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• ✅ No official API access required. Just use a valid LinkedIn user account.
• ✅ Direct HTTP API interface. No Selenium, Pupeteer, or other browser-based scraping methods.
• ✅ Get and search people, companies, jobs, posts
• ✅ Send and retrieve messages
• ✅ Send and accept connection requests
• ✅ Get and react to posts

And more! Read the docs for all API methods.

pip install linkedin-api

Or, for bleeding edge:

pip install git+https://github.com/tomquirk/linkedin-api.git

The following snippet demonstrates a few basic linkedin_api use cases:

from linkedin_api import Linkedin

# Authenticate using any Linkedin user account credentials
api = Linkedin('reedhoffman@linkedin.com', '*******')

# GET a profile
profile = api.get_profile('billy-g')

# GET a profiles contact info
contact_info = api.get_profile_contact_info('billy-g')

# GET 1st degree connections of a given profile
connections = api.get_profile_connections('1234asc12304')

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• poetry
• A valid Linkedin user account (don't use your personal account, if possible)

1. Create a .env config file (use .env.example as a reference)

2. Install dependencies using poetry:

   poetry install
   poetry self add poetry-plugin-dotenv

Run all tests:

poetry run pytest

Run unit tests:

poetry run pytest tests/unit

Run E2E tests:

poetry run pytest tests/e2e

poetry run black --check .

Or to fix:

poetry run black .

Linkedin will throw you a curve ball in the form of a Challenge URL. We currently don't handle this, and so you're kinda screwed. We think it could be only IP-based (i.e. logging in from different location). Your best chance at resolution is to log out and log back in on your browser.

Known reasons for Challenge include:

• 2FA
• Rate-limit - "It looks like you’re visiting a very high number of pages on LinkedIn.". Note - n=1 experiment where this page was hit after ~900 contiguous requests in a single session (within the hour) (these included random delays between each request), as well as a bunch of testing, so who knows the actual limit.

Please add more as you come across them.

• Mileage may vary when searching general keywords like "software" using the standard search method. They've recently added some smarts around search whereby they group results by people, company, jobs etc. if the query is general enough. Try to use an entity-specific search method (i.e. search_people) where possible.

This project attempts to provide a simple Python interface for the LinkedIn API.

Do you mean the legit LinkedIn API?

NO! To retrieve structured data, the LinkedIn Website uses a service they call Voyager. Voyager endpoints give us access to pretty much everything we could want from LinkedIn: profiles, companies, connections, messages, etc. - anything that you can see on linkedin.com, we can get from Voyager.

This project aims to provide complete coverage for Voyager.

How does it work?

Voyager endpoints look like this:

https://www.linkedin.com/voyager/api/identity/profileView/tom-quirk

Or, more clearly

 ___________________________________ _______________________________
|             base path             |            resource           |
https://www.linkedin.com/voyager/api /identity/profileView/tom-quirk

They are authenticated with a simple cookie, which we send with every request, along with a bunch of headers.

To get a cookie, we POST a given username and password (of a valid LinkedIn user account) to https://www.linkedin.com/uas/authenticate.

We're looking at the LinkedIn website and we spot some data we want. What now?

The following describes the most reliable method to find relevant endpoints:

1. view source

2. command-f/search the page for some keyword in the data. This will exist inside of a <code> tag.

3. Scroll down to the next adjacent element which will be another <code> tag, probably with an id that looks something like

   <code style="display: none" id="datalet-bpr-guid-3900675">
     {"request":"/voyager/api/identity/profiles/tom-quirk/profileView","status":200,"body":"bpr-guid-3900675"}
   </code>

The value of request is the url! 🤘

You can also use the network tab in you browsers developer tools, but you will encounter mixed results.

linkedin.com uses the Rest-li Protocol for querying data. Rest-li is an internal query language/syntax where clients (like linkedin.com) specify what data they want. It's conceptually similar to the GraphQL.

Here's an example of making a request for an organisation's name and groups (the Linkedin groups it manages):

/voyager/api/organization/companies?decoration=(name,groups*~(entityUrn,largeLogo,groupName,memberCount,websiteUrl,url))&q=universalName&universalName=linkedin

The "querying" happens in the decoration parameter, which looks like the following:

(
    name,
    groups*~(entityUrn,largeLogo,groupName,memberCount,websiteUrl,url)
)

Here, we request an organisation name and a list of groups, where for each group we want largeLogo, groupName, and so on.

Different endpoints use different parameters (and perhaps even different syntaxes) to specify these queries. Notice that the above query had a parameter q whose value was universalName; the query was then specified with the decoration parameter.

In contrast, the /search/cluster endpoint uses q=guided, and specifies its query with the guided parameter, whose value is something like

List(v->PEOPLE)

It could be possible to document (and implement a nice interface for) this query language - as we add more endpoints to this project, I'm sure it will become more clear if such a thing would be possible (and if it's worth it).

1. Bump version in pyproject.toml
2. poetry build
3. poetry publish -r test-pypi
4. poetry publish
5. Draft release notes in GitHub.

This library is not endorsed or supported by LinkedIn. It is an unofficial library intended for educational purposes and personal use only. By using this library, you agree to not hold the author or contributors responsible for any consequences resulting from its usage.