job-scraper-selenium 1.0.2

A Python package for scraping job postings from Indeed and LinkedIn

Job Scraper 🚀

A powerful and easy-to-use Python package for scraping job postings from Indeed and LinkedIn using Selenium browser automation.

Features ✨

• 🔍 Scrape job details from Indeed and LinkedIn
• 🤖 Automatic platform detection
• 📊 Extract title, company, location, and full job description
• 🎯 Simple and intuitive API
• 🛡️ Bypasses anti-bot protection using Selenium
• ⚙️ Configurable options (headless mode, verbose output)

Installation 📦

Install from source

# Clone or download the repository
git clone https://github.com/adilc0070/job-scraper.git
cd job-scraper

# Install the package
pip install .

Install in development mode

pip install -e .

Quick Start 🚀

Basic Usage

from job_scraper import scrape_job

# Scrape any supported job posting (auto-detects platform)
job = scrape_job('https://in.indeed.com/viewjob?jk=...')

if job:
    print(f"Title: {job['title']}")
    print(f"Company: {job['company']}")
    print(f"Location: {job['location']}")
    print(f"Description: {job['description'][:200]}...")

Platform-Specific Scraping

from job_scraper import scrape_indeed_job, scrape_linkedin_job

# Scrape from Indeed
indeed_job = scrape_indeed_job('https://in.indeed.com/viewjob?jk=...')

# Scrape from LinkedIn
linkedin_job = scrape_linkedin_job('https://www.linkedin.com/jobs/view/...')

Advanced Options

from job_scraper import scrape_job

# Run in non-headless mode (show browser window)
job = scrape_job(url, headless=False)

# Disable verbose output (silent mode)
job = scrape_job(url, verbose=False)

# Combine options
job = scrape_job(url, headless=False, verbose=False)

API Reference 📚

scrape_job(url, headless=True, verbose=True)

Automatically detect and scrape jobs from Indeed or LinkedIn.

Parameters:

• url (str): The job posting URL (Indeed or LinkedIn)
• headless (bool): Run browser in headless mode (default: True)
• verbose (bool): Print progress messages (default: True)

Returns:

• dict: Job details or None if scraping fails

Example:

job = scrape_job('https://in.indeed.com/viewjob?jk=123456')

scrape_indeed_job(url, headless=True, verbose=True)

Scrape a single Indeed job posting.

Parameters:

• Same as scrape_job()

Returns:

• dict: Job details with keys: title, company, location, description, source, url

scrape_linkedin_job(url, headless=True, verbose=True)

Scrape a single LinkedIn job posting.

Parameters:

• Same as scrape_job()

Returns:

• dict: Job details with keys: title, company, location, description, source, url

Response Format 📋

All scraping functions return a dictionary with the following structure:

{
    'title': 'Senior Python Developer',
    'company': 'Tech Company Inc.',
    'location': 'San Francisco, CA',
    'description': 'Full job description text...',
    'source': 'Indeed',  # or 'LinkedIn'
    'url': 'https://...'
}

Examples 💡

Scrape Multiple Jobs

from job_scraper import scrape_job

urls = [
    'https://in.indeed.com/viewjob?jk=123',
    'https://www.linkedin.com/jobs/view/456',
    'https://in.indeed.com/viewjob?jk=789'
]

jobs = []
for url in urls:
    job = scrape_job(url, verbose=False)
    if job:
        jobs.append(job)
        print(f"✓ Scraped: {job['title']}")

print(f"\nTotal jobs scraped: {len(jobs)}")

Save to JSON

import json
from job_scraper import scrape_job

job = scrape_job('https://in.indeed.com/viewjob?jk=...')

if job:
    with open('job_data.json', 'w', encoding='utf-8') as f:
        json.dump(job, f, indent=2, ensure_ascii=False)
    print("Job saved to job_data.json")

Filter by Keywords

from job_scraper import scrape_job

keywords = ['python', 'django', 'flask']

job = scrape_job('https://in.indeed.com/viewjob?jk=...')

if job and any(keyword.lower() in job['description'].lower() for keyword in keywords):
    print(f"✓ Job matches keywords: {job['title']}")
else:
    print("✗ Job doesn't match keywords")

Requirements 🛠️

• Python 3.7+
• selenium >= 4.0.0
• beautifulsoup4 >= 4.9.0
• webdriver-manager >= 4.0.0
• Google Chrome (installed automatically by webdriver-manager)

Limitations ⚠️

• Some job sites may block automated scraping
• LinkedIn may require authentication for certain jobs
• Rate limiting may apply - avoid scraping too many jobs rapidly
• Always respect the website's Terms of Service and robots.txt

Troubleshooting 🔧

Browser not found

The package automatically downloads ChromeDriver. Ensure you have Google Chrome installed.

403 Forbidden Error

Some sites may block requests. Try:

• Using headless=False to run in visible browser mode
• Adding delays between requests
• Using a VPN or proxy

Encoding errors

The package handles most encoding issues automatically. If problems persist, the scraped data is returned as UTF-8.

Contributing 🤝

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

Ways to Contribute

1. Report bugs - Open an issue on GitHub
2. Add features - Submit a pull request
3. Improve documentation - Fix typos or add examples
4. Support more platforms - Add scrapers for other job sites

Publishing to PyPI 📤

To publish this package to PyPI so others can install it with pip install job-scraper-selenium:

1. Create PyPI account

• Sign up at https://pypi.org/account/register/

2. Install publishing tools

pip install build twine

3. Build the package

python -m build

4. Upload to PyPI

# Test on TestPyPI first (optional)
twine upload --repository testpypi dist/*

# Upload to real PyPI
twine upload dist/*

5. Install your package

pip install job-scraper-selenium

License 📄

MIT License - see LICENSE file for details

Author ✍️

Your Name

• GitHub: @adilc0070
• Email: [e-mail]

Acknowledgments 🙏

• Selenium for browser automation
• BeautifulSoup for HTML parsing
• webdriver-manager for automatic driver management

Support 💬

If you found this package helpful, please:

• ⭐ Star the repository
• 🐛 Report issues
• 🔀 Submit pull requests
• 📢 Share with others

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Disclaimer: This package is for educational purposes. Always respect website Terms of Service and use responsibly.