Yet another LinkedIn Scraper...

Linky is a another LinkedIn scraper. Inspired by vysecurity and his LinkedInt project.

Currently, this method of extracting data from LinkedIn is limited to 1000 users at a time. So, Linky's HTML output has a small table at the bottom of the page which calculates the top 5 most common occupations that occur. This way, if the company has a weird naming scheme for devs, then Linky should be able to spot it and report it back. With these new found data points, the --keywords flag can be used to attempt to filter the output.

I will open to issues for the new features I'm working on implementing:

Installing

pip3 -r install requirements.txt

Help Page


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	<<<Yet another LinkedIn scraper>>>

usage: linky.py [-h] -c  [-i] [-k] [-d] [-o] [-f]

Yet another LinkedIn scraper.

optional arguments:
  -h, --help          show this help message and exit
  -c , --cookie       Cookie to authenticate to LinkedIn with [li_at]
  -i , --company-id   Company ID number
  -k , --keyword      Keyword for searches
  -d , --domain       Company domain name
  -o , --output       File to output to: Writes CSV, JSON and HTML.
  -f , --format       Format for email addresses

Usage

When working with cookies, Linky accepts both file and string:

--cookie cookie.txt OR --cookie alongcookiestring

Get Employees

python3 --cookie cookie.txt --company-id 1441 --domain google.com --output google_employees --format 'firstname.surname'

Get Employees with keyword

python3 --cookie cookie.txt --company-id 1441 --domain google.com --output google_employees --format 'firstname.surname' --keyword developer

Supported email formats

Currently, there is no support for middle names but its on the to-do list. Here are the current naming schemes:

firstname.surname
f.surname
firstnamesurname
fsurname
surname.firstname
s.firstname
surnamefirstname
sfirstname

They can all be referenced in --format, E.G:

f.surname: --format f.surname

michaelranaldo / linky