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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 }}
|
||||
11
.gitignore
vendored
11
.gitignore
vendored
@@ -1,9 +1,10 @@
|
||||
/.idea
|
||||
**/.DS_Store
|
||||
/venv/
|
||||
/ven/
|
||||
/.idea
|
||||
**/__pycache__/
|
||||
**/.pytest_cache/
|
||||
/.ipynb_checkpoints/
|
||||
**/output/
|
||||
**/.DS_Store
|
||||
*.pyc
|
||||
.env
|
||||
dist
|
||||
/.ipynb_checkpoints/
|
||||
dist
|
||||
7
.pre-commit-config.yaml
Normal file
7
.pre-commit-config.yaml
Normal file
@@ -0,0 +1,7 @@
|
||||
repos:
|
||||
- repo: https://github.com/psf/black
|
||||
rev: 24.2.0
|
||||
hooks:
|
||||
- id: black
|
||||
language_version: python
|
||||
args: [--line-length=88, --quiet]
|
||||
@@ -1,701 +0,0 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "c3f21577-477d-451e-9914-5d67e8a89075",
|
||||
"metadata": {
|
||||
"scrolled": true
|
||||
},
|
||||
"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>Firmware Engineer</td>\n",
|
||||
" <td>Advanced Motion Controls</td>\n",
|
||||
" <td>Camarillo</td>\n",
|
||||
" <td>CA</td>\n",
|
||||
" <td>fulltime</td>\n",
|
||||
" <td>yearly</td>\n",
|
||||
" <td>145000</td>\n",
|
||||
" <td>110000</td>\n",
|
||||
" <td>https://www.indeed.com/viewjob?jk=a2e7077fdd3c...</td>\n",
|
||||
" <td>We are looking for an experienced Firmware Eng...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</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>2</th>\n",
|
||||
" <td>indeed</td>\n",
|
||||
" <td>Software Engineer</td>\n",
|
||||
" <td>Splunk</td>\n",
|
||||
" <td>Remote</td>\n",
|
||||
" <td>None</td>\n",
|
||||
" <td>fulltime</td>\n",
|
||||
" <td>yearly</td>\n",
|
||||
" <td>159500</td>\n",
|
||||
" <td>116000</td>\n",
|
||||
" <td>https://www.indeed.com/viewjob?jk=155495ca3f46...</td>\n",
|
||||
" <td>A little about us. Splunk is the key to enterp...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>indeed</td>\n",
|
||||
" <td>Development Operations Engineer</td>\n",
|
||||
" <td>Stratacache</td>\n",
|
||||
" <td>Dayton</td>\n",
|
||||
" <td>OH</td>\n",
|
||||
" <td>fulltime</td>\n",
|
||||
" <td>yearly</td>\n",
|
||||
" <td>90000</td>\n",
|
||||
" <td>83573</td>\n",
|
||||
" <td>https://www.indeed.com/viewjob?jk=77cf3540c06e...</td>\n",
|
||||
" <td>Stratacache, Inc. delivers in-store retail exp...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</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=7fadbb7c936f...</td>\n",
|
||||
" <td>Join a team recognized for leadership, innovat...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>5</th>\n",
|
||||
" <td>indeed</td>\n",
|
||||
" <td>Full Stack Developer</td>\n",
|
||||
" <td>Reinventing Geospatial, Inc. (RGi)</td>\n",
|
||||
" <td>Herndon</td>\n",
|
||||
" <td>VA</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=11b2b5b0dd44...</td>\n",
|
||||
" <td>Job Highlights As a Full Stack Software Engine...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>6</th>\n",
|
||||
" <td>indeed</td>\n",
|
||||
" <td>Software Engineer</td>\n",
|
||||
" <td>Workiva</td>\n",
|
||||
" <td>Remote</td>\n",
|
||||
" <td>None</td>\n",
|
||||
" <td>None</td>\n",
|
||||
" <td>yearly</td>\n",
|
||||
" <td>134000</td>\n",
|
||||
" <td>79000</td>\n",
|
||||
" <td>https://www.indeed.com/viewjob?jk=ec3ab6eb9253...</td>\n",
|
||||
" <td>Are you ready to embark on an exciting journey...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>7</th>\n",
|
||||
" <td>indeed</td>\n",
|
||||
" <td>Senior Software Engineer</td>\n",
|
||||
" <td>SciTec</td>\n",
|
||||
" <td>Boulder</td>\n",
|
||||
" <td>CO</td>\n",
|
||||
" <td>fulltime</td>\n",
|
||||
" <td>yearly</td>\n",
|
||||
" <td>164000</td>\n",
|
||||
" <td>93000</td>\n",
|
||||
" <td>https://www.indeed.com/viewjob?jk=781e4cf0cf6d...</td>\n",
|
||||
" <td>SciTec has been awarded multiple government co...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>8</th>\n",
|
||||
" <td>indeed</td>\n",
|
||||
" <td>Software Engineer</td>\n",
|
||||
" <td>Microsoft</td>\n",
|
||||
" <td></td>\n",
|
||||
" <td>None</td>\n",
|
||||
" <td>fulltime</td>\n",
|
||||
" <td>yearly</td>\n",
|
||||
" <td>182600</td>\n",
|
||||
" <td>94300</td>\n",
|
||||
" <td>https://www.indeed.com/viewjob?jk=21e05b9e9d96...</td>\n",
|
||||
" <td>At Microsoft we are seeking people who have a ...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>9</th>\n",
|
||||
" <td>indeed</td>\n",
|
||||
" <td>Software Engineer</td>\n",
|
||||
" <td>Avalon Healthcare Solutions</td>\n",
|
||||
" <td>Remote</td>\n",
|
||||
" <td>None</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=da35b9bb74a0...</td>\n",
|
||||
" <td>Avalon Healthcare Solutions, headquartered in ...</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/3701775201</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/3701772329</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/3701769637</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</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>17</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>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>(USA) Software Engineer III - Prototype Engine...</td>\n",
|
||||
" <td>Walmart</td>\n",
|
||||
" <td>Dallas</td>\n",
|
||||
" <td>TX</td>\n",
|
||||
" <td>None</td>\n",
|
||||
" <td>None</td>\n",
|
||||
" <td>None</td>\n",
|
||||
" <td>None</td>\n",
|
||||
" <td>https://click.appcast.io/track/hcgsw4k?cs=ngp&...</td>\n",
|
||||
" <td>We are currently seeking a highly skilled and ...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>21</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/jobs/ziprecruiter...</td>\n",
|
||||
" <td>We offer a hybrid work environment. Most US-ba...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>22</th>\n",
|
||||
" <td>zip_recruiter</td>\n",
|
||||
" <td>Software Developer</td>\n",
|
||||
" <td>Robert Half</td>\n",
|
||||
" <td>Corpus Christi</td>\n",
|
||||
" <td>TX</td>\n",
|
||||
" <td>fulltime</td>\n",
|
||||
" <td>yearly</td>\n",
|
||||
" <td>105000</td>\n",
|
||||
" <td>115000</td>\n",
|
||||
" <td>https://www.ziprecruiter.com/jobs/robert-half-...</td>\n",
|
||||
" <td>Robert Half has an opening for a Software Deve...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>23</th>\n",
|
||||
" <td>zip_recruiter</td>\n",
|
||||
" <td>Software Engineer</td>\n",
|
||||
" <td>Advantage Technical</td>\n",
|
||||
" <td>Ontario</td>\n",
|
||||
" <td>CA</td>\n",
|
||||
" <td>fulltime</td>\n",
|
||||
" <td>yearly</td>\n",
|
||||
" <td>100000</td>\n",
|
||||
" <td>150000</td>\n",
|
||||
" <td>https://www.ziprecruiter.com/jobs/advantage-te...</td>\n",
|
||||
" <td>New career opportunity available with major Ma...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>24</th>\n",
|
||||
" <td>zip_recruiter</td>\n",
|
||||
" <td>Software Developer</td>\n",
|
||||
" <td>Robert Half</td>\n",
|
||||
" <td>Tucson</td>\n",
|
||||
" <td>AZ</td>\n",
|
||||
" <td>temporary</td>\n",
|
||||
" <td>hourly</td>\n",
|
||||
" <td>47</td>\n",
|
||||
" <td>55</td>\n",
|
||||
" <td>https://www.ziprecruiter.com/jobs/robert-half-...</td>\n",
|
||||
" <td>Robert Half is accepting inquiries for a SQL S...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>25</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/jobs/ziprecruiter...</td>\n",
|
||||
" <td>We offer a hybrid work environment. Most US-ba...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>26</th>\n",
|
||||
" <td>zip_recruiter</td>\n",
|
||||
" <td>Software Developer IV</td>\n",
|
||||
" <td>Kforce Inc.</td>\n",
|
||||
" <td>Mountain View</td>\n",
|
||||
" <td>CA</td>\n",
|
||||
" <td>contract</td>\n",
|
||||
" <td>hourly</td>\n",
|
||||
" <td>55</td>\n",
|
||||
" <td>75</td>\n",
|
||||
" <td>https://www.kforce.com/Jobs/job.aspx?job=1696~...</td>\n",
|
||||
" <td>Kforce has a client that is seeking a Software...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>27</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/jobs/onestaff-med...</td>\n",
|
||||
" <td>Company Description: We are looking for a well...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>28</th>\n",
|
||||
" <td>zip_recruiter</td>\n",
|
||||
" <td>Senior Software Engineer</td>\n",
|
||||
" <td>RightStaff, Inc.</td>\n",
|
||||
" <td>Dallas</td>\n",
|
||||
" <td>TX</td>\n",
|
||||
" <td>fulltime</td>\n",
|
||||
" <td>yearly</td>\n",
|
||||
" <td>120000</td>\n",
|
||||
" <td>180000</td>\n",
|
||||
" <td>https://www.ziprecruiter.com/jobs/rightstaff-i...</td>\n",
|
||||
" <td>Job Description:We are seeking a talented and ...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>29</th>\n",
|
||||
" <td>zip_recruiter</td>\n",
|
||||
" <td>Software Developer - .Net Core - 12886</td>\n",
|
||||
" <td>Walker Elliott</td>\n",
|
||||
" <td>Dallas</td>\n",
|
||||
" <td>TX</td>\n",
|
||||
" <td>fulltime</td>\n",
|
||||
" <td>yearly</td>\n",
|
||||
" <td>105000</td>\n",
|
||||
" <td>130000</td>\n",
|
||||
" <td>https://www.ziprecruiter.com/jobs/walker-ellio...</td>\n",
|
||||
" <td>Our highly successful DFW based client has bee...</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" site title \\\n",
|
||||
"0 indeed Firmware Engineer \n",
|
||||
"1 indeed Computer Engineer \n",
|
||||
"2 indeed Software Engineer \n",
|
||||
"3 indeed Development Operations Engineer \n",
|
||||
"4 indeed Computer Engineer \n",
|
||||
"5 indeed Full Stack Developer \n",
|
||||
"6 indeed Software Engineer \n",
|
||||
"7 indeed Senior Software Engineer \n",
|
||||
"8 indeed Software Engineer \n",
|
||||
"9 indeed Software 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 \n",
|
||||
"17 linkedin Software Engineer - Early Career \n",
|
||||
"18 linkedin Full-Stack Software Engineer \n",
|
||||
"19 linkedin Software Engineer \n",
|
||||
"20 zip_recruiter (USA) Software Engineer III - Prototype Engine... \n",
|
||||
"21 zip_recruiter Software Engineer - New Grad \n",
|
||||
"22 zip_recruiter Software Developer \n",
|
||||
"23 zip_recruiter Software Engineer \n",
|
||||
"24 zip_recruiter Software Developer \n",
|
||||
"25 zip_recruiter Full Stack Software Engineer \n",
|
||||
"26 zip_recruiter Software Developer IV \n",
|
||||
"27 zip_recruiter Software Developer | Onsite | Omaha, NE - Omaha \n",
|
||||
"28 zip_recruiter Senior Software Engineer \n",
|
||||
"29 zip_recruiter Software Developer - .Net Core - 12886 \n",
|
||||
"\n",
|
||||
" company_name city state job_type \\\n",
|
||||
"0 Advanced Motion Controls Camarillo CA fulltime \n",
|
||||
"1 Honeywell None fulltime \n",
|
||||
"2 Splunk Remote None fulltime \n",
|
||||
"3 Stratacache Dayton OH fulltime \n",
|
||||
"4 Honeywell None fulltime \n",
|
||||
"5 Reinventing Geospatial, Inc. (RGi) Herndon VA fulltime \n",
|
||||
"6 Workiva Remote None None \n",
|
||||
"7 SciTec Boulder CO fulltime \n",
|
||||
"8 Microsoft None fulltime \n",
|
||||
"9 Avalon Healthcare Solutions Remote None None \n",
|
||||
"10 Fieldguide San Francisco CA fulltime \n",
|
||||
"11 Lockheed Martin Sunnyvale CA fulltime \n",
|
||||
"12 Lockheed Martin Edwards CA fulltime \n",
|
||||
"13 Lockheed Martin Fort Worth TX fulltime \n",
|
||||
"14 Lockheed Martin Fort Worth TX fulltime \n",
|
||||
"15 Lockheed Martin Fort Worth TX fulltime \n",
|
||||
"16 SpiderOak Austin TX fulltime \n",
|
||||
"17 Lockheed Martin Fort Worth TX fulltime \n",
|
||||
"18 Rain New York NY fulltime \n",
|
||||
"19 Nike Portland OR contract \n",
|
||||
"20 Walmart Dallas TX None \n",
|
||||
"21 ZipRecruiter Santa Monica CA fulltime \n",
|
||||
"22 Robert Half Corpus Christi TX fulltime \n",
|
||||
"23 Advantage Technical Ontario CA fulltime \n",
|
||||
"24 Robert Half Tucson AZ temporary \n",
|
||||
"25 ZipRecruiter Phoenix AZ fulltime \n",
|
||||
"26 Kforce Inc. Mountain View CA contract \n",
|
||||
"27 OneStaff Medical Omaha NE fulltime \n",
|
||||
"28 RightStaff, Inc. Dallas TX fulltime \n",
|
||||
"29 Walker Elliott Dallas TX fulltime \n",
|
||||
"\n",
|
||||
" interval min_amount max_amount \\\n",
|
||||
"0 yearly 145000 110000 \n",
|
||||
"1 None None None \n",
|
||||
"2 yearly 159500 116000 \n",
|
||||
"3 yearly 90000 83573 \n",
|
||||
"4 None None None \n",
|
||||
"5 None None None \n",
|
||||
"6 yearly 134000 79000 \n",
|
||||
"7 yearly 164000 93000 \n",
|
||||
"8 yearly 182600 94300 \n",
|
||||
"9 None None None \n",
|
||||
"10 yearly None None \n",
|
||||
"11 yearly None None \n",
|
||||
"12 yearly None None \n",
|
||||
"13 yearly None None \n",
|
||||
"14 yearly None None \n",
|
||||
"15 yearly None None \n",
|
||||
"16 yearly None None \n",
|
||||
"17 yearly None None \n",
|
||||
"18 yearly None None \n",
|
||||
"19 yearly None None \n",
|
||||
"20 None None None \n",
|
||||
"21 yearly 130000 150000 \n",
|
||||
"22 yearly 105000 115000 \n",
|
||||
"23 yearly 100000 150000 \n",
|
||||
"24 hourly 47 55 \n",
|
||||
"25 yearly 105000 145000 \n",
|
||||
"26 hourly 55 75 \n",
|
||||
"27 yearly 60000 110000 \n",
|
||||
"28 yearly 120000 180000 \n",
|
||||
"29 yearly 105000 130000 \n",
|
||||
"\n",
|
||||
" job_url \\\n",
|
||||
"0 https://www.indeed.com/viewjob?jk=a2e7077fdd3c... \n",
|
||||
"1 https://www.indeed.com/viewjob?jk=5a1da623ee75... \n",
|
||||
"2 https://www.indeed.com/viewjob?jk=155495ca3f46... \n",
|
||||
"3 https://www.indeed.com/viewjob?jk=77cf3540c06e... \n",
|
||||
"4 https://www.indeed.com/viewjob?jk=7fadbb7c936f... \n",
|
||||
"5 https://www.indeed.com/viewjob?jk=11b2b5b0dd44... \n",
|
||||
"6 https://www.indeed.com/viewjob?jk=ec3ab6eb9253... \n",
|
||||
"7 https://www.indeed.com/viewjob?jk=781e4cf0cf6d... \n",
|
||||
"8 https://www.indeed.com/viewjob?jk=21e05b9e9d96... \n",
|
||||
"9 https://www.indeed.com/viewjob?jk=da35b9bb74a0... \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/3701775201 \n",
|
||||
"14 https://www.linkedin.com/jobs/view/3701772329 \n",
|
||||
"15 https://www.linkedin.com/jobs/view/3701769637 \n",
|
||||
"16 https://www.linkedin.com/jobs/view/3707174719 \n",
|
||||
"17 https://www.linkedin.com/jobs/view/3701770659 \n",
|
||||
"18 https://www.linkedin.com/jobs/view/3696158877 \n",
|
||||
"19 https://www.linkedin.com/jobs/view/3693340247 \n",
|
||||
"20 https://click.appcast.io/track/hcgsw4k?cs=ngp&... \n",
|
||||
"21 https://www.ziprecruiter.com/jobs/ziprecruiter... \n",
|
||||
"22 https://www.ziprecruiter.com/jobs/robert-half-... \n",
|
||||
"23 https://www.ziprecruiter.com/jobs/advantage-te... \n",
|
||||
"24 https://www.ziprecruiter.com/jobs/robert-half-... \n",
|
||||
"25 https://www.ziprecruiter.com/jobs/ziprecruiter... \n",
|
||||
"26 https://www.kforce.com/Jobs/job.aspx?job=1696~... \n",
|
||||
"27 https://www.ziprecruiter.com/jobs/onestaff-med... \n",
|
||||
"28 https://www.ziprecruiter.com/jobs/rightstaff-i... \n",
|
||||
"29 https://www.ziprecruiter.com/jobs/walker-ellio... \n",
|
||||
"\n",
|
||||
" description \n",
|
||||
"0 We are looking for an experienced Firmware Eng... \n",
|
||||
"1 Join a team recognized for leadership, innovat... \n",
|
||||
"2 A little about us. Splunk is the key to enterp... \n",
|
||||
"3 Stratacache, Inc. delivers in-store retail exp... \n",
|
||||
"4 Join a team recognized for leadership, innovat... \n",
|
||||
"5 Job Highlights As a Full Stack Software Engine... \n",
|
||||
"6 Are you ready to embark on an exciting journey... \n",
|
||||
"7 SciTec has been awarded multiple government co... \n",
|
||||
"8 At Microsoft we are seeking people who have a ... \n",
|
||||
"9 Avalon Healthcare Solutions, headquartered in ... \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 We're only as strong as our weakest link.In th... \n",
|
||||
"17 Description:By bringing together people that u... \n",
|
||||
"18 Rain’s mission is to create the fastest and ea... \n",
|
||||
"19 Work options: FlexibleWe consider remote, on-p... \n",
|
||||
"20 We are currently seeking a highly skilled and ... \n",
|
||||
"21 We offer a hybrid work environment. Most US-ba... \n",
|
||||
"22 Robert Half has an opening for a Software Deve... \n",
|
||||
"23 New career opportunity available with major Ma... \n",
|
||||
"24 Robert Half is accepting inquiries for a SQL S... \n",
|
||||
"25 We offer a hybrid work environment. Most US-ba... \n",
|
||||
"26 Kforce has a client that is seeking a Software... \n",
|
||||
"27 Company Description: We are looking for a well... \n",
|
||||
"28 Job Description:We are seeking a talented and ... \n",
|
||||
"29 Our highly successful DFW based client has bee... "
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from jobspy import scrape_jobs\n",
|
||||
"import pandas as pd\n",
|
||||
"\n",
|
||||
"jobs: pd.DataFrame = scrape_jobs(\n",
|
||||
" site_name=[\"indeed\", \"linkedin\", \"zip_recruiter\"],\n",
|
||||
" search_term=\"software engineer\",\n",
|
||||
" results_wanted=10\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"if jobs.empty:\n",
|
||||
" print(\"No jobs found.\")\n",
|
||||
"else:\n",
|
||||
" # 1 print\n",
|
||||
" 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) # set to 0 to see full job url / desc\n",
|
||||
" print(jobs)\n",
|
||||
"\n",
|
||||
" # 2 display in Jupyter Notebook\n",
|
||||
" display(jobs)\n",
|
||||
"\n",
|
||||
" # 3 output to csv\n",
|
||||
" jobs.to_csv('jobs.csv', index=False)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "efd667ef-fdf0-452a-b5e5-ce6825755be7",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "1574dc17-0a42-4655-964f-5c03a6d3deb0",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "my-poetry-env",
|
||||
"language": "python",
|
||||
"name": "my-poetry-env"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.10.11"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
182
README.md
182
README.md
@@ -1,48 +1,55 @@
|
||||
# <img src="https://github.com/cullenwatson/JobSpy/assets/78247585/2f61a059-9647-4a9c-bfb9-e3a9448bdc6a" style="vertical-align: sub; margin-right: 5px;"> JobSpy
|
||||
<img src="https://github.com/cullenwatson/JobSpy/assets/78247585/ae185b7e-e444-4712-8bb9-fa97f53e896b" width="400">
|
||||
|
||||
**JobSpy** is a simple, yet comprehensive, job scraping library.
|
||||
|
||||
**Not technical?** Try out the web scraping tool on our site at [usejobspy.com](https://usejobspy.com).
|
||||
|
||||
*Looking to build a data-focused software product?* **[Book a call](https://bunsly.com/)** *to
|
||||
work with us.*
|
||||
|
||||
## Features
|
||||
|
||||
- Scrapes job postings from **LinkedIn**, **Indeed** & **ZipRecruiter** simultaneously
|
||||
- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, & **ZipRecruiter** simultaneously
|
||||
- Aggregates the job postings in a Pandas DataFrame
|
||||
- Proxy support
|
||||
|
||||
[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 -U python-jobspy
|
||||
```
|
||||
|
||||
_Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_
|
||||
|
||||
### Usage
|
||||
|
||||
```python
|
||||
import csv
|
||||
from jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
jobs: pd.DataFrame = scrape_jobs(
|
||||
site_name=["indeed", "linkedin", "zip_recruiter"],
|
||||
jobs = scrape_jobs(
|
||||
site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"],
|
||||
search_term="software engineer",
|
||||
results_wanted=10
|
||||
location="Dallas, TX",
|
||||
results_wanted=20,
|
||||
hours_old=72, # (only Linkedin/Indeed is hour specific, others round up to days old)
|
||||
country_indeed='USA', # only needed for indeed / glassdoor
|
||||
# linkedin_fetch_description=True # get full description and direct job url for linkedin (slower)
|
||||
)
|
||||
|
||||
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", quoting=csv.QUOTE_NONNUMERIC, escapechar="\\", index=False) # to_xlsx
|
||||
```
|
||||
|
||||
### Output
|
||||
|
||||
```
|
||||
SITE TITLE COMPANY_NAME CITY STATE JOB_TYPE INTERVAL MIN_AMOUNT MAX_AMOUNT JOB_URL DESCRIPTION
|
||||
SITE TITLE COMPANY 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!...
|
||||
indeed Senior Software Engineer TherapyNotes.com Philadelphia PA fulltime yearly 135000 110000 https://www.indeed.com/viewjob?jk=da39574a40cb... About Us TherapyNotes is the national leader i...
|
||||
linkedin Software Engineer - Early Career Lockheed Martin Sunnyvale CA fulltime yearly None None https://www.linkedin.com/jobs/view/3693012711 Description:By bringing together people that u...
|
||||
@@ -50,49 +57,122 @@ 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
|
||||
└── search_term (str)
|
||||
Optional
|
||||
├── location (int)
|
||||
├── distance (int): in miles
|
||||
├── job_type (enum): fulltime, parttime, internship, contract
|
||||
├── site_name (list|str): linkedin, zip_recruiter, indeed, glassdoor (default is all four)
|
||||
├── search_term (str)
|
||||
├── location (str)
|
||||
├── distance (int): in miles, default 50
|
||||
├── job_type (str): fulltime, parttime, internship, contract
|
||||
├── proxy (str): in format 'http://user:pass@host:port'
|
||||
├── 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
|
||||
├── results_wanted (int): number of job results to retrieve for each site specified in 'site_name'
|
||||
├── easy_apply (bool): filters for jobs that are hosted on the job board site (LinkedIn & Indeed do not allow pairing this with hours_old)
|
||||
├── linkedin_fetch_description (bool): fetches full description and direct job url for LinkedIn (slower)
|
||||
├── linkedin_company_ids (list[int]): searches for linkedin jobs with specific company ids
|
||||
├── description_format (str): markdown, html (Format type of the job descriptions. Default is markdown.)
|
||||
├── country_indeed (str): filters the country on Indeed (see below for correct spelling)
|
||||
├── offset (int): starts the search from an offset (e.g. 25 will start the search from the 25th result)
|
||||
├── hours_old (int): filters jobs by the number of hours since the job was posted (ZipRecruiter and Glassdoor round up to next day. If you use this on Indeed, it will not filter by job_type/is_remote/easy_apply)
|
||||
├── verbose (int) {0, 1, 2}: Controls the verbosity of the runtime printouts (0 prints only errors, 1 is errors+warnings, 2 is all logs. Default is 2.)
|
||||
├── hyperlinks (bool): Whether to turn `job_url`s into hyperlinks. Default is false.
|
||||
```
|
||||
|
||||
### JobPost Schema
|
||||
|
||||
```plaintext
|
||||
JobPost
|
||||
├── title (str)
|
||||
├── company_name (str)
|
||||
├── company (str)
|
||||
├── company_url (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)
|
||||
└── is_remote (bool)
|
||||
|
||||
Indeed specific
|
||||
├── company_country (str)
|
||||
└── company_addresses (str)
|
||||
└── company_industry (str)
|
||||
└── company_employees_label (str)
|
||||
└── company_revenue_label (str)
|
||||
└── company_description (str)
|
||||
└── ceo_name (str)
|
||||
└── ceo_photo_url (str)
|
||||
└── logo_photo_url (str)
|
||||
└── banner_photo_url (str)
|
||||
```
|
||||
|
||||
## Supported Countries for Job Searching
|
||||
|
||||
### FAQ
|
||||
|
||||
#### Encountering issues with your queries?
|
||||
|
||||
Try reducing the number of `results_wanted` and/or broadening the filters. If problems persist, please submit an issue.
|
||||
|
||||
#### Received a response code 429?
|
||||
You have been blocked by the job board site for sending too many requests. ZipRecruiter seems to be the most aggressive at the moment. Consider waiting a few seconds, or try using a VPN. Proxy support coming soon.
|
||||
|
||||
### **LinkedIn**
|
||||
|
||||
LinkedIn searches globally & uses only the `location` parameter.
|
||||
|
||||
### **ZipRecruiter**
|
||||
|
||||
ZipRecruiter searches for jobs in **US/Canada** & uses only the `location` parameter.
|
||||
|
||||
### **Indeed / Glassdoor**
|
||||
|
||||
Indeed & Glassdoor supports most countries, but the `country_indeed` parameter is required. Additionally, use the `location`
|
||||
parameter to narrow down the location, e.g. city & state if necessary.
|
||||
|
||||
You can specify the following countries when searching on Indeed (use the exact name, * indicates support for Glassdoor):
|
||||
|
||||
| | | | |
|
||||
|----------------------|--------------|------------|----------------|
|
||||
| Argentina | Australia* | Austria* | Bahrain |
|
||||
| Belgium* | Brazil* | Canada* | Chile |
|
||||
| China | Colombia | Costa Rica | Czech Republic |
|
||||
| Denmark | Ecuador | Egypt | Finland |
|
||||
| France* | Germany* | Greece | Hong Kong* |
|
||||
| Hungary | India* | Indonesia | Ireland* |
|
||||
| Israel | Italy* | Japan | Kuwait |
|
||||
| Luxembourg | Malaysia | Mexico* | Morocco |
|
||||
| Netherlands* | New Zealand* | Nigeria | Norway |
|
||||
| Oman | Pakistan | Panama | Peru |
|
||||
| Philippines | Poland | Portugal | Qatar |
|
||||
| Romania | Saudi Arabia | Singapore* | South Africa |
|
||||
| South Korea | Spain* | Sweden | Switzerland* |
|
||||
| Taiwan | Thailand | Turkey | Ukraine |
|
||||
| United Arab Emirates | UK* | USA* | Uruguay |
|
||||
| Venezuela | Vietnam* | | |
|
||||
|
||||
|
||||
## Notes
|
||||
* Indeed is the best scraper currently with no rate limiting.
|
||||
* All the job board endpoints are capped at around 1000 jobs on a given search.
|
||||
* LinkedIn is the most restrictive and usually rate limits around the 10th page.
|
||||
|
||||
## 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](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. All of the job board sites are aggressive with blocking. We recommend:
|
||||
|
||||
- Waiting some time between scrapes (site-dependent).
|
||||
- Trying a VPN or proxy to change your IP address.
|
||||
|
||||
---
|
||||
|
||||
30
examples/JobSpy_AllSites.py
Normal file
30
examples/JobSpy_AllSites.py
Normal file
@@ -0,0 +1,30 @@
|
||||
from jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
jobs: pd.DataFrame = scrape_jobs(
|
||||
site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"],
|
||||
search_term="software engineer",
|
||||
location="Dallas, TX",
|
||||
results_wanted=25, # be wary the higher it is, the more likey you'll get blocked (rotating proxy can help tho)
|
||||
country_indeed="USA",
|
||||
# proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
|
||||
)
|
||||
|
||||
# formatting for pandas
|
||||
pd.set_option("display.max_columns", None)
|
||||
pd.set_option("display.max_rows", None)
|
||||
pd.set_option("display.width", None)
|
||||
pd.set_option("display.max_colwidth", 50) # set to 0 to see full job url / desc
|
||||
|
||||
# 1: output to console
|
||||
print(jobs)
|
||||
|
||||
# 2: output to .csv
|
||||
jobs.to_csv("./jobs.csv", index=False)
|
||||
print("outputted to jobs.csv")
|
||||
|
||||
# 3: output to .xlsx
|
||||
# jobs.to_xlsx('jobs.xlsx', index=False)
|
||||
|
||||
# 4: display in Jupyter Notebook (1. pip install jupyter 2. jupyter notebook)
|
||||
# display(jobs)
|
||||
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
|
||||
}
|
||||
78
examples/JobSpy_LongScrape.py
Normal file
78
examples/JobSpy_LongScrape.py
Normal file
@@ -0,0 +1,78 @@
|
||||
from jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
import os
|
||||
import time
|
||||
|
||||
# creates csv a new filename if the jobs.csv already exists.
|
||||
csv_filename = "jobs.csv"
|
||||
counter = 1
|
||||
while os.path.exists(csv_filename):
|
||||
csv_filename = f"jobs_{counter}.csv"
|
||||
counter += 1
|
||||
|
||||
# results wanted and offset
|
||||
results_wanted = 1000
|
||||
offset = 0
|
||||
|
||||
all_jobs = []
|
||||
|
||||
# max retries
|
||||
max_retries = 3
|
||||
|
||||
# nuumber of results at each iteration
|
||||
results_in_each_iteration = 30
|
||||
|
||||
while len(all_jobs) < results_wanted:
|
||||
retry_count = 0
|
||||
while retry_count < max_retries:
|
||||
print("Doing from", offset, "to", offset + results_in_each_iteration, "jobs")
|
||||
try:
|
||||
jobs = scrape_jobs(
|
||||
site_name=["indeed"],
|
||||
search_term="software engineer",
|
||||
# New York, NY
|
||||
# Dallas, TX
|
||||
# Los Angeles, CA
|
||||
location="Los Angeles, CA",
|
||||
results_wanted=min(
|
||||
results_in_each_iteration, results_wanted - len(all_jobs)
|
||||
),
|
||||
country_indeed="USA",
|
||||
offset=offset,
|
||||
# proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
|
||||
)
|
||||
|
||||
# Add the scraped jobs to the list
|
||||
all_jobs.extend(jobs.to_dict("records"))
|
||||
|
||||
# Increment the offset for the next page of results
|
||||
offset += results_in_each_iteration
|
||||
|
||||
# Add a delay to avoid rate limiting (you can adjust the delay time as needed)
|
||||
print(f"Scraped {len(all_jobs)} jobs")
|
||||
print("Sleeping secs", 100 * (retry_count + 1))
|
||||
time.sleep(100 * (retry_count + 1)) # Sleep for 2 seconds between requests
|
||||
|
||||
break # Break out of the retry loop if successful
|
||||
except Exception as e:
|
||||
print(f"Error: {e}")
|
||||
retry_count += 1
|
||||
print("Sleeping secs before retry", 100 * (retry_count + 1))
|
||||
time.sleep(100 * (retry_count + 1))
|
||||
if retry_count >= max_retries:
|
||||
print("Max retries reached. Exiting.")
|
||||
break
|
||||
|
||||
# DataFrame from the collected job data
|
||||
jobs_df = pd.DataFrame(all_jobs)
|
||||
|
||||
# Formatting
|
||||
pd.set_option("display.max_columns", None)
|
||||
pd.set_option("display.max_rows", None)
|
||||
pd.set_option("display.width", None)
|
||||
pd.set_option("display.max_colwidth", 50)
|
||||
|
||||
print(jobs_df)
|
||||
|
||||
jobs_df.to_csv(csv_filename, index=False)
|
||||
print(f"Outputted to {csv_filename}")
|
||||
2262
poetry.lock
generated
2262
poetry.lock
generated
File diff suppressed because it is too large
Load Diff
@@ -1,8 +1,9 @@
|
||||
[tool.poetry]
|
||||
name = "python-jobspy"
|
||||
version = "1.0.1"
|
||||
description = "Job scraper for LinkedIn, Indeed & ZipRecruiter"
|
||||
authors = ["Zachary Hampton <zachary@zacharysproducts.com>", "Cullen Watson <cullen@cullen.ai>"]
|
||||
version = "1.1.52"
|
||||
description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
|
||||
authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
|
||||
homepage = "https://github.com/Bunsly/JobSpy"
|
||||
readme = "README.md"
|
||||
|
||||
packages = [
|
||||
@@ -12,16 +13,24 @@ packages = [
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.10"
|
||||
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"
|
||||
tls-client = "^1.0.1"
|
||||
markdownify = "^0.11.6"
|
||||
regex = "^2024.4.28"
|
||||
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
pytest = "^7.4.1"
|
||||
jupyter = "^1.0.0"
|
||||
black = "*"
|
||||
pre-commit = "*"
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[tool.black]
|
||||
line-length = 88
|
||||
|
||||
@@ -1,118 +1,210 @@
|
||||
import pandas as pd
|
||||
from typing import List, Tuple
|
||||
from __future__ import annotations
|
||||
|
||||
from .jobs import JobType
|
||||
import pandas as pd
|
||||
from typing import Tuple
|
||||
from concurrent.futures import ThreadPoolExecutor, as_completed
|
||||
|
||||
from .jobs import JobType, Location
|
||||
from .scrapers.utils import logger, set_logger_level
|
||||
from .scrapers.indeed import IndeedScraper
|
||||
from .scrapers.ziprecruiter import ZipRecruiterScraper
|
||||
from .scrapers.glassdoor import GlassdoorScraper
|
||||
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,
|
||||
GlassdoorException,
|
||||
)
|
||||
|
||||
|
||||
SCRAPER_MAPPING = {
|
||||
Site.LINKEDIN: LinkedInScraper,
|
||||
Site.INDEED: IndeedScraper,
|
||||
Site.ZIP_RECRUITER: ZipRecruiterScraper,
|
||||
}
|
||||
|
||||
|
||||
def _map_str_to_site(site_name: str) -> Site:
|
||||
return Site[site_name.upper()]
|
||||
|
||||
|
||||
def scrape_jobs(
|
||||
site_name: str | Site | List[Site],
|
||||
search_term: str,
|
||||
|
||||
location: str = "",
|
||||
distance: int = None,
|
||||
is_remote: bool = False,
|
||||
job_type: JobType = None,
|
||||
easy_apply: bool = False, # linkedin
|
||||
results_wanted: int = 15
|
||||
site_name: str | list[str] | Site | list[Site] | None = None,
|
||||
search_term: str | None = None,
|
||||
location: str | None = None,
|
||||
distance: int | None = 50,
|
||||
is_remote: bool = False,
|
||||
job_type: str | None = None,
|
||||
easy_apply: bool | None = None,
|
||||
results_wanted: int = 15,
|
||||
country_indeed: str = "usa",
|
||||
hyperlinks: bool = False,
|
||||
proxy: str | None = None,
|
||||
description_format: str = "markdown",
|
||||
linkedin_fetch_description: bool | None = False,
|
||||
linkedin_company_ids: list[int] | None = None,
|
||||
offset: int | None = 0,
|
||||
hours_old: int = None,
|
||||
verbose: int = 2,
|
||||
**kwargs,
|
||||
) -> pd.DataFrame:
|
||||
"""
|
||||
Asynchronously scrapes job data from multiple job sites.
|
||||
:return: results_wanted: pandas dataframe containing job data
|
||||
Simultaneously scrapes job data from multiple job sites.
|
||||
:return: pandas dataframe containing job data
|
||||
"""
|
||||
SCRAPER_MAPPING = {
|
||||
Site.LINKEDIN: LinkedInScraper,
|
||||
Site.INDEED: IndeedScraper,
|
||||
Site.ZIP_RECRUITER: ZipRecruiterScraper,
|
||||
Site.GLASSDOOR: GlassdoorScraper,
|
||||
}
|
||||
set_logger_level(verbose)
|
||||
|
||||
if type(site_name) == str:
|
||||
site_name = _map_str_to_site(site_name)
|
||||
def map_str_to_site(site_name: str) -> Site:
|
||||
return Site[site_name.upper()]
|
||||
|
||||
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
|
||||
|
||||
def get_site_type():
|
||||
site_types = list(Site)
|
||||
if isinstance(site_name, str):
|
||||
site_types = [map_str_to_site(site_name)]
|
||||
elif isinstance(site_name, Site):
|
||||
site_types = [site_name]
|
||||
elif isinstance(site_name, list):
|
||||
site_types = [
|
||||
map_str_to_site(site) if isinstance(site, str) else site
|
||||
for site in site_name
|
||||
]
|
||||
return site_types
|
||||
|
||||
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,
|
||||
site_type=get_site_type(),
|
||||
country=country_enum,
|
||||
search_term=search_term,
|
||||
location=location,
|
||||
distance=distance,
|
||||
is_remote=is_remote,
|
||||
job_type=job_type,
|
||||
easy_apply=easy_apply,
|
||||
description_format=description_format,
|
||||
linkedin_fetch_description=linkedin_fetch_description,
|
||||
results_wanted=results_wanted,
|
||||
linkedin_company_ids=linkedin_company_ids,
|
||||
offset=offset,
|
||||
hours_old=hours_old,
|
||||
)
|
||||
|
||||
def scrape_site(site: Site) -> Tuple[str, JobResponse]:
|
||||
scraper_class = SCRAPER_MAPPING[site]
|
||||
scraper = scraper_class()
|
||||
scraper = scraper_class(proxy=proxy)
|
||||
scraped_data: JobResponse = scraper.scrape(scraper_input)
|
||||
|
||||
cap_name = site.value.capitalize()
|
||||
site_name = "ZipRecruiter" if cap_name == "Zip_recruiter" else cap_name
|
||||
logger.info(f"{site_name} finished scraping")
|
||||
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 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_url = job_data["job_url"]
|
||||
job_data["job_url_hyper"] = f'<a href="{job_url}">{job_url}</a>'
|
||||
job_data["site"] = site
|
||||
job_data["company"] = job_data["company_name"]
|
||||
job_data["job_type"] = (
|
||||
", ".join(job_type.value[0] for job_type in job_data["job_type"])
|
||||
if job_data["job_type"]
|
||||
else None
|
||||
)
|
||||
job_data["emails"] = (
|
||||
", ".join(job_data["emails"]) if job_data["emails"] else None
|
||||
)
|
||||
if job_data["location"]:
|
||||
job_data["location"] = Location(
|
||||
**job_data["location"]
|
||||
).display_location()
|
||||
|
||||
# Formatting JobType
|
||||
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'] = 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["interval"] = (
|
||||
compensation_obj.get("interval").value
|
||||
if compensation_obj.get("interval")
|
||||
else None
|
||||
)
|
||||
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 = ['site', 'title', 'company_name', 'city', 'state','job_type',
|
||||
'interval', 'min_amount', 'max_amount', 'job_url', 'description',]
|
||||
df = df[desired_order]
|
||||
if jobs_dfs:
|
||||
# Step 1: Filter out all-NA columns from each DataFrame before concatenation
|
||||
filtered_dfs = [df.dropna(axis=1, how="all") for df in jobs_dfs]
|
||||
|
||||
# Step 2: Concatenate the filtered DataFrames
|
||||
jobs_df = pd.concat(filtered_dfs, ignore_index=True)
|
||||
|
||||
# Desired column order
|
||||
desired_order = [
|
||||
"site",
|
||||
"job_url_hyper" if hyperlinks else "job_url",
|
||||
"job_url_direct",
|
||||
"title",
|
||||
"company",
|
||||
"location",
|
||||
"job_type",
|
||||
"date_posted",
|
||||
"interval",
|
||||
"min_amount",
|
||||
"max_amount",
|
||||
"currency",
|
||||
"is_remote",
|
||||
"emails",
|
||||
"description",
|
||||
"company_url",
|
||||
"company_url_direct",
|
||||
"company_addresses",
|
||||
"company_industry",
|
||||
"company_num_employees",
|
||||
"company_revenue",
|
||||
"company_description",
|
||||
"logo_photo_url",
|
||||
"banner_photo_url",
|
||||
"ceo_name",
|
||||
"ceo_photo_url",
|
||||
]
|
||||
|
||||
# Step 3: Ensure all desired columns are present, adding missing ones as empty
|
||||
for column in desired_order:
|
||||
if column not in jobs_df.columns:
|
||||
jobs_df[column] = None # Add missing columns as empty
|
||||
|
||||
# Reorder the DataFrame according to the desired order
|
||||
jobs_df = jobs_df[desired_order]
|
||||
|
||||
# Step 4: Sort the DataFrame as required
|
||||
return jobs_df.sort_values(by=["site", "date_posted"], ascending=[True, False])
|
||||
else:
|
||||
df = pd.DataFrame()
|
||||
|
||||
return df
|
||||
|
||||
|
||||
|
||||
|
||||
return pd.DataFrame()
|
||||
|
||||
@@ -1,30 +1,198 @@
|
||||
from typing import Union, Optional
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Optional
|
||||
from datetime import date
|
||||
from enum import Enum
|
||||
|
||||
from pydantic import BaseModel, validator
|
||||
from pydantic import BaseModel
|
||||
|
||||
|
||||
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):
|
||||
"""
|
||||
Gets the subdomain for Indeed and Glassdoor.
|
||||
The second item in the tuple is the subdomain (and API country code if there's a ':' separator) for Indeed
|
||||
The third item in the tuple is the subdomain (and tld if there's a ':' separator) for Glassdoor
|
||||
"""
|
||||
|
||||
ARGENTINA = ("argentina", "ar", "com.ar")
|
||||
AUSTRALIA = ("australia", "au", "com.au")
|
||||
AUSTRIA = ("austria", "at", "at")
|
||||
BAHRAIN = ("bahrain", "bh")
|
||||
BELGIUM = ("belgium", "be", "fr:be")
|
||||
BRAZIL = ("brazil", "br", "com.br")
|
||||
CANADA = ("canada", "ca", "ca")
|
||||
CHILE = ("chile", "cl")
|
||||
CHINA = ("china", "cn")
|
||||
COLOMBIA = ("colombia", "co")
|
||||
COSTARICA = ("costa rica", "cr")
|
||||
CZECHREPUBLIC = ("czech republic,czechia", "cz")
|
||||
DENMARK = ("denmark", "dk")
|
||||
ECUADOR = ("ecuador", "ec")
|
||||
EGYPT = ("egypt", "eg")
|
||||
FINLAND = ("finland", "fi")
|
||||
FRANCE = ("france", "fr", "fr")
|
||||
GERMANY = ("germany", "de", "de")
|
||||
GREECE = ("greece", "gr")
|
||||
HONGKONG = ("hong kong", "hk", "com.hk")
|
||||
HUNGARY = ("hungary", "hu")
|
||||
INDIA = ("india", "in", "co.in")
|
||||
INDONESIA = ("indonesia", "id")
|
||||
IRELAND = ("ireland", "ie", "ie")
|
||||
ISRAEL = ("israel", "il")
|
||||
ITALY = ("italy", "it", "it")
|
||||
JAPAN = ("japan", "jp")
|
||||
KUWAIT = ("kuwait", "kw")
|
||||
LUXEMBOURG = ("luxembourg", "lu")
|
||||
MALAYSIA = ("malaysia", "malaysia")
|
||||
MEXICO = ("mexico", "mx", "com.mx")
|
||||
MOROCCO = ("morocco", "ma")
|
||||
NETHERLANDS = ("netherlands", "nl", "nl")
|
||||
NEWZEALAND = ("new zealand", "nz", "co.nz")
|
||||
NIGERIA = ("nigeria", "ng")
|
||||
NORWAY = ("norway", "no")
|
||||
OMAN = ("oman", "om")
|
||||
PAKISTAN = ("pakistan", "pk")
|
||||
PANAMA = ("panama", "pa")
|
||||
PERU = ("peru", "pe")
|
||||
PHILIPPINES = ("philippines", "ph")
|
||||
POLAND = ("poland", "pl")
|
||||
PORTUGAL = ("portugal", "pt")
|
||||
QATAR = ("qatar", "qa")
|
||||
ROMANIA = ("romania", "ro")
|
||||
SAUDIARABIA = ("saudi arabia", "sa")
|
||||
SINGAPORE = ("singapore", "sg", "sg")
|
||||
SOUTHAFRICA = ("south africa", "za")
|
||||
SOUTHKOREA = ("south korea", "kr")
|
||||
SPAIN = ("spain", "es", "es")
|
||||
SWEDEN = ("sweden", "se")
|
||||
SWITZERLAND = ("switzerland", "ch", "de:ch")
|
||||
TAIWAN = ("taiwan", "tw")
|
||||
THAILAND = ("thailand", "th")
|
||||
TURKEY = ("turkey", "tr")
|
||||
UKRAINE = ("ukraine", "ua")
|
||||
UNITEDARABEMIRATES = ("united arab emirates", "ae")
|
||||
UK = ("uk,united kingdom", "uk:gb", "co.uk")
|
||||
USA = ("usa,us,united states", "www:us", "com")
|
||||
URUGUAY = ("uruguay", "uy")
|
||||
VENEZUELA = ("venezuela", "ve")
|
||||
VIETNAM = ("vietnam", "vn", "com")
|
||||
|
||||
# internal for ziprecruiter
|
||||
US_CANADA = ("usa/ca", "www")
|
||||
|
||||
# internal for linkedin
|
||||
WORLDWIDE = ("worldwide", "www")
|
||||
|
||||
@property
|
||||
def indeed_domain_value(self):
|
||||
subdomain, _, api_country_code = self.value[1].partition(":")
|
||||
if subdomain and api_country_code:
|
||||
return subdomain, api_country_code.upper()
|
||||
return self.value[1], self.value[1].upper()
|
||||
|
||||
@property
|
||||
def glassdoor_domain_value(self):
|
||||
if len(self.value) == 3:
|
||||
subdomain, _, domain = self.value[2].partition(":")
|
||||
if subdomain and domain:
|
||||
return f"{subdomain}.glassdoor.{domain}"
|
||||
else:
|
||||
return f"www.glassdoor.{self.value[2]}"
|
||||
else:
|
||||
raise Exception(f"Glassdoor is not available for {self.name}")
|
||||
|
||||
def get_glassdoor_url(self):
|
||||
return f"https://{self.glassdoor_domain_value}/"
|
||||
|
||||
@classmethod
|
||||
def from_string(cls, country_str: str):
|
||||
"""Convert a string to the corresponding Country enum."""
|
||||
country_str = country_str.strip().lower()
|
||||
for country in cls:
|
||||
country_names = country.value[0].split(",")
|
||||
if country_str in country_names:
|
||||
return country
|
||||
valid_countries = [country.value for country in cls]
|
||||
raise ValueError(
|
||||
f"Invalid country string: '{country_str}'. Valid countries are: {', '.join([country[0] for country in valid_countries])}"
|
||||
)
|
||||
|
||||
|
||||
class Location(BaseModel):
|
||||
country: str = "USA"
|
||||
city: str = None
|
||||
country: Country | str | None = 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 isinstance(self.country, str):
|
||||
location_parts.append(self.country)
|
||||
elif self.country and self.country not in (
|
||||
Country.US_CANADA,
|
||||
Country.WORLDWIDE,
|
||||
):
|
||||
country_name = self.country.value[0]
|
||||
if "," in country_name:
|
||||
country_name = country_name.split(",")[0]
|
||||
if country_name in ("usa", "uk"):
|
||||
location_parts.append(country_name.upper())
|
||||
else:
|
||||
location_parts.append(country_name.title())
|
||||
return ", ".join(location_parts)
|
||||
|
||||
|
||||
class CompensationInterval(Enum):
|
||||
YEARLY = "yearly"
|
||||
@@ -33,43 +201,58 @@ class CompensationInterval(Enum):
|
||||
DAILY = "daily"
|
||||
HOURLY = "hourly"
|
||||
|
||||
@classmethod
|
||||
def get_interval(cls, pay_period):
|
||||
interval_mapping = {
|
||||
"YEAR": cls.YEARLY,
|
||||
"HOUR": cls.HOURLY,
|
||||
}
|
||||
if pay_period in interval_mapping:
|
||||
return interval_mapping[pay_period].value
|
||||
else:
|
||||
return cls[pay_period].value if pay_period in cls.__members__ else None
|
||||
|
||||
|
||||
class Compensation(BaseModel):
|
||||
interval: CompensationInterval
|
||||
min_amount: int = None
|
||||
max_amount: int = None
|
||||
currency: str = "USD"
|
||||
interval: Optional[CompensationInterval] = None
|
||||
min_amount: float | None = None
|
||||
max_amount: float | None = None
|
||||
currency: Optional[str] = "USD"
|
||||
|
||||
|
||||
class DescriptionFormat(Enum):
|
||||
MARKDOWN = "markdown"
|
||||
HTML = "html"
|
||||
|
||||
|
||||
class JobPost(BaseModel):
|
||||
title: str
|
||||
company_name: str
|
||||
company_name: str | None
|
||||
job_url: str
|
||||
job_url_direct: str | None = None
|
||||
location: Optional[Location]
|
||||
|
||||
description: str = None
|
||||
job_type: Optional[JobType] = None
|
||||
compensation: Optional[Compensation] = None
|
||||
date_posted: date = None
|
||||
description: str | None = None
|
||||
company_url: str | None = None
|
||||
company_url_direct: str | None = None
|
||||
|
||||
job_type: list[JobType] | None = None
|
||||
compensation: Compensation | None = None
|
||||
date_posted: date | None = None
|
||||
emails: list[str] | None = None
|
||||
is_remote: bool | None = None
|
||||
|
||||
# indeed specific
|
||||
company_addresses: str | None = None
|
||||
company_industry: str | None = None
|
||||
company_num_employees: str | None = None
|
||||
company_revenue: str | None = None
|
||||
company_description: str | None = None
|
||||
ceo_name: str | None = None
|
||||
ceo_photo_url: str | None = None
|
||||
logo_photo_url: str | None = None
|
||||
banner_photo_url: 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
|
||||
|
||||
@@ -1,43 +1,47 @@
|
||||
from ..jobs import Enum, BaseModel, JobType, JobResponse
|
||||
from typing import List, Dict, Optional, Any
|
||||
from __future__ import annotations
|
||||
|
||||
from abc import ABC, abstractmethod
|
||||
|
||||
class StatusException(Exception):
|
||||
def __init__(self, status_code: int):
|
||||
self.status_code = status_code
|
||||
from ..jobs import (
|
||||
Enum,
|
||||
BaseModel,
|
||||
JobType,
|
||||
JobResponse,
|
||||
Country,
|
||||
DescriptionFormat,
|
||||
)
|
||||
|
||||
|
||||
class Site(Enum):
|
||||
LINKEDIN = "linkedin"
|
||||
INDEED = "indeed"
|
||||
ZIP_RECRUITER = "zip_recruiter"
|
||||
GLASSDOOR = "glassdoor"
|
||||
|
||||
|
||||
class ScraperInput(BaseModel):
|
||||
site_type: List[Site]
|
||||
search_term: str
|
||||
site_type: list[Site]
|
||||
search_term: str | None = None
|
||||
|
||||
location: str = None
|
||||
distance: Optional[int] = None
|
||||
location: str | None = None
|
||||
country: Country | None = Country.USA
|
||||
distance: int | None = None
|
||||
is_remote: bool = False
|
||||
job_type: Optional[JobType] = None
|
||||
easy_apply: bool = None # linkedin
|
||||
job_type: JobType | None = None
|
||||
easy_apply: bool | None = None
|
||||
offset: int = 0
|
||||
linkedin_fetch_description: bool = False
|
||||
linkedin_company_ids: list[int] | None = None
|
||||
description_format: DescriptionFormat | None = DescriptionFormat.MARKDOWN
|
||||
|
||||
results_wanted: int = 15
|
||||
hours_old: int | None = None
|
||||
|
||||
|
||||
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):
|
||||
class Scraper(ABC):
|
||||
def __init__(self, site: Site, proxy: list[str] | None = 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:
|
||||
...
|
||||
@abstractmethod
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse: ...
|
||||
|
||||
26
src/jobspy/scrapers/exceptions.py
Normal file
26
src/jobspy/scrapers/exceptions.py
Normal file
@@ -0,0 +1,26 @@
|
||||
"""
|
||||
jobspy.scrapers.exceptions
|
||||
~~~~~~~~~~~~~~~~~~~
|
||||
|
||||
This module contains the set of Scrapers' exceptions.
|
||||
"""
|
||||
|
||||
|
||||
class LinkedInException(Exception):
|
||||
def __init__(self, message=None):
|
||||
super().__init__(message or "An error occurred with LinkedIn")
|
||||
|
||||
|
||||
class IndeedException(Exception):
|
||||
def __init__(self, message=None):
|
||||
super().__init__(message or "An error occurred with Indeed")
|
||||
|
||||
|
||||
class ZipRecruiterException(Exception):
|
||||
def __init__(self, message=None):
|
||||
super().__init__(message or "An error occurred with ZipRecruiter")
|
||||
|
||||
|
||||
class GlassdoorException(Exception):
|
||||
def __init__(self, message=None):
|
||||
super().__init__(message or "An error occurred with Glassdoor")
|
||||
534
src/jobspy/scrapers/glassdoor/__init__.py
Normal file
534
src/jobspy/scrapers/glassdoor/__init__.py
Normal file
@@ -0,0 +1,534 @@
|
||||
"""
|
||||
jobspy.scrapers.glassdoor
|
||||
~~~~~~~~~~~~~~~~~~~
|
||||
|
||||
This module contains routines to scrape Glassdoor.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import re
|
||||
import json
|
||||
import requests
|
||||
from typing import Optional, Tuple
|
||||
from datetime import datetime, timedelta
|
||||
from concurrent.futures import ThreadPoolExecutor, as_completed
|
||||
|
||||
from .. import Scraper, ScraperInput, Site
|
||||
from ..utils import extract_emails_from_text
|
||||
from ..exceptions import GlassdoorException
|
||||
from ..utils import (
|
||||
create_session,
|
||||
markdown_converter,
|
||||
logger,
|
||||
)
|
||||
from ...jobs import (
|
||||
JobPost,
|
||||
Compensation,
|
||||
CompensationInterval,
|
||||
Location,
|
||||
JobResponse,
|
||||
JobType,
|
||||
DescriptionFormat,
|
||||
)
|
||||
|
||||
|
||||
class GlassdoorScraper(Scraper):
|
||||
def __init__(self, proxy: Optional[str] = None):
|
||||
"""
|
||||
Initializes GlassdoorScraper with the Glassdoor job search url
|
||||
"""
|
||||
site = Site(Site.GLASSDOOR)
|
||||
super().__init__(site, proxy=proxy)
|
||||
|
||||
self.base_url = None
|
||||
self.country = None
|
||||
self.session = None
|
||||
self.scraper_input = None
|
||||
self.jobs_per_page = 30
|
||||
self.max_pages = 30
|
||||
self.seen_urls = set()
|
||||
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||
"""
|
||||
Scrapes Glassdoor for jobs with scraper_input criteria.
|
||||
:param scraper_input: Information about job search criteria.
|
||||
:return: JobResponse containing a list of jobs.
|
||||
"""
|
||||
self.scraper_input = scraper_input
|
||||
self.scraper_input.results_wanted = min(900, scraper_input.results_wanted)
|
||||
self.base_url = self.scraper_input.country.get_glassdoor_url()
|
||||
|
||||
self.session = create_session(self.proxy, is_tls=True, has_retry=True)
|
||||
token = self._get_csrf_token()
|
||||
self.headers["gd-csrf-token"] = token if token else self.fallback_token
|
||||
|
||||
location_id, location_type = self._get_location(
|
||||
scraper_input.location, scraper_input.is_remote
|
||||
)
|
||||
if location_type is None:
|
||||
logger.error("Glassdoor: location not parsed")
|
||||
return JobResponse(jobs=[])
|
||||
all_jobs: list[JobPost] = []
|
||||
cursor = None
|
||||
|
||||
range_start = 1 + (scraper_input.offset // self.jobs_per_page)
|
||||
tot_pages = (scraper_input.results_wanted // self.jobs_per_page) + 2
|
||||
range_end = min(tot_pages, self.max_pages + 1)
|
||||
for page in range(range_start, range_end):
|
||||
logger.info(f"Glassdoor search page: {page}")
|
||||
try:
|
||||
jobs, cursor = self._fetch_jobs_page(
|
||||
scraper_input, location_id, location_type, page, cursor
|
||||
)
|
||||
all_jobs.extend(jobs)
|
||||
if not jobs or len(all_jobs) >= scraper_input.results_wanted:
|
||||
all_jobs = all_jobs[: scraper_input.results_wanted]
|
||||
break
|
||||
except Exception as e:
|
||||
logger.error(f"Glassdoor: {str(e)}")
|
||||
break
|
||||
return JobResponse(jobs=all_jobs)
|
||||
|
||||
def _fetch_jobs_page(
|
||||
self,
|
||||
scraper_input: ScraperInput,
|
||||
location_id: int,
|
||||
location_type: str,
|
||||
page_num: int,
|
||||
cursor: str | None,
|
||||
) -> Tuple[list[JobPost], str | None]:
|
||||
"""
|
||||
Scrapes a page of Glassdoor for jobs with scraper_input criteria
|
||||
"""
|
||||
jobs = []
|
||||
self.scraper_input = scraper_input
|
||||
try:
|
||||
payload = self._add_payload(location_id, location_type, page_num, cursor)
|
||||
response = self.session.post(
|
||||
f"{self.base_url}/graph",
|
||||
headers=self.headers,
|
||||
timeout_seconds=15,
|
||||
data=payload,
|
||||
)
|
||||
if response.status_code != 200:
|
||||
exc_msg = f"bad response status code: {response.status_code}"
|
||||
raise GlassdoorException(exc_msg)
|
||||
res_json = response.json()[0]
|
||||
if "errors" in res_json:
|
||||
raise ValueError("Error encountered in API response")
|
||||
except (
|
||||
requests.exceptions.ReadTimeout,
|
||||
GlassdoorException,
|
||||
ValueError,
|
||||
Exception,
|
||||
) as e:
|
||||
logger.error(f"Glassdoor: {str(e)}")
|
||||
return jobs, None
|
||||
|
||||
jobs_data = res_json["data"]["jobListings"]["jobListings"]
|
||||
|
||||
with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
|
||||
future_to_job_data = {
|
||||
executor.submit(self._process_job, job): job for job in jobs_data
|
||||
}
|
||||
for future in as_completed(future_to_job_data):
|
||||
try:
|
||||
job_post = future.result()
|
||||
if job_post:
|
||||
jobs.append(job_post)
|
||||
except Exception as exc:
|
||||
raise GlassdoorException(f"Glassdoor generated an exception: {exc}")
|
||||
|
||||
return jobs, self.get_cursor_for_page(
|
||||
res_json["data"]["jobListings"]["paginationCursors"], page_num + 1
|
||||
)
|
||||
|
||||
def _get_csrf_token(self):
|
||||
"""
|
||||
Fetches csrf token needed for API by visiting a generic page
|
||||
"""
|
||||
res = self.session.get(
|
||||
f"{self.base_url}/Job/computer-science-jobs.htm", headers=self.headers
|
||||
)
|
||||
pattern = r'"token":\s*"([^"]+)"'
|
||||
matches = re.findall(pattern, res.text)
|
||||
token = None
|
||||
if matches:
|
||||
token = matches[0]
|
||||
return token
|
||||
|
||||
def _process_job(self, job_data):
|
||||
"""
|
||||
Processes a single job and fetches its description.
|
||||
"""
|
||||
job_id = job_data["jobview"]["job"]["listingId"]
|
||||
job_url = f"{self.base_url}job-listing/j?jl={job_id}"
|
||||
if job_url in self.seen_urls:
|
||||
return None
|
||||
self.seen_urls.add(job_url)
|
||||
job = job_data["jobview"]
|
||||
title = job["job"]["jobTitleText"]
|
||||
company_name = job["header"]["employerNameFromSearch"]
|
||||
company_id = job_data["jobview"]["header"]["employer"]["id"]
|
||||
location_name = job["header"].get("locationName", "")
|
||||
location_type = job["header"].get("locationType", "")
|
||||
age_in_days = job["header"].get("ageInDays")
|
||||
is_remote, location = False, None
|
||||
date_diff = (datetime.now() - timedelta(days=age_in_days)).date()
|
||||
date_posted = date_diff if age_in_days is not None else None
|
||||
|
||||
if location_type == "S":
|
||||
is_remote = True
|
||||
else:
|
||||
location = self.parse_location(location_name)
|
||||
|
||||
compensation = self.parse_compensation(job["header"])
|
||||
try:
|
||||
description = self._fetch_job_description(job_id)
|
||||
except:
|
||||
description = None
|
||||
company_url = f"{self.base_url}Overview/W-EI_IE{company_id}.htm"
|
||||
return JobPost(
|
||||
title=title,
|
||||
company_url=company_url if company_id else None,
|
||||
company_name=company_name,
|
||||
date_posted=date_posted,
|
||||
job_url=job_url,
|
||||
location=location,
|
||||
compensation=compensation,
|
||||
is_remote=is_remote,
|
||||
description=description,
|
||||
emails=extract_emails_from_text(description) if description else None,
|
||||
)
|
||||
|
||||
def _fetch_job_description(self, job_id):
|
||||
"""
|
||||
Fetches the job description for a single job ID.
|
||||
"""
|
||||
url = f"{self.base_url}/graph"
|
||||
body = [
|
||||
{
|
||||
"operationName": "JobDetailQuery",
|
||||
"variables": {
|
||||
"jl": job_id,
|
||||
"queryString": "q",
|
||||
"pageTypeEnum": "SERP",
|
||||
},
|
||||
"query": """
|
||||
query JobDetailQuery($jl: Long!, $queryString: String, $pageTypeEnum: PageTypeEnum) {
|
||||
jobview: jobView(
|
||||
listingId: $jl
|
||||
contextHolder: {queryString: $queryString, pageTypeEnum: $pageTypeEnum}
|
||||
) {
|
||||
job {
|
||||
description
|
||||
__typename
|
||||
}
|
||||
__typename
|
||||
}
|
||||
}
|
||||
""",
|
||||
}
|
||||
]
|
||||
res = requests.post(url, json=body, headers=self.headers)
|
||||
if res.status_code != 200:
|
||||
return None
|
||||
data = res.json()[0]
|
||||
desc = data["data"]["jobview"]["job"]["description"]
|
||||
if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
|
||||
desc = markdown_converter(desc)
|
||||
return desc
|
||||
|
||||
def _get_location(self, location: str, is_remote: bool) -> (int, str):
|
||||
if not location or is_remote:
|
||||
return "11047", "STATE" # remote options
|
||||
url = f"{self.base_url}/findPopularLocationAjax.htm?maxLocationsToReturn=10&term={location}"
|
||||
session = create_session(self.proxy, has_retry=True)
|
||||
res = self.session.get(url, headers=self.headers)
|
||||
if res.status_code != 200:
|
||||
if res.status_code == 429:
|
||||
err = f"429 Response - Blocked by Glassdoor for too many requests"
|
||||
logger.error(err)
|
||||
return None, None
|
||||
else:
|
||||
err = f"Glassdoor response status code {res.status_code}"
|
||||
err += f" - {res.text}"
|
||||
logger.error(f"Glassdoor response status code {res.status_code}")
|
||||
return None, None
|
||||
items = res.json()
|
||||
|
||||
if not items:
|
||||
raise ValueError(f"Location '{location}' not found on Glassdoor")
|
||||
location_type = items[0]["locationType"]
|
||||
if location_type == "C":
|
||||
location_type = "CITY"
|
||||
elif location_type == "S":
|
||||
location_type = "STATE"
|
||||
elif location_type == "N":
|
||||
location_type = "COUNTRY"
|
||||
return int(items[0]["locationId"]), location_type
|
||||
|
||||
def _add_payload(
|
||||
self,
|
||||
location_id: int,
|
||||
location_type: str,
|
||||
page_num: int,
|
||||
cursor: str | None = None,
|
||||
) -> str:
|
||||
fromage = None
|
||||
if self.scraper_input.hours_old:
|
||||
fromage = max(self.scraper_input.hours_old // 24, 1)
|
||||
filter_params = []
|
||||
if self.scraper_input.easy_apply:
|
||||
filter_params.append({"filterKey": "applicationType", "values": "1"})
|
||||
if fromage:
|
||||
filter_params.append({"filterKey": "fromAge", "values": str(fromage)})
|
||||
payload = {
|
||||
"operationName": "JobSearchResultsQuery",
|
||||
"variables": {
|
||||
"excludeJobListingIds": [],
|
||||
"filterParams": filter_params,
|
||||
"keyword": self.scraper_input.search_term,
|
||||
"numJobsToShow": 30,
|
||||
"locationType": location_type,
|
||||
"locationId": int(location_id),
|
||||
"parameterUrlInput": f"IL.0,12_I{location_type}{location_id}",
|
||||
"pageNumber": page_num,
|
||||
"pageCursor": cursor,
|
||||
"fromage": fromage,
|
||||
"sort": "date",
|
||||
},
|
||||
"query": self.query_template,
|
||||
}
|
||||
if self.scraper_input.job_type:
|
||||
payload["variables"]["filterParams"].append(
|
||||
{"filterKey": "jobType", "values": self.scraper_input.job_type.value[0]}
|
||||
)
|
||||
return json.dumps([payload])
|
||||
|
||||
@staticmethod
|
||||
def parse_compensation(data: dict) -> Optional[Compensation]:
|
||||
pay_period = data.get("payPeriod")
|
||||
adjusted_pay = data.get("payPeriodAdjustedPay")
|
||||
currency = data.get("payCurrency", "USD")
|
||||
if not pay_period or not adjusted_pay:
|
||||
return None
|
||||
|
||||
interval = None
|
||||
if pay_period == "ANNUAL":
|
||||
interval = CompensationInterval.YEARLY
|
||||
elif pay_period:
|
||||
interval = CompensationInterval.get_interval(pay_period)
|
||||
min_amount = int(adjusted_pay.get("p10") // 1)
|
||||
max_amount = int(adjusted_pay.get("p90") // 1)
|
||||
return Compensation(
|
||||
interval=interval,
|
||||
min_amount=min_amount,
|
||||
max_amount=max_amount,
|
||||
currency=currency,
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
|
||||
for job_type in JobType:
|
||||
if job_type_str in job_type.value:
|
||||
return [job_type]
|
||||
|
||||
@staticmethod
|
||||
def parse_location(location_name: str) -> Location | None:
|
||||
if not location_name or location_name == "Remote":
|
||||
return
|
||||
city, _, state = location_name.partition(", ")
|
||||
return Location(city=city, state=state)
|
||||
|
||||
@staticmethod
|
||||
def get_cursor_for_page(pagination_cursors, page_num):
|
||||
for cursor_data in pagination_cursors:
|
||||
if cursor_data["pageNumber"] == page_num:
|
||||
return cursor_data["cursor"]
|
||||
|
||||
fallback_token = "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok"
|
||||
headers = {
|
||||
"authority": "www.glassdoor.com",
|
||||
"accept": "*/*",
|
||||
"accept-language": "en-US,en;q=0.9",
|
||||
"apollographql-client-name": "job-search-next",
|
||||
"apollographql-client-version": "4.65.5",
|
||||
"content-type": "application/json",
|
||||
"origin": "https://www.glassdoor.com",
|
||||
"referer": "https://www.glassdoor.com/",
|
||||
"sec-ch-ua": '"Chromium";v="118", "Google Chrome";v="118", "Not=A?Brand";v="99"',
|
||||
"sec-ch-ua-mobile": "?0",
|
||||
"sec-ch-ua-platform": '"macOS"',
|
||||
"sec-fetch-dest": "empty",
|
||||
"sec-fetch-mode": "cors",
|
||||
"sec-fetch-site": "same-origin",
|
||||
"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/118.0.0.0 Safari/537.36",
|
||||
}
|
||||
query_template = """
|
||||
query JobSearchResultsQuery(
|
||||
$excludeJobListingIds: [Long!],
|
||||
$keyword: String,
|
||||
$locationId: Int,
|
||||
$locationType: LocationTypeEnum,
|
||||
$numJobsToShow: Int!,
|
||||
$pageCursor: String,
|
||||
$pageNumber: Int,
|
||||
$filterParams: [FilterParams],
|
||||
$originalPageUrl: String,
|
||||
$seoFriendlyUrlInput: String,
|
||||
$parameterUrlInput: String,
|
||||
$seoUrl: Boolean
|
||||
) {
|
||||
jobListings(
|
||||
contextHolder: {
|
||||
searchParams: {
|
||||
excludeJobListingIds: $excludeJobListingIds,
|
||||
keyword: $keyword,
|
||||
locationId: $locationId,
|
||||
locationType: $locationType,
|
||||
numPerPage: $numJobsToShow,
|
||||
pageCursor: $pageCursor,
|
||||
pageNumber: $pageNumber,
|
||||
filterParams: $filterParams,
|
||||
originalPageUrl: $originalPageUrl,
|
||||
seoFriendlyUrlInput: $seoFriendlyUrlInput,
|
||||
parameterUrlInput: $parameterUrlInput,
|
||||
seoUrl: $seoUrl,
|
||||
searchType: SR
|
||||
}
|
||||
}
|
||||
) {
|
||||
companyFilterOptions {
|
||||
id
|
||||
shortName
|
||||
__typename
|
||||
}
|
||||
filterOptions
|
||||
indeedCtk
|
||||
jobListings {
|
||||
...JobView
|
||||
__typename
|
||||
}
|
||||
jobListingSeoLinks {
|
||||
linkItems {
|
||||
position
|
||||
url
|
||||
__typename
|
||||
}
|
||||
__typename
|
||||
}
|
||||
jobSearchTrackingKey
|
||||
jobsPageSeoData {
|
||||
pageMetaDescription
|
||||
pageTitle
|
||||
__typename
|
||||
}
|
||||
paginationCursors {
|
||||
cursor
|
||||
pageNumber
|
||||
__typename
|
||||
}
|
||||
indexablePageForSeo
|
||||
searchResultsMetadata {
|
||||
searchCriteria {
|
||||
implicitLocation {
|
||||
id
|
||||
localizedDisplayName
|
||||
type
|
||||
__typename
|
||||
}
|
||||
keyword
|
||||
location {
|
||||
id
|
||||
shortName
|
||||
localizedShortName
|
||||
localizedDisplayName
|
||||
type
|
||||
__typename
|
||||
}
|
||||
__typename
|
||||
}
|
||||
helpCenterDomain
|
||||
helpCenterLocale
|
||||
jobSerpJobOutlook {
|
||||
occupation
|
||||
paragraph
|
||||
__typename
|
||||
}
|
||||
showMachineReadableJobs
|
||||
__typename
|
||||
}
|
||||
totalJobsCount
|
||||
__typename
|
||||
}
|
||||
}
|
||||
|
||||
fragment JobView on JobListingSearchResult {
|
||||
jobview {
|
||||
header {
|
||||
adOrderId
|
||||
advertiserType
|
||||
adOrderSponsorshipLevel
|
||||
ageInDays
|
||||
divisionEmployerName
|
||||
easyApply
|
||||
employer {
|
||||
id
|
||||
name
|
||||
shortName
|
||||
__typename
|
||||
}
|
||||
employerNameFromSearch
|
||||
goc
|
||||
gocConfidence
|
||||
gocId
|
||||
jobCountryId
|
||||
jobLink
|
||||
jobResultTrackingKey
|
||||
jobTitleText
|
||||
locationName
|
||||
locationType
|
||||
locId
|
||||
needsCommission
|
||||
payCurrency
|
||||
payPeriod
|
||||
payPeriodAdjustedPay {
|
||||
p10
|
||||
p50
|
||||
p90
|
||||
__typename
|
||||
}
|
||||
rating
|
||||
salarySource
|
||||
savedJobId
|
||||
sponsored
|
||||
__typename
|
||||
}
|
||||
job {
|
||||
description
|
||||
importConfigId
|
||||
jobTitleId
|
||||
jobTitleText
|
||||
listingId
|
||||
__typename
|
||||
}
|
||||
jobListingAdminDetails {
|
||||
cpcVal
|
||||
importConfigId
|
||||
jobListingId
|
||||
jobSourceId
|
||||
userEligibleForAdminJobDetails
|
||||
__typename
|
||||
}
|
||||
overview {
|
||||
shortName
|
||||
squareLogoUrl
|
||||
__typename
|
||||
}
|
||||
__typename
|
||||
}
|
||||
__typename
|
||||
}
|
||||
"""
|
||||
@@ -1,147 +1,52 @@
|
||||
import re
|
||||
import sys
|
||||
import math
|
||||
import json
|
||||
from datetime import datetime
|
||||
from typing import Optional, Tuple, List
|
||||
"""
|
||||
jobspy.scrapers.indeed
|
||||
~~~~~~~~~~~~~~~~~~~
|
||||
|
||||
import tls_client
|
||||
import urllib.parse
|
||||
from bs4 import BeautifulSoup
|
||||
from bs4.element import Tag
|
||||
This module contains routines to scrape Indeed.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import math
|
||||
from typing import Tuple
|
||||
from datetime import datetime
|
||||
from concurrent.futures import ThreadPoolExecutor, Future
|
||||
|
||||
from ...jobs import JobPost, Compensation, CompensationInterval, Location, JobResponse, JobType
|
||||
from .. import Scraper, ScraperInput, Site, StatusException
|
||||
import requests
|
||||
|
||||
|
||||
class ParsingException(Exception):
|
||||
pass
|
||||
from .. import Scraper, ScraperInput, Site
|
||||
from ..utils import (
|
||||
extract_emails_from_text,
|
||||
get_enum_from_job_type,
|
||||
markdown_converter,
|
||||
logger,
|
||||
)
|
||||
from ...jobs import (
|
||||
JobPost,
|
||||
Compensation,
|
||||
CompensationInterval,
|
||||
Location,
|
||||
JobResponse,
|
||||
JobType,
|
||||
DescriptionFormat,
|
||||
)
|
||||
|
||||
|
||||
class IndeedScraper(Scraper):
|
||||
def __init__(self):
|
||||
def __init__(self, proxy: str | None = None):
|
||||
"""
|
||||
Initializes IndeedScraper with the Indeed job search url
|
||||
Initializes IndeedScraper with the Indeed API url
|
||||
"""
|
||||
site = Site(Site.INDEED)
|
||||
url = "https://www.indeed.com"
|
||||
super().__init__(site, url)
|
||||
|
||||
self.jobs_per_page = 15
|
||||
self.scraper_input = None
|
||||
self.jobs_per_page = 100
|
||||
self.num_workers = 10
|
||||
self.seen_urls = set()
|
||||
|
||||
def scrape_page(
|
||||
self, scraper_input: ScraperInput, page: int, session: tls_client.Session
|
||||
) -> 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 = []
|
||||
|
||||
params = {
|
||||
"q": scraper_input.search_term,
|
||||
"l": scraper_input.location,
|
||||
"radius": scraper_input.distance,
|
||||
"filter": 0,
|
||||
"start": 0 + page * 10,
|
||||
}
|
||||
sc_values = []
|
||||
if scraper_input.is_remote:
|
||||
sc_values.append("attr(DSQF7)")
|
||||
if scraper_input.job_type:
|
||||
sc_values.append("jt({})".format(scraper_input.job_type.value))
|
||||
|
||||
if sc_values:
|
||||
params["sc"] = "0kf:" + "".join(sc_values) + ";"
|
||||
response = session.get(self.url + "/jobs", params=params)
|
||||
|
||||
if (
|
||||
response.status_code != 200
|
||||
and response.status_code != 307
|
||||
):
|
||||
raise StatusException(response.status_code)
|
||||
|
||||
soup = BeautifulSoup(response.content, "html.parser")
|
||||
if "did not match any jobs" in str(soup):
|
||||
raise ParsingException("Search did not match any jobs")
|
||||
|
||||
jobs = IndeedScraper.parse_jobs(
|
||||
soup
|
||||
) #: can raise exception, handled by main scrape function
|
||||
total_num_jobs = IndeedScraper.total_jobs(soup)
|
||||
|
||||
if (
|
||||
not jobs.get("metaData", {})
|
||||
.get("mosaicProviderJobCardsModel", {})
|
||||
.get("results")
|
||||
):
|
||||
raise Exception("No jobs found.")
|
||||
|
||||
def process_job(job) -> Optional[JobPost]:
|
||||
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:
|
||||
salary_snippet = job.get("salarySnippet")
|
||||
currency = salary_snippet.get("currency") if salary_snippet else None
|
||||
interval = (extracted_salary.get("type"),)
|
||||
if isinstance(interval, tuple):
|
||||
interval = interval[0]
|
||||
|
||||
interval = interval.upper()
|
||||
if interval in CompensationInterval.__members__:
|
||||
compensation = Compensation(
|
||||
interval=CompensationInterval[interval],
|
||||
min_amount=int(extracted_salary.get("max")),
|
||||
max_amount=int(extracted_salary.get("min")),
|
||||
currency=currency,
|
||||
)
|
||||
|
||||
job_type = IndeedScraper.get_job_type(job)
|
||||
timestamp_seconds = job["pubDate"] / 1000
|
||||
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)
|
||||
|
||||
first_li = snippet_html.find("li")
|
||||
job_post = JobPost(
|
||||
title=job["normTitle"],
|
||||
description=description,
|
||||
company_name=job["company"],
|
||||
location=Location(
|
||||
city=job.get("jobLocationCity"),
|
||||
state=job.get("jobLocationState"),
|
||||
),
|
||||
job_type=job_type,
|
||||
compensation=compensation,
|
||||
date_posted=date_posted,
|
||||
job_url=job_url_client,
|
||||
)
|
||||
return job_post
|
||||
|
||||
with ThreadPoolExecutor(max_workers=10) as executor:
|
||||
job_results: list[Future] = [executor.submit(process_job, job) for job in
|
||||
jobs["metaData"]["mosaicProviderJobCardsModel"]["results"]]
|
||||
|
||||
job_list = [result.result() for result in job_results if result.result()]
|
||||
|
||||
return job_list, total_num_jobs
|
||||
self.headers = None
|
||||
self.api_country_code = None
|
||||
self.base_url = None
|
||||
self.api_url = "https://apis.indeed.com/graphql"
|
||||
site = Site(Site.INDEED)
|
||||
super().__init__(site, proxy=proxy)
|
||||
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||
"""
|
||||
@@ -149,153 +54,381 @@ class IndeedScraper(Scraper):
|
||||
:param scraper_input:
|
||||
:return: job_response
|
||||
"""
|
||||
session = tls_client.Session(
|
||||
client_identifier="chrome112", random_tls_extension_order=True
|
||||
)
|
||||
self.scraper_input = scraper_input
|
||||
domain, self.api_country_code = self.scraper_input.country.indeed_domain_value
|
||||
self.base_url = f"https://{domain}.indeed.com"
|
||||
self.headers = self.api_headers.copy()
|
||||
self.headers["indeed-co"] = self.scraper_input.country.indeed_domain_value
|
||||
job_list = []
|
||||
page = 1
|
||||
|
||||
pages_to_process = (
|
||||
math.ceil(scraper_input.results_wanted / self.jobs_per_page) - 1
|
||||
)
|
||||
cursor = None
|
||||
offset_pages = math.ceil(self.scraper_input.offset / 100)
|
||||
for _ in range(offset_pages):
|
||||
logger.info(f"Indeed skipping search page: {page}")
|
||||
__, cursor = self._scrape_page(cursor)
|
||||
if not __:
|
||||
logger.info(f"Indeed found no jobs on page: {page}")
|
||||
break
|
||||
|
||||
try:
|
||||
#: get first page to initialize session
|
||||
job_list, total_results = self.scrape_page(scraper_input, 0, session)
|
||||
while len(self.seen_urls) < scraper_input.results_wanted:
|
||||
logger.info(f"Indeed search page: {page}")
|
||||
jobs, cursor = self._scrape_page(cursor)
|
||||
if not jobs:
|
||||
logger.info(f"Indeed found no jobs on page: {page}")
|
||||
break
|
||||
job_list += jobs
|
||||
page += 1
|
||||
return JobResponse(jobs=job_list[: scraper_input.results_wanted])
|
||||
|
||||
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)
|
||||
]
|
||||
|
||||
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}",
|
||||
)
|
||||
|
||||
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 _scrape_page(self, cursor: str | None) -> Tuple[list[JobPost], str | None]:
|
||||
"""
|
||||
Retrieves job description by going to the job page url
|
||||
:param job_page_url:
|
||||
:param session:
|
||||
:return: description
|
||||
Scrapes a page of Indeed for jobs with scraper_input criteria
|
||||
:param cursor:
|
||||
:return: jobs found on page, next page cursor
|
||||
"""
|
||||
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"
|
||||
jobs = []
|
||||
new_cursor = None
|
||||
filters = self._build_filters()
|
||||
search_term = self.scraper_input.search_term.replace('"', '\\"') if self.scraper_input.search_term else ""
|
||||
query = self.job_search_query.format(
|
||||
what=(
|
||||
f'what: "{search_term}"'
|
||||
if search_term
|
||||
else ""
|
||||
),
|
||||
location=(
|
||||
f'location: {{where: "{self.scraper_input.location}", radius: {self.scraper_input.distance}, radiusUnit: MILES}}'
|
||||
if self.scraper_input.location
|
||||
else ""
|
||||
),
|
||||
dateOnIndeed=self.scraper_input.hours_old,
|
||||
cursor=f'cursor: "{cursor}"' if cursor else "",
|
||||
filters=filters,
|
||||
)
|
||||
payload = {
|
||||
"query": query,
|
||||
}
|
||||
api_headers = self.api_headers.copy()
|
||||
api_headers["indeed-co"] = self.api_country_code
|
||||
response = requests.post(
|
||||
self.api_url,
|
||||
headers=api_headers,
|
||||
json=payload,
|
||||
proxies=self.proxy,
|
||||
timeout=10,
|
||||
)
|
||||
if response.status_code != 200:
|
||||
logger.info(
|
||||
f"Indeed responded with status code: {response.status_code} (submit GitHub issue if this appears to be a bug)"
|
||||
)
|
||||
return jobs, new_cursor
|
||||
data = response.json()
|
||||
jobs = data["data"]["jobSearch"]["results"]
|
||||
new_cursor = data["data"]["jobSearch"]["pageInfo"]["nextCursor"]
|
||||
|
||||
response = session.get(formatted_url, allow_redirects=True)
|
||||
with ThreadPoolExecutor(max_workers=self.num_workers) as executor:
|
||||
job_results: list[Future] = [
|
||||
executor.submit(self._process_job, job["job"]) for job in jobs
|
||||
]
|
||||
job_list = [result.result() for result in job_results if result.result()]
|
||||
return job_list, new_cursor
|
||||
|
||||
if response.status_code not in range(200, 400):
|
||||
return None
|
||||
def _build_filters(self):
|
||||
"""
|
||||
Builds the filters dict for job type/is_remote. If hours_old is provided, composite filter for job_type/is_remote is not possible.
|
||||
IndeedApply: filters: { keyword: { field: "indeedApplyScope", keys: ["DESKTOP"] } }
|
||||
"""
|
||||
filters_str = ""
|
||||
if self.scraper_input.hours_old:
|
||||
filters_str = """
|
||||
filters: {{
|
||||
date: {{
|
||||
field: "dateOnIndeed",
|
||||
start: "{start}h"
|
||||
}}
|
||||
}}
|
||||
""".format(
|
||||
start=self.scraper_input.hours_old
|
||||
)
|
||||
elif self.scraper_input.easy_apply:
|
||||
filters_str = """
|
||||
filters: {
|
||||
keyword: {
|
||||
field: "indeedApplyScope",
|
||||
keys: ["DESKTOP"]
|
||||
}
|
||||
}
|
||||
"""
|
||||
elif self.scraper_input.job_type or self.scraper_input.is_remote:
|
||||
job_type_key_mapping = {
|
||||
JobType.FULL_TIME: "CF3CP",
|
||||
JobType.PART_TIME: "75GKK",
|
||||
JobType.CONTRACT: "NJXCK",
|
||||
JobType.INTERNSHIP: "VDTG7",
|
||||
}
|
||||
|
||||
raw_description = response.json()["body"]["jobInfoWrapperModel"][
|
||||
"jobInfoModel"
|
||||
]["sanitizedJobDescription"]
|
||||
soup = BeautifulSoup(raw_description, "html.parser")
|
||||
text_content = " ".join(soup.get_text().split()).strip()
|
||||
return text_content
|
||||
keys = []
|
||||
if self.scraper_input.job_type:
|
||||
key = job_type_key_mapping[self.scraper_input.job_type]
|
||||
keys.append(key)
|
||||
|
||||
if self.scraper_input.is_remote:
|
||||
keys.append("DSQF7")
|
||||
|
||||
if keys:
|
||||
keys_str = '", "'.join(keys) # Prepare your keys string
|
||||
filters_str = f"""
|
||||
filters: {{
|
||||
composite: {{
|
||||
filters: [{{
|
||||
keyword: {{
|
||||
field: "attributes",
|
||||
keys: ["{keys_str}"]
|
||||
}}
|
||||
}}]
|
||||
}}
|
||||
}}
|
||||
"""
|
||||
return filters_str
|
||||
|
||||
def _process_job(self, job: dict) -> JobPost | None:
|
||||
"""
|
||||
Parses the job dict into JobPost model
|
||||
:param job: dict to parse
|
||||
:return: JobPost if it's a new job
|
||||
"""
|
||||
job_url = f'{self.base_url}/viewjob?jk={job["key"]}'
|
||||
if job_url in self.seen_urls:
|
||||
return
|
||||
self.seen_urls.add(job_url)
|
||||
description = job["description"]["html"]
|
||||
if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
|
||||
description = markdown_converter(description)
|
||||
|
||||
job_type = self._get_job_type(job["attributes"])
|
||||
timestamp_seconds = job["datePublished"] / 1000
|
||||
date_posted = datetime.fromtimestamp(timestamp_seconds).strftime("%Y-%m-%d")
|
||||
employer = job["employer"].get("dossier") if job["employer"] else None
|
||||
employer_details = employer.get("employerDetails", {}) if employer else {}
|
||||
rel_url = job["employer"]["relativeCompanyPageUrl"] if job["employer"] else None
|
||||
return JobPost(
|
||||
title=job["title"],
|
||||
description=description,
|
||||
company_name=job["employer"].get("name") if job.get("employer") else None,
|
||||
company_url=(f"{self.base_url}{rel_url}" if job["employer"] else None),
|
||||
company_url_direct=(
|
||||
employer["links"]["corporateWebsite"] if employer else None
|
||||
),
|
||||
location=Location(
|
||||
city=job.get("location", {}).get("city"),
|
||||
state=job.get("location", {}).get("admin1Code"),
|
||||
country=job.get("location", {}).get("countryCode"),
|
||||
),
|
||||
job_type=job_type,
|
||||
compensation=self._get_compensation(job),
|
||||
date_posted=date_posted,
|
||||
job_url=job_url,
|
||||
job_url_direct=(
|
||||
job["recruit"].get("viewJobUrl") if job.get("recruit") else None
|
||||
),
|
||||
emails=extract_emails_from_text(description) if description else None,
|
||||
is_remote=self._is_job_remote(job, description),
|
||||
company_addresses=(
|
||||
employer_details["addresses"][0]
|
||||
if employer_details.get("addresses")
|
||||
else None
|
||||
),
|
||||
company_industry=(
|
||||
employer_details["industry"]
|
||||
.replace("Iv1", "")
|
||||
.replace("_", " ")
|
||||
.title()
|
||||
if employer_details.get("industry")
|
||||
else None
|
||||
),
|
||||
company_num_employees=employer_details.get("employeesLocalizedLabel"),
|
||||
company_revenue=employer_details.get("revenueLocalizedLabel"),
|
||||
company_description=employer_details.get("briefDescription"),
|
||||
ceo_name=employer_details.get("ceoName"),
|
||||
ceo_photo_url=employer_details.get("ceoPhotoUrl"),
|
||||
logo_photo_url=(
|
||||
employer["images"].get("squareLogoUrl")
|
||||
if employer and employer.get("images")
|
||||
else None
|
||||
),
|
||||
banner_photo_url=(
|
||||
employer["images"].get("headerImageUrl")
|
||||
if employer and employer.get("images")
|
||||
else None
|
||||
),
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def get_job_type(job: dict) -> Optional[JobType]:
|
||||
def _get_job_type(attributes: list) -> list[JobType]:
|
||||
"""
|
||||
Parses the job to get JobTypeIndeed
|
||||
Parses the attributes to get list of job types
|
||||
:param attributes:
|
||||
:return: list of JobType
|
||||
"""
|
||||
job_types: list[JobType] = []
|
||||
for attribute in attributes:
|
||||
job_type_str = attribute["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 _get_compensation(job: dict) -> Compensation | None:
|
||||
"""
|
||||
Parses the job to get compensation
|
||||
:param job:
|
||||
:return:
|
||||
:param job:
|
||||
:return: compensation object
|
||||
"""
|
||||
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
|
||||
|
||||
@staticmethod
|
||||
def parse_jobs(soup: BeautifulSoup) -> dict:
|
||||
"""
|
||||
Parses the jobs from the soup object
|
||||
:param soup:
|
||||
:return: jobs
|
||||
"""
|
||||
|
||||
def find_mosaic_script() -> Optional[Tag]:
|
||||
"""
|
||||
Finds jobcards script tag
|
||||
:return: script_tag
|
||||
"""
|
||||
script_tags = soup.find_all("script")
|
||||
|
||||
for tag in script_tags:
|
||||
if (
|
||||
tag.string
|
||||
and "mosaic.providerData" in tag.string
|
||||
and "mosaic-provider-jobcards" in tag.string
|
||||
):
|
||||
return tag
|
||||
comp = job["compensation"]["baseSalary"]
|
||||
if not comp:
|
||||
return None
|
||||
|
||||
script_tag = find_mosaic_script()
|
||||
|
||||
if script_tag:
|
||||
script_str = script_tag.string
|
||||
pattern = r'window.mosaic.providerData\["mosaic-provider-jobcards"\]\s*=\s*({.*?});'
|
||||
p = re.compile(pattern, re.DOTALL)
|
||||
m = p.search(script_str)
|
||||
if m:
|
||||
jobs = json.loads(m.group(1).strip())
|
||||
return jobs
|
||||
else:
|
||||
raise ParsingException("Could not find mosaic provider job cards data")
|
||||
else:
|
||||
raise ParsingException(
|
||||
"Could not find a script tag containing mosaic provider data"
|
||||
)
|
||||
interval = IndeedScraper._get_compensation_interval(comp["unitOfWork"])
|
||||
if not interval:
|
||||
return None
|
||||
min_range = comp["range"].get("min")
|
||||
max_range = comp["range"].get("max")
|
||||
return Compensation(
|
||||
interval=interval,
|
||||
min_amount=round(min_range, 2) if min_range is not None else None,
|
||||
max_amount=round(max_range, 2) if max_range is not None else None,
|
||||
currency=job["compensation"]["currencyCode"],
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def total_jobs(soup: BeautifulSoup) -> int:
|
||||
def _is_job_remote(job: dict, description: str) -> bool:
|
||||
"""
|
||||
Parses the total jobs for that search from soup object
|
||||
:param soup:
|
||||
:return: total_num_jobs
|
||||
Searches the description, location, and attributes to check if job is remote
|
||||
"""
|
||||
script = soup.find("script", string=lambda t: "window._initialData" in t)
|
||||
remote_keywords = ["remote", "work from home", "wfh"]
|
||||
is_remote_in_attributes = any(
|
||||
any(keyword in attr["label"].lower() for keyword in remote_keywords)
|
||||
for attr in job["attributes"]
|
||||
)
|
||||
is_remote_in_description = any(
|
||||
keyword in description.lower() for keyword in remote_keywords
|
||||
)
|
||||
is_remote_in_location = any(
|
||||
keyword in job["location"]["formatted"]["long"].lower()
|
||||
for keyword in remote_keywords
|
||||
)
|
||||
return (
|
||||
is_remote_in_attributes or is_remote_in_description or is_remote_in_location
|
||||
)
|
||||
|
||||
pattern = re.compile(r"window._initialData\s*=\s*({.*})\s*;", re.DOTALL)
|
||||
match = pattern.search(script.string)
|
||||
total_num_jobs = 0
|
||||
if match:
|
||||
json_str = match.group(1)
|
||||
data = json.loads(json_str)
|
||||
total_num_jobs = int(data["searchTitleBarModel"]["totalNumResults"])
|
||||
return total_num_jobs
|
||||
@staticmethod
|
||||
def _get_compensation_interval(interval: str) -> CompensationInterval:
|
||||
interval_mapping = {
|
||||
"DAY": "DAILY",
|
||||
"YEAR": "YEARLY",
|
||||
"HOUR": "HOURLY",
|
||||
"WEEK": "WEEKLY",
|
||||
"MONTH": "MONTHLY",
|
||||
}
|
||||
mapped_interval = interval_mapping.get(interval.upper(), None)
|
||||
if mapped_interval and mapped_interval in CompensationInterval.__members__:
|
||||
return CompensationInterval[mapped_interval]
|
||||
else:
|
||||
raise ValueError(f"Unsupported interval: {interval}")
|
||||
|
||||
api_headers = {
|
||||
"Host": "apis.indeed.com",
|
||||
"content-type": "application/json",
|
||||
"indeed-api-key": "161092c2017b5bbab13edb12461a62d5a833871e7cad6d9d475304573de67ac8",
|
||||
"accept": "application/json",
|
||||
"indeed-locale": "en-US",
|
||||
"accept-language": "en-US,en;q=0.9",
|
||||
"user-agent": "Mozilla/5.0 (iPhone; CPU iPhone OS 16_6_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/15E148 Indeed App 193.1",
|
||||
"indeed-app-info": "appv=193.1; appid=com.indeed.jobsearch; osv=16.6.1; os=ios; dtype=phone",
|
||||
}
|
||||
job_search_query = """
|
||||
query GetJobData {{
|
||||
jobSearch(
|
||||
{what}
|
||||
{location}
|
||||
includeSponsoredResults: NONE
|
||||
limit: 100
|
||||
sort: DATE
|
||||
{cursor}
|
||||
{filters}
|
||||
) {{
|
||||
pageInfo {{
|
||||
nextCursor
|
||||
}}
|
||||
results {{
|
||||
trackingKey
|
||||
job {{
|
||||
key
|
||||
title
|
||||
datePublished
|
||||
dateOnIndeed
|
||||
description {{
|
||||
html
|
||||
}}
|
||||
location {{
|
||||
countryName
|
||||
countryCode
|
||||
admin1Code
|
||||
city
|
||||
postalCode
|
||||
streetAddress
|
||||
formatted {{
|
||||
short
|
||||
long
|
||||
}}
|
||||
}}
|
||||
compensation {{
|
||||
baseSalary {{
|
||||
unitOfWork
|
||||
range {{
|
||||
... on Range {{
|
||||
min
|
||||
max
|
||||
}}
|
||||
}}
|
||||
}}
|
||||
currencyCode
|
||||
}}
|
||||
attributes {{
|
||||
key
|
||||
label
|
||||
}}
|
||||
employer {{
|
||||
relativeCompanyPageUrl
|
||||
name
|
||||
dossier {{
|
||||
employerDetails {{
|
||||
addresses
|
||||
industry
|
||||
employeesLocalizedLabel
|
||||
revenueLocalizedLabel
|
||||
briefDescription
|
||||
ceoName
|
||||
ceoPhotoUrl
|
||||
}}
|
||||
images {{
|
||||
headerImageUrl
|
||||
squareLogoUrl
|
||||
}}
|
||||
links {{
|
||||
corporateWebsite
|
||||
}}
|
||||
}}
|
||||
}}
|
||||
recruit {{
|
||||
viewJobUrl
|
||||
detailedSalary
|
||||
workSchedule
|
||||
}}
|
||||
}}
|
||||
}}
|
||||
}}
|
||||
}}
|
||||
"""
|
||||
|
||||
@@ -1,22 +1,59 @@
|
||||
from typing import Optional, Tuple
|
||||
"""
|
||||
jobspy.scrapers.linkedin
|
||||
~~~~~~~~~~~~~~~~~~~
|
||||
|
||||
This module contains routines to scrape LinkedIn.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import time
|
||||
import random
|
||||
import regex as re
|
||||
import urllib.parse
|
||||
from typing import Optional
|
||||
from datetime import datetime
|
||||
|
||||
import requests
|
||||
from bs4 import BeautifulSoup
|
||||
from threading import Lock
|
||||
from bs4.element import Tag
|
||||
from bs4 import BeautifulSoup
|
||||
from urllib.parse import urlparse, urlunparse
|
||||
|
||||
from .. import Scraper, ScraperInput, Site
|
||||
from ...jobs import JobPost, Location, JobResponse, JobType, Compensation, CompensationInterval
|
||||
from ..exceptions import LinkedInException
|
||||
from ..utils import create_session
|
||||
from ...jobs import (
|
||||
JobPost,
|
||||
Location,
|
||||
JobResponse,
|
||||
JobType,
|
||||
Country,
|
||||
Compensation,
|
||||
DescriptionFormat,
|
||||
)
|
||||
from ..utils import (
|
||||
logger,
|
||||
extract_emails_from_text,
|
||||
get_enum_from_job_type,
|
||||
currency_parser,
|
||||
markdown_converter,
|
||||
)
|
||||
|
||||
|
||||
class LinkedInScraper(Scraper):
|
||||
def __init__(self):
|
||||
base_url = "https://www.linkedin.com"
|
||||
delay = 3
|
||||
band_delay = 4
|
||||
jobs_per_page = 25
|
||||
|
||||
def __init__(self, proxy: Optional[str] = None):
|
||||
"""
|
||||
Initializes LinkedInScraper with the LinkedIn job search url
|
||||
"""
|
||||
site = Site(Site.LINKEDIN)
|
||||
url = "https://www.linkedin.com"
|
||||
super().__init__(site, url)
|
||||
super().__init__(Site(Site.LINKEDIN), proxy=proxy)
|
||||
self.scraper_input = None
|
||||
self.country = "worldwide"
|
||||
self.job_url_direct_regex = re.compile(r'(?<=\?url=)[^"]+')
|
||||
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||
"""
|
||||
@@ -24,179 +61,217 @@ class LinkedInScraper(Scraper):
|
||||
:param scraper_input:
|
||||
:return: job_response
|
||||
"""
|
||||
self.scraper_input = scraper_input
|
||||
job_list: list[JobPost] = []
|
||||
seen_urls = set()
|
||||
page, processed_jobs, job_count = 0, 0, 0
|
||||
|
||||
def job_type_code(job_type):
|
||||
mapping = {
|
||||
JobType.FULL_TIME: "F",
|
||||
JobType.PART_TIME: "P",
|
||||
JobType.INTERNSHIP: "I",
|
||||
JobType.CONTRACT: "C",
|
||||
JobType.TEMPORARY: "T",
|
||||
}
|
||||
|
||||
return mapping.get(job_type, "")
|
||||
|
||||
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)
|
||||
url_lock = Lock()
|
||||
page = scraper_input.offset // 25 + 25 if scraper_input.offset else 0
|
||||
seconds_old = (
|
||||
scraper_input.hours_old * 3600 if scraper_input.hours_old else None
|
||||
)
|
||||
continue_search = (
|
||||
lambda: len(job_list) < scraper_input.results_wanted and page < 1000
|
||||
)
|
||||
while continue_search():
|
||||
logger.info(f"LinkedIn search page: {page // 25 + 1}")
|
||||
session = create_session(is_tls=False, has_retry=True, delay=5)
|
||||
params = {
|
||||
"keywords": scraper_input.search_term,
|
||||
"location": scraper_input.location,
|
||||
"distance": scraper_input.distance,
|
||||
"f_WT": 2 if scraper_input.is_remote else None,
|
||||
"f_JT": (
|
||||
self.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,
|
||||
}
|
||||
else None
|
||||
),
|
||||
"pageNum": 0,
|
||||
"start": page + scraper_input.offset,
|
||||
"f_AL": "true" if scraper_input.easy_apply else None,
|
||||
"f_C": (
|
||||
",".join(map(str, scraper_input.linkedin_company_ids))
|
||||
if scraper_input.linkedin_company_ids
|
||||
else None
|
||||
),
|
||||
}
|
||||
if seconds_old is not None:
|
||||
params["f_TPR"] = f"r{seconds_old}"
|
||||
|
||||
params = {k: v for k, v in params.items() if v is not None}
|
||||
params = {k: v for k, v in params.items() if v is not None}
|
||||
try:
|
||||
response = session.get(
|
||||
f"{self.url}/jobs/search", params=params, allow_redirects=True
|
||||
f"{self.base_url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
|
||||
params=params,
|
||||
allow_redirects=True,
|
||||
proxies=self.proxy,
|
||||
headers=self.headers,
|
||||
timeout=10,
|
||||
)
|
||||
if response.status_code not in range(200, 400):
|
||||
if response.status_code == 429:
|
||||
err = (
|
||||
f"429 Response - Blocked by LinkedIn for too many requests"
|
||||
)
|
||||
else:
|
||||
err = f"LinkedIn response status code {response.status_code}"
|
||||
err += f" - {response.text}"
|
||||
logger.error(err)
|
||||
return JobResponse(jobs=job_list)
|
||||
except Exception as e:
|
||||
if "Proxy responded with" in str(e):
|
||||
logger.error(f"LinkedIn: Bad proxy")
|
||||
else:
|
||||
logger.error(f"LinkedIn: {str(e)}")
|
||||
return JobResponse(jobs=job_list)
|
||||
|
||||
if response.status_code != 200:
|
||||
return JobResponse(
|
||||
success=False,
|
||||
error=f"Response returned {response.status_code}",
|
||||
)
|
||||
soup = BeautifulSoup(response.text, "html.parser")
|
||||
job_cards = soup.find_all("div", class_="base-search-card")
|
||||
if len(job_cards) == 0:
|
||||
return JobResponse(jobs=job_list)
|
||||
|
||||
soup = BeautifulSoup(response.text, "html.parser")
|
||||
for job_card in job_cards:
|
||||
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.base_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)))
|
||||
|
||||
for job_card in soup.find_all(
|
||||
"div",
|
||||
class_="base-card relative w-full hover:no-underline focus:no-underline base-card--link base-search-card base-search-card--link job-search-card",
|
||||
):
|
||||
processed_jobs += 1
|
||||
data_entity_urn = job_card.get("data-entity-urn", "")
|
||||
job_id = (
|
||||
data_entity_urn.split(":")[-1] if data_entity_urn else "N/A"
|
||||
)
|
||||
job_url = f"{self.url}/jobs/view/{job_id}"
|
||||
with url_lock:
|
||||
if job_url in seen_urls:
|
||||
continue
|
||||
seen_urls.add(job_url)
|
||||
job_info = job_card.find("div", class_="base-search-card__info")
|
||||
if job_info is None:
|
||||
continue
|
||||
title_tag = job_info.find("h3", class_="base-search-card__title")
|
||||
title = title_tag.text.strip() if title_tag else "N/A"
|
||||
|
||||
company_tag = job_info.find("a", class_="hidden-nested-link")
|
||||
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
|
||||
):
|
||||
try:
|
||||
fetch_desc = scraper_input.linkedin_fetch_description
|
||||
job_post = self._process_job(job_card, job_url, fetch_desc)
|
||||
if job_post:
|
||||
job_list.append(job_post)
|
||||
if not continue_search():
|
||||
break
|
||||
if (
|
||||
len(job_list) >= scraper_input.results_wanted
|
||||
or processed_jobs >= job_count
|
||||
):
|
||||
break
|
||||
except Exception as e:
|
||||
raise LinkedInException(str(e))
|
||||
|
||||
page += 1
|
||||
if continue_search():
|
||||
time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
|
||||
page += self.jobs_per_page
|
||||
|
||||
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, full_descr: bool
|
||||
) -> Optional[JobPost]:
|
||||
salary_tag = job_card.find("span", class_="job-search-card__salary-info")
|
||||
|
||||
compensation = None
|
||||
if salary_tag:
|
||||
salary_text = salary_tag.get_text(separator=" ").strip()
|
||||
salary_values = [currency_parser(value) for value in salary_text.split("-")]
|
||||
salary_min = salary_values[0]
|
||||
salary_max = salary_values[1]
|
||||
currency = salary_text[0] if salary_text[0] != "$" else "USD"
|
||||
|
||||
compensation = Compensation(
|
||||
min_amount=int(salary_min),
|
||||
max_amount=int(salary_max),
|
||||
currency=currency,
|
||||
)
|
||||
|
||||
title_tag = job_card.find("span", class_="sr-only")
|
||||
title = title_tag.get_text(strip=True) if title_tag else "N/A"
|
||||
|
||||
company_tag = job_card.find("h4", class_="base-search-card__subtitle")
|
||||
company_a_tag = company_tag.find("a") if company_tag else None
|
||||
company_url = (
|
||||
urlunparse(urlparse(company_a_tag.get("href"))._replace(query=""))
|
||||
if company_a_tag and company_a_tag.has_attr("href")
|
||||
else ""
|
||||
)
|
||||
company = company_a_tag.get_text(strip=True) if company_a_tag else "N/A"
|
||||
|
||||
metadata_card = job_card.find("div", class_="base-search-card__metadata")
|
||||
location = self._get_location(metadata_card)
|
||||
|
||||
datetime_tag = (
|
||||
metadata_card.find("time", class_="job-search-card__listdate")
|
||||
if metadata_card
|
||||
else None
|
||||
)
|
||||
date_posted = 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:
|
||||
date_posted = None
|
||||
job_details = {}
|
||||
if full_descr:
|
||||
job_details = self._get_job_details(job_url)
|
||||
|
||||
return JobPost(
|
||||
title=title,
|
||||
company_name=company,
|
||||
company_url=company_url,
|
||||
location=location,
|
||||
date_posted=date_posted,
|
||||
job_url=job_url,
|
||||
compensation=compensation,
|
||||
job_type=job_details.get("job_type"),
|
||||
description=job_details.get("description"),
|
||||
job_url_direct=job_details.get("job_url_direct"),
|
||||
emails=extract_emails_from_text(job_details.get("description")),
|
||||
logo_photo_url=job_details.get("logo_photo_url"),
|
||||
)
|
||||
|
||||
def _get_job_details(self, job_page_url: str) -> dict:
|
||||
"""
|
||||
Retrieves job description by going to the job page url
|
||||
Retrieves job description and other job details by going to the job page url
|
||||
:param job_page_url:
|
||||
:return: description or None
|
||||
:return: dict
|
||||
"""
|
||||
response = requests.get(job_page_url, allow_redirects=True)
|
||||
if response.status_code not in range(200, 400):
|
||||
return None, None
|
||||
try:
|
||||
session = create_session(is_tls=False, has_retry=True)
|
||||
response = session.get(
|
||||
job_page_url, headers=self.headers, timeout=5, proxies=self.proxy
|
||||
)
|
||||
response.raise_for_status()
|
||||
except:
|
||||
return {}
|
||||
if response.url == "https://www.linkedin.com/signup":
|
||||
return {}
|
||||
|
||||
soup = BeautifulSoup(response.text, "html.parser")
|
||||
div_content = soup.find(
|
||||
"div", class_=lambda x: x and "show-more-less-html__markup" in x
|
||||
)
|
||||
description = None
|
||||
if div_content is not None:
|
||||
|
||||
text_content = None
|
||||
if div_content:
|
||||
text_content = " ".join(div_content.get_text().split()).strip()
|
||||
def remove_attributes(tag):
|
||||
for attr in list(tag.attrs):
|
||||
del tag[attr]
|
||||
return tag
|
||||
|
||||
def get_job_type(
|
||||
soup: BeautifulSoup,
|
||||
) -> Tuple[Optional[str], Optional[JobType]]:
|
||||
"""
|
||||
Gets the job type from job page
|
||||
:param soup:
|
||||
:return: JobType
|
||||
"""
|
||||
h3_tag = soup.find(
|
||||
"h3",
|
||||
class_="description__job-criteria-subheader",
|
||||
string=lambda text: "Employment type" in text,
|
||||
)
|
||||
div_content = remove_attributes(div_content)
|
||||
description = div_content.prettify(formatter="html")
|
||||
if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
|
||||
description = markdown_converter(description)
|
||||
return {
|
||||
"description": description,
|
||||
"job_type": self._parse_job_type(soup),
|
||||
"job_url_direct": self._parse_job_url_direct(soup),
|
||||
"logo_photo_url": soup.find("img", {"class": "artdeco-entity-image"}).get(
|
||||
"data-delayed-url"
|
||||
),
|
||||
}
|
||||
|
||||
employment_type = None
|
||||
if h3_tag:
|
||||
employment_type_span = h3_tag.find_next_sibling(
|
||||
"span",
|
||||
class_="description__job-criteria-text description__job-criteria-text--criteria",
|
||||
)
|
||||
if employment_type_span:
|
||||
employment_type = employment_type_span.get_text(strip=True)
|
||||
employment_type = employment_type.lower()
|
||||
employment_type = employment_type.replace("-", "")
|
||||
|
||||
return JobType(employment_type)
|
||||
|
||||
return text_content, 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=Country.from_string(self.country))
|
||||
if metadata_card is not None:
|
||||
location_tag = metadata_card.find(
|
||||
"span", class_="job-search-card__location"
|
||||
@@ -208,6 +283,71 @@ class LinkedInScraper(Scraper):
|
||||
location = Location(
|
||||
city=city,
|
||||
state=state,
|
||||
country=Country.from_string(self.country),
|
||||
)
|
||||
|
||||
elif len(parts) == 3:
|
||||
city, state, country = parts
|
||||
country = Country.from_string(country)
|
||||
location = Location(city=city, state=state, country=country)
|
||||
return location
|
||||
|
||||
@staticmethod
|
||||
def _parse_job_type(soup_job_type: BeautifulSoup) -> list[JobType] | None:
|
||||
"""
|
||||
Gets the job type from job page
|
||||
:param soup_job_type:
|
||||
:return: JobType
|
||||
"""
|
||||
h3_tag = soup_job_type.find(
|
||||
"h3",
|
||||
class_="description__job-criteria-subheader",
|
||||
string=lambda text: "Employment type" in text,
|
||||
)
|
||||
employment_type = None
|
||||
if h3_tag:
|
||||
employment_type_span = h3_tag.find_next_sibling(
|
||||
"span",
|
||||
class_="description__job-criteria-text description__job-criteria-text--criteria",
|
||||
)
|
||||
if employment_type_span:
|
||||
employment_type = employment_type_span.get_text(strip=True)
|
||||
employment_type = employment_type.lower()
|
||||
employment_type = employment_type.replace("-", "")
|
||||
|
||||
return [get_enum_from_job_type(employment_type)] if employment_type else []
|
||||
|
||||
def _parse_job_url_direct(self, soup: BeautifulSoup) -> str | None:
|
||||
"""
|
||||
Gets the job url direct from job page
|
||||
:param soup:
|
||||
:return: str
|
||||
"""
|
||||
job_url_direct = None
|
||||
job_url_direct_content = soup.find("code", id="applyUrl")
|
||||
if job_url_direct_content:
|
||||
job_url_direct_match = self.job_url_direct_regex.search(
|
||||
job_url_direct_content.decode_contents().strip()
|
||||
)
|
||||
if job_url_direct_match:
|
||||
job_url_direct = urllib.parse.unquote(job_url_direct_match.group())
|
||||
|
||||
return job_url_direct
|
||||
|
||||
@staticmethod
|
||||
def job_type_code(job_type_enum: JobType) -> str:
|
||||
return {
|
||||
JobType.FULL_TIME: "F",
|
||||
JobType.PART_TIME: "P",
|
||||
JobType.INTERNSHIP: "I",
|
||||
JobType.CONTRACT: "C",
|
||||
JobType.TEMPORARY: "T",
|
||||
}.get(job_type_enum, "")
|
||||
|
||||
headers = {
|
||||
"authority": "www.linkedin.com",
|
||||
"accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7",
|
||||
"accept-language": "en-US,en;q=0.9",
|
||||
"cache-control": "max-age=0",
|
||||
"upgrade-insecure-requests": "1",
|
||||
"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36",
|
||||
}
|
||||
|
||||
113
src/jobspy/scrapers/utils.py
Normal file
113
src/jobspy/scrapers/utils.py
Normal file
@@ -0,0 +1,113 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import re
|
||||
import logging
|
||||
import requests
|
||||
import tls_client
|
||||
import numpy as np
|
||||
from markdownify import markdownify as md
|
||||
from requests.adapters import HTTPAdapter, Retry
|
||||
|
||||
from ..jobs import JobType
|
||||
|
||||
logger = logging.getLogger("JobSpy")
|
||||
logger.propagate = False
|
||||
if not logger.handlers:
|
||||
logger.setLevel(logging.INFO)
|
||||
console_handler = logging.StreamHandler()
|
||||
format = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
|
||||
formatter = logging.Formatter(format)
|
||||
console_handler.setFormatter(formatter)
|
||||
logger.addHandler(console_handler)
|
||||
|
||||
|
||||
def set_logger_level(verbose: int = 2):
|
||||
"""
|
||||
Adjusts the logger's level. This function allows the logging level to be changed at runtime.
|
||||
|
||||
Parameters:
|
||||
- verbose: int {0, 1, 2} (default=2, all logs)
|
||||
"""
|
||||
if verbose is None:
|
||||
return
|
||||
level_name = {2: "INFO", 1: "WARNING", 0: "ERROR"}.get(verbose, "INFO")
|
||||
level = getattr(logging, level_name.upper(), None)
|
||||
if level is not None:
|
||||
logger.setLevel(level)
|
||||
else:
|
||||
raise ValueError(f"Invalid log level: {level_name}")
|
||||
|
||||
|
||||
def markdown_converter(description_html: str):
|
||||
if description_html is None:
|
||||
return None
|
||||
markdown = md(description_html)
|
||||
return markdown.strip()
|
||||
|
||||
|
||||
def extract_emails_from_text(text: str) -> list[str] | None:
|
||||
if not text:
|
||||
return None
|
||||
email_regex = re.compile(r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}")
|
||||
return email_regex.findall(text)
|
||||
|
||||
|
||||
def create_session(
|
||||
proxy: dict | None = None,
|
||||
is_tls: bool = True,
|
||||
has_retry: bool = False,
|
||||
delay: int = 1,
|
||||
) -> requests.Session:
|
||||
"""
|
||||
Creates a requests session with optional tls, proxy, and retry settings.
|
||||
:return: A session object
|
||||
"""
|
||||
if is_tls:
|
||||
session = tls_client.Session(random_tls_extension_order=True)
|
||||
session.proxies = proxy
|
||||
else:
|
||||
session = requests.Session()
|
||||
session.allow_redirects = True
|
||||
if proxy:
|
||||
session.proxies.update(proxy)
|
||||
if has_retry:
|
||||
retries = Retry(
|
||||
total=3,
|
||||
connect=3,
|
||||
status=3,
|
||||
status_forcelist=[500, 502, 503, 504, 429],
|
||||
backoff_factor=delay,
|
||||
)
|
||||
adapter = HTTPAdapter(max_retries=retries)
|
||||
|
||||
session.mount("http://", adapter)
|
||||
session.mount("https://", adapter)
|
||||
return session
|
||||
|
||||
|
||||
def get_enum_from_job_type(job_type_str: str) -> JobType | None:
|
||||
"""
|
||||
Given a string, returns the corresponding JobType enum member if a match is found.
|
||||
"""
|
||||
res = None
|
||||
for job_type in JobType:
|
||||
if job_type_str in job_type.value:
|
||||
res = job_type
|
||||
return res
|
||||
|
||||
|
||||
def currency_parser(cur_str):
|
||||
# Remove any non-numerical characters
|
||||
# except for ',' '.' or '-' (e.g. EUR)
|
||||
cur_str = re.sub("[^-0-9.,]", "", cur_str)
|
||||
# Remove any 000s separators (either , or .)
|
||||
cur_str = re.sub("[.,]", "", cur_str[:-3]) + cur_str[-3:]
|
||||
|
||||
if "." in list(cur_str[-3:]):
|
||||
num = float(cur_str)
|
||||
elif "," in list(cur_str[-3:]):
|
||||
num = float(cur_str.replace(",", "."))
|
||||
else:
|
||||
num = float(cur_str)
|
||||
|
||||
return np.round(num, 2)
|
||||
@@ -1,405 +1,211 @@
|
||||
"""
|
||||
jobspy.scrapers.ziprecruiter
|
||||
~~~~~~~~~~~~~~~~~~~
|
||||
|
||||
This module contains routines to scrape ZipRecruiter.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import math
|
||||
import json
|
||||
import re
|
||||
import time
|
||||
from datetime import datetime
|
||||
from typing import Optional, Tuple, List
|
||||
from urllib.parse import urlparse, parse_qs
|
||||
from typing import Optional, Tuple, Any
|
||||
|
||||
import tls_client
|
||||
from bs4 import BeautifulSoup
|
||||
from bs4.element import Tag
|
||||
from concurrent.futures import ThreadPoolExecutor, Future
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
|
||||
from .. import Scraper, ScraperInput, Site, StatusException
|
||||
from ...jobs import JobPost, Compensation, CompensationInterval, Location, JobResponse, JobType
|
||||
from .. import Scraper, ScraperInput, Site
|
||||
from ..utils import (
|
||||
logger,
|
||||
extract_emails_from_text,
|
||||
create_session,
|
||||
markdown_converter,
|
||||
)
|
||||
from ...jobs import (
|
||||
JobPost,
|
||||
Compensation,
|
||||
Location,
|
||||
JobResponse,
|
||||
JobType,
|
||||
Country,
|
||||
DescriptionFormat,
|
||||
)
|
||||
|
||||
|
||||
class ZipRecruiterScraper(Scraper):
|
||||
def __init__(self):
|
||||
"""
|
||||
Initializes LinkedInScraper with the ZipRecruiter job search url
|
||||
"""
|
||||
site = Site(Site.ZIP_RECRUITER)
|
||||
url = "https://www.ziprecruiter.com"
|
||||
super().__init__(site, url)
|
||||
base_url = "https://www.ziprecruiter.com"
|
||||
api_url = "https://api.ziprecruiter.com"
|
||||
|
||||
def __init__(self, proxy: Optional[str] = None):
|
||||
"""
|
||||
Initializes ZipRecruiterScraper with the ZipRecruiter job search url
|
||||
"""
|
||||
self.scraper_input = None
|
||||
self.session = create_session(proxy)
|
||||
self._get_cookies()
|
||||
super().__init__(Site.ZIP_RECRUITER, proxy=proxy)
|
||||
|
||||
self.delay = 5
|
||||
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]:
|
||||
"""
|
||||
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
|
||||
"""
|
||||
|
||||
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
|
||||
|
||||
with ThreadPoolExecutor(max_workers=10) as executor:
|
||||
if "jobList" in data and data["jobList"]:
|
||||
jobs_js = data["jobList"]
|
||||
job_results = [executor.submit(self.process_job_js, job) for job in jobs_js]
|
||||
else:
|
||||
jobs_html = soup.find_all("div", {"class": "job_content"})
|
||||
job_results = [executor.submit(self.process_job_html, job) for job in
|
||||
jobs_html]
|
||||
|
||||
job_list = [result.result() for result in job_results if result.result()]
|
||||
|
||||
return job_list, job_count
|
||||
|
||||
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.
|
||||
"""
|
||||
self.scraper_input = scraper_input
|
||||
job_list: list[JobPost] = []
|
||||
continue_token = None
|
||||
|
||||
|
||||
pages_to_process = max(3, 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)
|
||||
|
||||
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)
|
||||
]
|
||||
|
||||
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}",
|
||||
max_pages = math.ceil(scraper_input.results_wanted / self.jobs_per_page)
|
||||
for page in range(1, max_pages + 1):
|
||||
if len(job_list) >= scraper_input.results_wanted:
|
||||
break
|
||||
if page > 1:
|
||||
time.sleep(self.delay)
|
||||
logger.info(f"ZipRecruiter search page: {page}")
|
||||
jobs_on_page, continue_token = self._find_jobs_in_page(
|
||||
scraper_input, continue_token
|
||||
)
|
||||
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 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 process_job_html(self, job: Tag) -> Optional[JobPost]:
|
||||
"""
|
||||
Parses a job from the job content tag
|
||||
:param job: BeautifulSoup Tag for one job post
|
||||
:return JobPost
|
||||
"""
|
||||
job_url = job.find("a", {"class": "job_link"})["href"]
|
||||
if job_url in self.seen_urls:
|
||||
return None
|
||||
|
||||
title = job.find("h2", {"class": "title"}).text
|
||||
company = job.find("a", {"class": "company_name"}).text.strip()
|
||||
|
||||
description, updated_job_url = self.get_description(
|
||||
job_url
|
||||
)
|
||||
if updated_job_url is not None:
|
||||
job_url = updated_job_url
|
||||
if description is None:
|
||||
description = job.find("p", {"class": "job_snippet"}).text.strip()
|
||||
|
||||
job_type_element = job.find("li", {"class": "perk_item perk_type"})
|
||||
if job_type_element:
|
||||
job_type_text = (
|
||||
job_type_element.text.strip()
|
||||
.lower()
|
||||
.replace("-", "")
|
||||
.replace(" ", "")
|
||||
)
|
||||
if job_type_text == "contractor":
|
||||
job_type_text = "contract"
|
||||
job_type = JobType(job_type_text)
|
||||
else:
|
||||
job_type = None
|
||||
|
||||
date_posted = ZipRecruiterScraper.get_date_posted(job)
|
||||
|
||||
job_post = JobPost(
|
||||
title=title,
|
||||
description=description,
|
||||
company_name=company,
|
||||
location=ZipRecruiterScraper.get_location(job),
|
||||
job_type=job_type,
|
||||
compensation=ZipRecruiterScraper.get_compensation(job),
|
||||
date_posted=date_posted,
|
||||
job_url=job_url,
|
||||
)
|
||||
return job_post
|
||||
|
||||
def process_job_js(self, job: dict) -> JobPost:
|
||||
# Map the job data to the expected fields by the Pydantic model
|
||||
title = job.get("Title")
|
||||
description = BeautifulSoup(job.get("Snippet","").strip(), "html.parser").get_text()
|
||||
|
||||
company = job.get("OrgName")
|
||||
location = Location(city=job.get("City"), state=job.get("State"))
|
||||
try:
|
||||
job_type = ZipRecruiterScraper.job_type_from_string(job.get("EmploymentType", "").replace("-", "_").lower())
|
||||
except ValueError:
|
||||
# print(f"Skipping job due to unrecognized job type: {job.get('EmploymentType')}")
|
||||
return None
|
||||
|
||||
formatted_salary = job.get("FormattedSalaryShort", "")
|
||||
salary_parts = formatted_salary.split(" ")
|
||||
|
||||
min_salary_str = salary_parts[0][1:].replace(",", "")
|
||||
if '.' in min_salary_str:
|
||||
min_amount = int(float(min_salary_str) * 1000)
|
||||
else:
|
||||
min_amount = int(min_salary_str.replace("K", "000"))
|
||||
|
||||
if len(salary_parts) >= 3 and salary_parts[2].startswith("$"):
|
||||
max_salary_str = salary_parts[2][1:].replace(",", "")
|
||||
if '.' in max_salary_str:
|
||||
max_amount = int(float(max_salary_str) * 1000)
|
||||
if jobs_on_page:
|
||||
job_list.extend(jobs_on_page)
|
||||
else:
|
||||
max_amount = int(max_salary_str.replace("K", "000"))
|
||||
else:
|
||||
max_amount = 0
|
||||
break
|
||||
if not continue_token:
|
||||
break
|
||||
return JobResponse(jobs=job_list[: scraper_input.results_wanted])
|
||||
|
||||
compensation = Compensation(
|
||||
interval=CompensationInterval.YEARLY,
|
||||
min_amount=min_amount,
|
||||
max_amount=max_amount
|
||||
def _find_jobs_in_page(
|
||||
self, scraper_input: ScraperInput, continue_token: str | None = None
|
||||
) -> Tuple[list[JobPost], Optional[str]]:
|
||||
"""
|
||||
Scrapes a page of ZipRecruiter for jobs with scraper_input criteria
|
||||
:param scraper_input:
|
||||
:param continue_token:
|
||||
:return: jobs found on page
|
||||
"""
|
||||
jobs_list = []
|
||||
params = self._add_params(scraper_input)
|
||||
if continue_token:
|
||||
params["continue_from"] = continue_token
|
||||
try:
|
||||
res = self.session.get(
|
||||
f"{self.api_url}/jobs-app/jobs", headers=self.headers, params=params
|
||||
)
|
||||
if res.status_code not in range(200, 400):
|
||||
if res.status_code == 429:
|
||||
err = "429 Response - Blocked by ZipRecruiter for too many requests"
|
||||
else:
|
||||
err = f"ZipRecruiter response status code {res.status_code}"
|
||||
err += f" with response: {res.text}" # ZipRecruiter likely not available in EU
|
||||
logger.error(err)
|
||||
return jobs_list, ""
|
||||
except Exception as e:
|
||||
if "Proxy responded with" in str(e):
|
||||
logger.error(f"Indeed: Bad proxy")
|
||||
else:
|
||||
logger.error(f"Indeed: {str(e)}")
|
||||
return jobs_list, ""
|
||||
|
||||
res_data = res.json()
|
||||
jobs_list = res_data.get("jobs", [])
|
||||
next_continue_token = res_data.get("continue", None)
|
||||
with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
|
||||
job_results = [executor.submit(self._process_job, job) for job in jobs_list]
|
||||
|
||||
job_list = list(filter(None, (result.result() for result in job_results)))
|
||||
return job_list, next_continue_token
|
||||
|
||||
def _process_job(self, job: dict) -> JobPost | None:
|
||||
"""
|
||||
Processes an individual job dict from the response
|
||||
"""
|
||||
title = job.get("name")
|
||||
job_url = f"{self.base_url}/jobs//j?lvk={job['listing_key']}"
|
||||
if job_url in self.seen_urls:
|
||||
return
|
||||
self.seen_urls.add(job_url)
|
||||
|
||||
description = job.get("job_description", "").strip()
|
||||
description = (
|
||||
markdown_converter(description)
|
||||
if self.scraper_input.description_format == DescriptionFormat.MARKDOWN
|
||||
else description
|
||||
)
|
||||
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)
|
||||
if posted_time_match:
|
||||
date_time_str = posted_time_match.group(1)
|
||||
date_posted_obj = datetime.strptime(date_time_str, "%Y-%m-%dT%H:%M:%SZ")
|
||||
date_posted = date_posted_obj.date()
|
||||
else:
|
||||
date_posted = date.today()
|
||||
job_url = job.get("JobURL")
|
||||
company = job.get("hiring_company", {}).get("name")
|
||||
country_value = "usa" if job.get("job_country") == "US" else "canada"
|
||||
country_enum = Country.from_string(country_value)
|
||||
|
||||
location = Location(
|
||||
city=job.get("job_city"), state=job.get("job_state"), country=country_enum
|
||||
)
|
||||
job_type = self._get_job_type_enum(
|
||||
job.get("employment_type", "").replace("_", "").lower()
|
||||
)
|
||||
date_posted = datetime.fromisoformat(job["posted_time"].rstrip("Z")).date()
|
||||
comp_interval = job.get("compensation_interval")
|
||||
comp_interval = "yearly" if comp_interval == "annual" else comp_interval
|
||||
comp_min = int(job["compensation_min"]) if "compensation_min" in job else None
|
||||
comp_max = int(job["compensation_max"]) if "compensation_max" in job else None
|
||||
comp_currency = job.get("compensation_currency")
|
||||
return JobPost(
|
||||
title=title,
|
||||
description=description,
|
||||
company_name=company,
|
||||
location=location,
|
||||
job_type=job_type,
|
||||
compensation=compensation,
|
||||
compensation=Compensation(
|
||||
interval=comp_interval,
|
||||
min_amount=comp_min,
|
||||
max_amount=comp_max,
|
||||
currency=comp_currency,
|
||||
),
|
||||
date_posted=date_posted,
|
||||
job_url=job_url,
|
||||
description=description,
|
||||
emails=extract_emails_from_text(description) if description else None,
|
||||
)
|
||||
return job_post
|
||||
|
||||
def _get_cookies(self):
|
||||
data = "event_type=session&logged_in=false&number_of_retry=1&property=model%3AiPhone&property=os%3AiOS&property=locale%3Aen_us&property=app_build_number%3A4734&property=app_version%3A91.0&property=manufacturer%3AApple&property=timestamp%3A2024-01-12T12%3A04%3A42-06%3A00&property=screen_height%3A852&property=os_version%3A16.6.1&property=source%3Ainstall&property=screen_width%3A393&property=device_model%3AiPhone%2014%20Pro&property=brand%3AApple"
|
||||
url = f"{self.api_url}/jobs-app/event"
|
||||
self.session.post(url, data=data, headers=self.headers)
|
||||
|
||||
@staticmethod
|
||||
def job_type_from_string(value: str) -> Optional[JobType]:
|
||||
if not value:
|
||||
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}")
|
||||
|
||||
def get_description(
|
||||
self,
|
||||
job_page_url: str
|
||||
) -> Tuple[Optional[str], Optional[str]]:
|
||||
"""
|
||||
Retrieves job description by going to the job page url
|
||||
:param job_page_url:
|
||||
:param session:
|
||||
:return: description or None, response url
|
||||
"""
|
||||
response = self.session.get(
|
||||
job_page_url, headers=ZipRecruiterScraper.headers(), allow_redirects=True
|
||||
)
|
||||
if response.status_code not in range(200, 400):
|
||||
return None, None
|
||||
|
||||
html_string = response.content
|
||||
soup_job = BeautifulSoup(html_string, "html.parser")
|
||||
|
||||
job_description_div = soup_job.find("div", {"class": "job_description"})
|
||||
if job_description_div:
|
||||
return job_description_div.text.strip(), response.url
|
||||
return None, response.url
|
||||
|
||||
@staticmethod
|
||||
def get_interval(interval_str: str):
|
||||
"""
|
||||
Maps the interval alias to its appropriate CompensationInterval.
|
||||
:param interval_str
|
||||
:return: CompensationInterval
|
||||
"""
|
||||
interval_alias = {"annually": CompensationInterval.YEARLY}
|
||||
interval_str = interval_str.lower()
|
||||
|
||||
if interval_str in interval_alias:
|
||||
return interval_alias[interval_str]
|
||||
|
||||
return CompensationInterval(interval_str)
|
||||
|
||||
@staticmethod
|
||||
def get_date_posted(job: BeautifulSoup) -> Optional[datetime.date]:
|
||||
"""
|
||||
Extracts the date a job was posted
|
||||
:param job
|
||||
:return: date the job was posted or None
|
||||
"""
|
||||
button = job.find(
|
||||
"button", {"class": "action_input save_job zrs_btn_secondary_200"}
|
||||
)
|
||||
if not button:
|
||||
return None
|
||||
|
||||
url_time = button.get("data-href", "")
|
||||
url_components = urlparse(url_time)
|
||||
params = parse_qs(url_components.query)
|
||||
posted_time_str = params.get("posted_time", [None])[0]
|
||||
|
||||
if posted_time_str:
|
||||
posted_date = datetime.strptime(
|
||||
posted_time_str, "%Y-%m-%dT%H:%M:%SZ"
|
||||
).date()
|
||||
return posted_date
|
||||
|
||||
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
|
||||
|
||||
@staticmethod
|
||||
def get_compensation(job: BeautifulSoup) -> Optional[Compensation]:
|
||||
"""
|
||||
Parses the compensation tag from the job BeautifulSoup object
|
||||
:param job
|
||||
:return: Compensation object or None
|
||||
"""
|
||||
pay_element = job.find("li", {"class": "perk_item perk_pay"})
|
||||
if pay_element is None:
|
||||
return None
|
||||
pay = pay_element.find("div", {"class": "value"}).find("span").text.strip()
|
||||
|
||||
def create_compensation_object(pay_string: str) -> Compensation:
|
||||
"""
|
||||
Creates a Compensation object from a pay_string
|
||||
:param pay_string
|
||||
:return: compensation
|
||||
"""
|
||||
interval = ZipRecruiterScraper.get_interval(pay_string.split()[-1])
|
||||
|
||||
amounts = []
|
||||
for amount in pay_string.split("to"):
|
||||
amount = amount.replace(",", "").strip("$ ").split(" ")[0]
|
||||
if "K" in amount:
|
||||
amount = amount.replace("K", "")
|
||||
amount = int(float(amount)) * 1000
|
||||
else:
|
||||
amount = int(float(amount))
|
||||
amounts.append(amount)
|
||||
|
||||
compensation = Compensation(
|
||||
interval=interval, min_amount=min(amounts), max_amount=max(amounts)
|
||||
)
|
||||
|
||||
return compensation
|
||||
|
||||
return create_compensation_object(pay)
|
||||
|
||||
@staticmethod
|
||||
def get_location(job: BeautifulSoup) -> Location:
|
||||
"""
|
||||
Extracts the job location from BeatifulSoup object
|
||||
:param job:
|
||||
:return: location
|
||||
"""
|
||||
location_link = job.find("a", {"class": "company_location"})
|
||||
if location_link is not None:
|
||||
location_string = location_link.text.strip()
|
||||
parts = location_string.split(", ")
|
||||
if len(parts) == 2:
|
||||
city, state = parts
|
||||
else:
|
||||
city, state = None, None
|
||||
else:
|
||||
city, state = None, None
|
||||
return Location(
|
||||
city=city,
|
||||
state=state,
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def headers() -> dict:
|
||||
"""
|
||||
Returns headers needed for requests
|
||||
: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"
|
||||
def _add_params(scraper_input) -> dict[str, str | Any]:
|
||||
params = {
|
||||
"search": scraper_input.search_term,
|
||||
"location": scraper_input.location,
|
||||
}
|
||||
if scraper_input.hours_old:
|
||||
params["days"] = max(scraper_input.hours_old // 24, 1)
|
||||
job_type_map = {JobType.FULL_TIME: "full_time", JobType.PART_TIME: "part_time"}
|
||||
if scraper_input.job_type:
|
||||
job_type = scraper_input.job_type
|
||||
params["employment_type"] = job_type_map.get(job_type, job_type.value[0])
|
||||
if scraper_input.easy_apply:
|
||||
params["zipapply"] = 1
|
||||
if scraper_input.is_remote:
|
||||
params["remote"] = 1
|
||||
if scraper_input.distance:
|
||||
params["radius"] = scraper_input.distance
|
||||
return {k: v for k, v in params.items() if v is not None}
|
||||
|
||||
headers = {
|
||||
"Host": "api.ziprecruiter.com",
|
||||
"accept": "*/*",
|
||||
"x-zr-zva-override": "100000000;vid:ZT1huzm_EQlDTVEc",
|
||||
"x-pushnotificationid": "0ff4983d38d7fc5b3370297f2bcffcf4b3321c418f5c22dd152a0264707602a0",
|
||||
"x-deviceid": "D77B3A92-E589-46A4-8A39-6EF6F1D86006",
|
||||
"user-agent": "Job Search/87.0 (iPhone; CPU iOS 16_6_1 like Mac OS X)",
|
||||
"authorization": "Basic YTBlZjMyZDYtN2I0Yy00MWVkLWEyODMtYTI1NDAzMzI0YTcyOg==",
|
||||
"accept-language": "en-US,en;q=0.9",
|
||||
}
|
||||
|
||||
0
src/tests/__init__.py
Normal file
0
src/tests/__init__.py
Normal file
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", "glassdoor"],
|
||||
search_term="software engineer",
|
||||
results_wanted=5,
|
||||
)
|
||||
|
||||
assert (
|
||||
isinstance(result, pd.DataFrame) and not result.empty
|
||||
), "Result should be a non-empty DataFrame"
|
||||
11
src/tests/test_glassdoor.py
Normal file
11
src/tests/test_glassdoor.py
Normal file
@@ -0,0 +1,11 @@
|
||||
from ..jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def test_indeed():
|
||||
result = scrape_jobs(
|
||||
site_name="glassdoor", search_term="software engineer", country_indeed="USA"
|
||||
)
|
||||
assert (
|
||||
isinstance(result, pd.DataFrame) and not result.empty
|
||||
), "Result should be a non-empty DataFrame"
|
||||
@@ -1,9 +1,11 @@
|
||||
from jobspy import scrape_jobs
|
||||
from ..jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def test_indeed():
|
||||
result = scrape_jobs(
|
||||
site_name="indeed",
|
||||
search_term="software engineer",
|
||||
site_name="indeed", search_term="software engineer", country_indeed="usa"
|
||||
)
|
||||
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