LinkedIn Lead Scraper 🚀
A LinkedIn Scraper to scrape up to 10k LinkedIn profiles and save their e-mail addresses if available!
It collects 10k profiles from the LinkedIn directory and their details like name, current position/headline, and location information. After all profiles are collected, it starts finding their email addresses. You can narrow down your searches based on location, role, etc.
Trouble with the base version? Check the “Cookie Based” version here
Windows Compiled GUI Version
Download from here
GUI Version Screenshot
If you want to run the Windows compiled version on Linux, you can install Wine and try it.
Installation Guide for Source Code Version
- First, download Python software from Python’s official website. Python 3.x only is supported. Download from here or for a precise Python version, download this version and scroll to the bottom to download the correct version based on your operating system and make sure to tick on “Add to PATH” during installation in windows machines
- Now, from the start menu (Windows) or Applications list (Linux/Mac), search for Command Prompt (Windows) or terminal (on Mac/Linux) and copy-paste the command written below:
pip3 install requests
This will show some installation progress and will install the library eventually. If you see any pip warning, you may ignore that as that’s optional.
- If pip doesn’t get recognized as a command, please re-install Python with “Add python to executable path” enabled, or for Mac/Linux, run the command
apt-get install python3-pip
- An account on LinkedIn is a must! You can create temporary profiles if you want.
Usage Guide
- Assuming that the Python software and the library required by this project are installed, time for the script execution. First, download the Python script of your choice and put it inside a folder.
- Right-click on the Python script and select the option “Edit with IDLE”. If you don’t see this option, you have to figure that out yourself to fix the problem but a correct installation will show this option in the right-click menu.
- This option should open up a code window. Locate the linkedin_email and linkedin_password placeholders and put your login details (don’t worry, it won’t get leaked to anyone). After that, set the desired company profile URL inside the target_company_link placeholder and save the changes by pressing the ctrl+s shortcut.
- Now, locate the Run menu and select Run Module and the automation will start processing. When you see a >>> at the bottom of the output screen, it will mean that the process has finished.
Other Ways to Run the Script
Windows
- You can set the configuration of email, password, and company profile link and save the changes. Double-clicking the Python file will also execute it.
Linux/Mac
- In the terminal, cd to the script folder and type
python3 Random_Scraper.py
Or,
python3 CompanyWise_Leads.py
Variants Details
Random_Scraper.py is the initial development of the scraper that collects up to 10k random LinkedIn profiles from the directory and picks info from their profile
CompanyWise_Leads.py is the revised version of the code to be able to collect company wise employee profiles for more leads information.
If you’re having issues with the login-based version(the base script), you can try either the cookie version (doesn’t have e-mail scraping ability).
Limits
- Do not log in from the IP address from where you don’t usually login to your LinkedIn account, otherwise, it will trigger their security system and won’t let you log in.
- Result is limited to 10,000 records only (this is a limitation from LinkedIn’s side)
- First-page data is not collected due to being away from API endpoint capability. But the cookie version will get you covered.
Disclaimer
Do not flood LinkedIn using your account on a large number to avoid issues with your account. I don’t hold any responsibility if you face issues with your account in the future. Use at your own risk!
Loved This Open Source Project?
Star the repository and share it with your friends who might need this. More variants of the LinkedIn Scraper will come soon. Keep this on watch for more updates!
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