🚀 Blazing-fast LinkedIn data extractor — no browsers, no Selenium, just pure speed.

Extract profiles, emails, posts, jobs, and more in minutes instead of hours.

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📌 Table of Contents

#	Section
1	✨ What is this?
2	🆓 Free Version Features
3	💎 Paid PRO Features
4	⚡ Quick Start — Run in 3 Steps
5	🗂️ Output Formats
6	📊 Free vs PRO Comparison
7	🧠 How It Works
8	📁 Project Structure
9	💡 Use Cases
10	⚖️ Disclaimer
11	🤝 Contributing
12	📬 Contact & Hire Me

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✨ What is this?

LinkedIn Scraper is a super-fast, lightweight Python tool that extracts professional data from LinkedIn — without using Selenium, browsers, or heavy dependencies.

LinkedIn Profiles  ──►  Python Script  ──►  CSV / JSON / Excel

Whether you're a recruiter, sales professional, marketer, or researcher, this tool saves you hours of manual work by automating LinkedIn data collection at scale.

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🆓 Free Version Features

📂 File: Leade_generation.py

The free version extracts the following from LinkedIn search results:

Field	Description
🔗 Profile Link	Direct URL to the LinkedIn profile
👤 Full Name	Person's full name
💼 Designation	Current job title / headline
📍 Location	City, Country

✅ Sample Output

{
  "name": "Md. Shohanur Rahaman",
  "designation": "Machine Learning | Data Science | NLP | Researcher",
  "location": "Dhaka, Bangladesh",
  "profile_link": "https://www.linkedin.com/in/md-shohanur-rahaman"
}

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💎 Paid PRO Features

Unlock the Pro version for full automation power:

💎 PRO UNLOCK
├── 📧  Extract Emails (if publicly available)
├── 📞  Extract Phone Numbers
├── 📝  Scrape User Posts & Activity
├── 💼  Job Finder & Smart Search
├── 🔎  Filter by Keyword / Location / Industry
├── 🤝  Auto-Send Connection Requests
├── 📥  Read Inbox Messages
├── ✉️   Send Messages / SMS Automation
└── ⚡  And much more for Sales, Recruiting & Marketing

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⚡ Quick Start — Run in 3 Steps

Step 1 — Clone the Repository

git clone https://github.com/Mahdi-hasan-shuvo/linkedin-scraper.git
cd linkedin-scraper

Step 2 — Install Dependencies

pip install -r requirements.txt

Step 3 — Run the Scraper

python Leade_generation.py

🎉 That's it! Your leads will be saved automatically.

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🗂️ Output Formats

The scraper exports your data in 3 formats out of the box:

📊 leads.csv      ← Open in Excel / Google Sheets
📋 output.json    ← Use in any app or API
📘 leads.xlsx     ← Fully formatted spreadsheet

CSV Preview

Profile Link	Name	Designation	Location
linkedin.com/in/example	John Doe	Software Engineer at Google	USA
linkedin.com/in/example2	Jane Smith	Data Scientist	Canada
linkedin.com/in/example3	Ali Hassan	Full Stack Developer	Bangladesh

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📊 Free vs PRO Comparison

Feature	🆓 Free	💎 PRO
Profile Scraping	✅	✅
Name, Designation, Location	✅	✅
CSV / JSON / Excel Export	✅	✅
Contact Info (Email / Phone)	❌	✅
User Posts Scraping	❌	✅
Job Finder	❌	✅
Filter by Location / Industry	❌	✅
Auto Connection Requests	❌	✅
Inbox Reader	❌	✅
Message / SMS Automation	❌	✅
Priority Support	❌	✅

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🧠 How It Works

┌─────────────────────────────────────────────────────┐
│                   LinkedIn Scraper                   │
│                                                     │
│  1️⃣  You provide search keywords / filters           │
│       ↓                                             │
│  2️⃣  Script sends clean API / HTTP requests          │
│       ↓                                             │
│  3️⃣  LinkedIn returns profile data                   │
│       ↓                                             │
│  4️⃣  Data parsed → structured into clean format      │
│       ↓                                             │
│  5️⃣  Exported to CSV / JSON / Excel automatically    │
└─────────────────────────────────────────────────────┘

Key technical advantages:

• ✅ No Selenium, no browser automation
• ✅ No memory-heavy headless Chrome
• ✅ Pure Python requests + API calls
• ✅ Extremely fast — thousands of profiles in minutes
• ✅ Lightweight — runs on any machine

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📁 Project Structure

linkedin-scraper/
│
├── 📄 Leade_generation.py     ← Main scraper script (FREE version)
├── 📄 location_geoId.json     ← LinkedIn GeoID location mapping
├── 📄 leads.csv               ← Sample output file
├── 📂 output/                 ← Auto-generated output folder
├── 📂 user_scrap/             ← User profile scraping module
├── 📄 requirements.txt        ← Python dependencies
├── 📄 .gitignore
└── 📄 README.md

---

💡 Use Cases

Who	How They Use It
🎯 Sales Teams	Build targeted lead lists by industry, location & title
🔍 Recruiters	Find candidates matching specific skills and roles
📈 Marketers	Research prospects for B2B campaigns
🎓 Researchers	Collect professional data for academic studies
🤖 Automation Engineers	Integrate LinkedIn data into CRMs and pipelines

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⚖️ Disclaimer

⚠️ For Educational & Research Purposes Only

This tool is intended for learning and research purposes. Scraping LinkedIn may violate their Terms of Service. The author is not responsible for any misuse. Use at your own risk and responsibility.

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🤝 Contributing

Contributions are always welcome! Here's how:

# 1. Fork the repository
# 2. Create your feature branch
git checkout -b feature/amazing-feature

# 3. Commit your changes
git commit -m "Add amazing feature"

# 4. Push to the branch
git push origin feature/amazing-feature

# 5. Open a Pull Request 🎉

For major changes, please open an **Issue** first to discuss what you'd like to change.

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📬 Contact & Hire Me

Have a project in mind? Need custom scraping, automation, or data pipeline work? I'm available for freelance collaborations and paid projects.

Channel	Details
📩 Email	shuvobbhh@gmail.com
💬 WhatsApp / Telegram	+8801616397082
🌐 Portfolio	mahdi-hasan-shuvo.github.io
💼 GitHub	@Mahdi-hasan-shuvo

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"Quality work speaks louder than words. Let's build something remarkable together."

⭐ Star this repo if you found it useful — it means the world!

Made with ❤️ and ☕ by Mahdi Hasan Shuvo

# API DAMO

495251086-597fb18e-1dfa-4a03-b4a5-181fef976484.mp4