Automatically connect to over 900 million professionals on LinkedIn!
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inb is an automation tool for LinkedIn that allows users to automate various tasks, such as sending connection requests, messaging connections, and endorsing skills. With inb, users can save time and streamline their LinkedIn outreach efforts.
The tool is written in Python and uses the LinkedIn Voyager API to interact with LinkedIn.
inb is designed for professionals who want to expand their network and increase their visibility on LinkedIn. It can be used for personal or business purposes, and is ideal for individuals who want to grow their network without spending hours manually sending connection requests and messages.
The tool is open source and available on GitHub, so users can contribute to the development of the project and customize it to their specific needs. To get started, simply download the tool from GitHub and follow the instructions in the README
file.
No "official" API access required - Just use a valid LinkedIn account!
![Proxycurl APIs enrich people and company profiles with structured data](https://github.com/josephlimtech/linkedin-profile-scraper-api/raw/master/Proxycurl_scrape_LinkedIn.png)
Scrape public LinkedIn profile data at scale with Proxycurl APIs.
- Scraping Public profiles are battle tested in court in HiQ VS LinkedIn case.
- GDPR, CCPA, SOC2 compliant
- High rate Limit - 300 requests/minute
- Fast APIs respond in ~2s
- Fresh data - 88% of data is scraped real-time, other 12% are not older than 29 days
- High accuracy
- Tons of data points returned per profile
Built for developers, by developers.
Clone the repository.
git clone https://github.com/joshiayush/inb.git
To use the app with docker, you can use the following command, to build the app:
docker build -t inb .
Then, this one to run it:
docker run -it inb search --email username@service.domain --password xxx-xxx-xxx --keyword 'Software Engineer'
Next step is to install all the dependencies required for project inb listed in the requirements.txt
file.
python3 -m pip install [-r] requirements.txt
A quick usage guide on search
:
Usage: inb.py search [OPTIONS]
, searches for the specific keyword given and sends invitation to them. To send invitations to people on LinkedIn you could use:
./inb/inb.py search --email username@service.domain --password xxx-xxx-xxx --keyword 'Software Engineer'
inb
supports cookie based authentication - use --refresh-cookies
in case you encounter error LinkedInSessionExpiredException
.
./inb/inb.py search --email username@service.domain --password xxx-xxx-xxx --keyword 'Software developer' --refersh-cookies
Also, for security purpose you can omit the --pasword
argument over the command-line and later on executing the tool you'll be prompted to enter your password which will be hidden even after pressing keystrokes.
./inb/inb.py search --email username@service.domain --keyword 'Software developer' --refersh-cookies
And the best part is here, you can send connection request and not follow the LinkedIn profile. It will prevent your LinkedIn feed from going terrible.
./inb/inb.py search --email username@service.domain --keyword 'Software developer' --refersh-cookies --nofollow
Any problems encountered in non-linux environment should be reported immediately before passing comments on the portability of this tool as I've only built and tested it on Linux!
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement", "bug", or "documentation". Don't forget to give the project a star! Thanks again!
Project inb is hosted on GitHub. If you want to contribute changes please make sure to read the CONTRIBUTING.md
file. You can also contribute changes to the CONTRIBUTING.md
file itself.