🔍 JobSpy API - Job Scraping Service

Powerful job scraping API that aggregates jobs from LinkedIn, Indeed, Glassdoor, Google Jobs, ZipRecruiter, and more. Search millions of jobs in seconds.

🌐 Live API: https://jobscrape-actor.vercel.app
📖 API Documentation: https://jobscrape-actor.vercel.app/docs

✨ Features

🌍 Multi-Platform Support - Scrape from 8+ major job boards simultaneously
🚀 Fast & Reliable - Built on FastAPI for high performance
📊 Multiple Formats - Export results as JSON, CSV, or Excel
🔍 Advanced Filtering - Filter by location, remote, job type, salary, and more
🌐 Global Coverage - Support for 40+ countries
📝 Rich Data - Get job titles, descriptions, salaries, companies, and more
🔒 CORS Enabled - Ready for frontend integration
📚 Interactive Docs - Swagger UI for easy API exploration

🎯 Supported Job Boards

Platform	Description
LinkedIn	Professional network with quality job postings
Indeed	Large job aggregator with extensive listings
ZipRecruiter	US/Canada focused job board
Glassdoor	Jobs with company reviews and salary data
Google Jobs	Aggregated job listings from Google
Bayt	Middle East focused job portal
Naukri	India's leading job portal
BDJobs	Bangladesh job portal

🚀 Quick Start

Try it Now (No Setup Required)

curl -X POST "https://jobscrape-actor.vercel.app/api/scrape" \
  -H "Content-Type: application/json" \
  -d '{
    "site_name": ["indeed", "linkedin"],
    "search_term": "python developer",
    "location": "San Francisco, CA",
    "results_wanted": 20
  }'

Python Example

import requests

response = requests.post(
    "https://jobscrape-actor.vercel.app/api/scrape",
    json={
        "site_name": ["indeed", "linkedin", "glassdoor"],
        "search_term": "software engineer",
        "location": "New York, NY",
        "results_wanted": 50,
        "hours_old": 72,
        "job_type": "fulltime"
    }
)

jobs = response.json()
print(f"Found {jobs['total_results']} jobs")

# Access job details
for job in jobs['jobs']:
    print(f"{job['title']} at {job['company']}")

JavaScript/Node.js Example

const response = await fetch('https://jobscrape-actor.vercel.app/api/scrape', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    site_name: ['indeed', 'linkedin'],
    search_term: 'react developer',
    location: 'Remote',
    results_wanted: 30,
    is_remote: true
  })
});

const data = await response.json();
console.log(`Found ${data.total_results} jobs!`);

📡 API Endpoints

Main Endpoints

Endpoint	Method	Description
`/api/scrape`	POST	Main job scraping endpoint with full options
`/api/scrape/simple`	GET	Simplified endpoint for quick searches
`/api/sites`	GET	List all supported job sites
`/api/countries`	GET	List all supported countries
`/api/examples`	GET	Get example API requests
`/api/health`	GET	API health check
`/docs`	GET	Interactive API documentation (Swagger UI)

Quick GET Request

# Simple search - just use URL parameters
https://jobscrape-actor.vercel.app/api/scrape/simple?search_term=developer&site_name=indeed&results_wanted=5

📋 Request Parameters

Core Parameters

Parameter	Type	Default	Description
`site_name`	array	all	Job sites to scrape (e.g., ["indeed", "linkedin"])
`search_term`	string	null	Job search term (e.g., "software engineer")
`location`	string	null	Job location (e.g., "San Francisco, CA")
`results_wanted`	integer	20	Number of results per site (1-100)
`is_remote`	boolean	false	Filter for remote jobs only
`job_type`	string	null	Job type: fulltime, parttime, internship, contract
`distance`	integer	50	Search radius in miles (0-200)
`hours_old`	integer	null	Filter jobs posted within N hours

Advanced Parameters

Parameter	Type	Default	Description
`country_indeed`	string	"USA"	Country for Indeed/Glassdoor searches
`easy_apply`	boolean	null	Filter for easy apply jobs (LinkedIn)
`linkedin_company_ids`	array	null	Filter by specific LinkedIn company IDs
`description_format`	string	"markdown"	Format: markdown or html
`enforce_annual_salary`	boolean	false	Convert all salaries to annual format
`output_format`	string	"json"	Output format: json, csv, or excel
`offset`	integer	0	Pagination offset

📊 Response Format

{
  "success": true,
  "message": "Successfully scraped 42 jobs",
  "total_results": 42,
  "timestamp": "2025-10-09T12:00:00.000Z",
  "search_parameters": {
    "site_name": ["indeed", "linkedin"],
    "search_term": "python developer",
    "location": "San Francisco, CA"
  },
  "jobs": [
    {
      "site": "indeed",
      "title": "Senior Python Developer",
      "company": "Tech Corp",
      "location": "San Francisco, CA",
      "job_type": "fulltime",
      "date_posted": "2025-10-08",
      "salary_source": "indeed",
      "interval": "yearly",
      "min_amount": 120000,
      "max_amount": 160000,
      "currency": "USD",
      "is_remote": false,
      "job_url": "https://...",
      "description": "We are looking for...",
      "benefits": "Health insurance, 401k, Remote work options",
      "company_url": "https://www.techcorp.com",
      "company_industry": "Technology",
      "company_num_employees": "1000-5000"
    }
  ]
}

🌍 Supported Countries

USA, Canada, UK, Australia, India, Germany, France, Spain, Italy, Netherlands, Belgium, Switzerland, Austria, Sweden, Norway, Denmark, Finland, Ireland, Poland, Brazil, Mexico, Argentina, Chile, Colombia, Singapore, Hong Kong, Japan, South Korea, UAE, Saudi Arabia, Egypt, South Africa, New Zealand, Philippines, Malaysia, Indonesia, Thailand, Vietnam, Pakistan, Bangladesh, Turkey, Israel

🛠️ Use Cases & Integrations

1. 🤖 AI Agents & LangChain

Integrate JobSpy API as a tool for AI agents to search and analyze job market data:

from langchain.tools import Tool
from langchain.agents import initialize_agent
import requests

def search_jobs(query: str) -> str:
    """Search for jobs using JobSpy API"""
    response = requests.post(
        "https://jobscrape-actor.vercel.app/api/scrape",
        json={
            "search_term": query,
            "results_wanted": 10,
            "site_name": ["indeed", "linkedin"]
        }
    )
    return response.json()

job_search_tool = Tool(
    name="JobSearch",
    func=search_jobs,
    description="Search for job listings across multiple platforms"
)

# Add to your LangChain agent
agent = initialize_agent([job_search_tool], llm, agent="zero-shot-react-description")

2. 🔄 N8N Workflow Automation

Create powerful job search automation workflows:

HTTP Request Node → JobSpy API
Filter Node → Filter by salary/requirements
Slack/Email Node → Send notifications
Google Sheets Node → Save results

N8N Configuration:

{
  "method": "POST",
  "url": "https://jobscrape-actor.vercel.app/api/scrape",
  "body": {
    "site_name": ["indeed", "linkedin"],
    "search_term": "{{ $json.job_title }}",
    "location": "{{ $json.location }}",
    "results_wanted": 50
  }
}

3. 📊 Job Market Analytics Dashboard

Build real-time job market dashboards with:

Streamlit - Quick data visualization
Tableau - Advanced analytics
Power BI - Business intelligence
Grafana - Monitoring job trends

4. 🔔 Job Alert Systems

Create personalized job alert systems:

# Schedule this with cron/celery
def daily_job_alert():
    jobs = search_jobs("senior python developer", remote=True)
    new_jobs = filter_new_jobs(jobs)
    if new_jobs:
        send_email_notification(new_jobs)

5. 🤝 Recruitment CRM Integration

Integrate with recruitment platforms:

Bullhorn
Greenhouse
Lever
Workable

6. 📱 Mobile Apps & Chrome Extensions

Build job search applications:

React Native mobile apps
Chrome extensions for job tracking
Progressive Web Apps (PWA)

7. 🔬 Research & Data Analysis

Perfect for:

Job market research
Salary trend analysis
Skills demand analysis
Company hiring patterns
Geographic job distribution

8. 🎓 Career Counseling Platforms

Help students and job seekers:

Career path recommendations
Market demand analysis
Skill gap identification
Salary expectations

9. ⚡ Zapier & Make.com Automations

Connect with 5000+ apps:

Trigger job searches based on events
Auto-apply to matching positions
Send Slack notifications for new jobs
Update Airtable with job data

10. 🎯 Competitor Analysis Tools

Monitor competitor hiring:

Track companies hiring patterns
Analyze job requirements
Identify market trends
Plan competitive strategies

🔧 Local Development

Prerequisites

Python 3.8+
pip

Installation

# Clone the repository
git clone https://github.com/Amon20044/jobscraper-actor.git
cd jobscraper-actor

# Install dependencies
pip install -r requirements.txt

# Run the server
uvicorn main:app --reload --port 5001

The API will be available at http://localhost:5001

Dependencies

fastapi
uvicorn[standard]
pandas
openpyxl
python-jobspy
python-multipart
pydantic

🚀 Deployment

Vercel (Recommended)

Fork this repository
Import to Vercel
Deploy automatically

Other Platforms

Railway - One-click deploy
Render - Free tier available
Heroku - Classic PaaS
AWS Lambda - Serverless
Google Cloud Run - Container-based
Docker - Containerized deployment

📝 Example Use Cases

1. Remote Job Finder

response = requests.post(
    "https://jobscrape-actor.vercel.app/api/scrape",
    json={
        "search_term": "python developer",
        "is_remote": True,
        "hours_old": 24,
        "results_wanted": 50,
        "site_name": ["indeed", "linkedin", "zip_recruiter"]
    }
)

2. Salary Research

response = requests.post(
    "https://jobscrape-actor.vercel.app/api/scrape",
    json={
        "search_term": "data scientist",
        "location": "New York, NY",
        "enforce_annual_salary": True,
        "results_wanted": 100,
        "output_format": "csv"  # Export to CSV for analysis
    }
)

3. International Job Search

response = requests.post(
    "https://jobscrape-actor.vercel.app/api/scrape",
    json={
        "site_name": ["naukri", "indeed"],
        "search_term": "software engineer",
        "location": "Bangalore",
        "country_indeed": "India",
        "results_wanted": 30
    }
)

🤝 Contributing

Contributions are welcome! Feel free to:

Report bugs
Suggest features
Submit pull requests
Improve documentation

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

Built with python-jobspy by @cullenwatson
Powered by FastAPI
Deployed on Vercel

👤 Maintainer

Amon Sharma

GitHub: @Amon20044
LinkedIn: Amon Sharma

🌟 Support

If you find this project useful, please consider:

⭐ Starring the repository
🍴 Forking and contributing
🐛 Reporting issues
📢 Sharing with others

📞 Contact & Support

🌐 Website: https://jobscrape-actor.vercel.app
📖 Documentation: https://jobscrape-actor.vercel.app/docs
🐛 Issues: GitHub Issues

Made with ❤️ by Amon Sharma

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