensation,
@@ -18,61 +32,56 @@ from ...jobs import (
    JobResponse,
    JobType,
 )
-from .. import Scraper, ScraperInput, Site, StatusException
+from .. import Scraper, ScraperInput, Site
 class ParsingException(Exception):
    pass
 class IndeedScraper(Scraper):
-    def __init__(self):
+    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)
-        url = "https://www.indeed.com"
+        super().__init__(site, proxy=proxy)
        super().__init__(site, url)
-        self.jobs_per_page = 15
+        self.jobs_per_page = 25
        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.indeed_domain_value
        self.url = f"https://{domain}.indeed.com"
-        job_list = []
+        try:
-
+            session = create_session(self.proxy)
-        params = {
+            response = session.get(
-            "q": scraper_input.search_term,
+                f"{self.url}/m/jobs",
-            "l": scraper_input.location,
+                headers=self.get_headers(),
-            "radius": scraper_input.distance,
+                params=self.add_params(scraper_input, page),
-            "filter": 0,
+                allow_redirects=True,
-            "start": 0 + page * 10,
+                timeout_seconds=10,
-        }
+            )
-        sc_values = []
+            if response.status_code not in range(200, 400):
-        if scraper_input.is_remote:
+                raise IndeedException(
-            sc_values.append("attr(DSQF7)")
+                    f"bad response with status code: {response.status_code}"
-        if scraper_input.job_type:
+                )
-            sc_values.append("jt({})".format(scraper_input.job_type.value))
+        except Exception as e:
-
+            if "Proxy responded with" in str(e):
-        if sc_values:
+                raise IndeedException("bad proxy")
-            params["sc"] = "0kf:" + "".join(sc_values) + ";"
+            raise IndeedException(str(e))
        response = session.get(self.url + "/jobs", params=params)
        if response.status_code != 200 and response.status_code != 307:
            raise StatusException(response.status_code)
        soup = BeautifulSoup(response.content, "html.parser")
-        if "did not match any jobs" in str(soup):
+        if "did not match any jobs" in response.text:
-            raise ParsingException("Search did not match any jobs")
+            raise IndeedException("Parsing exception: Search did not match any jobs")
        jobs = IndeedScraper.parse_jobs(
            soup
@@ -84,16 +93,14 @@ class IndeedScraper(Scraper):
            .get("mosaicProviderJobCardsModel", {})
            .get("results")
        ):
-            raise Exception("No jobs found.")
+            raise IndeedException("No jobs found.")
-        def process_job(job) -> Optional[JobPost]:
+        def process_job(job: dict) -> JobPost | None:
-            job_url = f'{self.url}/jobs/viewjob?jk={job["jobkey"]}'
+            job_url = f'{self.url}/m/jobs/viewjob?jk={job["jobkey"]}'
            job_url_client = f'{self.url}/viewjob?jk={job["jobkey"]}'
            if job_url in self.seen_urls:
                return None
            snippet_html = BeautifulSoup(job["snippet"], "html.parser")
            extracted_salary = job.get("extractedSalary")
            compensation = None
            if extracted_salary:
@@ -107,8 +114,8 @@ 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,
                    )
@@ -117,31 +124,40 @@ 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) if scraper_input.full_description else None
-            li_elements = snippet_html.find_all("li")
+
-            if description is None and li_elements:
+            with io.StringIO(job["snippet"]) as f:
-                description = " ".join(li.text for li in li_elements)
+                soup_io = BeautifulSoup(f, "html.parser")
                li_elements = soup_io.find_all("li")
                if description is None and li_elements:
                    description = " ".join(li.text for li in li_elements)
            first_li = snippet_html.find("li")
            job_post = JobPost(
                title=job["normTitle"],
                description=description,
                company_name=job["company"],
                company_url=self.url + job["companyOverviewLink"] if "companyOverviewLink" in job else None,
                location=Location(
                    city=job.get("jobLocationCity"),
                    state=job.get("jobLocationState"),
                    country=self.country,
                ),
                job_type=job_type,
                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
-        with ThreadPoolExecutor(max_workers=10) as executor:
+        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()]
@@ -154,97 +170,87 @@ 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
        )
-        try:
+        #: get first page to initialize session
-            #: get first page to initialize session
+        job_list, total_results = self.scrape_page(scraper_input, 0)
            job_list, total_results = self.scrape_page(scraper_input, 0, session)
-            with ThreadPoolExecutor(max_workers=10) as executor:
+        with ThreadPoolExecutor(max_workers=10) as executor:
-                futures: list[Future] = [
+            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)
+                for page in range(1, pages_to_process + 1)
-                ]
+            ]
-                for future in futures:
+            for future in futures:
-                    jobs, _ = future.result()
+                jobs, _ = future.result()
-                    job_list += jobs
+                job_list += jobs
        except StatusException as e:
            return JobResponse(
                success=False,
                error=f"Indeed returned status code {e.status_code}",
            )
        except ParsingException as e:
            return JobResponse(
                success=False,
                error=f"Indeed failed to parse response: {e}",
            )
        except Exception as e:
            return JobResponse(
                success=False,
                error=f"Indeed failed to scrape: {e}",
            )
        if len(job_list) > scraper_input.results_wanted:
            job_list = job_list[: scraper_input.results_wanted]
        job_response = JobResponse(
            success=True,
            jobs=job_list,
            total_results=total_results,
        )
        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)
-        response = session.get(formatted_url, allow_redirects=True)
+        try:
            response = session.get(
                formatted_url,
                headers=self.get_headers(),
                allow_redirects=True,
                timeout_seconds=5,
            )
        except Exception as e:
            return None
        if response.status_code not in range(200, 400):
            return None
-        raw_description = response.json()["body"]["jobInfoWrapperModel"][
+        try:
-            "jobInfoModel"
+            data = json.loads(response.text)
-        ]["sanitizedJobDescription"]
+            job_description = data["body"]["jobInfoWrapperModel"]["jobInfoModel"][
-        soup = BeautifulSoup(raw_description, "html.parser")
+                "sanitizedJobDescription"
-        text_content = " ".join(soup.get_text().split()).strip()
+            ]
-        return text_content
+        except (KeyError, TypeError, IndexError):
            return None
        soup = BeautifulSoup(job_description, "html.parser")
        return modify_and_get_description(soup)
    @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"])):
-                    job_type_str = (
+                    label = taxonomy["attributes"][i].get("label")
-                        taxonomy["attributes"][0]["label"]
+                    if label:
-                        .replace("-", "_")
+                        job_type_str = label.replace("-", "").replace(" ", "").lower()
-                        .replace(" ", "_")
+                        job_type = get_enum_from_job_type(job_type_str)
-                        .upper()
+                        if job_type:
-                    )
+                            job_types.append(job_type)
-                    return JobType[job_type_str]
+        return job_types
        return None
    @staticmethod
    def parse_jobs(soup: BeautifulSoup) -> dict:
@@ -254,7 +260,7 @@ class IndeedScraper(Scraper):
        :return: jobs
        """
-        def find_mosaic_script() -> Optional[Tag]:
+        def find_mosaic_script() -> Tag | None:
            """
            Finds jobcards script tag
            :return: script_tag
@@ -281,10 +287,10 @@ class IndeedScraper(Scraper):
                jobs = json.loads(m.group(1).strip())
                return jobs
            else:
-                raise ParsingException("Could not find mosaic provider job cards data")
+                raise IndeedException("Could not find mosaic provider job cards data")
        else:
-            raise ParsingException(
+            raise IndeedException(
-                "Could not find a script tag containing mosaic provider data"
+                "Could not find any results for the search"
            )
    @staticmethod
@@ -294,7 +300,7 @@ class IndeedScraper(Scraper):
        :param soup:
        :return: total_num_jobs
        """
-        script = soup.find("script", string=lambda t: "window._initialData" in t)
+        script = soup.find("script", string=lambda t: t and "window._initialData" in t)
        pattern = re.compile(r"window._initialData\s*=\s*({.*})\s*;", re.DOTALL)
        match = pattern.search(script.string)
@@ -304,3 +310,53 @@ class IndeedScraper(Scraper):
            data = json.loads(json_str)
            total_num_jobs = int(data["searchTitleBarModel"]["totalNumResults"])
        return total_num_jobs
    @staticmethod
    def get_headers():
        return {
          'Host': 'www.indeed.com',
          'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
          'sec-fetch-site': 'same-origin',
          'sec-fetch-dest': 'document',
          'accept-language': 'en-US,en;q=0.9',
          'sec-fetch-mode': 'navigate',
          'user-agent': 'Mozilla/5.0 (iPhone; CPU iPhone OS 16_6_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/15E148 Indeed App 192.0',
          'referer': 'https://www.indeed.com/m/jobs?q=software%20intern&l=Dallas%2C%20TX&from=serpso&rq=1&rsIdx=3',
        }
    @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
    @staticmethod
    def add_params(scraper_input: ScraperInput, page: int) -> dict[str, str | Any]:
        params = {
            "q": scraper_input.search_term,
            "l": scraper_input.location,
            "filter": 0,
            "start": scraper_input.offset + page * 10,
            "sort": "date"
        }
        if scraper_input.distance:
            params["radius"] = scraper_input.distance
        sc_values = []
        if scraper_input.is_remote:
            sc_values.append("attr(DSQF7)")
        if scraper_input.job_type:
            sc_values.append("jt({})".format(scraper_input.job_type.value))
        if sc_values:
            params["sc"] = "0kf:" + "".join(sc_values) + ";"
        if scraper_input.easy_apply:
            params['iafilter'] = 1
        return params
--- a/src/jobspy/scrapers/linkedin/init.py
+++ b/src/jobspy/scrapers/linkedin/init.py
@@ -1,29 +1,52 @@
-from typing import Optional, Tuple
+"""
 jobspy.scrapers.linkedin
 ~~~~~~~~~~~~~~~~~~~
 This module contains routines to scrape LinkedIn.
 """
 import time
 import random
 from typing import Optional
 from datetime import datetime
 import requests
-from bs4 import BeautifulSoup
+from requests.exceptions import ProxyError
 from threading import Lock
 from bs4.element import Tag
 from bs4 import BeautifulSoup
 from urllib.parse import urlparse, urlunparse
 from .. import Scraper, ScraperInput, Site
 from ..exceptions import LinkedInException
 from ..utils import create_session
 from ...jobs import (
    JobPost,
    Location,
    JobResponse,
    JobType,
-    Compensation,
+    Country,
-    CompensationInterval,
+    Compensation
 )
 from ..utils import (
    count_urgent_words,
    extract_emails_from_text,
    get_enum_from_job_type,
    currency_parser,
    modify_and_get_description
 )
 class LinkedInScraper(Scraper):
-    def __init__(self):
+    DELAY = 3
    def __init__(self, proxy: Optional[str] = None):
        """
        Initializes LinkedInScraper with the LinkedIn job search url
        """
        site = Site(Site.LINKEDIN)
-        url = "https://www.linkedin.com"
+        self.country = "worldwide"
-        super().__init__(site, url)
+        self.url = "https://www.linkedin.com"
        super().__init__(site, proxy=proxy)
    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
        """
@@ -33,9 +56,10 @@ class LinkedInScraper(Scraper):
        """
        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",
@@ -44,121 +68,155 @@ 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:
+            session = create_session(is_tls=False, has_retry=True, delay=5)
-                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": page,
+                "pageNum": 0,
-                    "f_AL": "true" if scraper_input.easy_apply else None,
+                "start": 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}
            try:
                response = session.get(
-                    f"{self.url}/jobs/search", params=params, allow_redirects=True
+                    f"{self.url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
                    params=params,
                    allow_redirects=True,
                    proxies=self.proxy,
                    headers=self.headers(),
                    timeout=10,
                )
                response.raise_for_status()
-                if response.status_code != 200:
+            except requests.HTTPError as e:
-                    return JobResponse(
+                raise LinkedInException(f"bad response status code: {e.response.status_code}")
-                        success=False,
+            except ProxyError as e:
-                        error=f"Response returned {response.status_code}",
+                raise LinkedInException("bad proxy")
-                    )
+            except Exception as e:
                raise LinkedInException(str(e))
-                soup = BeautifulSoup(response.text, "html.parser")
+            soup = BeautifulSoup(response.text, "html.parser")
            job_cards = soup.find_all("div", class_="base-search-card")
            if len(job_cards) == 0:
                return JobResponse(jobs=job_list)
-                if page == 0:
+            for job_card in job_cards:
-                    job_count_text = soup.find(
+                job_url = None
-                        "span", class_="results-context-header__job-count"
+                href_tag = job_card.find("a", class_="base-card__full-link")
-                    ).text
+                if href_tag and "href" in href_tag.attrs:
-                    job_count = int("".join(filter(str.isdigit, job_count_text)))
+                    href = href_tag.attrs["href"].split("?")[0]
-
+                    job_id = href.split("-")[-1]
                for job_card in soup.find_all(
                    "div",
                    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")
+                # Call process_job directly without threading
-                    company = company_tag.text.strip() if company_tag else "N/A"
+                try:
                    job_post = self.process_job(job_card, job_url, scraper_input.full_description)
                    if job_post:
                        job_list.append(job_post)
                except Exception as e:
                    raise LinkedInException("Exception occurred while processing jobs")
-                    metadata_card = job_info.find(
+            page += 25
-                        "div", class_="base-search-card__metadata"
+            time.sleep(random.uniform(LinkedInScraper.DELAY, LinkedInScraper.DELAY + 2))
                    )
                    location: Location = LinkedInScraper.get_location(metadata_card)
                    datetime_tag = metadata_card.find(
                        "time", class_="job-search-card__listdate"
                    )
                    description, job_type = LinkedInScraper.get_description(job_url)
                    if datetime_tag:
                        datetime_str = datetime_tag["datetime"]
                        date_posted = datetime.strptime(datetime_str, "%Y-%m-%d")
                    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="USD"
                        ),
                    )
                    job_list.append(job_post)
                    if (
                        len(job_list) >= scraper_input.results_wanted
                        or processed_jobs >= job_count
                    ):
                        break
                if (
                    len(job_list) >= scraper_input.results_wanted
                    or processed_jobs >= job_count
                ):
                    break
                page += 1
        job_list = job_list[: scraper_input.results_wanted]
-        job_response = JobResponse(
+        return JobResponse(jobs=job_list)
            success=True,
            jobs=job_list,
            total_results=job_count,
        )
        return job_response
-    @staticmethod
+    def process_job(self, job_card: Tag, job_url: str, full_descr: bool) -> Optional[JobPost]:
-    def get_description(job_page_url: str) -> Optional[str]:
+        salary_tag = job_card.find('span', class_='job-search-card__salary-info')
        compensation = None
        if salary_tag:
            salary_text = salary_tag.get_text(separator=' ').strip()
            salary_values = [currency_parser(value) for value in salary_text.split('-')]
            salary_min = salary_values[0]
            salary_max = salary_values[1]
            currency = salary_text[0] if salary_text[0] != '$' else 'USD'
            compensation = Compensation(
                min_amount=int(salary_min),
                max_amount=int(salary_max),
                currency=currency,
            )
        title_tag = job_card.find("span", class_="sr-only")
        title = title_tag.get_text(strip=True) if title_tag else "N/A"
        company_tag = job_card.find("h4", class_="base-search-card__subtitle")
        company_a_tag = company_tag.find("a") if company_tag else None
        company_url = (
            urlunparse(urlparse(company_a_tag.get("href"))._replace(query=""))
            if company_a_tag and company_a_tag.has_attr("href")
            else ""
        )
        company = company_a_tag.get_text(strip=True) if company_a_tag else "N/A"
        metadata_card = job_card.find("div", class_="base-search-card__metadata")
        location = self.get_location(metadata_card)
        datetime_tag = (
            metadata_card.find("time", class_="job-search-card__listdate")
            if metadata_card
            else None
        )
        date_posted = description = job_type = None
        if datetime_tag and "datetime" in datetime_tag.attrs:
            datetime_str = datetime_tag["datetime"]
            try:
                date_posted = datetime.strptime(datetime_str, "%Y-%m-%d")
            except Exception as e:
                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
        if full_descr:
            description, job_type = self.get_job_description(job_url)
        return JobPost(
            title=title,
            company_name=company,
            company_url=company_url,
            location=location,
            date_posted=date_posted,
            job_url=job_url,
            compensation=compensation,
            benefits=benefits,
            job_type=job_type,
            description=description,
            emails=extract_emails_from_text(description) if description else None,
            num_urgent_words=count_urgent_words(description) if description else None,
        )
    def get_job_description(
        self, job_page_url: str
    ) -> tuple[None, None] | tuple[str | None, tuple[str | None, JobType | None]]:
        """
        Retrieves job description by going to the job page url
        :param job_page_url:
        :return: description or None
        """
-        response = requests.get(job_page_url, allow_redirects=True)
+        try:
-        if response.status_code not in range(200, 400):
+            session = create_session(is_tls=False, has_retry=True)
            response = session.get(job_page_url, timeout=5, proxies=self.proxy)
            response.raise_for_status()
        except requests.HTTPError as e:
            return None, None
        except Exception as e:
            return None, None
        if response.url == "https://www.linkedin.com/signup":
            return None, None
        soup = BeautifulSoup(response.text, "html.parser")
@@ -166,19 +224,19 @@ 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 = modify_and_get_description(div_content)
        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,
@@ -195,17 +253,17 @@ class LinkedInScraper(Scraper):
                    employment_type = employment_type.lower()
                    employment_type = employment_type.replace("-", "")
-            return JobType(employment_type)
+            return [get_enum_from_job_type(employment_type)] if employment_type else []
-        return text_content, get_job_type(soup)
+        return description, get_job_type(soup)
-    @staticmethod
+    def get_location(self, metadata_card: Optional[Tag]) -> Location:
    def get_location(metadata_card: Optional[Tag]) -> Location:
        """
        Extracts the location data from the job metadata card.
        :param metadata_card
        :return: location
        """
        location = Location(country=Country.from_string(self.country))
        if metadata_card is not None:
            location_tag = metadata_card.find(
                "span", class_="job-search-card__location"
@@ -217,6 +275,32 @@ class LinkedInScraper(Scraper):
                location = Location(
                    city=city,
                    state=state,
                    country=Country.from_string(self.country),
                )
            elif len(parts) == 3:
                city, state, country = parts
                location = Location(
                    city=city,
                    state=state,
                    country=Country.from_string(country),
                )
        return location
    @staticmethod
    def headers() -> dict:
        return {
            'authority': 'www.linkedin.com',
            'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7',
            'accept-language': 'en-US,en;q=0.9',
            'cache-control': 'max-age=0',
            'sec-ch-ua': '"Not_A Brand";v="8", "Chromium";v="120", "Google Chrome";v="120"',
            # 'sec-ch-ua-mobile': '?0',
            # 'sec-ch-ua-platform': '"macOS"',
            # 'sec-fetch-dest': 'document',
            # 'sec-fetch-mode': 'navigate',
            # 'sec-fetch-site': 'none',
            # 'sec-fetch-user': '?1',
            'upgrade-insecure-requests': '1',
            'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36'
        }
--- a/src/jobspy/scrapers/utils.py
+++ b/src/jobspy/scrapers/utils.py
@@ -0,0 +1,96 @@
 import re
 import numpy as np
 import tls_client
 import requests
 from requests.adapters import HTTPAdapter, Retry
 from ..jobs import JobType
 def modify_and_get_description(soup):
    for li in soup.find_all('li'):
        li.string = "- " + li.get_text()
    description = soup.get_text(separator='\n').strip()
    description = re.sub(r'\n+', '\n', description)
    return description
 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, has_retry: bool = False, delay: int = 1) -> requests.Session:
    """
    Creates a requests session with optional tls, proxy, and retry settings.
    :return: A session object
    """
    if is_tls:
        session = tls_client.Session(
            client_identifier="chrome112",
            random_tls_extension_order=True,
        )
        session.proxies = proxy
    else:
        session = requests.Session()
        session.allow_redirects = True
        if proxy:
            session.proxies.update(proxy)
        if has_retry:
            retries = Retry(total=3,
                            connect=3,
                            status=3,
                            status_forcelist=[500, 502, 503, 504, 429],
                            backoff_factor=delay)
            adapter = HTTPAdapter(max_retries=retries)
            session.mount('http://', adapter)
            session.mount('https://', adapter)
    return session
 def get_enum_from_job_type(job_type_str: str) -> JobType | None:
    """
    Given a string, returns the corresponding JobType enum member if a match is found.
    """
    res = None
    for job_type in JobType:
        if job_type_str in job_type.value:
            res = job_type
    return res
 def currency_parser(cur_str):
    # Remove any non-numerical characters
    # except for ',' '.' or '-' (e.g. EUR)
    cur_str = re.sub("[^-0-9.,]", '', cur_str)
    # Remove any 000s separators (either , or .)
    cur_str = re.sub("[.,]", '', cur_str[:-3]) + cur_str[-3:]
    if '.' in list(cur_str[-3:]):
        num = float(cur_str)
    elif ',' in list(cur_str[-3:]):
        num = float(cur_str.replace(',', '.'))
    else:
        num = float(cur_str)
    return np.round(num, 2)
--- a/src/jobspy/scrapers/ziprecruiter/init.py
+++ b/src/jobspy/scrapers/ziprecruiter/init.py
@@ -1,250 +1,126 @@
 """
 jobspy.scrapers.ziprecruiter
 ~~~~~~~~~~~~~~~~~~~
 This module contains routines to scrape ZipRecruiter.
 """
 import math
-import json
+import time
 import re
-from datetime import datetime
+from datetime import datetime, date
-from typing import Optional, Tuple
+from typing import Optional, Tuple, Any
 from urllib.parse import urlparse, parse_qs
 import tls_client
 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, StatusException
+from .. import Scraper, ScraperInput, Site
-from ...jobs import (
+from ..exceptions import ZipRecruiterException
-    JobPost,
+from ...jobs import JobPost, Compensation, Location, JobResponse, JobType, Country
-    Compensation,
+from ..utils import count_urgent_words, extract_emails_from_text, create_session, modify_and_get_description
    CompensationInterval,
    Location,
    JobResponse,
    JobType,
 )
 class ZipRecruiterScraper(Scraper):
-    def __init__(self):
+    def __init__(self, proxy: Optional[str] = None):
        """
-        Initializes LinkedInScraper with the ZipRecruiter job search url
+        Initializes ZipRecruiterScraper with the ZipRecruiter job search url
        """
        site = Site(Site.ZIP_RECRUITER)
-        url = "https://www.ziprecruiter.com"
+        self.url = "https://www.ziprecruiter.com"
-        super().__init__(site, url)
+        self.session = create_session(proxy)
        self.get_cookies()
        super().__init__(site, proxy=proxy)
        self.jobs_per_page = 20
        self.seen_urls = set()
        self.session = tls_client.Session(
            client_identifier="chrome112", random_tls_extension_order=True
        )
-    def scrape_page(
+    def find_jobs_in_page(
-        self, scraper_input: ScraperInput, page: int
+        self, scraper_input: ScraperInput, continue_token: str | None = None
-    ) -> tuple[list[JobPost], int | None]:
+    ) -> Tuple[list[JobPost], Optional[str]]:
        """
        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
        """
        params = self.add_params(scraper_input)
        if continue_token:
            params["continue"] = continue_token
        try:
            response = self.session.get(
                f"https://api.ziprecruiter.com/jobs-app/jobs",
                headers=self.headers(),
                params=self.add_params(scraper_input),
            )
            if response.status_code != 200:
                raise ZipRecruiterException(
                    f"bad response status code: {response.status_code}"
                )
        except Exception as e:
            if "Proxy responded with non 200 code" in str(e):
                raise ZipRecruiterException("bad proxy")
            raise ZipRecruiterException(str(e))
-        job_list = []
+        time.sleep(5)
        response_data = response.json()
        jobs_list = response_data.get("jobs", [])
        next_continue_token = response_data.get("continue", None)
-        job_type_value = None
+        with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
-        if scraper_input.job_type:
+            job_results = [executor.submit(self.process_job, job) for job in jobs_list]
            if scraper_input.job_type.value == "fulltime":
                job_type_value = "full_time"
            elif scraper_input.job_type.value == "parttime":
                job_type_value = "part_time"
            else:
                job_type_value = scraper_input.job_type.value
        params = {
            "search": scraper_input.search_term,
            "location": scraper_input.location,
            "page": page,
            "form": "jobs-landing",
        }
        if scraper_input.is_remote:
            params["refine_by_location_type"] = "only_remote"
        if scraper_input.distance:
            params["radius"] = scraper_input.distance
        if job_type_value:
            params[
                "refine_by_employment"
            ] = f"employment_type:employment_type:{job_type_value}"
        response = self.session.get(
            self.url + "/jobs-search",
            headers=ZipRecruiterScraper.headers(),
            params=params,
        )
        if response.status_code != 200:
            raise StatusException(response.status_code)
        html_string = response.text
        soup = BeautifulSoup(html_string, "html.parser")
        script_tag = soup.find("script", {"id": "js_variables"})
        data = json.loads(script_tag.string)
        if page == 1:
            job_count = int(data["totalJobCount"].replace(",", ""))
        else:
            job_count = None
        with ThreadPoolExecutor(max_workers=10) as executor:
            if "jobList" in data and data["jobList"]:
                jobs_js = data["jobList"]
                job_results = [
                    executor.submit(self.process_job_js, job) for job in jobs_js
                ]
            else:
                jobs_html = soup.find_all("div", {"class": "job_content"})
                job_results = [
                    executor.submit(self.process_job_html, job) for job in jobs_html
                ]
        job_list = [result.result() for result in job_results if result.result()]
-
+        return job_list, next_continue_token
        return job_list, job_count
    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.
        """
        job_list: list[JobPost] = []
        continue_token = None
-        pages_to_process = max(
+        max_pages = math.ceil(scraper_input.results_wanted / self.jobs_per_page)
            3, math.ceil(scraper_input.results_wanted / self.jobs_per_page)
        )
-        try:
+        for page in range(1, max_pages + 1):
-            #: get first page to initialize session
+            if len(job_list) >= scraper_input.results_wanted:
-            job_list, total_results = self.scrape_page(scraper_input, 1)
+                break
-            with ThreadPoolExecutor(max_workers=10) as executor:
+            jobs_on_page, continue_token = self.find_jobs_in_page(
-                futures: list[Future] = [
+                scraper_input, continue_token
                    executor.submit(self.scrape_page, scraper_input, page)
                    for page in range(2, pages_to_process + 1)
                ]
                for future in futures:
                    jobs, _ = future.result()
                    job_list += jobs
        except StatusException as e:
            return JobResponse(
                success=False,
                error=f"ZipRecruiter returned status code {e.status_code}",
            )
        except Exception as e:
            return JobResponse(
                success=False,
                error=f"ZipRecruiter failed to scrape: {e}",
            )
            if jobs_on_page:
                job_list.extend(jobs_on_page)
-        #: note: this does not handle if the results are more or less than the results_wanted
+            if not continue_token:
                break
        if len(job_list) > scraper_input.results_wanted:
            job_list = job_list[: scraper_input.results_wanted]
-        job_response = JobResponse(
+        return JobResponse(jobs=job_list)
-            success=True,
+
-            jobs=job_list,
+    @staticmethod
-            total_results=total_results,
+    def process_job(job: dict) -> JobPost:
        """Processes an individual job dict from the response"""
        title = job.get("name")
        job_url = job.get("job_url")
        job_description_html = job.get("job_description", "").strip()
        description_soup = BeautifulSoup(job_description_html, "html.parser")
        description = modify_and_get_description(description_soup)
        company = job["hiring_company"].get("name") if "hiring_company" in job else None
        country_value = "usa" if job.get("job_country") == "US" else "canada"
        country_enum = Country.from_string(country_value)
        location = Location(
            city=job.get("job_city"), state=job.get("job_state"), country=country_enum
        )
-        return job_response
+        job_type = ZipRecruiterScraper.get_job_type_enum(
-
+            job.get("employment_type", "").replace("_", "").lower()
    def process_job_html(self, job: Tag) -> Optional[JobPost]:
        """
        Parses a job from the job content tag
        :param job: BeautifulSoup Tag for one job post
        :return JobPost
        """
        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
        company = job.find("a", {"class": "company_name"}).text.strip()
        description, updated_job_url = self.get_description(job_url)
        if updated_job_url is not None:
            job_url = updated_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"})
        if job_type_element:
            job_type_text = (
                job_type_element.text.strip().lower().replace("-", "").replace(" ", "")
            )
            if job_type_text == "contractor":
                job_type_text = "contract"
            job_type = JobType(job_type_text)
        else:
            job_type = None
        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_js(self, job: dict) -> JobPost:
        # Map the job data to the expected fields by the Pydantic model
        title = job.get("Title")
        description = BeautifulSoup(
            job.get("Snippet", "").strip(), "html.parser"
        ).get_text()
        company = job.get("OrgName")
        location = Location(city=job.get("City"), state=job.get("State"))
        try:
            job_type = ZipRecruiterScraper.job_type_from_string(
                job.get("EmploymentType", "").replace("-", "_").lower()
            )
        except ValueError:
            # print(f"Skipping job due to unrecognized job type: {job.get('EmploymentType')}")
            return None
        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,
        )
        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
@@ -255,154 +131,73 @@ 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
+
    def get_cookies(self):
        url="https://api.ziprecruiter.com/jobs-app/event"
        data="event_type=session&logged_in=false&number_of_retry=1&property=model%3AiPhone&property=os%3AiOS&property=locale%3Aen_us&property=app_build_number%3A4734&property=app_version%3A91.0&property=manufacturer%3AApple&property=timestamp%3A2024-01-12T12%3A04%3A42-06%3A00&property=screen_height%3A852&property=os_version%3A16.6.1&property=source%3Ainstall&property=screen_width%3A393&property=device_model%3AiPhone%2014%20Pro&property=brand%3AApple"
        self.session.post(url, data=data, headers=ZipRecruiterScraper.headers())
    @staticmethod
-    def job_type_from_string(value: str) -> Optional[JobType]:
+    def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
-        if not value:
+        for job_type in JobType:
-            return None
+            if job_type_str in job_type.value:
-
+                return [job_type]
        if value.lower() == "contractor":
            value = "contract"
        normalized_value = value.replace("_", "")
        for item in JobType:
            if item.value == normalized_value:
                return item
        raise ValueError(f"Invalid value for JobType: {value}")
    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
        """
        response = self.session.get(
            job_page_url, headers=ZipRecruiterScraper.headers(), allow_redirects=True
        )
        if response.status_code not in range(200, 400):
            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 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]:
+    def add_params(scraper_input) -> dict[str, str | Any]:
-        """
+        params = {
-        Parses the compensation tag from the job BeautifulSoup object
+            "search": scraper_input.search_term,
-        :param job
+            "location": scraper_input.location,
-        :return: Compensation object or None
+            "form": "jobs-landing",
-        """
+        }
-        pay_element = job.find("li", {"class": "perk_item perk_pay"})
+        job_type_value = None
-        if pay_element is None:
+        if scraper_input.job_type:
-            return None
+            if scraper_input.job_type.value == "fulltime":
-        pay = pay_element.find("div", {"class": "value"}).find("span").text.strip()
+                job_type_value = "full_time"
-
+            elif scraper_input.job_type.value == "parttime":
-        def create_compensation_object(pay_string: str) -> Compensation:
+                job_type_value = "part_time"
            """
            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)
            )
            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
+                job_type_value = scraper_input.job_type.value
-        else:
+        if scraper_input.easy_apply:
-            city, state = None, None
+            params['zipapply'] = 1
-        return Location(
+
-            city=city,
+        if job_type_value:
-            state=state,
+            params[
-        )
+                "refine_by_employment"
            ] = f"employment_type:employment_type:{job_type_value}"
        if scraper_input.is_remote:
            params["refine_by_location_type"] = "only_remote"
        if scraper_input.distance:
            params["radius"] = scraper_input.distance
        return params
    @staticmethod
    def headers() -> dict:
@@ -411,5 +206,12 @@ 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",
            "accept": "*/*",
            "x-zr-zva-override": "100000000;vid:ZT1huzm_EQlDTVEc",
            "x-pushnotificationid": "0ff4983d38d7fc5b3370297f2bcffcf4b3321c418f5c22dd152a0264707602a0",
            "x-deviceid": "D77B3A92-E589-46A4-8A39-6EF6F1D86006",
            "user-agent": "Job Search/87.0 (iPhone; CPU iOS 16_6_1 like Mac OS X)",
            "authorization": "Basic YTBlZjMyZDYtN2I0Yy00MWVkLWEyODMtYTI1NDAzMzI0YTcyOg==",
            "accept-language": "en-US,en;q=0.9",
        }
--- a/src/tests/test_all.py
+++ b/src/tests/test_all.py
@@ -0,0 +1,14 @@
 from ..jobspy import scrape_jobs
 import pandas as pd
 def test_all():
    result = scrape_jobs(
        site_name=["linkedin", "indeed", "zip_recruiter", "glassdoor"],
        search_term="software engineer",
        results_wanted=5,
    )
    assert (
        isinstance(result, pd.DataFrame) and not result.empty
    ), "Result should be a non-empty DataFrame"
--- a/src/tests/test_glassdoor.py
+++ b/src/tests/test_glassdoor.py
@@ -0,0 +1,11 @@
 from ..jobspy import scrape_jobs
 import pandas as pd
 def test_indeed():
    result = scrape_jobs(
        site_name="glassdoor", search_term="software engineer", country_indeed="USA"
    )
    assert (
        isinstance(result, pd.DataFrame) and not result.empty
    ), "Result should be a non-empty DataFrame"
--- a/src/tests/test_indeed.py
+++ b/src/tests/test_indeed.py
@@ -1,9 +1,11 @@
 from ..jobspy import scrape_jobs
 import pandas as pd
 def test_indeed():
    result = scrape_jobs(
-        site_name="indeed",
+        site_name="indeed", search_term="software engineer", country_indeed="usa"
        search_term="software engineer",
    )
-    assert result is not None
+    assert (
        isinstance(result, pd.DataFrame) and not result.empty
    ), "Result should be a non-empty DataFrame"
--- a/src/tests/test_linkedin.py
+++ b/src/tests/test_linkedin.py
@@ -1,4 +1,5 @@
-from jobspy import scrape_jobs
+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
+    assert (
        isinstance(result, pd.DataFrame) and not result.empty
    ), "Result should be a non-empty DataFrame"
--- a/src/tests/test_ziprecruiter.py
+++ b/src/tests/test_ziprecruiter.py
@@ -1,4 +1,5 @@
-from jobspy import scrape_jobs
+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
+    assert (
        isinstance(result, pd.DataFrame) and not result.empty
    ), "Result should be a non-empty DataFrame"
Author	SHA1	Message	Date
Cullen Watson	13c7694474	Easy apply (#95 ) * enh(glassdoor): easy apply filter * enh(ziprecruiter): easy apply * enh(indeed): use mobile headers * chore: version	2024-02-02 17:47:15 -06:00
Cullen Watson	bbe46fe3f4	enh(glassdoor): easy apply filter (#92 )	2024-02-01 19:42:24 -06:00
Cullen Watson	b97c73ffd6	fix: clean description (#88 )	2024-01-28 21:50:41 -06:00
Cullen Watson	5b3627b244	enh: full description param (#85 )	2024-01-22 20:22:32 -06:00
Cullen Watson	2ec3b04777	fix(ziprecruiter): init cookies (#82 )	2024-01-12 12:28:35 -06:00
Harish Vadaparty	89a5264391	add long scrape example (#81 )	2024-01-12 12:24:00 -06:00
Cullen Watson	a7ad616567	fix: linkedin no results (#80 )	2024-01-10 14:01:10 -06:00
cullenwatson	53bc33a43a	chore: version	2024-01-09 19:33:56 -06:00
Cullen Watson	22870438c7	linkedin fix delays (#79 )	2024-01-09 19:32:51 -06:00
Cullen Watson	aeb93b99f5	Update pyproject.toml	2024-01-03 12:04:50 -06:00
Cullen Watson	a5916edcdd	fix(glassdoor): add retry adapter (#77 )	2024-01-03 12:04:32 -06:00
Augusto Gunsch	33d442bf1e	Add czech to Indeed (#72 )	2023-12-02 02:42:54 -06:00
Zachary Hampton	6587e464fa	Update README.md	2023-11-30 11:49:31 -07:00
Vincent Yan	eed7fca300	Get full indeed description (#70 )	2023-11-27 15:00:36 -06:00
Faraz Khan	dfb8c18c51	include location with 3 parts (#69 )	2023-11-10 16:59:42 -06:00
Faraz Khan	81f70ff8a5	added salary data for linkedin (#68 )	2023-11-09 14:57:15 -06:00
Cullen Watson	cc9e7866b7	fix linkedin bug & add linkedin company url (#67 )	2023-11-08 15:51:07 -06:00
Zachary Hampton	a2c8fe046e	Update README.md	2023-11-06 22:13:19 -07:00
Cullen Watson	2b7fea40a5	[fix] glassdoor duplicates	2023-10-30 20:29:55 -05:00
Cullen Watson	d37f86e1b9	[fix] glassdoor location	2023-10-30 20:19:56 -05:00
Cullen Watson	0302ab14f5	glassdoor keywords	2023-10-30 20:07:31 -05:00
Cullen Watson	3f2b582445	add glassdoor (#66 )	2023-10-30 19:57:36 -05:00
Cullen Watson	93223b6a38	bug fix	2023-10-30 13:57:23 -05:00
Cullen Watson	e3fc222eb5	readd proxy support for zip (#64 )	2023-10-29 08:54:56 -05:00
Cullen	b303b3f841	chore: version	2023-10-28 16:58:32 -05:00
Cullen	1a0c75f323	chore: version	2023-10-28 16:54:04 -05:00
Cullen	e2f6885d61	chore: format	2023-10-28 16:52:05 -05:00
Cullen	8d65d1b652	[chore] version	2023-10-28 16:43:44 -05:00
Cullen	216d3fd39f	ziprecruiter: 5s delay	2023-10-28 16:41:32 -05:00
Cullen Watson	d3bfdc0a6e	ziprecruiter api (#63 )	2023-10-28 16:17:28 -05:00
Cullen Watson	ba5ed803ca	use ziprecuriter api (#62 )	2023-10-28 15:51:29 -05:00
Cullen Watson	ff1eb0f7b0	[docs] update readme	2023-10-18 14:32:21 -05:00
Cullen Watson	f2cc74b7f2	Fix Indeed exceptions on parsing description	2023-10-18 14:25:53 -05:00
Cullen Watson	5e71866630	[docs] link change	2023-10-18 11:18:03 -05:00
Zachary Hampton	4e67c6e5a3	Update README.md	2023-10-17 20:22:56 -07:00
Cullen Watson	caf655525a	docs: update readme	2023-10-10 11:54:14 -05:00
Cullen Watson	90fa4a4c4f	feat: utils.py	2023-10-10 11:29:29 -05:00
Cullen Watson	e5353e604d	Multiple job types for Indeed, urgent keywords column (#56 ) * 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	2023-10-10 11:23:04 -05:00
Cullen Watson	628f4dee9c	[fix] indeed - min & max values swapped (#54 )	2023-10-03 09:22:18 -05:00
Cullen Watson	2e59ab03e3	Merge branch 'main' of https://github.com/cullenwatson/JobSpy	2023-09-28 18:53:59 -05:00
Cullen Watson	008ca61e12	[fix] readd hyperlink param	2023-09-28 18:53:21 -05:00
Cullen Watson	8fc4c3bf90	[docs] readme	2023-09-28 18:35:40 -05:00
Cullen Watson	bff39a2625	[fix] util func	2023-09-28 18:33:14 -05:00
Cullen Watson	c676050dc0	[fix] util func	2023-09-28 18:33:02 -05:00
Cullen Watson	37976f7ec2	[chore] version number	2023-09-28 18:26:55 -05:00
Cullen Watson	9fb2fdd80f	[fix] add utils.py	2023-09-28 18:25:56 -05:00
Cullen Watson	af07c1ecbd	add offset param & email extraction (#51 ) * add offset param * [enh]: extract emails	2023-09-28 18:11:28 -05:00
Cullen Watson	286b9e1256	chore: version number	2023-09-21 20:28:57 -05:00
Cullen Watson	162dd40b0f	docs: add usejobspy.com	2023-09-21 20:27:04 -05:00
Cullen Watson	558e352939	fix: job type param bug	2023-09-21 17:42:24 -05:00
Zachary Hampton	efad1a1b7d	Update README.md	2023-09-21 09:52:18 -07:00
Cullen Watson	eaa481c2f4	docs: add macos catalina to faq	2023-09-19 12:50:14 -05:00
Zachary Hampton	b914aa6449	Update README.md	2023-09-16 13:52:30 -07:00
Zachary Hampton	6adbfb8b29	Update README.md	2023-09-16 13:51:45 -07:00
Zachary Hampton	a3b9dd50ff	(docs) homepage	2023-09-15 16:14:26 -07:00
Zachary Hampton	d3ba3a4878	docs: sales call	2023-09-15 11:51:22 -07:00
Cullen Watson	f524789d74	docs: grammar readme	2023-09-15 10:18:24 -05:00
Cullen Watson	f3890d4830	docs: update	2023-09-09 10:55:33 -05:00
Cullen Watson	60c9728691	docs: typo	2023-09-08 12:27:49 -05:00
Cullen Watson	f79d975e5f	docs: clarify - README.md	2023-09-07 13:46:14 -05:00
Cullen Watson	d6368f909b	docs: typo	2023-09-07 13:39:56 -05:00
Cullen Watson	6fcf7f666e	docs: update typo in example	2023-09-07 13:37:53 -05:00
Cullen Watson	4406f9350f	docs: update vid	2023-09-07 13:35:10 -05:00
Cullen Watson	ca5155f234	docs: add feature	2023-09-07 11:36:16 -05:00
Cullen Watson	822a55783e	docs: temp update	2023-09-07 11:35:14 -05:00
Cullen Watson	59f739018a	Proxy support (#44 ) * add proxy support * return as data frame	2023-09-07 11:28:17 -05:00
Zachary Hampton	a37e7f235e	Merge pull request #42 from cullenwatson/fix/class-type-error - refactor & #41 bug fix	2023-09-06 16:33:59 -07:00
Zachary Hampton	690739e858	- refactor & #41 bug fix	2023-09-06 16:32:51 -07:00
Cullen Watson	43eb2fe0e8	remove gitattr	2023-09-06 11:34:51 -05:00
Cullen Watson	e50227bba6	clear output jupyter	2023-09-06 11:32:32 -05:00
Cullen Watson	45c2d76e15	add yt guide	2023-09-06 11:26:55 -05:00
Cullen Watson	fd883178be	Thread sites (#40 )	2023-09-06 09:47:11 -05:00
Cullen Watson	70e2218c67	reduce size of jupyter notebook	2023-09-05 13:09:18 -05:00
Cullen Watson	d6947ecdd7	Update README.md	2023-09-05 13:03:32 -05:00
Cullen Watson	5191658562	Update README.md	2023-09-05 12:27:00 -05:00
Cullen Watson	1c264b8c58	Indeed country support (#38 )	2023-09-05 12:17:22 -05:00
Cullen Watson	1598d4ff63	update README.md	2023-09-04 22:58:46 -05:00
Cullen Watson	bf2460684b	update README.md	2023-09-04 22:52:21 -05:00