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42
.github/workflows/publish-to-pypi.yml
vendored
42
.github/workflows/publish-to-pypi.yml
vendored
@@ -7,27 +7,27 @@ jobs:
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v4
|
||||
with:
|
||||
python-version: "3.10"
|
||||
- uses: actions/checkout@v3
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v4
|
||||
with:
|
||||
python-version: "3.10"
|
||||
|
||||
- name: Install poetry
|
||||
run: >-
|
||||
python3 -m
|
||||
pip install
|
||||
poetry
|
||||
--user
|
||||
- name: Install poetry
|
||||
run: >-
|
||||
python3 -m
|
||||
pip install
|
||||
poetry
|
||||
--user
|
||||
|
||||
- name: Build distribution 📦
|
||||
run: >-
|
||||
python3 -m
|
||||
poetry
|
||||
build
|
||||
- name: Build distribution 📦
|
||||
run: >-
|
||||
python3 -m
|
||||
poetry
|
||||
build
|
||||
|
||||
- name: Publish distribution 📦 to PyPI
|
||||
if: startsWith(github.ref, 'refs/tags')
|
||||
uses: pypa/gh-action-pypi-publish@release/v1
|
||||
with:
|
||||
password: ${{ secrets.PYPI_API_TOKEN }}
|
||||
- name: Publish distribution 📦 to PyPI
|
||||
if: startsWith(github.ref, 'refs/tags')
|
||||
uses: pypa/gh-action-pypi-publish@release/v1
|
||||
with:
|
||||
password: ${{ secrets.PYPI_API_TOKEN }}
|
||||
10
.gitignore
vendored
10
.gitignore
vendored
@@ -1,10 +1,10 @@
|
||||
/.idea
|
||||
**/.DS_Store
|
||||
/venv/
|
||||
/ven/
|
||||
/.idea
|
||||
**/__pycache__/
|
||||
**/.pytest_cache/
|
||||
/.ipynb_checkpoints/
|
||||
**/output/
|
||||
**/.DS_Store
|
||||
*.pyc
|
||||
.env
|
||||
dist
|
||||
/.ipynb_checkpoints/
|
||||
dist
|
||||
@@ -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&...</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 & 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&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": {
|
||||
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|
||||
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|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.11.4"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
139
README.md
139
README.md
@@ -1,48 +1,53 @@
|
||||
# <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://calendly.com/bunsly/15min)** *to
|
||||
work with us.*
|
||||
\
|
||||
Check out another project we wrote: ***[HomeHarvest](https://github.com/Bunsly/HomeHarvest)** – a Python package
|
||||
for real estate scraping*
|
||||
|
||||
## Features
|
||||
|
||||
- Scrapes job postings from **LinkedIn**, **Indeed** & **ZipRecruiter** simultaneously
|
||||
- Aggregates the job postings in a Pandas DataFrame
|
||||
|
||||
- Proxy support (HTTP/S, SOCKS)
|
||||
|
||||
[Video Guide for JobSpy](https://www.youtube.com/watch?v=RuP1HrAZnxs&pp=ygUgam9icyBzY3JhcGVyIGJvdCBsaW5rZWRpbiBpbmRlZWQ%3D) -
|
||||
Updated for release v1.1.3
|
||||
|
||||
|
||||
|
||||
|
||||
### 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"],
|
||||
search_term="software engineer",
|
||||
results_wanted=10
|
||||
location="Dallas, TX",
|
||||
results_wanted=10,
|
||||
country_indeed='USA' # only needed for indeed
|
||||
)
|
||||
|
||||
if jobs.empty:
|
||||
print("No jobs found.")
|
||||
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)
|
||||
print(f"Found {len(jobs)} jobs")
|
||||
print(jobs.head())
|
||||
jobs.to_csv("jobs.csv", index=False) # / to_xlsx
|
||||
```
|
||||
|
||||
### 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!...
|
||||
@@ -52,7 +57,9 @@ linkedin Full-Stack Software Engineer Rain New York
|
||||
zip_recruiter Software Engineer - New Grad ZipRecruiter Santa Monica CA fulltime yearly 130000 150000 https://www.ziprecruiter.com/jobs/ziprecruiter... We offer a hybrid work environment. Most US-ba...
|
||||
zip_recruiter Software Developer TEKsystems Phoenix AZ fulltime hourly 65 75 https://www.ziprecruiter.com/jobs/teksystems-0... Top Skills' Details• 6 years of Java developme...
|
||||
```
|
||||
|
||||
### Parameters for `scrape_jobs()`
|
||||
|
||||
```plaintext
|
||||
Required
|
||||
├── site_type (List[enum]): linkedin, zip_recruiter, indeed
|
||||
@@ -61,49 +68,105 @@ Optional
|
||||
├── location (int)
|
||||
├── distance (int): in miles
|
||||
├── job_type (enum): fulltime, parttime, internship, contract
|
||||
├── proxy (str): in format 'http://user:pass@host:port' or [https, socks]
|
||||
├── is_remote (bool)
|
||||
├── results_wanted (int): number of job results to retrieve for each site specified in 'site_type'
|
||||
├── easy_apply (bool): filters for jobs on LinkedIn that have the 'Easy Apply' option
|
||||
├── easy_apply (bool): filters for jobs that are hosted on LinkedIn
|
||||
├── country_indeed (enum): filters the country on Indeed (see below for correct spelling)
|
||||
├── offset (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
|
||||
│ ├── min_amount (float)
|
||||
│ ├── max_amount (float)
|
||||
│ └── currency (str)
|
||||
└── date_posted (datetime)
|
||||
│ ├── interval (str): yearly, monthly, weekly, daily, hourly
|
||||
│ ├── min_amount (int)
|
||||
│ ├── max_amount (int)
|
||||
│ └── currency (enum)
|
||||
└── date_posted (date)
|
||||
└── emails (str)
|
||||
└── num_urgent_words (int)
|
||||
└── is_remote (bool)
|
||||
```
|
||||
|
||||
### Exceptions
|
||||
|
||||
The following exceptions may be raised when using JobSpy:
|
||||
|
||||
* `LinkedInException`
|
||||
* `IndeedException`
|
||||
* `ZipRecruiterException`
|
||||
|
||||
## Supported Countries for Job Searching
|
||||
|
||||
### **LinkedIn**
|
||||
|
||||
LinkedIn searches globally & uses only the `location` parameter.
|
||||
|
||||
### **ZipRecruiter**
|
||||
|
||||
ZipRecruiter searches for jobs in **US/Canada** & uses only the `location` parameter.
|
||||
|
||||
### **Indeed**
|
||||
|
||||
Indeed supports most countries, but the `country_indeed` parameter is required. Additionally, use the `location`
|
||||
parameter to narrow down the location, e.g. city & state if necessary.
|
||||
|
||||
You can specify the following countries when searching on Indeed (use the exact name):
|
||||
|
||||
| | | | |
|
||||
|----------------------|--------------|------------|----------------|
|
||||
| Argentina | Australia | Austria | Bahrain |
|
||||
| Belgium | Brazil | Canada | Chile |
|
||||
| China | Colombia | Costa Rica | Czech Republic |
|
||||
| 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 | | |
|
||||
|
||||
## 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.
|
||||
|
||||
**Note:** Proxy support is in development and coming soon!
|
||||
- Trying a VPN or proxy to change your IP address.
|
||||
|
||||
---
|
||||
|
||||
**Q: Experiencing a "Segmentation fault: 11" on macOS Catalina?**
|
||||
**A:** This is due to `tls_client` dependency not supporting your architecture. Solutions and workarounds include:
|
||||
|
||||
- Upgrade to a newer version of MacOS
|
||||
- Reach out to the maintainers of [tls_client](https://github.com/bogdanfinn/tls-client) for fixes
|
||||
|
||||
|
||||
|
||||
|
||||
167
examples/JobSpy_Demo.ipynb
Normal file
167
examples/JobSpy_Demo.ipynb
Normal file
@@ -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
|
||||
}
|
||||
31
examples/JobSpy_Demo.py
Normal file
31
examples/JobSpy_Demo.py
Normal file
@@ -0,0 +1,31 @@
|
||||
from jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
jobs: pd.DataFrame = scrape_jobs(
|
||||
site_name=["indeed", "linkedin", "zip_recruiter"],
|
||||
search_term="software engineer",
|
||||
location="Dallas, TX",
|
||||
results_wanted=50, # be wary the higher it is, the more likey you'll get blocked (rotating proxy should work tho)
|
||||
country_indeed="USA",
|
||||
offset=25 # start jobs from an offset (use if search failed and want to continue)
|
||||
# proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
|
||||
)
|
||||
|
||||
# formatting for pandas
|
||||
pd.set_option("display.max_columns", None)
|
||||
pd.set_option("display.max_rows", None)
|
||||
pd.set_option("display.width", None)
|
||||
pd.set_option("display.max_colwidth", 50) # set to 0 to see full job url / desc
|
||||
|
||||
# 1: output to console
|
||||
print(jobs)
|
||||
|
||||
# 2: output to .csv
|
||||
jobs.to_csv("./jobs.csv", index=False)
|
||||
print("outputted to jobs.csv")
|
||||
|
||||
# 3: output to .xlsx
|
||||
# jobs.to_xlsx('jobs.xlsx', index=False)
|
||||
|
||||
# 4: display in Jupyter Notebook (1. pip install jupyter 2. jupyter notebook)
|
||||
# display(jobs)
|
||||
69
poetry.lock
generated
69
poetry.lock
generated
@@ -1053,6 +1053,16 @@ files = [
|
||||
{file = "MarkupSafe-2.1.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:5bbe06f8eeafd38e5d0a4894ffec89378b6c6a625ff57e3028921f8ff59318ac"},
|
||||
{file = "MarkupSafe-2.1.3-cp311-cp311-win32.whl", hash = "sha256:dd15ff04ffd7e05ffcb7fe79f1b98041b8ea30ae9234aed2a9168b5797c3effb"},
|
||||
{file = "MarkupSafe-2.1.3-cp311-cp311-win_amd64.whl", hash = "sha256:134da1eca9ec0ae528110ccc9e48041e0828d79f24121a1a146161103c76e686"},
|
||||
{file = "MarkupSafe-2.1.3-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:f698de3fd0c4e6972b92290a45bd9b1536bffe8c6759c62471efaa8acb4c37bc"},
|
||||
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|
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|
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|
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|
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|
||||
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|
||||
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|
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||||
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|
||||
@@ -1243,36 +1253,39 @@ test = ["pytest", "pytest-console-scripts", "pytest-jupyter", "pytest-tornasync"
|
||||
|
||||
[[package]]
|
||||
name = "numpy"
|
||||
version = "1.25.2"
|
||||
version = "1.24.2"
|
||||
description = "Fundamental package for array computing in Python"
|
||||
optional = false
|
||||
python-versions = ">=3.9"
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "numpy-1.25.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:db3ccc4e37a6873045580d413fe79b68e47a681af8db2e046f1dacfa11f86eb3"},
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{file = "numpy-1.25.2.tar.gz", hash = "sha256:fd608e19c8d7c55021dffd43bfe5492fab8cc105cc8986f813f8c3c048b38760"},
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{file = "numpy-1.24.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c29e6bd0ec49a44d7690ecb623a8eac5ab8a923bce0bea6293953992edf3a76a"},
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{file = "numpy-1.24.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2eabd64ddb96a1239791da78fa5f4e1693ae2dadc82a76bc76a14cbb2b966e96"},
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{file = "numpy-1.24.2-cp38-cp38-win32.whl", hash = "sha256:e3ab5d32784e843fc0dd3ab6dcafc67ef806e6b6828dc6af2f689be0eb4d781d"},
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{file = "numpy-1.24.2-cp38-cp38-win_amd64.whl", hash = "sha256:76807b4063f0002c8532cfeac47a3068a69561e9c8715efdad3c642eb27c0756"},
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{file = "numpy-1.24.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:4199e7cfc307a778f72d293372736223e39ec9ac096ff0a2e64853b866a8e18a"},
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{file = "numpy-1.24.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:adbdce121896fd3a17a77ab0b0b5eedf05a9834a18699db6829a64e1dfccca7f"},
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||||
{file = "numpy-1.24.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:889b2cc88b837d86eda1b17008ebeb679d82875022200c6e8e4ce6cf549b7acb"},
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{file = "numpy-1.24.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f64bb98ac59b3ea3bf74b02f13836eb2e24e48e0ab0145bbda646295769bd780"},
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{file = "numpy-1.24.2-cp39-cp39-win32.whl", hash = "sha256:63e45511ee4d9d976637d11e6c9864eae50e12dc9598f531c035265991910468"},
|
||||
{file = "numpy-1.24.2-cp39-cp39-win_amd64.whl", hash = "sha256:a77d3e1163a7770164404607b7ba3967fb49b24782a6ef85d9b5f54126cc39e5"},
|
||||
{file = "numpy-1.24.2-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:92011118955724465fb6853def593cf397b4a1367495e0b59a7e69d40c4eb71d"},
|
||||
{file = "numpy-1.24.2-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f9006288bcf4895917d02583cf3411f98631275bc67cce355a7f39f8c14338fa"},
|
||||
{file = "numpy-1.24.2-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:150947adbdfeceec4e5926d956a06865c1c690f2fd902efede4ca6fe2e657c3f"},
|
||||
{file = "numpy-1.24.2.tar.gz", hash = "sha256:003a9f530e880cb2cd177cba1af7220b9aa42def9c4afc2a2fc3ee6be7eb2b22"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -2432,4 +2445,4 @@ files = [
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.10"
|
||||
content-hash = "0c50057af9ebbbe5c124c81758b41f05c05636739c3d1747e1bac74e75a046cb"
|
||||
content-hash = "f966f3979873eec2c3b13460067f5aa414c69aa8ab5cd3239c1cfa564fcb5deb"
|
||||
|
||||
@@ -1,8 +1,9 @@
|
||||
[tool.poetry]
|
||||
name = "python-jobspy"
|
||||
version = "1.0.3"
|
||||
version = "1.1.17"
|
||||
description = "Job scraper for LinkedIn, Indeed & ZipRecruiter"
|
||||
authors = ["Zachary Hampton <zachary@zacharysproducts.com>", "Cullen Watson <cullen@cullen.ai>"]
|
||||
authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
|
||||
homepage = "https://github.com/Bunsly/JobSpy"
|
||||
readme = "README.md"
|
||||
|
||||
packages = [
|
||||
@@ -15,6 +16,7 @@ requests = "^2.31.0"
|
||||
tls-client = "^0.2.1"
|
||||
beautifulsoup4 = "^4.12.2"
|
||||
pandas = "^2.1.0"
|
||||
NUMPY = "1.24.2"
|
||||
pydantic = "^2.3.0"
|
||||
|
||||
|
||||
|
||||
@@ -1,17 +1,19 @@
|
||||
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.linkedin import LinkedInScraper
|
||||
from .scrapers import (
|
||||
ScraperInput,
|
||||
Site,
|
||||
JobResponse,
|
||||
from .scrapers import ScraperInput, Site, JobResponse, Country
|
||||
from .scrapers.exceptions import (
|
||||
LinkedInException,
|
||||
IndeedException,
|
||||
ZipRecruiterException,
|
||||
)
|
||||
|
||||
|
||||
SCRAPER_MAPPING = {
|
||||
Site.LINKEDIN: LinkedInScraper,
|
||||
Site.INDEED: IndeedScraper,
|
||||
@@ -24,26 +26,45 @@ 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,
|
||||
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:
|
||||
site_name = _map_str_to_site(site_name)
|
||||
def get_enum_from_value(value_str):
|
||||
for job_type in JobType:
|
||||
if value_str in job_type.value:
|
||||
return job_type
|
||||
raise Exception(f"Invalid job type: {value_str}")
|
||||
|
||||
job_type = get_enum_from_value(job_type) if job_type else None
|
||||
|
||||
if type(site_name) == str:
|
||||
site_type = [_map_str_to_site(site_name)]
|
||||
else: #: if type(site_name) == list
|
||||
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,
|
||||
@@ -51,78 +72,104 @@ def scrape_jobs(
|
||||
job_type=job_type,
|
||||
easy_apply=easy_apply,
|
||||
results_wanted=results_wanted,
|
||||
offset=offset,
|
||||
)
|
||||
|
||||
def scrape_site(site: Site) -> Tuple[str, JobResponse]:
|
||||
scraper_class = SCRAPER_MAPPING[site]
|
||||
scraper = scraper_class()
|
||||
scraped_data: JobResponse = scraper.scrape(scraper_input)
|
||||
scraper = scraper_class(proxy=proxy)
|
||||
|
||||
try:
|
||||
scraped_data: JobResponse = scraper.scrape(scraper_input)
|
||||
except (LinkedInException, IndeedException, ZipRecruiterException) as lie:
|
||||
raise lie
|
||||
except Exception as e:
|
||||
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))
|
||||
else:
|
||||
raise e
|
||||
return site.value, scraped_data
|
||||
|
||||
results = {}
|
||||
for site in scraper_input.site_type:
|
||||
site_value, scraped_data = scrape_site(site)
|
||||
results[site_value] = scraped_data
|
||||
site_to_jobs_dict = {}
|
||||
|
||||
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()
|
||||
data["site"] = site
|
||||
job_data = job.dict()
|
||||
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
|
||||
)
|
||||
job_data["location"] = Location(**job_data["location"]).display_location()
|
||||
|
||||
# Formatting JobType
|
||||
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")
|
||||
compensation_obj = job_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")
|
||||
data["max_amount"] = compensation_obj.get("max_amount")
|
||||
data["currency"] = compensation_obj.get("currency", "USD")
|
||||
job_data["min_amount"] = compensation_obj.get("min_amount")
|
||||
job_data["max_amount"] = compensation_obj.get("max_amount")
|
||||
job_data["currency"] = compensation_obj.get("currency", "USD")
|
||||
else:
|
||||
data["interval"] = None
|
||||
data["min_amount"] = None
|
||||
data["max_amount"] = None
|
||||
data["currency"] = None
|
||||
job_data["interval"] = None
|
||||
job_data["min_amount"] = None
|
||||
job_data["max_amount"] = None
|
||||
job_data["currency"] = None
|
||||
|
||||
job_df = pd.DataFrame([data])
|
||||
dfs.append(job_df)
|
||||
job_df = pd.DataFrame([job_data])
|
||||
jobs_dfs.append(job_df)
|
||||
|
||||
if dfs:
|
||||
df = pd.concat(dfs, ignore_index=True)
|
||||
desired_order = [
|
||||
if jobs_dfs:
|
||||
jobs_df = pd.concat(jobs_dfs, ignore_index=True)
|
||||
desired_order: list[str] = [
|
||||
"job_url_hyper" if hyperlinks else "job_url",
|
||||
"site",
|
||||
"title",
|
||||
"company_name",
|
||||
"city",
|
||||
"state",
|
||||
"company",
|
||||
"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
|
||||
|
||||
@@ -6,24 +6,166 @@ from pydantic import BaseModel, validator
|
||||
|
||||
|
||||
class JobType(Enum):
|
||||
FULL_TIME = "fulltime"
|
||||
PART_TIME = "parttime"
|
||||
CONTRACT = "contract"
|
||||
TEMPORARY = "temporary"
|
||||
INTERNSHIP = "internship"
|
||||
FULL_TIME = (
|
||||
"fulltime",
|
||||
"períodointegral",
|
||||
"estágio/trainee",
|
||||
"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"
|
||||
NIGHTS = "nights"
|
||||
OTHER = "other"
|
||||
SUMMER = "summer"
|
||||
VOLUNTEER = "volunteer"
|
||||
PER_DIEM = ("perdiem",)
|
||||
NIGHTS = ("nights",)
|
||||
OTHER = ("other",)
|
||||
SUMMER = ("summer",)
|
||||
VOLUNTEER = ("volunteer",)
|
||||
|
||||
|
||||
class Country(Enum):
|
||||
ARGENTINA = ("argentina", "ar")
|
||||
AUSTRALIA = ("australia", "au")
|
||||
AUSTRIA = ("austria", "at")
|
||||
BAHRAIN = ("bahrain", "bh")
|
||||
BELGIUM = ("belgium", "be")
|
||||
BRAZIL = ("brazil", "br")
|
||||
CANADA = ("canada", "ca")
|
||||
CHILE = ("chile", "cl")
|
||||
CHINA = ("china", "cn")
|
||||
COLOMBIA = ("colombia", "co")
|
||||
COSTARICA = ("costa rica", "cr")
|
||||
CZECHREPUBLIC = ("czech republic", "cz")
|
||||
DENMARK = ("denmark", "dk")
|
||||
ECUADOR = ("ecuador", "ec")
|
||||
EGYPT = ("egypt", "eg")
|
||||
FINLAND = ("finland", "fi")
|
||||
FRANCE = ("france", "fr")
|
||||
GERMANY = ("germany", "de")
|
||||
GREECE = ("greece", "gr")
|
||||
HONGKONG = ("hong kong", "hk")
|
||||
HUNGARY = ("hungary", "hu")
|
||||
INDIA = ("india", "in")
|
||||
INDONESIA = ("indonesia", "id")
|
||||
IRELAND = ("ireland", "ie")
|
||||
ISRAEL = ("israel", "il")
|
||||
ITALY = ("italy", "it")
|
||||
JAPAN = ("japan", "jp")
|
||||
KUWAIT = ("kuwait", "kw")
|
||||
LUXEMBOURG = ("luxembourg", "lu")
|
||||
MALAYSIA = ("malaysia", "malaysia")
|
||||
MEXICO = ("mexico", "mx")
|
||||
MOROCCO = ("morocco", "ma")
|
||||
NETHERLANDS = ("netherlands", "nl")
|
||||
NEWZEALAND = ("new zealand", "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")
|
||||
SOUTHAFRICA = ("south africa", "za")
|
||||
SOUTHKOREA = ("south korea", "kr")
|
||||
SPAIN = ("spain", "es")
|
||||
SWEDEN = ("sweden", "se")
|
||||
SWITZERLAND = ("switzerland", "ch")
|
||||
TAIWAN = ("taiwan", "tw")
|
||||
THAILAND = ("thailand", "th")
|
||||
TURKEY = ("turkey", "tr")
|
||||
UKRAINE = ("ukraine", "ua")
|
||||
UNITEDARABEMIRATES = ("united arab emirates", "ae")
|
||||
UK = ("uk", "uk")
|
||||
USA = ("usa", "www")
|
||||
URUGUAY = ("uruguay", "uy")
|
||||
VENEZUELA = ("venezuela", "ve")
|
||||
VIETNAM = ("vietnam", "vn")
|
||||
|
||||
# internal for ziprecruiter
|
||||
US_CANADA = ("usa/ca", "www")
|
||||
|
||||
# internal for linkeind
|
||||
WORLDWIDE = ("worldwide", "www")
|
||||
|
||||
def __new__(cls, country, domain):
|
||||
obj = object.__new__(cls)
|
||||
obj._value_ = country
|
||||
obj.domain = domain
|
||||
return obj
|
||||
|
||||
@property
|
||||
def domain_value(self):
|
||||
return self.domain
|
||||
|
||||
@classmethod
|
||||
def from_string(cls, country_str: str):
|
||||
"""Convert a string to the corresponding Country enum."""
|
||||
country_str = country_str.strip().lower()
|
||||
for country in cls:
|
||||
if country.value == country_str:
|
||||
return country
|
||||
valid_countries = [country.value for country in cls]
|
||||
raise ValueError(
|
||||
f"Invalid country string: '{country_str}'. Valid countries (only include this param for Indeed) are: {', '.join(valid_countries)}"
|
||||
)
|
||||
|
||||
|
||||
class Location(BaseModel):
|
||||
country: str = "USA"
|
||||
city: str = None
|
||||
country: Country = 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):
|
||||
if self.country.value in ("usa", "uk"):
|
||||
location_parts.append(self.country.value.upper())
|
||||
else:
|
||||
location_parts.append(self.country.value.title())
|
||||
return ", ".join(location_parts)
|
||||
|
||||
|
||||
class CompensationInterval(Enum):
|
||||
YEARLY = "yearly"
|
||||
@@ -34,10 +176,10 @@ class CompensationInterval(Enum):
|
||||
|
||||
|
||||
class Compensation(BaseModel):
|
||||
interval: CompensationInterval
|
||||
min_amount: int = None
|
||||
max_amount: int = None
|
||||
currency: str = "USD"
|
||||
interval: Optional[CompensationInterval] = None
|
||||
min_amount: int | None = None
|
||||
max_amount: int | None = None
|
||||
currency: Optional[str] = "USD"
|
||||
|
||||
|
||||
class JobPost(BaseModel):
|
||||
@@ -46,29 +188,16 @@ class JobPost(BaseModel):
|
||||
job_url: str
|
||||
location: Optional[Location]
|
||||
|
||||
description: Optional[str] = None
|
||||
job_type: Optional[JobType] = None
|
||||
compensation: Optional[Compensation] = None
|
||||
date_posted: Optional[date] = None
|
||||
description: str | None = None
|
||||
job_type: list[JobType] | None = None
|
||||
compensation: Compensation | None = None
|
||||
date_posted: date | None = None
|
||||
benefits: str | None = None
|
||||
emails: list[str] | None = None
|
||||
num_urgent_words: int | None = None
|
||||
is_remote: bool | None = None
|
||||
# company_industry: str | None = None
|
||||
|
||||
|
||||
class JobResponse(BaseModel):
|
||||
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
|
||||
|
||||
@@ -1,12 +1,7 @@
|
||||
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"
|
||||
@@ -18,26 +13,20 @@ 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
|
||||
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:
|
||||
...
|
||||
|
||||
21
src/jobspy/scrapers/exceptions.py
Normal file
21
src/jobspy/scrapers/exceptions.py
Normal file
@@ -0,0 +1,21 @@
|
||||
"""
|
||||
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")
|
||||
@@ -1,15 +1,27 @@
|
||||
"""
|
||||
jobspy.scrapers.indeed
|
||||
~~~~~~~~~~~~~~~~~~~
|
||||
|
||||
This module contains routines to scrape Indeed.
|
||||
"""
|
||||
import re
|
||||
import math
|
||||
import io
|
||||
import json
|
||||
from datetime import datetime
|
||||
from typing import Optional
|
||||
|
||||
import tls_client
|
||||
import urllib.parse
|
||||
from bs4 import BeautifulSoup
|
||||
from bs4.element import Tag
|
||||
from concurrent.futures import ThreadPoolExecutor, Future
|
||||
|
||||
from ..exceptions import IndeedException
|
||||
from ..utils import (
|
||||
count_urgent_words,
|
||||
extract_emails_from_text,
|
||||
create_session,
|
||||
get_enum_from_job_type,
|
||||
)
|
||||
from ...jobs import (
|
||||
JobPost,
|
||||
Compensation,
|
||||
@@ -18,45 +30,45 @@ from ...jobs import (
|
||||
JobResponse,
|
||||
JobType,
|
||||
)
|
||||
from .. import Scraper, ScraperInput, Site, StatusException
|
||||
|
||||
|
||||
class ParsingException(Exception):
|
||||
pass
|
||||
from .. import Scraper, ScraperInput, Site
|
||||
|
||||
|
||||
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, url)
|
||||
super().__init__(site, proxy=proxy)
|
||||
|
||||
self.jobs_per_page = 15
|
||||
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
|
||||
"""
|
||||
|
||||
job_list = []
|
||||
self.country = scraper_input.country
|
||||
domain = self.country.domain_value
|
||||
self.url = f"https://{domain}.indeed.com"
|
||||
session = create_session(self.proxy)
|
||||
|
||||
params = {
|
||||
"q": scraper_input.search_term,
|
||||
"l": scraper_input.location,
|
||||
"radius": scraper_input.distance,
|
||||
"filter": 0,
|
||||
"start": 0 + page * 10,
|
||||
"start": scraper_input.offset + page * 10,
|
||||
}
|
||||
if scraper_input.distance:
|
||||
params["radius"] = scraper_input.distance
|
||||
|
||||
sc_values = []
|
||||
if scraper_input.is_remote:
|
||||
sc_values.append("attr(DSQF7)")
|
||||
@@ -65,14 +77,26 @@ class IndeedScraper(Scraper):
|
||||
|
||||
if sc_values:
|
||||
params["sc"] = "0kf:" + "".join(sc_values) + ";"
|
||||
response = session.get(self.url + "/jobs", params=params)
|
||||
|
||||
if response.status_code != 200 and response.status_code != 307:
|
||||
raise StatusException(response.status_code)
|
||||
try:
|
||||
response = session.get(
|
||||
f"{self.url}/jobs",
|
||||
headers=self.get_headers(),
|
||||
params=params,
|
||||
allow_redirects=True,
|
||||
timeout_seconds=10,
|
||||
)
|
||||
if response.status_code not in range(200, 400):
|
||||
raise IndeedException(
|
||||
f"bad response with status code: {response.status_code}"
|
||||
)
|
||||
except Exception as e:
|
||||
if "Proxy responded with" in str(e):
|
||||
raise IndeedException("bad proxy")
|
||||
raise IndeedException(str(e))
|
||||
|
||||
soup = BeautifulSoup(response.content, "html.parser")
|
||||
if "did not match any jobs" in str(soup):
|
||||
raise ParsingException("Search did not match any jobs")
|
||||
if "did not match any jobs" in response.text:
|
||||
raise IndeedException("Parsing exception: Search did not match any jobs")
|
||||
|
||||
jobs = IndeedScraper.parse_jobs(
|
||||
soup
|
||||
@@ -84,16 +108,14 @@ 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) -> JobPost | None:
|
||||
job_url = f'{self.url}/jobs/viewjob?jk={job["jobkey"]}'
|
||||
job_url_client = f'{self.url}/viewjob?jk={job["jobkey"]}'
|
||||
if job_url in self.seen_urls:
|
||||
return None
|
||||
|
||||
snippet_html = BeautifulSoup(job["snippet"], "html.parser")
|
||||
|
||||
extracted_salary = job.get("extractedSalary")
|
||||
compensation = None
|
||||
if extracted_salary:
|
||||
@@ -107,8 +129,8 @@ class IndeedScraper(Scraper):
|
||||
if interval in CompensationInterval.__members__:
|
||||
compensation = Compensation(
|
||||
interval=CompensationInterval[interval],
|
||||
min_amount=int(extracted_salary.get("max")),
|
||||
max_amount=int(extracted_salary.get("min")),
|
||||
min_amount=int(extracted_salary.get("min")),
|
||||
max_amount=int(extracted_salary.get("max")),
|
||||
currency=currency,
|
||||
)
|
||||
|
||||
@@ -117,12 +139,13 @@ class IndeedScraper(Scraper):
|
||||
date_posted = datetime.fromtimestamp(timestamp_seconds)
|
||||
date_posted = date_posted.strftime("%Y-%m-%d")
|
||||
|
||||
description = self.get_description(job_url, session)
|
||||
li_elements = snippet_html.find_all("li")
|
||||
if description is None and li_elements:
|
||||
description = " ".join(li.text for li in li_elements)
|
||||
description = self.get_description(job_url)
|
||||
with io.StringIO(job["snippet"]) as f:
|
||||
soup_io = BeautifulSoup(f, "html.parser")
|
||||
li_elements = soup_io.find_all("li")
|
||||
if description is None and li_elements:
|
||||
description = " ".join(li.text for li in li_elements)
|
||||
|
||||
first_li = snippet_html.find("li")
|
||||
job_post = JobPost(
|
||||
title=job["normTitle"],
|
||||
description=description,
|
||||
@@ -130,18 +153,24 @@ class IndeedScraper(Scraper):
|
||||
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)
|
||||
for job in jobs["metaData"]["mosaicProviderJobCardsModel"]["results"]
|
||||
executor.submit(process_job, job) for job in jobs
|
||||
]
|
||||
|
||||
job_list = [result.result() for result in job_results if result.result()]
|
||||
@@ -154,97 +183,108 @@ 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
|
||||
job_list, total_results = self.scrape_page(scraper_input, 0, session)
|
||||
#: get first page to initialize session
|
||||
job_list, total_results = self.scrape_page(scraper_input, 0)
|
||||
|
||||
with ThreadPoolExecutor(max_workers=10) as executor:
|
||||
futures: list[Future] = [
|
||||
executor.submit(self.scrape_page, scraper_input, page, session)
|
||||
for page in range(1, pages_to_process + 1)
|
||||
]
|
||||
with ThreadPoolExecutor(max_workers=1) as executor:
|
||||
futures: list[Future] = [
|
||||
executor.submit(self.scrape_page, scraper_input, page)
|
||||
for page in range(1, pages_to_process + 1)
|
||||
]
|
||||
|
||||
for future in futures:
|
||||
jobs, _ = future.result()
|
||||
for future in futures:
|
||||
jobs, _ = future.result()
|
||||
|
||||
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}",
|
||||
)
|
||||
job_list += jobs
|
||||
|
||||
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"][
|
||||
"jobInfoModel"
|
||||
]["sanitizedJobDescription"]
|
||||
soup = BeautifulSoup(raw_description, "html.parser")
|
||||
text_content = " ".join(soup.get_text().split()).strip()
|
||||
soup = BeautifulSoup(response.text, "html.parser")
|
||||
script_tag = soup.find(
|
||||
"script", text=lambda x: x and "window._initialData" in x
|
||||
)
|
||||
|
||||
if not script_tag:
|
||||
return None
|
||||
|
||||
script_code = script_tag.string
|
||||
match = re.search(r"window\._initialData\s*=\s*({.*?})\s*;", script_code, re.S)
|
||||
|
||||
if not match:
|
||||
return None
|
||||
|
||||
json_string = match.group(1)
|
||||
data = json.loads(json_string)
|
||||
try:
|
||||
job_description = data["jobInfoWrapperModel"]["jobInfoModel"][
|
||||
"sanitizedJobDescription"
|
||||
]
|
||||
except (KeyError, TypeError, IndexError):
|
||||
return None
|
||||
|
||||
soup = BeautifulSoup(
|
||||
job_description, "html.parser"
|
||||
)
|
||||
text_content = " ".join(
|
||||
soup.get_text(separator=" ").split()
|
||||
).strip()
|
||||
|
||||
return text_content
|
||||
|
||||
@staticmethod
|
||||
def get_job_type(job: dict) -> Optional[JobType]:
|
||||
def get_job_type(job: dict) -> list[JobType] | None:
|
||||
"""
|
||||
Parses the job to get JobTypeIndeed
|
||||
Parses the job to get list of job types
|
||||
:param job:
|
||||
:return:
|
||||
"""
|
||||
job_types: list[JobType] = []
|
||||
for taxonomy in job["taxonomyAttributes"]:
|
||||
if taxonomy["label"] == "job-types":
|
||||
if len(taxonomy["attributes"]) > 0:
|
||||
job_type_str = (
|
||||
taxonomy["attributes"][0]["label"]
|
||||
.replace("-", "_")
|
||||
.replace(" ", "_")
|
||||
.upper()
|
||||
)
|
||||
return JobType[job_type_str]
|
||||
return None
|
||||
for i in range(len(taxonomy["attributes"])):
|
||||
label = taxonomy["attributes"][i].get("label")
|
||||
if label:
|
||||
job_type_str = label.replace("-", "").replace(" ", "").lower()
|
||||
job_type = get_enum_from_job_type(job_type_str)
|
||||
if job_type:
|
||||
job_types.append(job_type)
|
||||
return job_types
|
||||
|
||||
@staticmethod
|
||||
def parse_jobs(soup: BeautifulSoup) -> dict:
|
||||
@@ -254,7 +294,7 @@ class IndeedScraper(Scraper):
|
||||
:return: jobs
|
||||
"""
|
||||
|
||||
def find_mosaic_script() -> Optional[Tag]:
|
||||
def find_mosaic_script() -> Tag | None:
|
||||
"""
|
||||
Finds jobcards script tag
|
||||
:return: script_tag
|
||||
@@ -281,9 +321,9 @@ 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"
|
||||
)
|
||||
|
||||
@@ -294,7 +334,7 @@ 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 +344,30 @@ class IndeedScraper(Scraper):
|
||||
data = json.loads(json_str)
|
||||
total_num_jobs = int(data["searchTitleBarModel"]["totalNumResults"])
|
||||
return total_num_jobs
|
||||
|
||||
@staticmethod
|
||||
def get_headers():
|
||||
return {
|
||||
"authority": "www.indeed.com",
|
||||
"accept": "*/*",
|
||||
"accept-language": "en-US,en;q=0.9",
|
||||
"referer": "https://www.indeed.com/viewjob?jk=fe6182337d72c7b1&tk=1hcbfcmd0k62t802&from=serp&vjs=3&advn=8132938064490989&adid=408692607&ad=-6NYlbfkN0A3Osc99MJFDKjquSk4WOGT28ALb_ad4QMtrHreCb9ICg6MiSVy9oDAp3evvOrI7Q-O9qOtQTg1EPbthP9xWtBN2cOuVeHQijxHjHpJC65TjDtftH3AXeINjBvAyDrE8DrRaAXl8LD3Fs1e_xuDHQIssdZ2Mlzcav8m5jHrA0fA64ZaqJV77myldaNlM7-qyQpy4AsJQfvg9iR2MY7qeC5_FnjIgjKIy_lNi9OPMOjGRWXA94CuvC7zC6WeiJmBQCHISl8IOBxf7EdJZlYdtzgae3593TFxbkd6LUwbijAfjax39aAuuCXy3s9C4YgcEP3TwEFGQoTpYu9Pmle-Ae1tHGPgsjxwXkgMm7Cz5mBBdJioglRCj9pssn-1u1blHZM4uL1nK9p1Y6HoFgPUU9xvKQTHjKGdH8d4y4ETyCMoNF4hAIyUaysCKdJKitC8PXoYaWhDqFtSMR4Jys8UPqUV&xkcb=SoDD-_M3JLQfWnQTDh0LbzkdCdPP&xpse=SoBa6_I3JLW9FlWZlB0PbzkdCdPP&sjdu=i6xVERweJM_pVUvgf-MzuaunBTY7G71J5eEX6t4DrDs5EMPQdODrX7Nn-WIPMezoqr5wA_l7Of-3CtoiUawcHw",
|
||||
"sec-ch-ua": '"Google Chrome";v="119", "Chromium";v="119", "Not?A_Brand";v="24"',
|
||||
"sec-ch-ua-mobile": "?0",
|
||||
"sec-ch-ua-platform": '"Windows"',
|
||||
"sec-fetch-dest": "empty",
|
||||
"sec-fetch-mode": "cors",
|
||||
"sec-fetch-site": "same-origin",
|
||||
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36",
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def is_remote_job(job: dict) -> bool:
|
||||
"""
|
||||
:param job:
|
||||
:return: bool
|
||||
"""
|
||||
for taxonomy in job.get("taxonomyAttributes", []):
|
||||
if taxonomy["label"] == "remote" and len(taxonomy["attributes"]) > 0:
|
||||
return True
|
||||
return False
|
||||
|
||||
@@ -1,29 +1,43 @@
|
||||
from typing import Optional, Tuple
|
||||
"""
|
||||
jobspy.scrapers.linkedin
|
||||
~~~~~~~~~~~~~~~~~~~
|
||||
|
||||
This module contains routines to scrape LinkedIn.
|
||||
"""
|
||||
from typing import Optional
|
||||
from datetime import datetime
|
||||
|
||||
import requests
|
||||
import time
|
||||
from requests.exceptions import ProxyError
|
||||
from concurrent.futures import ThreadPoolExecutor, as_completed
|
||||
from bs4 import BeautifulSoup
|
||||
from bs4.element import Tag
|
||||
from threading import Lock
|
||||
|
||||
from .. import Scraper, ScraperInput, Site
|
||||
from ..utils import count_urgent_words, extract_emails_from_text, get_enum_from_job_type
|
||||
from ..exceptions import LinkedInException
|
||||
from ...jobs import (
|
||||
JobPost,
|
||||
Location,
|
||||
JobResponse,
|
||||
JobType,
|
||||
Compensation,
|
||||
CompensationInterval,
|
||||
)
|
||||
|
||||
|
||||
class LinkedInScraper(Scraper):
|
||||
def __init__(self):
|
||||
MAX_RETRIES = 3
|
||||
DELAY = 10
|
||||
|
||||
def __init__(self, proxy: Optional[str] = None):
|
||||
"""
|
||||
Initializes LinkedInScraper with the LinkedIn job search url
|
||||
"""
|
||||
site = Site(Site.LINKEDIN)
|
||||
url = "https://www.linkedin.com"
|
||||
super().__init__(site, url)
|
||||
self.country = "worldwide"
|
||||
self.url = "https://www.linkedin.com"
|
||||
super().__init__(site, proxy=proxy)
|
||||
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||
"""
|
||||
@@ -33,9 +47,10 @@ 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 +59,147 @@ 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:
|
||||
params = {
|
||||
"keywords": scraper_input.search_term,
|
||||
"location": scraper_input.location,
|
||||
"distance": scraper_input.distance,
|
||||
"f_WT": 2 if scraper_input.is_remote else None,
|
||||
"f_JT": job_type_code(scraper_input.job_type)
|
||||
if scraper_input.job_type
|
||||
else None,
|
||||
"pageNum": page,
|
||||
"f_AL": "true" if scraper_input.easy_apply else None,
|
||||
}
|
||||
while len(job_list) < scraper_input.results_wanted and page < 1000:
|
||||
params = {
|
||||
"keywords": scraper_input.search_term,
|
||||
"location": scraper_input.location,
|
||||
"distance": scraper_input.distance,
|
||||
"f_WT": 2 if scraper_input.is_remote else None,
|
||||
"f_JT": job_type_code(scraper_input.job_type)
|
||||
if scraper_input.job_type
|
||||
else None,
|
||||
"pageNum": 0,
|
||||
page: page + scraper_input.offset,
|
||||
"f_AL": "true" if scraper_input.easy_apply else None,
|
||||
}
|
||||
|
||||
params = {k: v for k, v in params.items() if v is not None}
|
||||
response = session.get(
|
||||
f"{self.url}/jobs/search", params=params, allow_redirects=True
|
||||
params = {k: v for k, v in params.items() if v is not None}
|
||||
|
||||
params = {k: v for k, v in params.items() if v is not None}
|
||||
retries = 0
|
||||
while retries < self.MAX_RETRIES:
|
||||
try:
|
||||
response = requests.get(
|
||||
f"{self.url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
|
||||
params=params,
|
||||
allow_redirects=True,
|
||||
proxies=self.proxy,
|
||||
timeout=10,
|
||||
)
|
||||
response.raise_for_status()
|
||||
|
||||
break
|
||||
except requests.HTTPError as e:
|
||||
if hasattr(e, "response") and e.response is not None:
|
||||
if e.response.status_code == 429:
|
||||
time.sleep(self.DELAY)
|
||||
retries += 1
|
||||
continue
|
||||
else:
|
||||
raise LinkedInException(
|
||||
f"bad response status code: {e.response.status_code}"
|
||||
)
|
||||
else:
|
||||
raise
|
||||
except ProxyError as e:
|
||||
raise LinkedInException("bad proxy")
|
||||
except Exception as e:
|
||||
raise LinkedInException(str(e))
|
||||
else:
|
||||
# Raise an exception if the maximum number of retries is reached
|
||||
raise LinkedInException(
|
||||
"Max retries reached, failed to get a valid response"
|
||||
)
|
||||
|
||||
if response.status_code != 200:
|
||||
return JobResponse(
|
||||
success=False,
|
||||
error=f"Response returned {response.status_code}",
|
||||
)
|
||||
soup = BeautifulSoup(response.text, "html.parser")
|
||||
|
||||
soup = BeautifulSoup(response.text, "html.parser")
|
||||
with ThreadPoolExecutor(max_workers=5) as executor:
|
||||
futures = []
|
||||
for job_card in soup.find_all("div", class_="base-search-card"):
|
||||
job_url = None
|
||||
href_tag = job_card.find("a", class_="base-card__full-link")
|
||||
if href_tag and "href" in href_tag.attrs:
|
||||
href = href_tag.attrs["href"].split("?")[0]
|
||||
job_id = href.split("-")[-1]
|
||||
job_url = f"{self.url}/jobs/view/{job_id}"
|
||||
|
||||
if page == 0:
|
||||
job_count_text = soup.find(
|
||||
"span", class_="results-context-header__job-count"
|
||||
).text
|
||||
job_count = int("".join(filter(str.isdigit, job_count_text)))
|
||||
with url_lock:
|
||||
if job_url in seen_urls:
|
||||
continue
|
||||
seen_urls.add(job_url)
|
||||
|
||||
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}"
|
||||
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"
|
||||
futures.append(executor.submit(self.process_job, job_card, job_url))
|
||||
|
||||
company_tag = job_info.find("a", class_="hidden-nested-link")
|
||||
company = company_tag.text.strip() if company_tag else "N/A"
|
||||
|
||||
metadata_card = job_info.find(
|
||||
"div", class_="base-search-card__metadata"
|
||||
)
|
||||
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
|
||||
for future in as_completed(futures):
|
||||
try:
|
||||
job_post = future.result()
|
||||
if job_post:
|
||||
job_list.append(job_post)
|
||||
except Exception as e:
|
||||
raise LinkedInException(
|
||||
"Exception occurred while processing jobs"
|
||||
)
|
||||
page += 25
|
||||
|
||||
job_list = job_list[: scraper_input.results_wanted]
|
||||
job_response = JobResponse(
|
||||
success=True,
|
||||
jobs=job_list,
|
||||
total_results=job_count,
|
||||
)
|
||||
return job_response
|
||||
return JobResponse(jobs=job_list)
|
||||
|
||||
@staticmethod
|
||||
def get_description(job_page_url: str) -> Optional[str]:
|
||||
def process_job(self, job_card: Tag, job_url: str) -> Optional[JobPost]:
|
||||
title_tag = job_card.find("span", class_="sr-only")
|
||||
title = title_tag.get_text(strip=True) if title_tag else "N/A"
|
||||
|
||||
company_tag = job_card.find("h4", class_="base-search-card__subtitle")
|
||||
company_a_tag = company_tag.find("a") if company_tag else None
|
||||
company = company_a_tag.get_text(strip=True) if company_a_tag else "N/A"
|
||||
|
||||
metadata_card = job_card.find("div", class_="base-search-card__metadata")
|
||||
location = self.get_location(metadata_card)
|
||||
|
||||
datetime_tag = (
|
||||
metadata_card.find("time", class_="job-search-card__listdate")
|
||||
if metadata_card
|
||||
else None
|
||||
)
|
||||
date_posted = None
|
||||
if datetime_tag and "datetime" in datetime_tag.attrs:
|
||||
datetime_str = datetime_tag["datetime"]
|
||||
try:
|
||||
date_posted = datetime.strptime(datetime_str, "%Y-%m-%d")
|
||||
except Exception as e:
|
||||
date_posted = None
|
||||
benefits_tag = job_card.find("span", class_="result-benefits__text")
|
||||
benefits = " ".join(benefits_tag.get_text().split()) if benefits_tag else None
|
||||
|
||||
description, job_type = self.get_job_description(job_url)
|
||||
|
||||
return JobPost(
|
||||
title=title,
|
||||
description=description,
|
||||
company_name=company,
|
||||
location=location,
|
||||
date_posted=date_posted,
|
||||
job_url=job_url,
|
||||
# job_type=[JobType.FULL_TIME],
|
||||
job_type=job_type,
|
||||
benefits=benefits,
|
||||
emails=extract_emails_from_text(description) if description else None,
|
||||
num_urgent_words=count_urgent_words(description) if description else None,
|
||||
)
|
||||
|
||||
def get_job_description(
|
||||
self, job_page_url: str
|
||||
) -> tuple[None, None] | tuple[str | None, tuple[str | None, JobType | None]]:
|
||||
"""
|
||||
Retrieves job description by going to the job page url
|
||||
:param job_page_url:
|
||||
:return: description or None
|
||||
"""
|
||||
response = requests.get(job_page_url, allow_redirects=True)
|
||||
if response.status_code not in range(200, 400):
|
||||
try:
|
||||
response = requests.get(job_page_url, timeout=5, proxies=self.proxy)
|
||||
response.raise_for_status()
|
||||
except Exception as e:
|
||||
return None, None
|
||||
|
||||
soup = BeautifulSoup(response.text, "html.parser")
|
||||
@@ -166,19 +207,19 @@ class LinkedInScraper(Scraper):
|
||||
"div", class_=lambda x: x and "show-more-less-html__markup" in x
|
||||
)
|
||||
|
||||
text_content = None
|
||||
description = None
|
||||
if div_content:
|
||||
text_content = " ".join(div_content.get_text().split()).strip()
|
||||
description = " ".join(div_content.get_text().split()).strip()
|
||||
|
||||
def get_job_type(
|
||||
soup: BeautifulSoup,
|
||||
) -> Tuple[Optional[str], Optional[JobType]]:
|
||||
soup_job_type: BeautifulSoup,
|
||||
) -> 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 +236,17 @@ 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)]
|
||||
|
||||
return text_content, get_job_type(soup)
|
||||
return description, get_job_type(soup)
|
||||
|
||||
@staticmethod
|
||||
def get_location(metadata_card: Optional[Tag]) -> Location:
|
||||
def get_location(self, metadata_card: Optional[Tag]) -> Location:
|
||||
"""
|
||||
Extracts the location data from the job metadata card.
|
||||
:param metadata_card
|
||||
:return: location
|
||||
"""
|
||||
location = Location(country=self.country)
|
||||
if metadata_card is not None:
|
||||
location_tag = metadata_card.find(
|
||||
"span", class_="job-search-card__location"
|
||||
@@ -217,6 +258,7 @@ class LinkedInScraper(Scraper):
|
||||
location = Location(
|
||||
city=city,
|
||||
state=state,
|
||||
country=self.country,
|
||||
)
|
||||
|
||||
return location
|
||||
|
||||
56
src/jobspy/scrapers/utils.py
Normal file
56
src/jobspy/scrapers/utils.py
Normal file
@@ -0,0 +1,56 @@
|
||||
import re
|
||||
import tls_client
|
||||
from ..jobs import JobType
|
||||
|
||||
|
||||
def count_urgent_words(description: str) -> int:
|
||||
"""
|
||||
Count the number of urgent words or phrases in a job description.
|
||||
"""
|
||||
urgent_patterns = re.compile(
|
||||
r"\burgen(t|cy)|\bimmediate(ly)?\b|start asap|\bhiring (now|immediate(ly)?)\b",
|
||||
re.IGNORECASE,
|
||||
)
|
||||
matches = re.findall(urgent_patterns, description)
|
||||
count = len(matches)
|
||||
|
||||
return count
|
||||
|
||||
|
||||
def extract_emails_from_text(text: str) -> list[str] | None:
|
||||
if not text:
|
||||
return None
|
||||
email_regex = re.compile(r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}")
|
||||
return email_regex.findall(text)
|
||||
|
||||
|
||||
def create_session(proxy: str | None = None):
|
||||
"""
|
||||
Creates a tls client session
|
||||
|
||||
:return: A session object with or without proxies.
|
||||
"""
|
||||
session = tls_client.Session(
|
||||
client_identifier="chrome112",
|
||||
random_tls_extension_order=True,
|
||||
)
|
||||
session.proxies = proxy
|
||||
# TODO multiple proxies
|
||||
# if self.proxies:
|
||||
# session.proxies = {
|
||||
# "http": random.choice(self.proxies),
|
||||
# "https": random.choice(self.proxies),
|
||||
# }
|
||||
|
||||
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
|
||||
@@ -1,16 +1,24 @@
|
||||
import math
|
||||
import json
|
||||
import re
|
||||
from datetime import datetime
|
||||
from typing import Optional, Tuple
|
||||
from urllib.parse import urlparse, parse_qs
|
||||
"""
|
||||
jobspy.scrapers.ziprecruiter
|
||||
~~~~~~~~~~~~~~~~~~~
|
||||
|
||||
import tls_client
|
||||
This module contains routines to scrape ZipRecruiter.
|
||||
"""
|
||||
import math
|
||||
import time
|
||||
import re
|
||||
from datetime import datetime, date
|
||||
from typing import Optional, Tuple, Any
|
||||
from urllib.parse import urlparse, parse_qs, urlunparse
|
||||
|
||||
import requests
|
||||
from bs4 import BeautifulSoup
|
||||
from bs4.element import Tag
|
||||
from concurrent.futures import ThreadPoolExecutor, Future
|
||||
|
||||
from .. import Scraper, ScraperInput, Site, StatusException
|
||||
from .. import Scraper, ScraperInput, Site
|
||||
from ..exceptions import ZipRecruiterException
|
||||
from ..utils import count_urgent_words, extract_emails_from_text, create_session
|
||||
from ...jobs import (
|
||||
JobPost,
|
||||
Compensation,
|
||||
@@ -18,233 +26,107 @@ from ...jobs import (
|
||||
Location,
|
||||
JobResponse,
|
||||
JobType,
|
||||
Country,
|
||||
)
|
||||
|
||||
|
||||
class ZipRecruiterScraper(Scraper):
|
||||
def __init__(self):
|
||||
def __init__(self, proxy: Optional[str] = None):
|
||||
"""
|
||||
Initializes LinkedInScraper with the ZipRecruiter job search url
|
||||
"""
|
||||
site = Site(Site.ZIP_RECRUITER)
|
||||
url = "https://www.ziprecruiter.com"
|
||||
super().__init__(site, url)
|
||||
self.url = "https://www.ziprecruiter.com"
|
||||
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(
|
||||
self, scraper_input: ScraperInput, page: int
|
||||
) -> tuple[list[JobPost], int | None]:
|
||||
def find_jobs_in_page(self, scraper_input: ScraperInput, continue_token: Optional[str] = None) -> Tuple[list[JobPost], Optional[str]]:
|
||||
"""
|
||||
Scrapes a page of ZipRecruiter 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
|
||||
:return: jobs found on page
|
||||
"""
|
||||
params = self.add_params(scraper_input)
|
||||
if continue_token:
|
||||
params['continue'] = continue_token
|
||||
try:
|
||||
response = requests.get(
|
||||
f"https://api.ziprecruiter.com/jobs-app/jobs",
|
||||
headers=self.headers(),
|
||||
params=self.add_params(scraper_input),
|
||||
allow_redirects=True,
|
||||
timeout=10,
|
||||
)
|
||||
if response.status_code != 200:
|
||||
raise ZipRecruiterException(
|
||||
f"bad response status code: {response.status_code}"
|
||||
)
|
||||
except Exception as e:
|
||||
if "Proxy responded with non 200 code" in str(e):
|
||||
raise ZipRecruiterException("bad proxy")
|
||||
raise ZipRecruiterException(str(e))
|
||||
|
||||
job_list = []
|
||||
|
||||
job_type_value = None
|
||||
if scraper_input.job_type:
|
||||
if scraper_input.job_type.value == "fulltime":
|
||||
job_type_value = "full_time"
|
||||
elif scraper_input.job_type.value == "parttime":
|
||||
job_type_value = "part_time"
|
||||
else:
|
||||
job_type_value = scraper_input.job_type.value
|
||||
|
||||
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
|
||||
time.sleep(5)
|
||||
response_data = response.json()
|
||||
jobs_list = response_data.get("jobs", [])
|
||||
next_continue_token = response_data.get('continue', 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_results = [
|
||||
executor.submit(self.process_job, job)
|
||||
for job in jobs_list
|
||||
]
|
||||
|
||||
job_list = [result.result() for result in job_results if result.result()]
|
||||
|
||||
return job_list, job_count
|
||||
return job_list, next_continue_token
|
||||
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||
"""
|
||||
Scrapes ZipRecruiter for jobs with scraper_input criteria
|
||||
:param scraper_input:
|
||||
:return: job_response
|
||||
Scrapes ZipRecruiter for jobs with scraper_input criteria.
|
||||
:param scraper_input: Information about job search criteria.
|
||||
:return: JobResponse containing a list of jobs.
|
||||
"""
|
||||
job_list: list[JobPost] = []
|
||||
continue_token = None
|
||||
|
||||
pages_to_process = max(
|
||||
3, math.ceil(scraper_input.results_wanted / self.jobs_per_page)
|
||||
)
|
||||
max_pages = math.ceil(scraper_input.results_wanted / self.jobs_per_page)
|
||||
|
||||
try:
|
||||
#: get first page to initialize session
|
||||
job_list, total_results = self.scrape_page(scraper_input, 1)
|
||||
for page in range(1, max_pages + 1):
|
||||
if len(job_list) >= scraper_input.results_wanted:
|
||||
break
|
||||
|
||||
with ThreadPoolExecutor(max_workers=10) as executor:
|
||||
futures: list[Future] = [
|
||||
executor.submit(self.scrape_page, scraper_input, page)
|
||||
for page in range(2, pages_to_process + 1)
|
||||
]
|
||||
jobs_on_page, continue_token = self.find_jobs_in_page(scraper_input, continue_token)
|
||||
if jobs_on_page:
|
||||
job_list.extend(jobs_on_page)
|
||||
|
||||
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}",
|
||||
)
|
||||
|
||||
#: 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_list = job_list[:scraper_input.results_wanted]
|
||||
|
||||
job_response = JobResponse(
|
||||
success=True,
|
||||
jobs=job_list,
|
||||
total_results=total_results,
|
||||
)
|
||||
return job_response
|
||||
return JobResponse(jobs=job_list)
|
||||
|
||||
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
|
||||
def process_job(self, job: dict) -> JobPost:
|
||||
"""the most common type of jobs page on ZR"""
|
||||
title = job.get("name")
|
||||
job_url = job.get("job_url")
|
||||
|
||||
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"
|
||||
job.get("job_description", "").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,
|
||||
company = job['hiring_company'].get("name") if "hiring_company" in job else None
|
||||
location = Location(
|
||||
city=job.get("job_city"), state=job.get("job_state"), country='usa' if job.get("job_country") == 'US' else 'canada'
|
||||
)
|
||||
job_type = ZipRecruiterScraper.get_job_type_enum(
|
||||
job.get("employment_type", "").replace("_", "").lower()
|
||||
)
|
||||
|
||||
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
|
||||
@@ -255,53 +137,60 @@ class ZipRecruiterScraper(Scraper):
|
||||
date_posted = date_posted_obj.date()
|
||||
else:
|
||||
date_posted = date.today()
|
||||
job_url = job.get("JobURL")
|
||||
|
||||
return JobPost(
|
||||
title=title,
|
||||
description=description,
|
||||
company_name=company,
|
||||
location=location,
|
||||
job_type=job_type,
|
||||
compensation=compensation,
|
||||
compensation=Compensation(
|
||||
interval="yearly" if job.get("compensation_interval") == "annual" else job.get("compensation_interval") ,
|
||||
min_amount=int(job["compensation_min"]) if "compensation_min" in job else None,
|
||||
max_amount=int(job["compensation_max"]) if "compensation_max" in job else None,
|
||||
currency=job.get("compensation_currency"),
|
||||
),
|
||||
date_posted=date_posted,
|
||||
job_url=job_url,
|
||||
description=description,
|
||||
emails=extract_emails_from_text(description) if description else None,
|
||||
num_urgent_words=count_urgent_words(description) if description else None,
|
||||
)
|
||||
return job_post
|
||||
|
||||
@staticmethod
|
||||
def job_type_from_string(value: str) -> Optional[JobType]:
|
||||
if not value:
|
||||
return None
|
||||
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]
|
||||
return None
|
||||
|
||||
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}")
|
||||
@staticmethod
|
||||
def add_params(scraper_input) -> dict[str, str | Any]:
|
||||
params = {
|
||||
"search": scraper_input.search_term,
|
||||
"location": scraper_input.location,
|
||||
"form": "jobs-landing",
|
||||
}
|
||||
job_type_value = None
|
||||
if scraper_input.job_type:
|
||||
if scraper_input.job_type.value == "fulltime":
|
||||
job_type_value = "full_time"
|
||||
elif scraper_input.job_type.value == "parttime":
|
||||
job_type_value = "part_time"
|
||||
else:
|
||||
job_type_value = scraper_input.job_type.value
|
||||
|
||||
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
|
||||
if job_type_value:
|
||||
params[
|
||||
"refine_by_employment"
|
||||
] = f"employment_type:employment_type:{job_type_value}"
|
||||
|
||||
html_string = response.content
|
||||
soup_job = BeautifulSoup(html_string, "html.parser")
|
||||
if scraper_input.is_remote:
|
||||
params["refine_by_location_type"] = "only_remote"
|
||||
|
||||
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
|
||||
if scraper_input.distance:
|
||||
params["radius"] = scraper_input.distance
|
||||
|
||||
return params
|
||||
|
||||
@staticmethod
|
||||
def get_interval(interval_str: str):
|
||||
@@ -319,7 +208,7 @@ class ZipRecruiterScraper(Scraper):
|
||||
return CompensationInterval(interval_str)
|
||||
|
||||
@staticmethod
|
||||
def get_date_posted(job: BeautifulSoup) -> Optional[datetime.date]:
|
||||
def get_date_posted(job: Tag) -> Optional[datetime.date]:
|
||||
"""
|
||||
Extracts the date a job was posted
|
||||
:param job
|
||||
@@ -345,7 +234,7 @@ class ZipRecruiterScraper(Scraper):
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
def get_compensation(job: BeautifulSoup) -> Optional[Compensation]:
|
||||
def get_compensation(job: Tag) -> Optional[Compensation]:
|
||||
"""
|
||||
Parses the compensation tag from the job BeautifulSoup object
|
||||
:param job
|
||||
@@ -375,7 +264,10 @@ class ZipRecruiterScraper(Scraper):
|
||||
amounts.append(amount)
|
||||
|
||||
compensation = Compensation(
|
||||
interval=interval, min_amount=min(amounts), max_amount=max(amounts)
|
||||
interval=interval,
|
||||
min_amount=min(amounts),
|
||||
max_amount=max(amounts),
|
||||
currency="USD/CAD",
|
||||
)
|
||||
|
||||
return compensation
|
||||
@@ -383,7 +275,7 @@ class ZipRecruiterScraper(Scraper):
|
||||
return create_compensation_object(pay)
|
||||
|
||||
@staticmethod
|
||||
def get_location(job: BeautifulSoup) -> Location:
|
||||
def get_location(job: Tag) -> Location:
|
||||
"""
|
||||
Extracts the job location from BeatifulSoup object
|
||||
:param job:
|
||||
@@ -399,10 +291,7 @@ class ZipRecruiterScraper(Scraper):
|
||||
city, state = None, None
|
||||
else:
|
||||
city, state = None, None
|
||||
return Location(
|
||||
city=city,
|
||||
state=state,
|
||||
)
|
||||
return Location(city=city, state=state, country=Country.US_CANADA)
|
||||
|
||||
@staticmethod
|
||||
def headers() -> dict:
|
||||
@@ -411,5 +300,13 @@ class ZipRecruiterScraper(Scraper):
|
||||
:return: dict - Dictionary containing headers
|
||||
"""
|
||||
return {
|
||||
"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.97 Safari/537.36"
|
||||
'Host': 'api.ziprecruiter.com',
|
||||
'Cookie': 'ziprecruiter_browser=018188e0-045b-4ad7-aa50-627a6c3d43aa; ziprecruiter_session=5259b2219bf95b6d2299a1417424bc2edc9f4b38; SplitSV=2016-10-19%3AU2FsdGVkX19f9%2Bx70knxc%2FeR3xXR8lWoTcYfq5QjmLU%3D%0A; __cf_bm=qXim3DtLPbOL83GIp.ddQEOFVFTc1OBGPckiHYxcz3o-1698521532-0-AfUOCkgCZyVbiW1ziUwyefCfzNrJJTTKPYnif1FZGQkT60dMowmSU/Y/lP+WiygkFPW/KbYJmyc+MQSkkad5YygYaARflaRj51abnD+SyF9V; zglobalid=68d49bd5-0326-428e-aba8-8a04b64bc67c.af2d99ff7c03.653d61bb; ziprecruiter_browser=018188e0-045b-4ad7-aa50-627a6c3d43aa; ziprecruiter_session=5259b2219bf95b6d2299a1417424bc2edc9f4b38',
|
||||
'accept': '*/*',
|
||||
'x-zr-zva-override': '100000000;vid:ZT1huzm_EQlDTVEc',
|
||||
'x-pushnotificationid': '0ff4983d38d7fc5b3370297f2bcffcf4b3321c418f5c22dd152a0264707602a0',
|
||||
'x-deviceid': 'D77B3A92-E589-46A4-8A39-6EF6F1D86006',
|
||||
'user-agent': 'Job Search/87.0 (iPhone; CPU iOS 16_6_1 like Mac OS X)',
|
||||
'authorization': 'Basic YTBlZjMyZDYtN2I0Yy00MWVkLWEyODMtYTI1NDAzMzI0YTcyOg==',
|
||||
'accept-language': 'en-US,en;q=0.9'
|
||||
}
|
||||
|
||||
14
src/tests/test_all.py
Normal file
14
src/tests/test_all.py
Normal file
@@ -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"],
|
||||
search_term="software engineer",
|
||||
results_wanted=5,
|
||||
)
|
||||
|
||||
assert (
|
||||
isinstance(result, pd.DataFrame) and not result.empty
|
||||
), "Result should be a non-empty DataFrame"
|
||||
@@ -1,4 +1,5 @@
|
||||
from ..jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def test_indeed():
|
||||
@@ -6,4 +7,6 @@ def test_indeed():
|
||||
site_name="indeed",
|
||||
search_term="software engineer",
|
||||
)
|
||||
assert result is not None
|
||||
assert (
|
||||
isinstance(result, pd.DataFrame) and not result.empty
|
||||
), "Result should be a non-empty DataFrame"
|
||||
|
||||
@@ -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"
|
||||
|
||||
@@ -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"
|
||||
|
||||
Reference in New Issue
Block a user