linkedin-scraper-python

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LinkedIn profiles, companies, jobs and posts as JSON, in Python. No LinkedIn login, no browser. Built on the Bright Data LinkedIn Scraper API.

Uses the Bright Data Python SDK. Full API docs: LinkedIn Scraper API.

Also here: a one-command CLI for profiles, and the Bright Data CLI, which needs no Python at all.

LinkedIn profile data is personal data. Use it within the law that applies to you: Bright Data compliance.

Quickstart

Python 3.10 or newer.

pip install brightdata-sdk
export BRIGHTDATA_API_TOKEN=YOUR_API_KEY

Get a token from the Bright Data control panel. A .env file in the project root works too, as long as the virtualenv is inside the project.

Or skip the token. Run npx -p @brightdata/cli bdata login once: it opens a browser, and from then on the SDK finds the stored credentials on its own, for you and for any coding agent working in that terminal. Agents cannot click through the login, so do it yourself first.

No account yet? Create one; new accounts get 5,000 free credits a month.

from brightdata import SyncBrightDataClient

with SyncBrightDataClient(auto_create_zones=False) as client:
    profile = client.scrape.linkedin.profiles("https://www.linkedin.com/in/satyanadella/").data
    print(profile["name"], "|", profile["position"])
    print(profile["followers"], "followers,", profile["connections"], "connections")

Satya Nadella | Chairman and CEO at Microsoft
12173313 followers, 500 connections

Expect under a minute: the API runs a job and the SDK waits for it. One credit per profile.

Pass auto_create_zones=False every time. Left on, the SDK creates zones on startup for Web Unlocker and SERP, two other Bright Data products this scraper never touches, and zone creation fails on accounts without a payment method (sdk-python#57).

Or run it as a command

The command in this repo does the same for several profiles and writes one JSON file.

pip install git+https://github.com/brightdata/linkedin-scraper-python
linkedin-scraper satyanadella reidhoffman

Fetching 2 LinkedIn profiles: satyanadella, reidhoffman
One job for all of them, usually one to three minutes. One credit per profile.
asking  2 profiles...

got     satyanadella: 34 fields (Satya Nadella)
got     reidhoffman: 38 fields (Reid Hoffman)

Saved 2 of 2 profiles as JSON to linkedin.json

It takes a profile URL just as happily as the slug inside it.

In a terminal the asking line is replaced by this, updating in place, so you can see it is working and how long it has been going:

⠹ 2 profiles 0:00:41

--out PATH   output file, default linkedin.json

python -m linkedin_scraper works too.

Every profile you ask for goes into one job. The API bills per record, not per job, and a job takes about the same time for one URL as for ten.

Import it instead of running it, for ok and error per profile instead of raw rows. scrape never raises for one bad profile; check ok before reading profile:

from linkedin_scraper import scrape

for outcome in scrape(["satyanadella", "zz-not-a-real-profile-zz"]):
    if outcome.ok:
        print(f"{outcome.slug}: {outcome.profile['name']}")
    else:
        print(f"{outcome.slug} failed: {outcome.error}")

satyanadella: Satya Nadella
zz-not-a-real-profile-zz failed: The profile is hidden or private.

The rest of the API

The command covers the first row of the table below. The rest of the SDK's LinkedIn surface is the other rows, documented in the LinkedIn Scraper API docs. Every snippet below is complete and needs only brightdata-sdk: paste it as is. Every one of them runs in Actions each Monday, a smaller check runs every other day, and the badge at the top is the latest result.

you have	want	call
a profile URL	that profile	client.scrape.linkedin.profiles(url)
a first and last name	matching profiles	client.search.linkedin.profiles(first_name, last_name), see the note below
a company URL	that company	client.scrape.linkedin.companies(url)
a job URL	that job posting	client.scrape.linkedin.jobs(url)
a keyword or a location	matching job postings	client.search.linkedin.jobs(keyword=..., location=...), see the note below
a post URL	that post	client.scrape.linkedin.posts(url)
a profile or company URL	its posts	client.search.linkedin.posts(url, start_date=..., end_date=...)

search.linkedin.profiles takes a first and last name, not a URL. It is people search by name. This README documents that it exists and does not demonstrate it against a real person.

search.linkedin.jobs has no parameter that caps how many postings it returns, and it bills one credit per posting. A broad keyword matches thousands. It is not run here, because every snippet in this README reruns weekly. Narrow it with company, location and timeRange before running it wide.

There is no example here built on a pinned job URL. A posting closes, and a snippet pinned to it would turn red the week that happened.

Every one of these is an asynchronous job. The SDK triggers it, polls, and returns when it is ready. The API's synchronous endpoint, 20 URLs and a one-minute limit, is raw HTTP only.

Error rows, like the dead profile above, appear because the SDK asks for them with include_errors=true. The API default is off.

scrape calls with one URL return one record as a dict, and several as a list. The timeout argument is seconds, 180 by default.

Several profiles, one job

A list of URLs is one job, not one per profile.

from brightdata import SyncBrightDataClient

with SyncBrightDataClient(auto_create_zones=False) as client:
    results = client.scrape.linkedin.profiles([
        "https://www.linkedin.com/in/satyanadella/",
        "https://www.linkedin.com/in/reidhoffman/",
    ])
    for result in results:
        row = result.data
        source = row.get("input_url") or row["input"]["url"]  # an error row has only input
        print(source, "|", row.get("name") or row["error"])

https://www.linkedin.com/in/reidhoffman/ | Reid Hoffman
https://www.linkedin.com/in/satyanadella/ | Satya Nadella

The URLs went in as satyanadella then reidhoffman, and the rows came back the other way round. Each line is still right, because it reads the row's own input_url.

Read which profile a row is from its own input_url, as above, never from result.url. The SDK pairs results with the URLs you passed by position, and the API returns rows in a different order each run, so result.url can name one person while result.data holds another's profile. Every result is also marked success=True, including a dead profile's error row (sdk-python#60). An error row has no input_url; it names its profile in input["url"].

Trigger now, fetch later

For anything bigger than a few profiles, do not block a process for an hour. Trigger, keep the snapshot id, fetch when ready. Snapshots stay downloadable for 30 days.

import time

from brightdata import SyncBrightDataClient

with SyncBrightDataClient(auto_create_zones=False) as client:
    job = client.scrape.linkedin.profiles_trigger("https://www.linkedin.com/in/satyanadella/")
    print("snapshot:", job.snapshot_id)
    while (status := client.scrape.linkedin.profiles_status(job.snapshot_id)) not in ("ready", "failed"):
        time.sleep(5)
    print("status:", status)
    record = client.scrape.linkedin.profiles_fetch(job.snapshot_id)[0]
    print("fetched:", record["name"], "|", record["current_company_name"])

snapshot: sd_mu717o9x2md4afafsv
status: ready
fetched: Satya Nadella | Microsoft

A company

from brightdata import SyncBrightDataClient

with SyncBrightDataClient(auto_create_zones=False) as client:
    company = client.scrape.linkedin.companies("https://www.linkedin.com/company/bright-data/").data
    print(company["name"], "|", company["employees_in_linkedin"], "employees on LinkedIn")

Bright Data | 407 employees on LinkedIn

The data

The fields most people want from a profile:

name  position  city  current_company_name  followers  connections  experience

The code hardcodes no field list. Whatever the API returns lands in result.data, and in the command's file.

The API marks 8 of these fields as personal data, with pii: true in the schema: id, name, about, url, input_url, linkedin_id, first_name and last_name.

get_metadata() drops that flag. It keeps type, active, required and description for each field and discards the rest (sdk-python#61). To read it, request https://api.brightdata.com/datasets/gd_l1viktl72bvl7bjuj0/metadata yourself with the same token. The table below does that.

All 47 fields, with type and description

Regenerated every day from the dataset schema, via the raw metadata endpoint, so it cannot go stale. A profile carries the fields that apply to it: the sample file has 32 of these 47, plus timestamp and input, which the schema does not list.

field	type	description
id	text	Personal data. A unique identifier for the person's LinkedIn profile
name	text	Personal data. Profile name
city	text	Geographical location of the user
country_code	text	Geographical location of the user
position	text	The current job title or position of the profile
about	text	Personal data. A concise profile summary. In some cases, only a truncated version with "…" is displayed on the website, and this is the version we capture
posts	array	Contains information related to the user's last LinkedIn posts. It typically includes the post title, created date, URL link to the post, etc.
groups	array	The LinkedIn groups that the profile is a part of
current_company	object	Provides information about the user's current professional position. It typically includes the company name, the user's job title, the company ID, and the industry or sector to which the company belongs
experience	array	Contains information about user's professional history. It typically includes the user's job title, length of time the user held the position, the geographic location of the company, the start and end date, the company name, URL link to the company profile, etc.
url	url	Personal data. URL that link directly to the LinkedIn profile
people_also_viewed	array	Provides a list of LinkedIn profiles that users who have viewed the user's profile, have viewed these as well
educations_details	text	Provides information about the user's educational background
education	array	Provides information about the user's educational background. It typically includes the degree, the start and end year, the filed, etc.
recommendations_count	number	A numeric count of the total number of recommendations that the user has received
avatar	url	URL that link to the profile picture of the LinkedIn user
courses	array	Contains information about courses or educational programs that the user has undertaken
languages	array	Contains information about the user's proficiency in different languages
certifications	array	Licenses & Certifications
recommendations	array	Recommendations that the user has received from their connections or colleagues on LinkedIn
volunteer_experience	array	Contains information related to the user's volunteer work
followers	number	How many users/ companies following the profile
connections	number	How many connections the profile has
current_company_company_id	text	The id of the latest/current company of the profile
current_company_name	text	The name of the latest/current company of the profile
publications	array	Published works or presentations
patents	array	Patents filed or granted
projects	array	Professional or academic projects
organizations	array	Memberships in professional organizations
location	text	Geographical location of the user
input_url	url	Personal data. The URL that was entered when starting the scraping process
linkedin_id	text	Personal data. LinkedIn profile identifier
activity	array	Any activity the user has regarding posts
linkedin_num_id	text	Numeric LinkedIn profile ID
banner_image	url	Banner image
honors_and_awards	array	Awards and recognitions received
similar_profiles	array	Profiles similar to the current one
default_avatar	boolean	Is the avatar picture the default avatar empty picture
memorialized_account	boolean	Boolean indicating if the account is memorialized
bio_links	array	External links added to the bio
first_name	text	Personal data. First name of the user
last_name	text	Personal data. Last name of the user
urn_id	text	The Uniform Resource Name (URN) used by LinkedIn
urn	text	Uniform Resource Name
influencer	boolean	Indicator if the profile marked as influencer
fsd_profile_id	text	FSD profile ID
backfilled_columns	object	Indicates whether sticky columns were backfilled. Keys are column names and values are true/false.

The start of a real output file, from linkedin-scraper satyanadella

{
  "generated_at": "2026-09-18T14:15:08.047993+00:00",
  "profiles": [
    {
      "slug": "satyanadella",
      "profile": {
        "id": "satyanadella",
        "name": "Satya Nadella",
        "city": "Redmond, Washington, United States",
        "country_code": "US",
        "position": "Chairman and CEO at Microsoft",
        "about": "As chairman and CEO of Microsoft, I define my mission and that of my company as empowering every person and every organization on the planet to achieve more.",
        "posts": [
          {
            "title": "How do we build a frontier intelligence ecosystem?",
            "attribution": "Great to be back at Microsoft Build today. For us, it is not about any one piece of technology or even the platform.",
            "img": "https://media.licdn.com/dms/image/v2/D560DAQHI1Iu8CrO8CQ/learning-public-crop_288_512/B56ZvrnmmhJ8AQ-/0/1769184586791?e=2147483647&v=beta&t=IZT3h7JK8tLoX5KYgwA0xLjxIKtc14hmHqKCk1cOLP8",
            "link": "https://www.linkedin.com/pulse/how-do-we-build-frontier-intelligence-ecosystem-satya-nadella-73jhc",
            "created_at": "2026-06-02T00:00:00.000Z",
  ...

The whole file, one profile with every field, is examples/sample_output.json.

When it fails

you see	what it means
API token required but not found.	Exit 2, before any request. Set the token.
failed slug: The profile is hidden or private.	Exit 1. No such profile, or not public. Usually a typo in the slug.
failed slug: the API returned no row for this profile	Exit 1. The job came back without a row for that input. Run it again.
failed slug: timeout	Exit 1. A request gives up after 180 seconds. Run it again.
failed slug: Failed to fetch results: Request timeout after 30 seconds	Exit 1. The job finished, but downloading it took longer than 30 seconds. Run it again.
failed slug: Crawler error: Your system is sending too many of this type of request. ...	Exit 1. The account is being throttled, and a valid profile fails with it. Wait, then run it again. It clears on its own.

Any failure exits 1, so a run is safe to gate a script on.

From the SDK, the same conditions look like this:

you see	what it means
AuthenticationError: Unauthorized (401)	The token is set but wrong.
result.success is False, result.status is "timeout"	The SDK gave up waiting for the job, 180 seconds by default. Pass timeout=420 to the call, or run it again.
Failed to fetch results: Request timeout after 30 seconds	The job finished; downloading it did not. That is the client's own limit on each HTTP request, SyncBrightDataClient(timeout=30), not the timeout you pass to the call. Raising the call's timeout does not help. Run it again, or pass a larger timeout to the client.
a dict in result.data with an error key	The API's answer for one input. result.success still says True; read the row.

Coding agents

No Python, nothing installed. Paste both lines; the first opens a browser once, or use bdata login --device over SSH and in CI:

npx -p @brightdata/cli bdata login
npx -p @brightdata/cli bdata pipelines linkedin_person_profile "https://www.linkedin.com/in/satyanadella/"

bdata pipelines list prints every type. The LinkedIn ones are linkedin_person_profile, linkedin_company_profile, linkedin_job_listings, linkedin_posts and linkedin_people_search. Each takes URLs, prints JSON, and costs one credit per record.

npx skills add brightdata/skills teaches Claude Code, Cursor and Codex these commands and the docs, so plain language works afterwards. Full guide: Bright Data for your coding agent.

No terminal, for a hosted assistant? The Bright Data MCP server has LinkedIn tools in its social group, which is off unless you ask for it:

https://mcp.brightdata.com/mcp?token=YOUR_API_TOKEN&groups=social

An agent can also open the account itself, no signup form: agent registration. Everything else Bright Data connects to, from LangChain to Zapier and n8n: integrations.

Support

Bugs in this repo: open an issue, and CONTRIBUTING.md says what to put in it. Anything about the API, your account or your credits: Bright Data support.

License

MIT.